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Proactive monitoring and troubleshooting across the entire app network path, from your users to the application
Make sure the network is fast and reliable, no matter what application it supports.
The AppNeta Difference: TruPath™
TruPath is a unique and patented technology that provides active, continuous and low overhead real-time network performance for every hop in the network path. Unlike traditional device-centric solutions, TruPath can provide deep insight regardless of whether or not the network is private or public.
Monitor Any Network Without Impacting Production
Monitor into hosted services, IaaS, PaaS and Web applications: PathView is built into the core of the IP stack, so if you can ping a target, you can see everything.
Correlate Application and Network Performance
Understand the network end-to-end by actively monitoring entire network paths. Get insight into even cloud providers' networks by sending & receiving precisely timed network traffic, assessing performance in real time.
Find and Fix Problems Fast on Any Network
PathView was built to automatically run diagnostic tests when poor performance is detected to pinpoint the locations & cause of more than 80 network faults, even if they're occurring on devices you don't own or control.
PathView — How to diagnose and resolve performance problems
This is an overview of PathView, AppNeta's network health monitoring tool. With PathView, you can ensure the network is fast and reliable, no matter what application it supports.Request Trial
Features Included
- Continuous, lightweight monitoring
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PathView is part of AppNeta's APM for All SaaS solution, including AppView and FlowView.
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"AppNeta has accurate network metrics over long time periods for trending, baselining, and troubleshooting. It keeps our carrier honest."
Ralph Buschner | IT Systems Analyst, PITO - Ministry of Health


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Customs Minister Nicky Wagner today said she is continuing to look at different ways to collect tax effectively.
Pastoral tenure reviews to boost Nature Heritage Fund-inspired park in hobbit country
Pastoral tenure reivew will boost the size of the park to 100,000 hectares.
SmartGates boost NZ's airport efficiency in world rankings
Two surveys put New Zealand sixth in the world for airport efficiency.
Outdated law dictates insolvency guidelines
Paul Goldsmith wrote to Nicky Wagner, that the Insolvency Service "through the Official Assignee, administers all bankruptcies pursuant to the Insolvency Act 2006.
Rodney Hide discusses his latest column on NBR Radio and on demand on MyNBR Radio.
Wow - everyone thought Paul Goldsmith was up for a promotion|653611

subset: commoncrawl


text:
Light fog
3-Day Forecast
INDIANAPOLIS - One of the leaders of the Indianapolis Ten Point Coalition said the group has been invited to Ferguson, Missouri to share its experience in dealing with violence and turmoil on the streets.
Rev. Charles Harrison of Ten Point announced the development Thursday night.
The trip comes after nearly two weeks of protests and clashes following the police-shooting death of 18-year-old Michael Brown. Although things have turned more peaceful, the area is still tense.
Local pastors and volunteers who make up the Ten Point Coalition will train Ferguson community leaders on how to safely and peacefully patrol their neighborhoods.
"We're going to go to the St. Louis-Ferguson area sometime in mid to late September. We're trying to work out the details. We want to take them out probably the first night into one of the neighborhoods and teach them how to do street patrols," Harrison said.
Ten Point organizers frequently head to the scene of a violent crime to help calm members of the community that are nearby, and keep peace between police and civilians.
Ten Point will also show Ferguson leaders ways to establish better working relationships with elected officials, police and community organizations.
"We really know how to do it very effectively and we want to teach them so that they can begin to build some relationships with the young men and women out on the streets," Harrison said.
Harrison said he feels honored to be able to help.
Follow Chance Walser on Twitter: @chancewalserrtv | Facebook: Chance Walser
ALERT…Scattered showers and isolated storms continue today.
At deadly accident has closed a busy Indianapolis intersection on the city's northeast side.
A Call 6 Investigation reveals private sellers often not disclose a car's hidden problems to potential buyers, including open recalls,…
INDIANAPOLIS – Ritter defeats Beech Grove 27-20
Guerin Catholic beat Brebeuf Friday night with a school record-setting field goal.


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Biblical Womanhood
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Product Description
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|Format: Other
Number of Pages: 96
Vendor: Good Book Company
Publication Date: 2013
Dimensions: 8.1 X 5.3 X 0.4 (inches)
Availability: In Stock
Series: Good Book Guide
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From the Publisher
Fully revised and updated edition with a new study - Women and their children
Everywhere women face choices - home or career, money or relationships, 'secure' marriage or 'free' singleness, using your looks to get on or ignoring your looks and getting ignored, competing with the boys or retreating into the sisterhood ghetto, the 'progress' of feminism or the 'nostalgia' of motherhood and apple-pie, women bishops or tea-ladies and baby-sitters?
Our culture has plenty to say on all these issues. But a Christian woman, seeking to live for her Lord, will first of all want to find out God's design, purposes and promises for women.
And here's the book to help. Sarah Collins (nee Young), in this set of ten Bible studies, aims to answer questions such as
- What does the Bible say about the 'big issues' facing women today?
- How should this affect my own life?
- How can I be helped to live like this in a society with a very different agenda?
- Some things will be controversial in our culture, even in some of our churches.
This course doesn't set out to be politically correct but faithful to Scripture.
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Emdr Side Effects
EMDR Side Effects
EMDR Side Effects – As with anything and everything in life, there is always a side effect, but in the case of this particular therapy, there is not much to talk about:
- It has been noted that patients that underwent the treatment had distressing and unresolved memories which may emerge occasionally. This is a normal and
natural part of the treatment process. Rather than calling it a "side effect," this could be
considered a part of the main effect, leading to desensitizing and reprocessing of the root cause of the memories.
- Some unexpected results may occur during or after therapy that was not part of the plan, reactions like having a high level of sensitivity or emotions or some physical sensations. By this time in the treatment process, much work was done to prepare you for this possibility. Plus, your therapist will help you handle whatever comes up during the session.
- Subsequent to the treatment session, the processing of incidents/material may continue, and other dreams, memories feelings, etc., may emerge. If this should become too much for you to handle on your own, you are welcome to call your therapist, who will help you.
After speaking with one of the EMDR therapists at work, I was told that the stages involve taking the patient to his/her happy place before embarking on the treatment. It's also been noted that some patients could not be treated with this reprocessing technique, which so far has a low percentage rate. That would not surprise me as I know every form of medication in life has its pros and cons, which in turn has side effects. The journey to resolve PTSD and/or abusive memory is just beginning and I can't wait to see how well it will develop.
Learn More by Visiting:
- http://www.emdr.com
- EMDRIA.org
- http://www.emdriafoundation.org
- PTSD.va.gov
- http://www.crimesolutions.gov/ProgramDetails.aspx?ID=131
- NREPP.gov


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Related Articles
Adoption of a Clinical Pharmacogenomics Implementation Program During Outpatient Care–Initial Results of The University of Chicago '1200 Patients Project'
O'Donnell, Peter H.
Danahey, Keith
Jacobs, Michael
Wadhwa, Nisha R.
Yuen, Shennin
Bush, Angela
Sacro, Yasmin
Sorrentino, Matthew J.
Siegler, Mark
Harper, William
Warrick, Andrea
Das, Soma
Saner, Don
Corless, Christopher L.
Ratain, Mark J.
American journal of medical genetics. Part C, Seminars in medical genetics
Pharmacogenomic testing is viewed as an integral part of precision medicine. To achieve this, we originated The 1200 Patients Project which offers broad, preemptive pharmacogenomic testing to patients at our institution.
We analyzed enrollment, genotype, and encounter-level data from the first year of implementation to assess utility of providing pharmacogenomic results. Results were delivered via a genomic prescribing system (GPS) in the form of traffic lights: green (favorable), yellow (caution), and red (high risk). Additional supporting information was provided as a virtual pharmacogenomic consult, including citation to relevant publications.
Currently, 812 patients have participated, representing 90% of those approached; 608 have been successfully genotyped across a custom array. A total of 268 clinic encounters have occurred at which results were accessible via the GPS. At 86% of visits, physicians accessed the GPS, receiving 367 result signals for medications patients were taking: 57% green lights, 41% yellow lights, and 1.4% red lights. Physician click frequencies to obtain clinical details about alerts varied according to color severity (100% of red were clicked, 72% yellow, 20% green). For 85% of visits, clinical pharmacogenomic information was available for at least one drug the patient was taking, suggesting relevance of the delivered information.
We successfully implemented an individualized health care model of preemptive pharmacogenomic testing, delivering results along with pharmacogenomic decision support. Patient interest was robust, physician adoption of information was high, and results were routinely utilized. Ongoing examination of a larger number of clinic encounters and inclusion of more physicians and patients is warranted.
pharmacogenomics; implementation; genomic medicine; precision medicine
Related Articles
Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies
Samwald, Matthias
Miñarro Giménez, Jose Antonio
Boyce, Richard D
Freimuth, Robert R
Adlassnig, Klaus-Peter
Dumontier, Michel
BMC Medical Informatics and Decision Making
Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics.
We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles.
Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners.
The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-015-0130-1) contains supplementary material, which is available to authorized users.
Pharmacogenomics; Ontology; Automated reasoning; Personalized medicine; Clinical decision support
Related Articles
Harmonization and Semantic Annotation of Data Dictionaries from the Pharmacogenomics Research Network: a case study
Zhu, Qian
Freimuth, Robert R.
Lian, Zonghui
Bauer, Scott
Pathak, Jyotishman
Tao, Cui
Durski, Matthew J.
Chute, Christopher G.
Journal of biomedical informatics
The Pharmacogenomics Research Network (PGRN) is a collaborative partnership of research groups funded by NIH to discover and understand how genome contributes to an individual's response to medication. Since traditional biomedical research studies and clinical trials are often conducted independently, common and standardized representations for data are seldom used. This leads to heterogeneity in data representation, which hinders data reuse, data integration and meta-analyses.
This study demonstrates harmonization and semantic annotation work for pharmacogenomics data dictionaries collected from PGRN research groups. A semi-automated system was developed to support the harmonization/annotation process, which includes four individual steps, 1) pre-processing PGRN variables; 2) decomposing and normalizing variable descriptions; 3) semantically annotating words and phrases using controlled terminologies; 4) grouping PGRN variables into categories based on the annotation results and semantic types, for total 1514 PGRN variables.
Our results demonstrate that there is a significant amount of variability in how pharmacogenomics data is represented and that additional standardization efforts are needed. This represents a critical first step toward identifying and creating data standards for pharmacogenomics studies.
Data harmonization; semantic annotation; Pharmacogenomics
Related Articles
KRAS Testing for Anti-EGFR Therapy in Advanced Colorectal Cancer
Ontario Health Technology Assessment Series
Executive Summary
In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of the literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.
Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.
The following reports can be publicly accessed at the MAS website at: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.html
Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer: An Evidence-Based and Economic Analysis
Epidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: an Evidence-Based and Economic Analysis
K-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis.
The objective of this systematic review is to determine the predictive value of KRAS testing in the treatment of metastatic colorectal cancer (mCRC) with two anti-EGFR agents, cetuximab and panitumumab. Economic analyses are also being conducted to evaluate the cost-effectiveness of KRAS testing.
Clinical Need: Condition and Target Population
Metastatic colorectal cancer (mCRC) is usually defined as stage IV disease according to the American Joint Committee on Cancer tumour node metastasis (TNM) system or stage D in the Duke's classification system. Patients with advanced colorectal cancer (mCRC) either present with metastatic disease or develop it through disease progression.
KRAS (Kristen-RAS, a member of the rat sarcoma virus (ras) gene family of oncogenes) is frequently mutated in epithelial cancers such as colorectal cancer, with mutations occurring in mutational hotspots (codons 12 and 13) of the KRAS protein. Involved in EGFR-mediated signalling of cellular processes such as cell proliferation, resistance to apoptosis, enhanced cell motility and neoangiogenesis, a mutation in the KRAS gene is believed to be involved in cancer pathogenesis. Such a mutation is also hypothesized to be involved in resistance to targeted anti-EGFR (epidermal growth factor receptor with tyrosine kinase activity) treatments such as cetuximab and panitumumab, hence, the important in evaluating the evidence on the predictive value of KRAS testing in this context.
KRAS Mutation Testing in Advanced Colorectal Cancer
Both cetuximab and panitumumab are indicated by Health Canada in the treatment of patients with metastatic colorectal cancer whose tumours are WT for the KRAS gene. Cetuximab may be offered as monotherapy in patients intolerant to irinotecan-based chemotherapy or in patients who have failed both irinotecan and oxaliplatin-based regimens and who received a fluoropyrimidine. It can also be administered in combination with irinotecan in patients refractory to other irinotecan-based chemotherapy regimens. Panitumumab is only indicated as a single agent after failure of fluoropyrimidine-, oxaliplatin-, and irinotecan-containing chemotherapy regimens.
In Ontario, patients with advanced colorectal cancer who are refractory to chemotherapy may be offered the targeted anti-EGFR treatments cetuximab or panitumumab. Eligibility for these treatments is based on the KRAS status of their tumour, derived from tissue collected from surgical or biopsy specimens. It is believed that KRAS status is not affected by treatments, therefore, for patients for whom surgical tissue is available for KRAS testing, additional biopsies prior to treatment with these targeted agents is not necessary. For patients that have not undergone surgery or for whom surgical tissue is not available, a biopsy of either the primary or metastatic site is required to determine their KRAS status. This is possible as status at the metastatic and primary tumour sites is considered to be similar.
Research Question
To determine if there is predictive value of KRAS testing in guiding treatment decisions with anti-EGFR targeted therapies in advanced colorectal cancer patients refractory to chemotherapy.
Research Methods
Literature Search
The Medical Advisory Secretariat followed its standard procedures and on May 18, 2010, searched the following electronic databases: Ovid MEDLINE, EMBASE, Ovid MEDLINE In-Process & Other Non-Indexed Citations, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and The International Network of Agencies for Health Technology Assessment database.
The subject headings and keywords searched included colorectal cancer, cetuximab, panitumumab, and KRAS testing. The search was further restricted to English-language articles published between January 1, 2009 and May 18, 2010 resulting in 1335 articles for review. Excluded were case reports, comments, editorials, nonsystematic reviews, and letters. Studies published from January 1, 2005 to December 31, 2008 were identified in a health technology assessment conducted by the Agency for Healthcare Research and Quality (AHRQ), published in 2010. In total, 14 observational studies were identified for inclusion in this EBA: 4 for cetuximab monotherapy, 7 for the cetuximab-irinotecan combination therapy, and 3 to be included in the review for panitumumab monotherapy
Inclusion Criteria
English-language articles, and English or French-language HTAs published from January 2005 to May 2010, inclusive.
Randomized controlled trials (RCTs) or observational studies, including single arm treatment studies that include KRAS testing.
Studies with data on main outcomes of interest, overall and progression-free survival.
Studies of third line treatment with cetuximab or panitumumab in patients with advanced colorectal cancer refractory to chemotherapy.
For the cetuximab-irinotecan evaluation, studies in which at least 70% of patients in the study received this combination therapy.
Exclusion Criteria
Studies whose entire sample was included in subsequent publications which have been included in this EBA.
Studies in pediatric populations.
Case reports, comments, editorials, or letters.
Outcomes of Interest
Overall survival (OS), median
Progression-free-survival (PFS), median.
Response rates.
Adverse event rates.
Quality of life (QOL).
Summary of Findings of Systematic Review
Cetuximab or Panitumumab Monotherapy
Based on moderate GRADE observational evidence, there is improvement in PFS and OS favouring patients without the KRAS mutation (KRAS wildtype, or KRAS WT) compared to those with the mutation.
Cetuximab-Irinotecan Combination Therapy
There is low GRADE evidence that testing for KRAS may optimize survival benefits in patients without the KRAS mutation (KRAS wildtype, or KRAS WT) compared to those with the mutation.
However, cetuximab-irinotecan combination treatments based on KRAS status discount any effect of cetuximab in possibly reversing resistance to irinotecan in patients with the mutation, as observed effects were lower than for patients without the mutation. Clinical experts have raised concerns about the biological plausibility of this observation and this conclusion would, therefore, be regarded as hypothesis generating.
Economic Analysis
Cost-effectiveness and budget impact analyses were conducted incorporating estimates of effectiveness from this systematic review. Evaluation of relative cost-effectiveness, based on a decision-analytic cost-utility analysis, assessed testing for KRAS genetic mutations versus no testing in the context of treatment with cetuximab monotherapy, panitumumab monotherapy, cetuximab in combination with irinotecan, and best supportive care.
Of importance to note is that the cost-effectiveness analysis focused on the impact of testing for KRAS mutations compared to no testing in the context of different treatment options, and does not assess the cost-effectiveness of the drug treatments alone.
KRAS status is predictive of outcomes in cetuximab and panitumumab monotherapy, and in cetuximab-irinotecan combination therapy.
While KRAS testing is cost-effective for all strategies considered, it is not equally cost-effective for all treatment options.
Related Articles
Development and Validation of a Portable Platform for Deploying Decision-Support Algorithms in Prehospital Settings
Reisner, A. T.
Khitrov, M. Y.
Chen, L.
Blood, A.
Wilkins, K.
Doyle, W.
Wilcox, S.
Denison, T.
Reifman, J.
Applied Clinical Informatics
Advanced decision-support capabilities for prehospital trauma care may prove effective at improving patient care. Such functionality would be possible if an analysis platform were connected to a transport vital-signs monitor. In practice, there are technical challenges to implementing such a system. Not only must each individual component be reliable, but, in addition, the connectivity between components must be reliable.
We describe the development, validation, and deployment of the Automated Processing of Physiologic Registry for Assessment of Injury Severity (APPRAISE) platform, intended to serve as a test bed to help evaluate the performance of decision-support algorithms in a prehospital environment.
We describe the hardware selected and the software implemented, and the procedures used for laboratory and field testing.
The APPRAISE platform met performance goals in both laboratory testing (using a vital-sign data simulator) and initial field testing. After its field testing, the platform has been in use on Boston MedFlight air ambulances since February of 2010.
These experiences may prove informative to other technology developers and to healthcare stakeholders seeking to invest in connected electronic systems for prehospital as well as in-hospital use. Our experiences illustrate two sets of important questions: are the individual components reliable (e.g., physical integrity, power, core functionality, and end-user interaction) and is the connectivity between components reliable (e.g., communication protocols and the metadata necessary for data interpretation)? While all potential operational issues cannot be fully anticipated and eliminated during development, thoughtful design and phased testing steps can reduce, if not eliminate, technical surprises.
Decision-support algorithms; prehospital care; device connectivity; vital-sign data; combat casualty care
Related Articles
An Ontology-Based, Mobile-Optimized System for Pharmacogenomic Decision Support at the Point-of-Care
Miñarro-Giménez, Jose Antonio
Blagec, Kathrin
Boyce, Richard D.
Adlassnig, Klaus-Peter
Samwald, Matthias
PLoS ONE
The development of genotyping and genetic sequencing techniques and their evolution towards low costs and quick turnaround have encouraged a wide range of applications. One of the most promising applications is pharmacogenomics, where genetic profiles are used to predict the most suitable drugs and drug dosages for the individual patient. This approach aims to ensure appropriate medical treatment and avoid, or properly manage, undesired side effects.
We developed the Medicine Safety Code (MSC) service, a novel pharmacogenomics decision support system, to provide physicians and patients with the ability to represent pharmacogenomic data in computable form and to provide pharmacogenomic guidance at the point-of-care. Pharmacogenomic data of individual patients are encoded as Quick Response (QR) codes and can be decoded and interpreted with common mobile devices without requiring a centralized repository for storing genetic patient data. In this paper, we present the first fully functional release of this system and describe its architecture, which utilizes Web Ontology Language 2 (OWL 2) ontologies to formalize pharmacogenomic knowledge and to provide clinical decision support functionalities.
The MSC system provides a novel approach for enabling the implementation of personalized medicine in clinical routine.
Related Articles
A Comparison of Acute Hemorrhagic Stroke Outcomes in two Populations: The Crete-Boston Study
Zaganas, Ioannis
Halpin, Amy P
Oleinik, Alexandra
Alegakis, Athanasios
Kotzamani, Dimitra
Zafiris, Spiros
Chlapoutaki, Chryssanthi
Tsimoulis, Dimitris
Giannakoudakis, Emmanouil
Chochlidakis, Nikolaos
Ntailiani, Aikaterini
Valatsou, Christina
Papadaki, Efrosini
Vakis, Antonios
Furie, Karen L
Greenberg, Steven M
Plaitakis, Andreas
Stroke; a journal of cerebral circulation
While corticosteroid use in Acute Hemorrhagic Stroke (AHS) is not widely adopted, management with intravenous dexamethasone (IVDxM) has been standard of care at the University Hospital of Heraklion, Crete (UH-Crete) with observed outcomes superior to those reported in literature. To explore this further, we conducted a retrospective, multivariable-adjusted two-center study.
We studied 391 AHS cases admitted to UH-Crete between 1/1997 and 7/2010 and compared them with 510 AHS cases admitted to Massachusetts General Hospital, Boston from 1/2003 to 9/2009. Of the Cretan cases, 340 received a tapering scheme of IVDxM, starting with 16–32 mg/day, while the Boston patients were managed without steroids.
The two cohorts had comparable demographics and stroke severity on admission, although anticoagulation was more frequent in Boston. The in-hospital mortality was significantly lower on Crete (23.8%, n=340) than in Boston (38.0 %, n=510; p<0.001) as was the 30-day mortality (Crete: 25.4%, n=307; Boston: 39.4%, n=510; p<0.001). Exclusion of patients on anticoagulants showed even greater differences (30-day mortality: Crete 20.8%; n=259; Boston 37.0%; n=359; p<0.001). The improved survival on Crete was observed three days after initiation of IVDxM and was pronounced for deep-seated hemorrhages. After adjusting for AHS volume/location, GCS, hypertension, diabetes mellitus, smoking, coronary artery disease and statin, antiplatelet and anticoagulant use, IVDxM treatment was associated with better functional outcomes and significantly lower risk of death at 30-days (odds ratio 0.357; 95% C.I. 0.174–0.732).
This study suggests that IVDxM improves outcome in AHS and supports a randomized clinical trial using this approach.
ICH; Dexamethasone; stroke management
Related Articles
Prospective participant selection and ranking to maximize actionable pharmacogenetic variants and discovery in the eMERGE Network
Crosslin, David R.
Robertson, Peggy D.
Carrell, David S.
Gordon, Adam S.
Hanna, David S.
Burt, Amber
Fullerton, Stephanie M.
Scrol, Aaron
Ralston, James
Leppig, Kathleen
Hartzler, Andrea
Baldwin, Eric
Andrade, Mariza de
Kullo, Iftikhar J.
Tromp, Gerard
Doheny, Kimberly F.
Ritchie, Marylyn D.
Crane, Paul K.
Nickerson, Deborah A.
Larson, Eric B.
Jarvik, Gail P.
Genome Medicine
In an effort to return actionable results from variant data to electronic health records (EHRs), participants in the Electronic Medical Records and Genomics (eMERGE) Network are being sequenced with the targeted Pharmacogenomics Research Network sequence platform (PGRNseq). This cost-effective, highly-scalable, and highly-accurate platform was created to explore rare variation in 84 key pharmacogenetic genes with strong drug phenotype associations.
To return Clinical Laboratory Improvement Amendments (CLIA) results to our participants at the Group Health Cooperative, we sequenced the DNA of 900 participants (61 % female) with non-CLIA biobanked samples. We then selected 450 of those to be re-consented, to redraw blood, and ultimately to validate CLIA variants in anticipation of returning the results to the participant and EHR. These 450 were selected using an algorithm we designed to harness data from self-reported race, diagnosis and procedure codes, medical notes, laboratory results, and variant-level bioinformatics to ensure selection of an informative sample. We annotated the multi-sample variant call format by a combination of SeattleSeq and SnpEff tools, with additional custom variables including evidence from ClinVar, OMIM, HGMD, and prior clinical associations.
We focused our analyses on 27 actionable genes, largely driven by the Clinical Pharmacogenetics Implementation Consortium. We derived a ranking system based on the total number of coding variants per participant (75.2±14.7), and the number of coding variants with high or moderate impact (11.5±3.9). Notably, we identified 11 stop-gained (1 %) and 519 missense (20 %) variants out of a total of 1785 in these 27 genes. Finally, we prioritized variants to be returned to the EHR with prior clinical evidence of pathogenicity or annotated as stop-gain for the following genes: CACNA1S and RYR1 (malignant hyperthermia); SCN5A, KCNH2, and RYR2 (arrhythmia); and LDLR (high cholesterol).
The incorporation of genetics into the EHR for clinical decision support is a complex undertaking for many reasons including lack of prior consent for return of results, lack of biospecimens collected in a CLIA environment, and EHR integration. Our study design accounts for these hurdles and is an example of a pilot system that can be utilized before expanding to an entire health system.
Electronic supplementary material
The online version of this article (doi:10.1186/s13073-015-0181-z) contains supplementary material, which is available to authorized users.
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Pharmacogenomics and individualized medicine: Translating science into practice
Crews, Kristine R.
Hicks, J. Kevin
Pui, Ching-Hon
Relling, Mary V.
Evans, William E.
Clinical pharmacology and therapeutics
Research on genes and medications has advanced our understanding of the genetic basis of individual drug responses. The aim of pharmacogenomics is to develop strategies for individualizing therapy for patients, to optimize outcome through knowledge of human genome variability and its influence on drug response. Pharmacogenomics research is translational in nature and ranges from discovery of genotype-phenotype relationships to clinical trials which provide proof of clinical impact. Advances in pharmacogenomics offer significant potential for subsequent clinical application in individual patients; however, the translation of pharmacogenomics research findings into clinical practice has been slow. Key components to successful clinical implementation of pharmacogenomics will include consistent interpretation of pharmacogenomic test results, availability of clinical guidelines for prescribing based on test results, and knowledge-based decision support systems.
pharmacogenomics; genetic testing; personalized medicine
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Electronic Health Record Design and Implementation for Pharmacogenomics: a Local Perspective
Peterson, Josh F.
Bowton, Erica
Field, Julie R.
Beller, Marc
Mitchell, Jennifer
Schildcrout, Jonathan
Gregg, William
Johnson, Kevin
Jirjis, Jim N
Roden, Dan M.
Pulley, Jill M.
Denny, Josh C.
Genetics in medicine : official journal of the American College of Medical Genetics
The design of electronic health records (EHR) to translate genomic medicine into clinical care is crucial to successful introduction of new genomic services, yet there are few published guides to implementation.
The design, implemented features, and evolution of a locally developed EHR that supports a large pharmacogenomics program at a tertiary care academic medical center was tracked over a 4-year development period.
Developers and program staff created EHR mechanisms for ordering a pharmacogenomics panel in advance of clinical need (preemptive genotyping) and in response to a specific drug indication. Genetic data from panel-based genotyping were sequestered from the EHR until drug-gene interactions (DGIs) met evidentiary standards and deemed clinically actionable. A service to translate genotype to predicted drug response phenotype populated a summary of DGIs, triggered inpatient and outpatient clinical decision support, updated laboratory records, and created gene results within online personal health records.
The design of a locally developed EHR supporting pharmacogenomics has generalizable utility. The challenge of representing genomic data in a comprehensible and clinically actionable format is discussed along with reflection on the scalability of the model to larger sets of genomic data.
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Semantically enabling pharmacogenomic data for the realization of personalized medicine
Samwald, Matthias
Coulet, Adrien
Huerga, Iker
Powers, Robert L
Luciano, Joanne S
Freimuth, Robert R
Whipple, Frederick
Pichler, Elgar
Prud'hommeaux, Eric
Dumontier, Michel
Marshall, M Scott
Understanding how each individual's genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients' medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products.
clinical decision support systems; knowledge representation; ontologies; personalized medicine; pharmacogenomics; translational medicine
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Implementation of workflow engine technology to deliver basic clinical decision support functionality
Huser, Vojtech
Rasmussen, Luke V
Oberg, Ryan
Starren, Justin B
BMC Medical Research Methodology
Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic.
We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture.
We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.
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Pharmacogenomic knowledge gaps and educational resource needs among physicians in selected specialties
Johansen Taber, Katherine A
Dickinson, Barry D
Pharmacogenomics and Personalized Medicine
The use of pharmacogenomic testing in the clinical setting has the potential to improve the safety and effectiveness of drug therapy, yet studies have revealed that physicians lack knowledge about the topic of pharmacogenomics, and are not prepared to implement it in the clinical setting. This study further explores the pharmacogenomic knowledge deficit and educational resource needs among physicians.
Materials and methods
Surveys of primary care physicians, cardiologists, and psychiatrists were conducted.
Few physicians reported familiarity with the topic of pharmacogenomics, but more reported confidence in their knowledge about the influence of genetics on drug therapy. Only a small minority had undergone formal training in pharmacogenomics, and a majority reported being unsure what type of pharmacogenomic tests were appropriate to order for the clinical situation. Respondents indicated that an ideal pharmacogenomic educational resource should be electronic and include such components as how to interpret pharmacogenomic test results, recommendations for prescribing, population subgroups most likely to be affected, and contact information for laboratories offering pharmacogenomic testing.
Physicians continue to demonstrate pharmacogenomic knowledge gaps, and are unsure about how to use pharmacogenomic testing in clinical practice. Educational resources that are clinically oriented and easily accessible are preferred by physicians, and may best support appropriate clinical implementation of pharmacogenomics.
pharmacogenomics; knowledge gap; drug response; educational resource
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DMET-Analyzer: automatic analysis of Affymetrix DMET Data
Guzzi, Pietro Hiram
Agapito, Giuseppe
Di Martino, Maria Teresa
Arbitrio, Mariamena
Tassone, Pierfrancesco
Tagliaferri, Pierosandro
Cannataro, Mario
BMC Bioinformatics
Clinical Bioinformatics is currently growing and is based on the integration of clinical and omics data aiming at the development of personalized medicine. Thus the introduction of novel technologies able to investigate the relationship among clinical states and biological machineries may help the development of this field. For instance the Affymetrix DMET platform (drug metabolism enzymes and transporters) is able to study the relationship among the variation of the genome of patients and drug metabolism, detecting SNPs (Single Nucleotide Polymorphism) on genes related to drug metabolism. This may allow for instance to find genetic variants in patients which present different drug responses, in pharmacogenomics and clinical studies. Despite this, there is currently a lack in the development of open-source algorithms and tools for the analysis of DMET data. Existing software tools for DMET data generally allow only the preprocessing of binary data (e.g. the DMET-Console provided by Affymetrix) and simple data analysis operations, but do not allow to test the association of the presence of SNPs with the response to drugs.
We developed DMET-Analyzer a tool for the automatic association analysis among the variation of the patient genomes and the clinical conditions of patients, i.e. the different response to drugs. The proposed system allows: (i) to automatize the workflow of analysis of DMET-SNP data avoiding the use of multiple tools; (ii) the automatic annotation of DMET-SNP data and the search in existing databases of SNPs (e.g. dbSNP), (iii) the association of SNP with pathway through the search in PharmaGKB, a major knowledge base for pharmacogenomic studies. DMET-Analyzer has a simple graphical user interface that allows users (doctors/biologists) to upload and analyse DMET files produced by Affymetrix DMET-Console in an interactive way. The effectiveness and easy use of DMET Analyzer is demonstrated through different case studies regarding the analysis of clinical datasets produced in the University Hospital of Catanzaro, Italy.
DMET Analyzer is a novel tool able to automatically analyse data produced by the DMET-platform in case-control association studies. Using such tool user may avoid wasting time in the manual execution of multiple statistical tests avoiding possible errors and reducing the amount of time needed for a whole experiment. Moreover annotations and the direct link to external databases may increase the biological knowledge extracted. The system is freely available for academic purposes at: https://sourceforge.net/projects/dmetanalyzer/files/
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Using Clinical Element Models for Pharmacogenomic Study Data Standardization
Zhu, Qian
Freimuth, Robert R
Pathak, Jyotishman
Chute, Christopher G
AMIA Summits on Translational Science Proceedings
Standardized representations for pharmacogenomics data are seldom used, which leads to data heterogeneity and hinders data reuse and integration. In this study, we attempted to represent data elements from the Pharmacogenomics Research Network (PGRN) that are related to four categories, patient, drug, disease and laboratory, in a standard way using Clinical Element Models (CEMs), which have been adopted in the Strategic Health IT Advanced Research Project, secondary use of EHR (SHARPn) as a library of common logical models that facilitate consistent data representation, interpretation, and exchange within and across heterogeneous sources and applications. This was accomplished by grouping PGRN data elements into categories based on UMLS semantic type, then mapping each to one or more CEM attributes using a web-based tool that was developed to support curation activities. This study demonstrates the successful application of SHARPn CEMs to the pharmacogenomic domain. It also identified several categories of data elements that are not currently supported by SHARPn CEMs, which represent opportunities for further development and collaboration.
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The Role of the Pediatric Pharmacist in Personalized Medicine and Clinical Pharmacogenomics for Children
Kennedy, Mary Jayne
Phan, Hanna
Benavides, Sandra
Potts, Amy
Sorensen, Susan
The Journal of Pediatric Pharmacology and Therapeutics : JPPT
With the initiatives by the National Institutes of Health and the Food and Drug Administration, pharmacogenomics has now moved from the laboratory to the patient bedside. Over 100 drug-products now contain pharmacogenomic information as part of their labeling. Many of these are commonly used in the pediatric population. Direct-to-consumer genetic test kits also require intervention and guidance from healthcare professionals. This increased trend towards personalized medicine mandates that healthcare professionals develop a working knowledge about pharmacogenomics and its application towards patient care. Because pharmacogenomic testing can provide patient-specific predictors for response to and safety of medications, pharmacists are positioned to play an active role in pharmacogenomic testing, clinical interpretation of results, and recommendations for individualization of drug therapy. Opportunities for pharmacists exist in both inpatient and outpatient settings, such as pharmacist-managed clinical pharmacogenomics consultation services and educating patients and families about pharmacogenomic testing. In addition to clinical roles, pharmacists may also be involved in genetically-influenced drug discovery and development. Given the potential for genetic and age-dependent factors to influence drug selection and dosing, pediatric pharmacists should be involved in the development of dosing recommendations and interprofessional practice guidelines regarding pharmacogenomic testing in pediatric patients. Opportunities to become knowledgeable and competent in pharmacogenomics span from coursework as part of the pharmacy curriculum to postgraduate education (e.g., residencies, fellowships, continuing education). However, there exists a need for additional postgraduate learning opportunities for practicing pharmacists. As a result, the Pediatric Pharmacy Advocacy Group (PPAG) acknowledges a need for increased education of both student and practicing pharmacists, with consideration of special patient populations, such as infants and children. PPAG endorses and advocates for the involvement of pediatric pharmacists in pharmacogenomic testing and in using those results to provide safe and effective medication use in pediatric patients of all ages. Additionally, PPAG strongly encourages pediatric pharmacists to take responsibility for educating patients and their families about the importance of pharmacogenomic testing and its role in the safe and effective use of medications.
pediatrics; personalized medicine; pharmacist; pharmacogenomics; testing
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Mapping the Incidentalome: Estimating Incidental Findings Generated Through Clinical Pharmacogenomics Testing
Westbrook, Matthew J.
Wright, M. Frances
Van Driest, Sara L.
McGregor, Tracy L.
Denny, Joshua C.
Zuvich, Rebecca L.
Clayton, Ellen Wright
Brothers, Kyle B.
Genetics in medicine : official journal of the American College of Medical Genetics
Greater clinical validity and economic feasibility are driving the more widespread use of multiplex genetic technologies in routine clinical care, especially for pharmacogenomics applications. Empirical data on the numbers and types of incidental findings generated through such testing are needed so that policies and practices for their clinical use can be developed. Of particular importance are disparities in findings relevant to different ancestry groups.
The Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment Resource (PREDICT) is an institutional program to implement prospective clinical genotyping of 34 pharmacogenomic-related genes to guide drug selection and dosing. We curated 5566 journal articles to quantify and characterize the incidental, non-pharmacogenomic genotype-phenotype associations that could be generated through this clinical genotyping project.
We identified 372 putative incidental genotype-phenotype associations that might be revealed in patients undergoing clinical genotyping for pharmacogenomic purposes. Of these, 287 associations were supported by at least one study demonstrating an odds ratio ≥2.0 or ≤0.5. Numbers of potentially relevant findings varied widely by ancestry group.
Rigorous clinical policies for the clinical management of incidental findings are needed since the sheer number of significant findings could prove overwhelming to healthcare institutions, providers, and patients.
Incidental Findings; Incidentalome; Pharmacogenomics; Disease Susceptibility; Genomics
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Pharmacogenomics: Application to the Management of Cardiovascular Disease
Johnson, JA
Cavallari, LH
Beitelshees, AL
Lewis, JP
Shuldiner, AR
Roden, DM
Clinical pharmacology and therapeutics
The past decade has seen substantial advances in cardiovascular pharmacogenomics. Genetic determinants of response to clopidogrel and warfarin have been defined, resulting in changes to the product labels for these drugs that suggest the use of genetic information as a guide for therapy. Genetic tests are available, as are guidelines for incorporation of genetic information into patient-care decisions. These guidelines and the literature supporting them are reviewed herein. Significant advances have also been made in the pharmacogenomics of statin-induced myopathy and the response to β-blockers in heart failure, although the clinical applications of these findings are less clear. Other areas hold promise, including the pharmacogenomics of antihypertensive drugs, aspirin, and drug-induced long-QT syndrome (diLQTS). The potential value of pharmacogenomics in the discovery and development of new drugs is also described. In summary, pharmacogenomics has current applications in the management of cardiovascular disease, with clinically relevant data continuing to mount.
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Chapter 7: Pharmacogenomics
Karczewski, Konrad J.
Daneshjou, Roxana
Altman, Russ B.
PLoS Computational Biology
There is great variation in drug-response phenotypes, and a "one size fits all" paradigm for drug delivery is flawed. Pharmacogenomics is the study of how human genetic information impacts drug response, and it aims to improve efficacy and reduced side effects. In this article, we provide an overview of pharmacogenetics, including pharmacokinetics (PK), pharmacodynamics (PD), gene and pathway interactions, and off-target effects. We describe methods for discovering genetic factors in drug response, including genome-wide association studies (GWAS), expression analysis, and other methods such as chemoinformatics and natural language processing (NLP). We cover the practical applications of pharmacogenomics both in the pharmaceutical industry and in a clinical setting. In drug discovery, pharmacogenomics can be used to aid lead identification, anticipate adverse events, and assist in drug repurposing efforts. Moreover, pharmacogenomic discoveries show promise as important elements of physician decision support. Finally, we consider the ethical, regulatory, and reimbursement challenges that remain for the clinical implementation of pharmacogenomics.
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Assessing the cost-effectiveness of pharmacogenomics
Veenstra, David L.
Higashi, Mitchell K.
Phillips, Kathryn A.
AAPS PharmSci
The use of pharmacogenomics to individualize drug therapy offers the potential to improve drug effectiveness, reduce adverse side effects, and provide cost-effective pharmaceutical care. However, the combinations of disease, drug, and genetic test characteristics that will provide clinically useful and economically feasible therapeutic interventions have not been clearly elucidated. The purpose of this paper was to develop a framework for evaluating the potential cost-effectiveness of pharmacogenomic strategies that will help scientists better understand the strategic implications of their research assist in the design of clinical trials, and provide a guide for health care providers making reimbursement decisions. We reviewed concepts of cost-effectiveness analysis and pharmacogenomics and identified 5 primary characteristics that will enhance the cost-effectiveness of pharmacogenomics: 1) there are severe clinical or economic consequence that are avoided through the use of pharmacogenomics, 2) monitoring drug response using current methods is difficult, 3) a well-established association between genotype and clinical phenotype exists, 4) there is a rapid and relatively inexpensive genetic test, and 5) the variant gene is relatively common. We use this framework to evaluate several examples of pharmacogenomics. We found that pharmacogenomics offers great potential to improve patients' health in a cost-effective manner. However, pharmacogenomics will not be applied to all currently marketed drugs, and careful evaluations are needed on a case-by-case basis before investing resources in research and development of pharmacogenomic-based therapeutics and making reimbursement decisions.
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Pharmacogenomics in Early Phase Oncology Clinical Trials: Is There a Sweet Spot in Phase II?
O'Donnell, Peter H.
Stadler, Walter M.
Clinical Cancer Research
Many clinical trials of oncology drugs now include at least a consideration of pharmacogenomics, the study of germline or acquired genetic factors governing a drug's response and toxicity. Besides the potential benefit to patients from the consideration of personalized pharmacogenomic information when making treatment decisions, there is a clear incentive for oncology drug developers to incorporate pharmacogenomic factors in the drug development process since pharmacogenomic biomarkers may allow predictive characterization of sub-populations within a disease that may particularly respond, or may allow preidentification of patients at highest risk for adverse events. There is, however, a lack of agreement in actual practice as to where in the oncology clinical drug development process pharmacogenomic studies should be incorporated. In this article, we examine the recent growth of pharmacogenomics in oncology clinical trials, especially in early phase studies, and examine several critical questions facing the incorporation of pharmacogenomics in early oncologic drug development. We show that phase II clinical trials in particular have a favorable track record for demonstrating positive pharmacogenomic signals, worthy of additional follow-up and validation, and that the phase II setting holds significant promise for potentially accelerating and informing future phase III trials. We conclude that phase II trials offer an ideal "sweet spot" for routine incorporation of pharmacogenomic questions in oncology drug development.
phase II; oncology; clinical trials; pharmacogenomics; biomarker development
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Internet-Based Device-Assisted Remote Monitoring of Cardiovascular Implantable Electronic Devices
Pron, G
Ieraci, L
Kaulback, K
Ontario Health Technology Assessment Series
Executive Summary
The objective of this Medical Advisory Secretariat (MAS) report was to conduct a systematic review of the available published evidence on the safety, effectiveness, and cost-effectiveness of Internet-based device-assisted remote monitoring systems (RMSs) for therapeutic cardiac implantable electronic devices (CIEDs) such as pacemakers (PMs), implantable cardioverter-defibrillators (ICDs), and cardiac resynchronization therapy (CRT) devices. The MAS evidence-based review was performed to support public financing decisions.
Clinical Need: Condition and Target Population
Sudden cardiac death (SCD) is a major cause of fatalities in developed countries. In the United States almost half a million people die of SCD annually, resulting in more deaths than stroke, lung cancer, breast cancer, and AIDS combined. In Canada each year more than 40,000 people die from a cardiovascular related cause; approximately half of these deaths are attributable to SCD.
Most cases of SCD occur in the general population typically in those without a known history of heart disease. Most SCDs are caused by cardiac arrhythmia, an abnormal heart rhythm caused by malfunctions of the heart's electrical system. Up to half of patients with significant heart failure (HF) also have advanced conduction abnormalities.
Cardiac arrhythmias are managed by a variety of drugs, ablative procedures, and therapeutic CIEDs. The range of CIEDs includes pacemakers (PMs), implantable cardioverter-defibrillators (ICDs), and cardiac resynchronization therapy (CRT) devices. Bradycardia is the main indication for PMs and individuals at high risk for SCD are often treated by ICDs.
Heart failure (HF) is also a significant health problem and is the most frequent cause of hospitalization in those over 65 years of age. Patients with moderate to severe HF may also have cardiac arrhythmias, although the cause may be related more to heart pump or haemodynamic failure. The presence of HF, however, increases the risk of SCD five-fold, regardless of aetiology. Patients with HF who remain highly symptomatic despite optimal drug therapy are sometimes also treated with CRT devices.
With an increasing prevalence of age-related conditions such as chronic HF and the expanding indications for ICD therapy, the rate of ICD placement has been dramatically increasing. The appropriate indications for ICD placement, as well as the rate of ICD placement, are increasingly an issue. In the United States, after the introduction of expanded coverage of ICDs, a national ICD registry was created in 2005 to track these devices. A recent survey based on this national ICD registry reported that 22.5% (25,145) of patients had received a non-evidence based ICD and that these patients experienced significantly higher in-hospital mortality and post-procedural complications.
In addition to the increased ICD device placement and the upfront device costs, there is the need for lifelong follow-up or surveillance, placing a significant burden on patients and device clinics. In 2007, over 1.6 million CIEDs were implanted in Europe and the United States, which translates to over 5.5 million patient encounters per year if the recommended follow-up practices are considered. A safe and effective RMS could potentially improve the efficiency of long-term follow-up of patients and their CIEDs.
In addition to being therapeutic devices, CIEDs have extensive diagnostic abilities. All CIEDs can be interrogated and reprogrammed during an in-clinic visit using an inductive programming wand. Remote monitoring would allow patients to transmit information recorded in their devices from the comfort of their own homes. Currently most ICD devices also have the potential to be remotely monitored. Remote monitoring (RM) can be used to check system integrity, to alert on arrhythmic episodes, and to potentially replace in-clinic follow-ups and manage disease remotely. They do not currently have the capability of being reprogrammed remotely, although this feature is being tested in pilot settings.
Every RMS is specifically designed by a manufacturer for their cardiac implant devices. For Internet-based device-assisted RMSs, this customization includes details such as web application, multiplatform sensors, custom algorithms, programming information, and types and methods of alerting patients and/or physicians. The addition of peripherals for monitoring weight and pressure or communicating with patients through the onsite communicators also varies by manufacturer. Internet-based device-assisted RMSs for CIEDs are intended to function as a surveillance system rather than an emergency system.
Health care providers therefore need to learn each application, and as more than one application may be used at one site, multiple applications may need to be reviewed for alarms. All RMSs deliver system integrity alerting; however, some systems seem to be better geared to fast arrhythmic alerting, whereas other systems appear to be more intended for remote follow-up or supplemental remote disease management. The different RMSs may therefore have different impacts on workflow organization because of their varying frequency of interrogation and methods of alerts. The integration of these proprietary RM web-based registry systems with hospital-based electronic health record systems has so far not been commonly implemented.
Currently there are 2 general types of RMSs: those that transmit device diagnostic information automatically and without patient assistance to secure Internet-based registry systems, and those that require patient assistance to transmit information. Both systems employ the use of preprogrammed alerts that are either transmitted automatically or at regular scheduled intervals to patients and/or physicians.
The current web applications, programming, and registry systems differ greatly between the manufacturers of transmitting cardiac devices. In Canada there are currently 4 manufacturers—Medtronic Inc., Biotronik, Boston Scientific Corp., and St Jude Medical Inc.—which have regulatory approval for remote transmitting CIEDs. Remote monitoring systems are proprietary to the manufacturer of the implant device. An RMS for one device will not work with another device, and the RMS may not work with all versions of the manufacturer's devices.
All Internet-based device-assisted RMSs have common components. The implanted device is equipped with a micro-antenna that communicates with a small external device (at bedside or wearable) commonly known as the transmitter. Transmitters are able to interrogate programmed parameters and diagnostic data stored in the patients' implant device. The information transfer to the communicator can occur at preset time intervals with the participation of the patient (waving a wand over the device) or it can be sent automatically (wirelessly) without their participation. The encrypted data are then uploaded to an Internet-based database on a secure central server. The data processing facilities at the central database, depending on the clinical urgency, can trigger an alert for the physician(s) that can be sent via email, fax, text message, or phone. The details are also posted on the secure website for viewing by the physician (or their delegate) at their convenience.
Research Questions
The research directions and specific research questions for this evidence review were as follows:
To identify the Internet-based device-assisted RMSs available for follow-up of patients with therapeutic CIEDs such as PMs, ICDs, and CRT devices.
To identify the potential risks, operational issues, or organizational issues related to Internet-based device-assisted RM for CIEDs.
To evaluate the safety, acceptability, and effectiveness of Internet-based device-assisted RMSs for CIEDs such as PMs, ICDs, and CRT devices.
To evaluate the safety, effectiveness, and cost-effectiveness of Internet-based device-assisted RMSs for CIEDs compared to usual outpatient in-office monitoring strategies.
To evaluate the resource implications or budget impact of RMSs for CIEDs in Ontario, Canada.
Research Methods
Literature Search
The review included a systematic review of published scientific literature and consultations with experts and manufacturers of all 4 approved RMSs for CIEDs in Canada. Information on CIED cardiac implant clinics was also obtained from Provincial Programs, a division within the Ministry of Health and Long-Term Care with a mandate for cardiac implant specialty care. Various administrative databases and registries were used to outline the current clinical follow-up burden of CIEDs in Ontario. The provincial population-based ICD database developed and maintained by the Institute for Clinical Evaluative Sciences (ICES) was used to review the current follow-up practices with Ontario patients implanted with ICD devices.
Search Strategy
A literature search was performed on September 21, 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from 1950 to September 2010. Search alerts were generated and reviewed for additional relevant literature until December 31, 2010. Abstracts were reviewed by a single reviewer and, for those studies meeting the eligibility criteria full-text articles were obtained. Reference lists were also examined for any additional relevant studies not identified through the search.
Inclusion Criteria
published between 1950 and September 2010;
English language full-reports and human studies;
original reports including clinical evaluations of Internet-based device-assisted RMSs for CIEDs in clinical settings;
reports including standardized measurements on outcome events such as technical success, safety, effectiveness, cost, measures of health care utilization, morbidity, mortality, quality of life or patient satisfaction;
randomized controlled trials (RCTs), systematic reviews and meta-analyses, cohort and controlled clinical studies.
Exclusion Criteria
non-systematic reviews, letters, comments and editorials;
reports not involving standardized outcome events;
clinical reports not involving Internet-based device assisted RM systems for CIEDs in clinical settings;
reports involving studies testing or validating algorithms without RM;
studies with small samples (<10 subjects).
Outcomes of Interest
The outcomes of interest included: technical outcomes, emergency department visits, complications, major adverse events, symptoms, hospital admissions, clinic visits (scheduled and/or unscheduled), survival, morbidity (disease progression, stroke, etc.), patient satisfaction, and quality of life.
Summary of Findings
The MAS evidence review was performed to review available evidence on Internet-based device-assisted RMSs for CIEDs published until September 2010. The search identified 6 systematic reviews, 7 randomized controlled trials, and 19 reports for 16 cohort studies—3 of these being registry-based and 4 being multi-centered. The evidence is summarized in the 3 sections that follow.
1. Effectiveness of Remote Monitoring Systems of CIEDs for Cardiac Arrhythmia and Device Functioning
In total, 15 reports on 13 cohort studies involving investigations with 4 different RMSs for CIEDs in cardiology implant clinic groups were identified in the review. The 4 RMSs were: Care Link Network® (Medtronic Inc,, Minneapolis, MN, USA); Home Monitoring® (Biotronic, Berlin, Germany); House Call 11® (St Jude Medical Inc., St Pauls, MN, USA); and a manufacturer-independent RMS. Eight of these reports were with the Home Monitoring® RMS (12,949 patients), 3 were with the Care Link® RMS (167 patients), 1 was with the House Call 11® RMS (124 patients), and 1 was with a manufacturer-independent RMS (44 patients). All of the studies, except for 2 in the United States, (1 with Home Monitoring® and 1 with House Call 11®), were performed in European countries.
The RMSs in the studies were evaluated with different cardiac implant device populations: ICDs only (6 studies), ICD and CRT devices (3 studies), PM and ICD and CRT devices (4 studies), and PMs only (2 studies). The patient populations were predominately male (range, 52%–87%) in all studies, with mean ages ranging from 58 to 76 years. One study population was unique in that RMSs were evaluated for ICDs implanted solely for primary prevention in young patients (mean age, 44 years) with Brugada syndrome, which carries an inherited increased genetic risk for sudden heart attack in young adults.
Most of the cohort studies reported on the feasibility of RMSs in clinical settings with limited follow-up. In the short follow-up periods of the studies, the majority of the events were related to detection of medical events rather than system configuration or device abnormalities. The results of the studies are summarized below:
The interrogation of devices on the web platform, both for continuous and scheduled transmissions, was significantly quicker with remote follow-up, both for nurses and physicians.
In a case-control study focusing on a Brugada population–based registry with patients followed-up remotely, there were significantly fewer outpatient visits and greater detection of inappropriate shocks. One death occurred in the control group not followed remotely and post-mortem analysis indicated early signs of lead failure prior to the event.
Two studies examined the role of RMSs in following ICD leads under regulatory advisory in a European clinical setting and noted:
– Fewer inappropriate shocks were administered in the RM group.
– Urgent in-office interrogations and surgical revisions were performed within 12 days of remote alerts.
– No signs of lead fracture were detected at in-office follow-up; all were detected at remote follow-up.
Only 1 study reported evaluating quality of life in patients followed up remotely at 3 and 6 months; no values were reported.
Patient satisfaction was evaluated in 5 cohort studies, all in short term follow-up: 1 for the Home Monitoring® RMS, 3 for the Care Link® RMS, and 1 for the House Call 11® RMS.
– Patients reported receiving a sense of security from the transmitter, a good relationship with nurses and physicians, positive implications for their health, and satisfaction with RM and organization of services.
– Although patients reported that the system was easy to implement and required less than 10 minutes to transmit information, a variable proportion of patients (range, 9% 39%) reported that they needed the assistance of a caregiver for their transmission.
– The majority of patients would recommend RM to other ICD patients.
– Patients with hearing or other physical or mental conditions hindering the use of the system were excluded from studies, but the frequency of this was not reported.
Physician satisfaction was evaluated in 3 studies, all with the Care Link® RMS:
– Physicians reported an ease of use and high satisfaction with a generally short-term use of the RMS.
– Physicians reported being able to address the problems in unscheduled patient transmissions or physician initiated transmissions remotely, and were able to handle the majority of the troubleshooting calls remotely.
– Both nurses and physicians reported a high level of satisfaction with the web registry system.
2. Effectiveness of Remote Monitoring Systems in Heart Failure Patients for Cardiac Arrhythmia and Heart Failure Episodes
Remote follow-up of HF patients implanted with ICD or CRT devices, generally managed in specialized HF clinics, was evaluated in 3 cohort studies: 1 involved the Home Monitoring® RMS and 2 involved the Care Link® RMS. In these RMSs, in addition to the standard diagnostic features, the cardiac devices continuously assess other variables such as patient activity, mean heart rate, and heart rate variability. Intra-thoracic impedance, a proxy measure for lung fluid overload, was also measured in the Care Link® studies. The overall diagnostic performance of these measures cannot be evaluated, as the information was not reported for patients who did not experience intra-thoracic impedance threshold crossings or did not undergo interventions. The trial results involved descriptive information on transmissions and alerts in patients experiencing high morbidity and hospitalization in the short study periods.
3. Comparative Effectiveness of Remote Monitoring Systems for CIEDs
Seven RCTs were identified evaluating RMSs for CIEDs: 2 were for PMs (1276 patients) and 5 were for ICD/CRT devices (3733 patients). Studies performed in the clinical setting in the United States involved both the Care Link® RMS and the Home Monitoring® RMS, whereas all studies performed in European countries involved only the Home Monitoring® RMS.
3A. Randomized Controlled Trials of Remote Monitoring Systems for Pacemakers
Two trials, both multicenter RCTs, were conducted in different countries with different RMSs and study objectives. The PREFER trial was a large trial (897 patients) performed in the United States examining the ability of Care Link®, an Internet-based remote PM interrogation system, to detect clinically actionable events (CAEs) sooner than the current in-office follow-up supplemented with transtelephonic monitoring transmissions, a limited form of remote device interrogation. The trial results are summarized below:
In the 375-day mean follow-up, 382 patients were identified with at least 1 CAE—111 patients in the control arm and 271 in the remote arm.
The event rate detected per patient for every type of CAE, except for loss of atrial capture, was higher in the remote arm than the control arm.
The median time to first detection of CAEs (4.9 vs. 6.3 months) was significantly shorter in the RMS group compared to the control group (P < 0.0001).
Additionally, only 2% (3/190) of the CAEs in the control arm were detected during a transtelephonic monitoring transmission (the rest were detected at in-office follow-ups), whereas 66% (446/676) of the CAEs were detected during remote interrogation.
The second study, the OEDIPE trial, was a smaller trial (379 patients) performed in France evaluating the ability of the Home Monitoring® RMS to shorten PM post-operative hospitalization while preserving the safety of conventional management of longer hospital stays.
Implementation and operationalization of the RMS was reported to be successful in 91% (346/379) of the patients and represented 8144 transmissions.
In the RM group 6.5% of patients failed to send messages (10 due to improper use of the transmitter, 2 with unmanageable stress). Of the 172 patients transmitting, 108 patients sent a total of 167 warnings during the trial, with a greater proportion of warnings being attributed to medical rather than technical causes.
Forty percent had no warning message transmission and among these, 6 patients experienced a major adverse event and 1 patient experienced a non-major adverse event. Of the 6 patients having a major adverse event, 5 contacted their physician.
The mean medical reaction time was faster in the RM group (6.5 ± 7.6 days vs. 11.4 ± 11.6 days).
The mean duration of hospitalization was significantly shorter (P < 0.001) for the RM group than the control group (3.2 ± 3.2 days vs. 4.8 ± 3.7 days).
Quality of life estimates by the SF-36 questionnaire were similar for the 2 groups at 1-month follow-up.
3B. Randomized Controlled Trials Evaluating Remote Monitoring Systems for ICD or CRT Devices
The 5 studies evaluating the impact of RMSs with ICD/CRT devices were conducted in the United States and in European countries and involved 2 RMSs—Care Link® and Home Monitoring ®. The objectives of the trials varied and 3 of the trials were smaller pilot investigations.
The first of the smaller studies (151 patients) evaluated patient satisfaction, achievement of patient outcomes, and the cost-effectiveness of the Care Link® RMS compared to quarterly in-office device interrogations with 1-year follow-up.
Individual outcomes such as hospitalizations, emergency department visits, and unscheduled clinic visits were not significantly different between the study groups.
Except for a significantly higher detection of atrial fibrillation in the RM group, data on ICD detection and therapy were similar in the study groups.
Health-related quality of life evaluated by the EuroQoL at 6-month or 12-month follow-up was not different between study groups.
Patients were more satisfied with their ICD care in the clinic follow-up group than in the remote follow-up group at 6-month follow-up, but were equally satisfied at 12- month follow-up.
The second small pilot trial (20 patients) examined the impact of RM follow-up with the House Call 11® system on work schedules and cost savings in patients randomized to 2 study arms varying in the degree of remote follow-up.
The total time including device interrogation, transmission time, data analysis, and physician time required was significantly shorter for the RM follow-up group.
The in-clinic waiting time was eliminated for patients in the RM follow-up group.
The physician talk time was significantly reduced in the RM follow-up group (P < 0.05).
The time for the actual device interrogation did not differ in the study groups.
The third small trial (115 patients) examined the impact of RM with the Home Monitoring® system compared to scheduled trimonthly in-clinic visits on the number of unplanned visits, total costs, health-related quality of life (SF-36), and overall mortality.
There was a 63.2% reduction in in-office visits in the RM group.
Hospitalizations or overall mortality (values not stated) were not significantly different between the study groups.
Patient-induced visits were higher in the RM group than the in-clinic follow-up group.
The TRUST Trial
The TRUST trial was a large multicenter RCT conducted at 102 centers in the United States involving the Home Monitoring® RMS for ICD devices for 1450 patients. The primary objectives of the trial were to determine if remote follow-up could be safely substituted for in-office clinic follow-up (3 in-office visits replaced) and still enable earlier physician detection of clinically actionable events.
Adherence to the protocol follow-up schedule was significantly higher in the RM group than the in-office follow-up group (93.5% vs. 88.7%, P < 0.001).
Actionability of trimonthly scheduled checks was low (6.6%) in both study groups. Overall, actionable causes were reprogramming (76.2%), medication changes (24.8%), and lead/system revisions (4%), and these were not different between the 2 study groups.
The overall mean number of in-clinic and hospital visits was significantly lower in the RM group than the in-office follow-up group (2.1 per patient-year vs. 3.8 per patient-year, P < 0.001), representing a 45% visit reduction at 12 months.
The median time from onset of first arrhythmia to physician evaluation was significantly shorter (P < 0.001) in the RM group than in the in-office follow-up group for all arrhythmias (1 day vs. 35.5 days).
The median time to detect clinically asymptomatic arrhythmia events—atrial fibrillation (AF), ventricular fibrillation (VF), ventricular tachycardia (VT), and supra-ventricular tachycardia (SVT)—was also significantly shorter (P < 0.001) in the RM group compared to the in-office follow-up group (1 day vs. 41.5 days) and was significantly quicker for each of the clinical arrhythmia events—AF (5.5 days vs. 40 days), VT (1 day vs. 28 days), VF (1 day vs. 36 days), and SVT (2 days vs. 39 days).
System-related problems occurred infrequently in both groups—in 1.5% of patients (14/908) in the RM group and in 0.7% of patients (3/432) in the in-office follow-up group.
The overall adverse event rate over 12 months was not significantly different between the 2 groups and individual adverse events were also not significantly different between the RM group and the in-office follow-up group: death (3.4% vs. 4.9%), stroke (0.3% vs. 1.2%), and surgical intervention (6.6% vs. 4.9%), respectively.
The 12-month cumulative survival was 96.4% (95% confidence interval [CI], 95.5%–97.6%) in the RM group and 94.2% (95% confidence interval [CI], 91.8%–96.6%) in the in-office follow-up group, and was not significantly different between the 2 groups (P = 0.174).
The CONNECT Trial
The CONNECT trial, another major multicenter RCT, involved the Care Link® RMS for ICD/CRT devices in a15-month follow-up study of 1,997 patients at 133 sites in the United States. The primary objective of the trial was to determine whether automatically transmitted physician alerts decreased the time from the occurrence of clinically relevant events to medical decisions. The trial results are summarized below:
Of the 575 clinical alerts sent in the study, 246 did not trigger an automatic physician alert. Transmission failures were related to technical issues such as the alert not being programmed or not being reset, and/or a variety of patient factors such as not being at home and the monitor not being plugged in or set up.
The overall mean time from the clinically relevant event to the clinical decision was significantly shorter (P < 0.001) by 17.4 days in the remote follow-up group (4.6 days for 172 patients) than the in-office follow-up group (22 days for 145 patients).
– The median time to a clinical decision was shorter in the remote follow-up group than in the in-office follow-up group for an AT/AF burden greater than or equal to 12 hours (3 days vs. 24 days) and a fast VF rate greater than or equal to 120 beats per minute (4 days vs. 23 days).
Although infrequent, similar low numbers of events involving low battery and VF detection/therapy turned off were noted in both groups. More alerts, however, were noted for out-of-range lead impedance in the RM group (18 vs. 6 patients), and the time to detect these critical events was significantly shorter in the RM group (same day vs. 17 days).
Total in-office clinic visits were reduced by 38% from 6.27 visits per patient-year in the in-office follow-up group to 3.29 visits per patient-year in the remote follow-up group.
Health care utilization visits (N = 6,227) that included cardiovascular-related hospitalization, emergency department visits, and unscheduled clinic visits were not significantly higher in the remote follow-up group.
The overall mean length of hospitalization was significantly shorter (P = 0.002) for those in the remote follow-up group (3.3 days vs. 4.0 days) and was shorter both for patients with ICD (3.0 days vs. 3.6 days) and CRT (3.8 days vs. 4.7 days) implants.
The mortality rate between the study arms was not significantly different between the follow-up groups for the ICDs (P = 0.31) or the CRT devices with defribillator (P = 0.46).
There is limited clinical trial information on the effectiveness of RMSs for PMs. However, for RMSs for ICD devices, multiple cohort studies and 2 large multicenter RCTs demonstrated feasibility and significant reductions in in-office clinic follow-ups with RMSs in the first year post implantation. The detection rates of clinically significant events (and asymptomatic events) were higher, and the time to a clinical decision for these events was significantly shorter, in the remote follow-up groups than in the in-office follow-up groups. The earlier detection of clinical events in the remote follow-up groups, however, was not associated with lower morbidity or mortality rates in the 1-year follow-up. The substitution of almost all the first year in-office clinic follow-ups with RM was also not associated with an increased health care utilization such as emergency department visits or hospitalizations.
The follow-up in the trials was generally short-term, up to 1 year, and was a more limited assessment of potential longer term device/lead integrity complications or issues. None of the studies compared the different RMSs, particularly the different RMSs involving patient-scheduled transmissions or automatic transmissions. Patients' acceptance of and satisfaction with RM were reported to be high, but the impact of RM on patients' health-related quality of life, particularly the psychological aspects, was not evaluated thoroughly. Patients who are not technologically competent, having hearing or other physical/mental impairments, were identified as potentially disadvantaged with remote surveillance. Cohort studies consistently identified subgroups of patients who preferred in-office follow-up. The evaluation of costs and workflow impact to the health care system were evaluated in European or American clinical settings, and only in a limited way.
Internet-based device-assisted RMSs involve a new approach to monitoring patients, their disease progression, and their CIEDs. Remote monitoring also has the potential to improve the current postmarket surveillance systems of evolving CIEDs and their ongoing hardware and software modifications. At this point, however, there is insufficient information to evaluate the overall impact to the health care system, although the time saving and convenience to patients and physicians associated with a substitution of in-office follow-up by RM is more certain. The broader issues surrounding infrastructure, impacts on existing clinical care systems, and regulatory concerns need to be considered for the implementation of Internet-based RMSs in jurisdictions involving different clinical practices.
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text:
Andrew Davidson (Army surgeon)
From Wikipedia, the free encyclopedia
|Andrew Davidson
July 1, 1819
Middlebury, Vermont
|June 30, 1901
(aged 81)-->
Lancaster, Ohio
|Buried at
|Forest Rose Cemetery
|United States of America
|United States Army
|Years of service
|January 28, 1863 to July 26, 1863
|Assistant Surgeon
|47th Ohio Infantry
|Battle of Vicksburg
|Medal of Honor
Assistant Surgeon Andrew Davidson (July 1, 1819 to June 30, 1901) was an American soldier who fought in the American Civil War. Davidson received the country's highest award for bravery during combat, the Medal of Honor, for his action during the Battle of Vicksburg in Mississippi on 3 May 1863. He was honored with the award on 17 October 1892.[1][2][3]
Davidson was born in Middlebury, Vermont on 1 July 1819. He enlisted into the 47th Ohio Infantry. He died on 30 June 1901 and his remains are interred at the Forest Rose Cemetery in Ohio.[4]
Medal of Honor citation[edit]
See also[edit]
- ^ a b "Civil War (A-L) Medal of Honor Recipients". Retrieved 7 December 2013.
- ^ a b "Andrew Davidson". Retrieved 7 December 2013.
- ^ "U.S. Army Medal of Honor Recipients". Retrieved 7 December 2013.
- ^ "Andrew Davidson is buried in Forest Rose Cemetery, Lancaster, OH 43130" (PDF). Retrieved 7 December 2013.


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