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Disclosures | Hypertension, Preeclampsia | HYPERTENSION, PREECLAMPSIA | A. Jeyabalan declares Grants or contracts from Mirvie, Inc (Miracle of Life Study) to work as Site PI—overseeing sample collection for a sponsored research agreement between UPMC and Mirvie and Royalties or licenses with UpToDate to work as coauthor of 2 topics—Prevention of Preeclampsia and Chronic Hypertension in Pregnancy. K. Blount declares a contribution to salary paid by Bill and Melinda Gates Foundation to Magee-Womens Research Institute. P.T. Seed declares a contribution to salary paid by Bill and Melinda Gates Foundation to KCL. | PMC10510842 |
Supplemental Material | Supplemental MethodsParticipating centersProceduresKnowledge transfer programData safety and monitoring committee (DMC)Tables S1–S7Figure S1 | PMC10510842 |
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Supplementary Material | PMC10510842 |
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Nonstandard Abbreviations and Acronyms | Preterm Preeclampsia, Preeclampsia | APPENDIX, PREECLAMPSIA | adjusted odds ratioPreeclampsia Integrated Estimate of RiskPlanned Early Delivery or Expectant Management for Late Preterm Preeclampsia Trialplacental growth factorPrematurity Reduction by Preeclampsia Caresoluble fms-like tyrosine kinase-1For Sources of Funding and Disclosures, see page 2027.L.C. Chappell and M.A.B. Dias contributed equally.A list of all PREPARE trial group members is given in the Appendix.Supplemental Material is available at | PMC10510842 |
APPENDIX | PREPARE Trial group: Guilherme de Jesús MD, PhD; Wallace Mendes-Silva, MD; José Guilherme Cecatti, MD, PhD; Maria Laura Costa, MD, PhD; José Paulo Guida, MD, PhD; Lucienne Frayha, MD; Corintio Mariani-Neto, MD, PhD; Marcos Antonio Nogueira Santos, MD; José Geraldo Lopes Ramos, MD, PhD; Sérgio Hofmeister Martins-Costa, MD, PhD; José Carlos Peraçoli, MD, PhD; Roberto Antonio de Araújo Costa, MD, PhD; Francisco Lázaro Pereira de Sousa, MD, PhD | PMC10510842 |
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REFERENCES | PMC10510842 |
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Background and Aims: | To achieve the World Health Organization’s goal of eliminating HCV by 2030, reengagement of lost to follow-up cases is mandatory. However, there is lack of evidence concerning the best strategy. Our study evaluated the effectiveness, efficiency, predictive factors, and costs of 2 different strategies. | PMC10538908 |
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Methods: | NCT04153708 | We identified patients positive for HCV antibodies without RNA requests from 2005 to 2018. Patients fulfilling trial criteria (NCT04153708) were randomized to (1) phone call or (2) letter of invitation to schedule an appointment, followed by switching strategy. | PMC10538908 |
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Results: | Three hundred forty-five patients among 1167 lost to follow-up were identified. An analysis of the first 270 randomized patients (72% male, 51±13 y) showed a higher contact rate in the mail than in the phone call strategy (84.5% vs. 50.3%). In the intention-to-treat analysis, no differences were found related to appointment attendance (26.5% vs. 28.5%). Regarding efficiency, 3.1 letters and 8 phone calls were needed to successfully link 1 patient ( | PMC10538908 |
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Conclusions: | Reengagement of patients with HCV is feasible, and equally effective with similar costs in both strategies. The mail letter was more efficient, except when only 1 phone call was considered. Prior specialist’s evaluation and testing in the predirect-acting antiviral era were factors associated with nonattendance to the appointment. | PMC10538908 |
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INTRODUCTION | HCV infection | CHRONIC LIVER DISEASE | HCV infection is a major public health problem and a leading cause of chronic liver disease. | PMC10538908 |
METHODS | PMC10538908 |
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Study design | deaths, comorbidity, HBV and HIV tests | LIVER FIBROSIS, HIV COINFECTION | Microbiology data files from patients seen between 2005 and 2018 at our tertiary center (Hospital Universitario de Canarias), which serves a population of ~400,000 subjects, were retrospectively reviewed. From all the cases with positive HCV antibodies, we identified those with positive HCV antibodies but without RNA investigation, therefore, unknown RNA.After excluding deaths from potential candidates for reengagement, we included those fulfilling the following criteria: older than 18 years old, without regular (at least once a year) specialist (internal medicine or hepatology) follow-ups, without HIV coinfection, nondependent people for daily living activities, with enough data available to be contacted (by phone and mail), and those who remain in our health care area. The contact information was gathered from the administrative data records of the patients, which are usually updated after any health-related consultation, including routine blood tests. When the residency address was no longer in our catchment health area, the patient was considered moved to another health area.Randomization in a 1:1 ratio (ClinicalTrials.gov, Number NCT04153708) was stratified by age and sex, undertaken in blocks of 50 patients, and assigned to any of the following 2 strategies: (1) phone call contact (up to 3 call attempts at different times from inside the hospital) to provide patients with an appointment or (2) mailed invitation letter with a scheduled appointment 10–14 days after receiving the letter. The letters and phone calls were carried out by nonmedical staff (administrative staff). Twenty letters were posted every week, and ~30 calls per day (3 d per week) were performed. In both strategies, the patient was informed about an abnormal laboratory finding and the need to schedule an appointment with a hepatologist for further evaluation. The information given was the same in both strategies, with scarce details in accordance with confidentiality. In addition, in cases where an answering machine or voicemail was encountered, no message was delivered. The letter content and the script used in the phone calls are available as Supplemental Material 1 and 2 (The number of phone calls needed to contact patients, wrong numbers, nonanswered calls, and returned-to-sender letters were registered. All patients had free access to the health care system called “Seguridad Social” in Spain, without cost for visits, complementary tests, and treatment, if needed.We registered age, sex, mortality, comorbidity, social support, date of the first positive antibody screen for HCV, previous HBV and HIV tests, transaminases at the time of serology request, history of i.v. or inhaled drug use, and previous specialist evaluation (hepatology or internal medicine department).Patients who showed up for the appointment were informed about the aims of the study, and informed consent was obtained. Patients who attended the appointment were fully evaluated through a fast-track service, which included elastography (Fibroscan, Echosens, France) and treatment prescription on the same day of the visit; if blood tests were needed for RNA investigation, a second appointment was scheduled within 2 weeks.Liver fibrosis was assessed using elastography, treatment prescription, and laboratory variables, including RNA results and HBV/HIV status were recorded. | PMC10538908 |
Effectiveness and efficiency analysis | SECONDARY | To compare both strategies, and as a primary aim of the study, we evaluated effectiveness as the rate of patients successfully linked to care (patients who showed up for the appointment with the specialist) and secondary efficiency by considering the number of contacts needed (total number of letters or phone calls) to successfully link 1 patient to care. | PMC10538908 |
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Sample size calculation | CORONAVIRUS, MAY | A sample size of 172 patients for each strategy was estimated, assuming a 15% increase in effectiveness (from 28% to 43%) of the phone call strategy over the mail strategy (power 80%, alpha error 5%) and a 10% lose in each intervention.For extraordinary reasons that may have influenced the results because of the nature of the study, an unplanned interim analysis was conducted on March 15th, 2020, 5 days before the national lockdown because of the coronavirus pandemic, which included 270 patients (78% of the planned sample size). One strategy was considered to have a statistically significant difference (The switch strategy was postponed after the lockdown was finished and normality arrived at hospital appointments (May 2021). | PMC10538908 |
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Statistics and analysis | Continuous variables were presented as mean (SD) or median (interquartile range) according to the distribution of the data. Categorical variables were presented as absolute frequencies and percentages. The chi-square test was used to compare qualitative variables. Continuous variables were analyzed using the Student Intention-to-treat (ITT) and PP analyses were performed. Patients who were successfully contacted were included in the PP analysis. Relative risk (RR) with CIs was calculated for efficiency evaluation.Statistical significance was set at | PMC10538908 |
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Cost-effectiveness analysis | An economic evaluation was performed to estimate the cost of each strategy. It was calculated taking into consideration the actual number of calls, the time dedicated to each call, the number of letters sent, and the time dedicated to sending them. The cost per minute of each call, together with the cost of the administrative staff making the calls was obtained from our Hospital Administrative Department (Supplementary Table 3, For cost-effectiveness analysis, a Markov model was designed with a time horizon of 10 years. Cost assessment was performed from the perspective of the Spanish National Health Service, considering direct health costs in both strategies as described. | PMC10538908 |
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Ethical aspects | This study was conducted in accordance with the ethical principles of the Declaration of Helsinki in October 2013 and approved on March 14, 2019, by The Ethics Committee of the Hospital Universitario de Canarias [code CHUC_2019_23 (VHC-ACTIVA)]. | PMC10538908 |
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RESULTS | PMC10538908 |
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Patient selection and baseline characteristics | HIV COINFECTION | Between 2005 and 2018, 4414 patients were positive for HCV antibodies, of whom 2734 (61.9%) had a negative RNA result or a positive then negative RNA result. After exclusion of 513 (11.6%) patients who died during the study period, 1167 patients were potential candidates for initial reengagement. Finally, 822 (70.4%) were excluded from the study: 713 patients moved to another health area, 53 had HIV coinfection, 35 patients did not have full contact data, 7 were under 18 years old, 12 were linked to care recently pending RNA test results, and 2 patients were dependent people for daily living activities with restricted mobility.Eventually, among the 345 patients fulfilling the criteria to be included in the study, 344 subjects (72.2% male, 51.1±12.9 y) were randomized into the 2 strategies. At the time of the interim analysis, 270 patients were analyzed: 123 patients (45.6%) in the mail strategy and 147 patients (54.4%) in the phone call strategy group (Figure Flow diagram of patient selection and randomization.Characteristics of randomized patients according to reengagement strategyAbbreviations: DAA, direct-acting antivirals; IQR, interquartile range.Included patients had a median of 7 (range 4–10) years with a positive HCV serology test, 181 (67%) had the HCV testing serology done before the DAA era, and 15% of patients were previously evaluated by a specialist. | PMC10538908 |
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Effectiveness of both strategies | In the phone call strategy, 15 (10.2%) patients had an incorrect phone number registered in the medical records, and 58 (39.4%) patients did not answer the phone call. Seven (4.8%) patients answered that they did not want to participate in the study. In the mail strategy, 19 (15.4%) letters failed to reach the registered address and were returned. Finally, 74 patients (50.3%) in the phone call strategy and 104 patients (84.5%) in the mail strategy (In the ITT analysis (n=270), there were no significant differences between the percentage of patients who showed up for the appointment with the specialist in the phone call strategy compared with the mail strategy (26.5% vs. 28.5%, respectively; Effectiveness of mail and phone call strategies for reengagement. Abbreviations: ITT, intention to treat, PP, per protocol.In the ITT analysis, patients who did not show up for the specialist appointment compared with patients who showed up for the appointment had a higher percentage of patients with a history of injected or inhaled drugs (45.1% vs. 37.8%, respectively; Characteristics of patients who attended the specialist appointment compared with patients who did not attend the appointment in ITT and PP analysisAbbreviations: DAA, direct-acting antivirals; IQR, interquartile range; ITT, intention to treat; PP, per protocol.In the ITT analysis, a prior specialist’s evaluation and HCV testing in the pre-DAA era were associated with not showing up for the appointment (Table Independent predictors for reengagement according to the strategy (ITT analysis)Abbreviations: DAA, direct-acting antivirals; ITT, intention-to-treat.Among patients who showed up for the appointment, there was no significant difference in the waiting time for a specialist appointment in the phone call strategy compared with the mail strategy (median 7 d, interquartile range 7–11 vs. 10 d, interquartile range 10–11, respectively; | PMC10538908 |
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Efficiency of both strategies | In the ITT analysis, 3.1 mailed letters and 8 phone calls were necessary to successfully link 1 patient to care with the specialist (RR: 2.53, 95% CI, 1.57–4.07, | PMC10538908 |
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Switching strategies | Of 270 patients and after excluding patients who attended the appointment (n=74) and patients who declined participation (n=12), 184 patients remained to be contacted and were switched to the other strategy. Because of the time gap until the switch was performed, 5 (2.7%) patients deceased and 18 (9.8%) received HCV treatment by other means while the study was paused. Finally, 161 (87.5%) patients were included (77% male, 51.4±12.9 y), 82 (51%) in the phone call strategy, and 79 (49%) in the mail letter strategy.Overall, 44 (53.7%) in the phone call strategy and 62 patients (78.5%) in the mail letter strategy group were successfully contacted (In the ITT analysis (n=161), there were no significant differences between the proportion of patients who showed up for the appointment in the phone call strategy compared with the mail letter strategy group (22% vs. 11.4%, Regarding efficiency, in the ITT analysis, 8.2 phone calls and 8.8 letters were needed to link to care with the hepatologist (RR: 1.1, 95% CI, 0.7–1.5, When all the patients reengaged were considered (n=431) in the analysis after the first reengagement and switch path, similar results were obtained. The phone call strategy was not different to mail letter strategy for patients to show up for the appointment in the ITT analysis (24,9% vs. 21,8%, | PMC10538908 |
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Characteristics of reengaged patients | active infection | Of the reengaged patients, 101 attended the specialist appointment, of whom 41 (40.6%) had a positive RNA test result. Among patients with active infection, 3 (7.3%) were categorized as F3 and 11 (26.8%) as F4 using elastography. Thirty-eight patients (92.7%) started HCV therapy, and a sustained virological response was tested and documented in 28 (73.7%) patients. | PMC10538908 |
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Cost-effectiveness analysis of each strategy | The direct cost of the phone call strategy was €430.38, whereas the mail letter strategy was €222.6. If we include the switch path in this calculation, the cost of the phone call strategy amounts to €681.08 compared with €360.8 for the mail letter strategy.The cost per patient who attended the medical visit was €621.3 (2.5 QALY) in the phone call strategy and €611.8 (2.4 QALY) in the mail letter strategy, with an incremental cost-effectiveness ratio of €235/QALY. When the switch is included, the cost of the phone call strategy was €854.2 (1.9 QALY) and €650 (1.1 QALY), with an incremental cost-effectiveness ratio of €259/QALY. Figure Two-way sensitivity analysis. | PMC10538908 |
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DISCUSSION | HCV-infected, HCV microelimination, liver disease | ADVERSE EFFECTS | In this randomized clinical trial, we investigated the effectiveness and efficiency of 2 different strategies for reengagement in specialist care for HCV patients lost to follow-up. In our setting, both the strategies were feasible and similar in terms of effectiveness; meanwhile, the mail letter strategy seemed to be more efficient, except if only 1 call attempt was considered, in which case, the phone call was superior. Prior specialist’s evaluation and being tested for HCV in the pre-DAA era were the factors associated with not showing up for the appointment. Both strategies were similar in costs. Patients with suboptimal diagnosis, that is, with a positive HCV antibody with unknown RNA, and those with active infection lost to follow-up, were considered a priority group to be linked to care in the microelimination plansThe first reengagement attempt implemented to rescue patients lost to follow-up using laboratory records was conducted in the Netherlands, where patients were invited to participate by a mailed letter.In our study, the number of patients contacted by mail was 34% higher than that by phone calls. However, in the phone call strategy, half of the patients were successfully contacted and scheduled for an appointment, a rate similar to that in the REACH study considering the mail strategy. However, in terms of contacting potential cases, both the strategies are insufficient and far from perfect if patient reengagement is the main objective.The high number of eligible patients for reengagement that were excluded from the study because of the change in residency or no contact data available since the HCV diagnostic test date recorded (overall 64%) was the main limiting factor in the development of successful reengagement strategies. In this regard, automatic electronic alerts addressed to the primary care physician for a referral to specialist cases with HCV antibodies could be a better way to contact this group of difficult-to-reach patients.Our findings support that the mail strategy is more efficient than the phone call strategy with a 3.1 ratio of contact attempts, except when only 1 call attempt is considered in the analysis, which then favors the phone call strategy. In our study, to improve the chances of contact, up to 3 different attempts at different times were planned. The use of answering machines could increase efficiency. Nevertheless, because of confidentiality reasons, their use was not permitted.The phone call strategy nearly doubled the percentage of patients who attended the appointment after contact was successfully established (PP analysis 52.7% vs. 33.7%). Therefore, phone calls were more effective than letters when contact was established; however, in the ITT analysis among randomized patients, there were no differences (26.5% vs. 28.5%). It is still unclear whether mobile text messages would be more effective than phone calls, as there is evidence suggesting that mobile messages and phone calls have similar efficacy in promoting attendance at health care appointments.One recent study has demonstrated that reengagement is cost saving for the public health system because of the estimated reductions in liver disease complications and mortality, being able to link to care 26% of the candidate patients, which is quite similar to our global results (27.4%).With both the strategies, patients could perceive a medical confidentiality breach. However, the basic principles of medical ethics were considered,The factors associated with unsuccessful reengagement were previous evaluation by any specialist and HCV-antibody detection in the pre-DAA era. None of the reengaged patients were previously treated, so it is tempting to speculate that patients who were lost to follow-up after being evaluated by a specialist, keep in mind the complexity and adverse effects of previous treatment regimens or the lack of compliance perceived by the physicians. In this regard, news media information about DAAs is relevant and could improve linkage to care, as shown in this study and by our group.Imprison and homeless population are usually excluded from reengagement plansIn conclusion, the phone call and mail strategies are feasible for the reengagement of HCV patients lost to follow-up. Both the strategies were similar in effectiveness and costs, whereas the mail strategy was more efficient, except when only 1 phone call attempt was considered. This pragmatic study may guide other institutions to implement a systematic strategy to reengage care for HCV-infected patients and may contribute to achieving HCV microelimination and get us closer to meeting the World Health Organization elimination goals. | PMC10538908 |
Supplementary Material | PMC10538908 |
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SUPPLEMENTARY MATERIAL | PMC10538908 |
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AUTHOR CONTRIBUTIONS | Alberto Hernández-Bustabad, Dalia Morales-Arraez, and Manuel Hernández-Guerra: material preparation, data collection, and analysis. Dalia Morales Arraez and Alberto Hernández Bustabad: first draft of the manuscript. | PMC10538908 |
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ACKNOWLEDGMENTS | Claudia | The authors thank BIOAVANCE and CIBICAN for the editorial support, Alejandro Jiménez for statistical analysis, and Claudia Velázquez for the database support. | PMC10538908 |
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FUNDING INFORMATION | This study was supported in part by grants from Fondo Europeo de Desarrollo Regional (FEDER). Dr. M. Hernandez-Guerra is the recipient of a grant from Instituto de Salud Carlos III (PI19/01756). | PMC10538908 |
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CONFLICTS OF INTEREST | Dalia | Dr. M. Hernandez-Guerra has received research grants from Abbvie and Gilead Science and has participated as a consultant for Bayer, Intercept and Orphalan. Dr. Dalia Morales-Arráez has received a research grant from Gilead Science. The remaining authors have no conflicts to report.
Written informed consent was requested from all patients who attended the appointment for participation and giving their acceptance for publishing.Dalia Morales-Arraez and Alberto Hernández-Bustabad contributed equally to this work.Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website, | PMC10538908 |
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REFERENCES | PMC10538908 |
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Abstract | PMC10358195 |
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Purpose | CHILDHOOD CANCER | Meeting intervention requirements is crucial in behavioral trials. We examined patterns and predictors of physical activity (PA) adherence and contamination in a 1‐year individualized randomized controlled PA behavioral intervention in childhood cancer survivors (CCS). | PMC10358195 |
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Methods | REGRESSION, CHILDHOOD CANCER, REMISSION | CCS aged ≥16 at enrolment, <16 at diagnosis, and ≥5 years in remission were identified from the Swiss Childhood Cancer Registry. We asked participants randomized to the intervention group to perform an additional ≥2.5 h of intense PA/week and controls to continue as usual. Adherence to the intervention was assessed by online diary (adherent if ≥2/3 of individual PA goal reached) and contamination for the control group by pre‐ and post‐questionnaire including PA levels (contaminated if >60 min increase/week in PA). Predictors of adherence/contamination including quality of life (36‐Item Short Form Survey) were assessed by questionnaire. We used logistic (control group) and mixed logistic regression models (exercise group) to estimate predictors of study adherence and contamination. | PMC10358195 |
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Results | One hundred and forty‐four survivors (30.4 ± 8.7 years old, 43% females) were included. Adherence was 48% (35/73) in the intervention group, while 17% (12/71) of controls contaminated group allocation. Predictors for PA adherence were female sex (OR 2.35, | PMC10358195 |
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Conclusion | der | DER, CHILDHOOD CANCER | Adherence to PA behavior interventions remain challenging in both groups. Further long‐term trials should consider intense motivational support within the first month, more detailed data collection for the control group, adjustments to power calculations and other study designs to minimize non‐adherence and contamination.We examined patterns and predictors of physical activity (PA) adherence and contamination in a one‐year individualized randomized controlled PA behavioral intervention in childhood cancer survivors (CCS). Adherence was 48% in the intervention group, while 17% of controls contaminated group allocation. Clear differences in PA behavior of adherent and non‐adherent participants were seen from week 4. Further long‐term trials should consider intense motivational support within the first month, adjustments to power calculations and other study designs to minimize non‐adherence and contamination.
Nicolas X. von der Weid, Corina S. Rueegg, and Susi Kriemler shared last co‐authorship. | PMC10358195 |
INTRODUCTION | cancer | CANCER | Physical activity (PA) is generally known to be associated with improved overall health including reduced all‐cause mortality, improved cardiovascular health, and lower risk of developing cancer.Many trials to increase PA are ineffective and show null results.The aim of this study was to describe and identify predictors of exercise adherence and contamination of the intervention and control group within an RCT aiming to increase PA over 1 year in adult CCS participating in the SURfit study. | PMC10358195 |
METHODS | PMC10358195 |
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Trial design and participants | We used data from the SURfit study (ClinicalTrials.gov identifier: NCT02730767), | PMC10358195 |
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Intervention and control conditions | Participants of the intervention group were asked to add ≥2.5 h of intense PA/week to their baseline activity level. Intense PA was reached when participants had a fast breathing/heartbeat for at least 20 min. Together with a physiotherapist, individualized PA programs were developed and self‐implemented into each survivor's daily living, aiming to reach a plus of 2 h aerobic and 0.5 h strength building PA per week. The PA program was not supervised except for follow‐up contacts with the physiotherapist described below. The intervention participants increased their target PA from week one. We used the following motivational tools to achieve optimal adherence: Regular contact with the physiotherapist (face‐to‐face at 0, 3, 6, and 12 months, and phone calls after 1, 2, 4, 5, 8, and 10 months), pedometers (daily reporting of steps), and a self‐administered web‐based daily activity diary with immediate graphical feedback. Diary entries were monitored, and participants reminded to complete missing entries each week. Participants of the control group were asked to keep their PA levels constant. | PMC10358195 |
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Outcome: Adherence and contamination | REGRESSION | PA levels of the intervention group were assessed by a web‐based diary filled out on daily basis. Automated reminders were sent out by email, and if participants were not responsive within 3 days, phone calls were initiated. In the diary, intervention participants registered each sport session performed, the duration and type of PA performed. The types of activities were manually grouped into jogging/bicycling/swimming, fitness/gym, team sports, hiking/winter sports, and other activities. PA of the control group was assessed by a 7‐day recall questionnaire filled out by the participant at baseline and at the 12‐month assessment. Answers were verified and discussed by an exercise specialist during an interview. It was specifically emphasized to have a typical week reported within the last 3 months. As the controls were allowed to switch to the exercise program after the trial, the 12‐month interview was taken as baseline assessment of their PA behavior to receive the same personalized PA counseling with motivational tools as the intervention group, but without personal follow‐up coaching.We defined participants of the intervention group to be adherent if they reached ≥2/3 of their individual intense PA goal (100 min of the agreed 150 min additional PA/week) based on the web‐based diary and referred to them as “exercise adherent.” For this, all cumulative PA hours over the 1 year were considered and a binary variable was built to determine whether a participant was adherent or not for each week. For the regression model, we used the percentage of weeks where the PA goal was reached as outcome. Days with no PA entries were set to 0 min PA suggesting that no sport was performed. Control group participants were defined as “control contaminated” if they reported >60 min increase in intense PA/week based on the questionnaire and confirmed by an interview at T0 and T12 done by the coach. | PMC10358195 |
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Predictors | Predictors of adherence were not an a priori research question and were thus selected from our available data and a literature review, and on their ease to be assessed in clinical practice through simple questions at the beginning of an intended increase in PA. | PMC10358195 |
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Statistical analyses | REGRESSION | We calculated the average PA h/week and the percentage of individual goal reached for the intervention group, overall and stratified for adherent/non‐adherent participants over the year, and for the first and second half of the 1‐year intervention period. We investigated the average number/duration of each PA session, the type of sport performed; and the predictors mentioned above. We used two separate models to look at associations (predictors) for contamination in controls and adherence in intervention participants, respectively. Predictors of contamination within the control group were investigated using a multivariable logistic regression model (increase T0/T12). Predictors of adherence within the intervention group were investigated with a mixed effects logistic regression (with repeated measures of weekly adherence as yes/no outcome) with random intercept and updated time‐varying covariates where available (T3: BMI, CIS; T6: BMI, PCS, MCS, CIS). For dropouts, observations until withdrawal were included in the analysis. R (v4.0.2, R Foundation) software was used with the packages lme4, ggplot2, and dplyr. | PMC10358195 |
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RESULTS | CHILDHOOD CANCER | From a total of 1450 eligible CCS, 842 got invited for study participation whereof 151 (18%) were randomly assigned to one of the two treatment arms with 76 intervention and 75 control group participants. From those, seven participants were not included in the current analysis due to dropout reasons unrelated to the study. From 144 included CCS, 132 (92%) completed the study; 10 intervention and 2 control group participants dropped out (see Table Baseline characteristics of the study population (
Number of participants included (Intervention/Control): Education Abbreviations: BMI, body mass index; ICCC‐3, international classification for childhood cancer third edition.Less than 3 healthy portions per day (vegetables or fruits).Overall, 17 (23%) intervention group participants reached 100% of their personalized goal (+2.5 h/week), while 35 (48%) adhered to the study program (≥2/3 of individual goal reached). Eight intervention participants dropped out in the first and two in the second half of the study. In the control group, 12 (17%) participants increased their weekly PA more than allowed (>60 min/week). Of those, 2 dropped out and 10 contaminated group allocation. | PMC10358195 |
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Details on adherence to the physical activity intervention | PA behavior | POSITIVE | Figure Percent of individual weekly physical activity goal reached based on self‐reported online diary entries. Accordingly, an example of an adherent (top) and non‐adherent (bottom) participant of the intervention group are displayed. Assessment periods at mid‐term (T6) and study end (T12) are highlighted and participants annual weekly mean of physical activity shown as dashed line. Gray areas highlight when the weekly goal was not reached (<2/3).Distribution and mean (dashed line) of difference in individual weekly intense physical activity (PA) hours between the two assessments at mid‐term (T6) and study end (T12) and their annual PA average (0‐line). Positive values denote participants that were more active than their mean of PA.Intervention group participants reporting their PA behavior (Types of sport and physical activity behavior of participants of the intervention group according to adherence status.
Tracking of adherence to physical activity (PA) during the study duration according to adherent/non‐adherent participants by diary entries. Values denote overall means and 95%‐CI. A clear difference among the PA behavior can be detected (95%‐CI did not overlap) from week 4 on. Participant's PA goal (+150 min) and threshold to be defined as adherent (+100 min) are highlighted. T0, baseline visit; T6, 6‐month follow‐up; T12, 12‐month follow‐up. | PMC10358195 |
Predictors of study adherence and contamination | Predictors of study adherence can be found in Table Predictors of study adherence for the intervention and contamination for the control group.
Abbreviation: BMI, body mass index. | PMC10358195 |
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DISCUSSION | cancer, PA behavior | CANCER | This analysis (To estimate the true treatment effect of an RCT, it is important that the intervention and the control group adhere to their allocated study program. The definition of adherence differs across exercise studiesPA hours of the intervention group were self‐reported in a web‐based diary, which has been successfully used for assessing adherence in RCTs also in cancer survivors.We found descending intervention week, female sex, and low physical and mental quality of life to be significant positive predictors for intervention adherence. This is in agreement with most studies that reported a high adherence in short‐term, but a striking loss of adherence in long‐term PA trials.For the control group, no significant predictors for study contamination were found which may be partly explained by the small sample size in the “contaminated” group. Misclassification based on reporting bias cannot be ruled out either. As trials are always prone to a clear selection bias toward those willing and ready to increase their PA behavior, other designs such as SCEDs as mentioned above could be a solution to solve this problem.Predictors of adherence to the intervention can help to understand adherence in trials focusing on behavioral change, for example, whom we might reach and why. Female compared to male sex is globally associated with poorer PA during adolescence in the healthy population and CCS. | PMC10358195 |
Strengths and limitations | cancer | CANCER, PHYSICAL HANDICAP | Strengths of our study include the RCT design and the long duration of a 1‐year individualized program. The schedule was embedded in each participant's daily living, allowing greatest flexibility in the planning and performing of PA as well as sustained behavioral change to take place. The PA program was followed‐up by regular phone calls and meetings by trained physiotherapists and supported by various motivational features. In parallel, long‐term adherence was tracked which is much more relevant than short‐term adherence.A limitation in all trials focusing on change in PA behavior is the highly selective and mostly sport‐motivated participants, especially in CCS where survivors with mental or physical handicaps related or not related to the cancer history tend not to participate. | PMC10358195 |
Practical implications | Our findings can help to improve future PA behavioral interventions. Trials should be aware of non‐adherence, especially in the beginning of a behavioral intervention. Our results showed that the attitude towards behavioral change was established in the first month of the intervention. Furthermore, contamination needs to be considered in studies that recruit participants willing or motivated to enhance their PA. Power calculations are a critical first step when a trial is planned; expected effect sizes could be modeled on the assumption of a lower increase in PA than expected among the intervention group because of non‐adherence, a parallel increase in PA among controls, and dropouts thereby reducing the actual delta between the two arms. Taking our findings of non‐adherence and contamination together, alternative study designs like attention control groups, SCEDs or step‐wedged designs could be valuable alternative options. One also needs to be aware of the problem of self‐selection bias in PA behavior interventions, particularly in studies of survivors where strategies should be applied to screen and potentially exclude already highly active participants. | PMC10358195 |
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Conclusion | PA behavior | Adherence to the intervention, prevention of contamination in the control group and the assessment of their predictors are crucial to interpret efficacy and clinical relevance of PA behavior RCTs. Even with high motivational support, only half of the intervention group adhered to their expected exercise regimen, while one in six controls contaminated the study by increasing their PA level beyond 1 h/week. While exercise adherents reached about 100% of their individual goal during the whole study, non‐adherents reduced their weekly PA hours already after the first months and remained there. Assessing PA levels at this time could identify participants that could benefit from more strenuous supervision and advice. This would accurately reflect the goal of properly enabling everyone to participate in these valuable research studies. Our results raise awareness about the problem of non‐adherence and contamination in behavioral trials. These problems should be considered when interpreting results of comparable trials; they should be part of any sample size calculation when a behavioral intervention is planned; and they may even be indicative for using alternative study designs such as SCEDs or step‐wedge designs where optimal treatments based on individual interventions and proper monitoring of PA could be reached, while minimizing non‐adherence and contamination. | PMC10358195 |
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AUTHOR CONTRIBUTIONS | PMC10358195 |
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FUNDING INFORMATION | 609020‐Scientia, Cancer | CANCER | Swiss Cancer League (KLS‐3175‐02‐2013), “Stiftung für krebskranke Kinder, Regio Basiliensis,” “Gedächtnis‐Stiftung Susy Rückert zur Krebsbekämpfung,” “Taecker‐Stiftung für Krebsforschung,” “Stiftung Henriette&Hans‐Rudolf Dubach‐Bucher,” “Stiftung zur Krebsbekämpfung,” “Stiftung Krebs‐Hilfe Zürich,” “Fondation Recherche sur le Cancer de l'Enfant (FORCE),” Fond'Action contre le Cancer, and South‐Eastern Norway Regional Health Authority (project number 2019039). CSR has received funding from European Union Seventh Framework Programme (FP7‐PEOPLE‐2013‐COFUND, grant agreement no 609020‐Scientia Fellows). WHD is paid by a research grant from the South‐Eastern Norway Regional Health Authority (grant number 2019039, to CSR). | PMC10358195 |
CONFLICT OF INTEREST STATEMENT | None. | PMC10358195 |
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Supporting information |
Figure S1.
Click here for additional data file. | PMC10358195 |
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ACKNOWLEDGMENTS | The authors thank all participants for taking part in our study and the study nurses, assistants, master students and physiotherapists for their great work. | PMC10358195 |
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DATA AVAILABILITY STATEMENT | Data sharing is not applicable to this article as no new data were created or analyzed in this study. | PMC10358195 |
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REFERENCES | PMC10358195 |
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Background | EEG monitoring techniques are receiving increasing clinical attention as a common method of reflecting the depth of sedation in the perioperative period. The influence of depth of sedation indices such as the bispectral index (BIS) generated by the processed electroencephalogram (pEEG) machine to guide the management of anesthetic depth of sedation on postoperative outcome remains controversial. This research was designed to decide whether an anesthetic agent exposure determined by raw electroencephalogram (rEEG) can influence anesthetic management and cause different EEG patterns and affect various patient outcomes. | PMC10557275 |
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Methods | SECONDARY, POSTOPERATIVE COMPLICATIONS | A total of 141 participants aged ≥ 60 years undergoing abdominal major surgery were randomized to rEEG-guided anesthesia or routine care group. The rEEG-guided anesthesia group had propofol titrated to keep the rEEG waveform at the C-D sedation depth during surgery, while in the routine care group the anesthetist was masked to the patient’s rEEG waveform and guided the anesthetic management only through clinical experience. The primary outcome was the presence of postoperative complications, the secondary outcomes included intraoperative anesthetic management and different EEG patterns. | PMC10557275 |
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Results | neurological and gastrointestinal complications | There were no statistically significant differences in the occurrence of postoperative respiratory, circulatory, neurological and gastrointestinal complications. Further EEG analysis revealed that lower frontal alpha power was significantly associated with a higher incidence of POD, and that rEEG-guidance not only reduced the duration of deeper anesthesia in patients with lower frontal alpha power, but also allowed patients with higher frontal alpha power to receive deeper and more appropriate depths of anesthesia than in the routine care group. | PMC10557275 |
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Conclusions | neurological and gastrointestinal complications | In elderly patients undergoing major abdominal surgery, rEEG-guided anesthesia did not reduce the incidence of postoperative respiratory, circulatory, neurological and gastrointestinal complications. rEEG-guided anesthesia management reduced the duration of intraoperative BS in patients and the duration of over-deep sedation in patients with lower frontal alpha waves under anesthesia, and there was a strong association between lower frontal alpha power under anesthesia and the development of POD. rEEG-guided anesthesia may improve the prognosis of patients with vulnerable brains by improving the early identification of frail elderly patients and providing them with a more effective individualized anesthetic managements. | PMC10557275 |
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Keywords | PMC10557275 |
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Introduction | neurocognitive disorders, rEEG-based intraoperative visual | Intraoperative neuromonitoring allows monitoring of the changes in brain electrical activity during the changing states of consciousness under general anesthesia and offers information on anesthesia depth. EEG monitoring can help anesthesiologists to avoid the use of unnecessary high anesthetics doses, which is able to be a risk factor for occurring peri-operative neurocognitive disorders [The raw electroencephalogram (rEEG) correlates significantly with the level of consciousness in patients under general anesthesia [Given that the pEEG method of monitoring depth of sedation has been widely used in clinical practice, and that the limitations of the pEEG itself and the neurological changes in elderly patients lead to limitations in the accuracy of pEEG-guided anesthesia in elderly patients, the aim of this study was to investigate whether rEEG-based intraoperative visual analysis of EEG-guided anesthetic depth management could have an impact on intraoperative anesthetic management and EEG patterns and affect postoperative outcomes in elderly patients undergoing major abdominal surgery compared with routine anesthetic care monitoring, and to provide a reference for the clinical application of rEEG in elderly patients.
Six levels of anesthesia | PMC10557275 |
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Materials and methods | MAY | This single-center and randomized controlled trial compared the outcomes of two parallel groups, which were the rEEG-guided group and the routine care group. The research was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University Institutional Review Board (IRB number: No. PJ2020-13-09), and written informed consent was obtained from each subject that attends the trial. In addition, the trial was registered before patient enrollment at the Chinese Clinical Trial Registry at 12/11/2020 (Clinical Trials Number: ChiCTR2000039864) and was conducted from November 2020 to May 2022 in accordance with the Helsinki Declaration. | PMC10557275 |
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Participants | psychiatric illness, dementia | The male or female patients over 60 years old scheduled for elective major abdominal surgery were involved. Below present the exclusion criteria: patient refusal, a history of dementia or psychiatric illness, difficulty with follow-up, or poor compliance. | PMC10557275 |
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Randomization, blinding, and allocation concealment | RECRUITMENT | By using randomized closed envelopes, the randomization procedure was carried out by the responsible senior consultant. The group allocation was performed following the recruitment through the opening of the sequential envelopes. The anesthesiologists were not masked due to the nature of the anesthetic technique. The patients and research staff in charge of the postoperative patient assessments did not learn about the group assignment. | PMC10557275 |
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Intervention | After the participants entered the operation room, the five-lead electrocardiogram (ECG), invasive blood pressure via a radial artery, and pulse oxygen saturation (SpO
EEG tracing at various stages of anesthesia | PMC10557275 |
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Outcomes and data collection | loss of consciousness | RESPIRATORY COMPLICATIONS, COMPLICATIONS | The demographic and hospital characteristics of the patients, such as age, body mass index, gender, coexisting medical conditions, type of operation (laparotomy or laparoscopy) were all recorded. Intraoperative data on the procedure and anesthesia were recorded, including time of induction of anesthesia (midazolam start time), time of start of operation (skin cut time), MAP and heart rate at all key intraoperative time points (baseline, at loss of consciousness, skin cut, every 30 min during the operation, at end of operation), time of end of operation (time of last suture) and time of end of anesthesia (propofol stop time). Intraoperative dose of maintenance (propofol, remifentanil) and additional drugs (sufentanil, cisatracurium), record of vasoactive drug use, time of patient admission to PACU and time of discharge from PACU. Patients were assessed for the occurrence of major organ system complications during hospitalization, postoperative length of stay and 30-day postoperative all-cause mortality. In the present study, the primary outcomes of interest were systemic complications within the hospitalization after surgery. Systemic complications were divided into respiratory complications [ | PMC10557275 |
EEG processing | A 4-channel Sedline brain function monitor (Masimo, Irvine, CA, USA) was used for forehead EEG acquisition. The electrodes for the sensors record EEG between Fp1, Fp2, F7 and F8 with the ground electrode at Fpz, and the reference electrode at roughly 1 cm more than Fpz. A sampling rate of 178 Hz (16 bits) and a preamplifier bandwidth of 0.5–92 Hz was used to record the EEG data. In order to check the exact time and anesthesia level, an experienced researcher manually browsed EEG data of all of the patients. For the purpose of carrying out the spectral analysis, 10 s [ | PMC10557275 |
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Statistical analysis | ADVERSE EVENTS | In this trial, the sample size was estimated for an α level of 0.05 and 90% power in order to detect a 10% difference in the occurrence between groups. On the basis of the preliminary results, the incidence of adverse events after surgery was indicated to be 50% in the routine care group, and we calculated that a sample of 55 patients would provide 90% power to reduce it to 25% [ | PMC10557275 |
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Results | gastrointestinal, hepatobiliary-pancreatic), arthritis | MAY, ARTHRITIS | 141 patients that had undergone abdominal major surgeries from November 2020 to May 2022 (e.g., gastrointestinal, hepatobiliary-pancreatic) were included in the trial. Among them, 69 were randomized to the rEEG-guided group and 72 to the routine care group, respectively. Taking into account the 5 patients within the rEEG-guided group and 4 within the routine care group, a technical failure of EEG monitoring prevented the clinicians from analyzing the EEG results. Missing data was distributed almost evenly between the two groups, the final 125 patients were included in the outcome analysis, 61 in the rEEG-guided anesthesia management group and 64 in the conventional anesthesia management group (Fig.
Flow diagram of included patients
Patient characteristics in each groupRheumatoid arthritis or connectivetissue diseaseValues are presented as number (%) or median (1Q, 3Q). ASA: American Society of Anesthesiologists classification; ICU: intensive care unit | PMC10557275 |
Primary outcomes | Postoperative pain | INTRAOPERATIVE COMPLICATIONS | There were no intraoperative complications in either group. There was no statistically significant difference in respiratory, cardiovascular, gastrointestinal and neurological complications between the two groups (P > 0.05). The incidence of POD was 3% in the rEEG-guided group compared to 11% in the routine care group, indicating no significant difference (P > 0.05). Postoperative pain was assessed using the NRS scale and no significant difference was found between the two groups (P > 0.05). In addition, the rEEG guidance showed no effect on length of hospital stay or postoperative hospital stay (P > 0.05) or all-cause mortality at 30 days postoperatively (P > 0.05) (Table
Postoperative OutcomesValues are presented as number (%) or median (1Q, 3Q). ICU: intensive care unit; NRS: numerical rating scale; POD: postoperative delirium | PMC10557275 |
Secondary outcomes | SD | In both groups, no statistically significant difference was found in the surgery type or location. There was a total of 5 patients with BS, with an incidence of 8% and a median BS duration of 5.3s in the rEEG-guided group, while the routine care group had 12 patients with BS. There was no statistically significant difference in the incidence of BS between the two groups (P > 0.05), while the duration of BS in the routine care group was longer than that in the rEEG-guided group (P < 0.05). The median duration of anesthesia was 155.0 (IQR 120.5–213.0) in the rEEG-guided group and 160.0 (128.5–190.5) in the routine care group, meaning no significant difference. Moreover, there were no significantly different doses of propofol, opioids and neuromuscular blocking agents in both groups. During the maintenance of anesthesia, MAP was 90 mmHg within the rEEG-guided group and 91 mmHg within the routine care group, therefore showing no significant difference, and there was no statistically significant difference between basal and intraoperative MAP at any time point in either group. Furthermore, no inversely significant difference was observed in the time taken in PACU between the two groups (Table
Perioperative Care MeasuresValues are presented as number (%), mean ± SD or median (1Q, 3Q). MAP: mean arterial pressure; BS: burst suppression; PACU: post-anesthesia care unit | PMC10557275 |
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Subgroup analyses | PMC10557275 |
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Frontal alpha power and POD | Patients that suffer from a lower alpha power are reported to be more prone to the development of BS under anesthesia [
The receiving operating characteristic curves for the model | PMC10557275 |
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Subgroup analysis on sedation and postoperative complications | POSTOPERATIVE COMPLICATIONS | Alpha oscillations can be viewed to be a neurophysiological biomarker of brain vulnerability [
Examples of high(left) and low(right) alpha power within a left frontal spectral display. The vertical axis is frequency (Hz). The blue and red colors represent low and high power (dB). The horizontal axis is time (s). The dark horizontal lines present the alpha band range (8–12 Hz)
The box-and-whisker plots show the medians (thick horizontal lines) and interquartile ranges (IQRs; boundaries of the box) and ranges. Whisker boundaries are set at 1.5 × IQR. The sedation time plots depict the cumulative times in each of the study groups during which the electroencephalogram sedation ratio was > 1%
Subgroup analyses of postoperative complications | PMC10557275 |
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Discussion | neurological and gastrointestinal complications | POSTOPERATIVE COMPLICATIONS | In the randomized controlled trial, the impact of the raw EEG guidance of anesthesia on postoperative complications after surgery in older adults (≥ 60) undergoing major abdominal surgery was assessed. There was no statistically significant difference between the two groups in terms of postoperative respiratory, cardiovascular, neurological and gastrointestinal complications and all-cause mortality at 30 days postoperatively. There was no statistically significant difference in the number of intraoperative BS between the two groups, but rEEG-guided anesthesia management significantly reduced the time patients spent in BS. In post hoc exploratory analyses, low frontal alpha power was found to be independently linked to POD, and that rEEG-guided anesthesia allowed individual regulation of depth of anesthesia to avoid over-anesthesia in patients with a fragile brain, while ensuring the depth of anesthesia required in older patients with a healthy brain.As the brain is the target organ for general anesthesia, with the continuous research and development of EEG monitoring, some experts advocate the incorporation of EEG-based monitoring into routine anesthetic management. EEG monitoring can avoid too light anesthesia and prevent the occurrence of intraoperative awareness, while EEG monitoring can avoid too deep anesthesia, which usually leads to prolonged recovery time as well as impaired quality of recovery for patients [Gamma-aminobutyric acidergic (GABAergic) anesthetics, i.e., sevoflurane, and propofol, generate stereotyped slow (0.1–1 Hz) activity and frontal alpha (8–12 Hz) oscillations of EEG in the process of unconsciousness, both of which are quantified by using a power spectral analysis. A correlation between frontal alpha band activity and preoperative cognitive function has been found which was not present in other EEG bands. Also, EEG alpha band activity strength is linked to age [This study has several limitations. Firstly, the same anesthesiologist may manage patients in either the rEEG-guided group or the routine care group. Although the anesthesiologists managing the routine care group were masked to the EEG, their previous experience of offering rEEG-guided anesthesia care could have not only enabled them to know more about the anesthesia propofol maintenance but also potentially affected the dosage level. As a result, this research is likely to under-evaluate the actual difference between rEEG-guided and routine care. Secondly, in this research, the explored EEG data comes from the frontal 4-channel pathway, and therefore the analysis only focuses on frontal alpha oscillations in the EEG during unconsciousness, which cannot evaluate other cortical EEG activity. Therefore, high-density EEG research is needed to improve the reliability and utility in the recognition of vulnerable brains and measuring anesthetic depth. Thirdly, a significant correlation was found between the frontal alpha power and POD probability. Taking into account that frontal alpha power is seen as an underlying brain frailty trait, the intervention effect size may be larger when including more cognitively impaired patients, and therefore further validation within bigger research is needed. | PMC10557275 |
Acknowledgements | We thank our departmental colleagues for their help in recruiting patients for this study. | PMC10557275 |
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Authors’ contributions | EG, LC and LZ designed this study. ZH and YX wrote the manuscript. ZH, YX, HZ, JL and YG performed the experiments. ZH and YH assisted with data analysis. EG and LC revised the final manuscript. All authors read and approved the final manuscript. | PMC10557275 |
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Funding | This study was supported by China primary health care foundation (YLGX-WS-2020001 to Lijian Chen) and China primary health care foundation (WKZX2023CX170005 to Guanghong Xu) which provided funds for collection and analysis of clinical data. | PMC10557275 |
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Data Availability | The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. | PMC10557275 |
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Declarations | PMC10557275 |
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Ethics approval and consent to participate | MAY | The research was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University Institutional Review Board (IRB number: No. PJ2020-13-09), and written informed consent was obtained from each subject that attends the trial. In addition, the trial was registered before patient enrollment at the Chinese Clinical Trial Registry at 12/11/2020 (Clinical Trials Number: ChiCTR2000039864) and was conducted from November 2020 to May 2022 in accordance with the Helsinki Declaration. | PMC10557275 |
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Consent for publication | Not applicable. | PMC10557275 |
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Competing interests | The authors declare no competing interests. | PMC10557275 |
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Abbreviations | analgesiaPost-anesthesia | American Society of AnesthesiologistsBispectral indexBody mass indexBurst suppressionBurst suppression ratioBlood pressureConfidence intervalElectroencephalogramElectrocardiogramGamma-aminobutyric acidIntensive care unitMean arterial pressureNumeric rating scalesProcessed electroencephalogramPatient controlled intravenous analgesiaPost-anesthesia care unitPostoperative deliriumPostoperative nausea and vomitingRaw electroencephalogram | PMC10557275 |
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References | PMC10557275 |
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Background | In this study, we investigated the impact of 10.6-μm CO | PMC10666435 |
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Methods | KOA | A total of 392 individuals diagnosed with KOA and meeting the specified eligibility criteria were assigned randomly into two groups: the LM treatment group and the sham LM control group (ratio 1:1). Both groups received either LM therapy or simulated LM therapy to address the affected area of the knee joint. This treatment was administered three times a week for a duration of 4 weeks. | PMC10666435 |
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Results | In the LM group, the fastest 15-m walking times at both Week 4 and Week 12 were significantly reduced compared to the times before treatment (all | PMC10666435 |
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Conclusion | The use of CO | PMC10666435 |
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Keywords | PMC10666435 |
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Introduction | Knee osteoarthritis, pain, KOA | KNEE OSTEOARTHRITIS | Knee osteoarthritis (KOA) is a common source of impairment in the elderly [White et al. examined gait speed over a distance of 20 m in patients with KOA aged 45–79. Their findings revealed a significant reduction in gait speed at this shorter distance among patients experiencing pain symptoms [ | PMC10666435 |
Materials and methods | PMC10666435 |
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Ethical approval and protocol registration | This research involved a double-blind, sham-controlled, multi-site randomized trial. The details of this trial can be accessed at this URL: | PMC10666435 |
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Sample size and recruitment | Previous studies revealed that laser moxibustion showed a significant improvement rate of 14.1% in fast walking time, while the sham laser moxibustion group only exhibited a rate of 4.8%. There was a significant difference between the two groups (To determine the appropriate sample size, a power analysis was conducted using PASS20.0.1 software (Power Analysis and Sample Size, PASS20 NCSS), considering a significance level (Between January 2015 and November 2017, a total of 603 individuals were assessed for participation, primarily recruited through print ads in local newspapers and posters distributed in nearby communities (as illustrated in Fig. Participant flowchart | PMC10666435 |
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Eligibility criteria, randomization, and blinding | PMC10666435 |
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Inclusion criteria | arthritic pain, knee pain, knee osteoarthritis | KNEE OSTEOARTHRITIS | Prior to enrollment, a specialist doctor conducted an assessment of knee joint function in the patients. Anteroposterior and lateral X-ray images were obtained for the affected joint, and inclusion criteria were applied to select the subjects for the study.Age 50 to 75 years.According to the American College of Rheumatology criteria for the diagnosis of knee osteoarthritis [Radiological confirmation of knee osteoarthritis (Kellgren–Lawrence grade ≥ 1) [Moderate or worse knee pain most time during the past month; subjects had a vas baseline score of 40 or greater for arthritic pain.Agree to be randomized and understand and be willing to sign the informed consent. | PMC10666435 |
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