Efficacy and safety of a dual boosted protease inhibitor-based regimen, atazanavir and fosamprenavir/ritonavir, against HIV: experience in a pediatric population

Stefano Rusconi
Vania Giacomet
†
Chiara Mameli
†
Alessandra Viganò
Ottavia Viganò
Fulvio Adorni
Massimo Galli
Gian Vincenzo Zuccotti
Efficacy and safety of a dual boosted protease inhibitor-based regimen, atazanavir and fosamprenavir/ritonavir, against HIV: experience in a pediatric population
R E S E A R C H A R T I C L E Open Access
Background: Although dual-boosted protease inhibitors regimen is not recommended in children with HIV infection, such a strategy could be useful in subjects with a complex resistance profile. This study was aimed at assessing the long term efficacy and safety of a double-boosted protease inhibitor combination, fosamprenavir (fAVP) and atazanavir/ritonavir (ATV/r) in a cohort of HIV-infected children and adolescents who had failed with nucleoside reverse transcriptase inhibitors.Methods: Seven vertically infected children and adolescents who had previously failed highly active antiretroviral therapy and were resistant to nucleoside reverse transcriptase inhibitors, received a dual protease inhibitor (PI) regimen including fAVP plus ATV/r for 42 months. The patients were assessed at baseline, every month for the first 24 weeks of therapy and every 3 months until month 32. Physical examination, CD4+ cell count, HIV-RNA viral load, lipid profile and hepatic function were assessed throughout the follow up.Results: During the study no serious adverse events were reported. CD4 absolute number increased over-time in all subjects. At baseline the median HIV-RNA was 6562 cp/mL (ranging 1048 -102772 cp/mL) and rapidly decreased below the limit of detection (50 cp/mL) after 2 months of the new treatment and remained undetectable in all cases through the entire study period. At the beginning of the study all cases showed a normal lipid profile. During the study period, 4/7 subjects showed total cholesterol, low density lipoprotein and triglyceride levels >97 th cent.le for the males and 94 th cent.le for the females. HDL cholesterol showed protective values. Hepatic enzymes remained stable during the entire observation, whereas total bilirubin showed toxicity II/III grade in 6/7 subjects. No change in fat redistribution and insulin resistance was observed. Conclusion: Dual-boosted protease inhibitor therapy was virologically and immunologically effective and it could be considered as a possible alternative to a rescue regimen in children and adolescents. However, hypercholesterolemia and hypertriglyceridemia need close follow-up and may limit the use of this therapeutic option.

Background

The introduction of potent combination antiretroviral (ARV) therapy has been found to improve disease progression and prolonged survival in HIV-infected adults and children [1][2][3]. Despite the clinical favourable outcome observed with ARV, it is difficult to choose an effective alternative regimen after multiple therapeutic failures in many patients. Approximately 40 to 50% of adult patients receiving ARV regimen containing a protease inhibitor (PI) experience virologic failure [4,5], mainly due to side effects and unfavourable pill burden. Moreover the long term control of viral replication is even lower in paediatric patients [6]. Most patients show primary mutations to protease inhibitors (PIs), resistance to non-nucleoside reverse transcriptase inhibitors (NNRTI) and low activity of nucleoside reverse transcriptase inhibitors (N[n]RTIs). In this setting, the idea of using a dual-boosted PI regimen with low-dose boosting ritonavir may be considered.

The rationale of using a dual-boosted PI regimen is to reach synergistic or additive activity against HIV and to further increase the genetic barrier to resistance, to obtain high plasma concentrations of both PIs with only one boost and to avoid toxicity with N(n)RTI-sparing regimens [7].

The short-term efficacy of double-boosted PI in naïve adults has been disappointing [8,9], while studies in treatment experienced patients showed more favourable results. In an observational cohort study of 128 heavily pre-treated patients, the combination of lopinavir/ritonavir (LPV/r) and saquinavir (SQV) obtained a virological response (HIV-RNA < 400 copies/ml) at week 48 [10,1]. In a recent randomized study in patients who had failed NNRTI-based regimen, comparing single-boosted PI with double-boosted PI, Siripasson et al found an acceptable virological outcome without differences in the two groups [11].

In pediatric patients, dual boosted PI regimen is not recommended because few data are available in this population [12]. However, two recent studies showed that dual-boosted SQV and LPV may be an effective and safe alternative for a second-line regimen in pre-treated children, nevertheless a close follow up is necessary because dislipidemia can occur during treatment [13,14]. Therefore, we decided to test this therapeutic option in a long term observational cohort of 7 HIV-infected children.

Methods

Our observational study evaluated the immuno-virologic efficacy and the safety profile of dual boosted PI-based therapy in a cohort of vertically HIV-infected pediatric patients who had failed nucleoside N(n)RTI based therapy. Inclusion criteria were: ongoing viral replication, multiple virological failures using a N(n)RTI-containing regimen, and presence of resistance-associated mutations to N(n)RTI and NNRTI in the current genotype.

Genotype resistance testing (Siemens Healthcare Diagnostics Trugene W HIV-1, Siemens Healthcare Diagnostics, 1717 Deerfield Road, Deerfield, IL 60015-0778, USA) was performed in each patient before the introduction of the dual boosted PI-based regimen. Mutations were defined according to International AIDS Society-USA Drug Resistance Mutation Group [15]. The interpretation of resistance mutations was done through the Stanford HIV Db, Genotypic Resistance Interpretation Algorithm, version 6.2.0.

Each patient switched to a dual PI-based regimen consisting of fosamprenavir (fAVP) and atazanavir (ATV) boosted ritonavir (RTV) in association with lamivudine (3TC) and this regimen was maintained over 42 months. Lamivudine was included in the drug regimen due to its low viral fitness maintenance in the presence of M184V mutation. The administration schedule was fAPV 18 mg/kg bid, ATV 150 mg bid with the booster of RTV 100 mg bid and 3TC 4 mg/ kg bid. Adherence was assessed through the subject's pill count and a self-reported evaluation.

CD4 cell counts, HIV-RNA viral load, serum chemistry, fasting lipid levels and clinical assessments were performed in each patient at baseline (T0), 3 months after the switch and every six months until month 42. HIV viral load was assessed by Branched-DNA, Chiron Diagnostics, Emeryville, CA, USA with a lower limit of detection < 50 copies/mL; CD4 cell count was performed using standard flow cytometry. Serum chemistry and lipid levels were assessed by standard laboratory methods.

The efficacy endpoint was the achievement of plasma HIV-RNA < 50 copies cp/mL with stable or increasing CD4 cell counts through 42 months. Virological failure was defined as having 2 consecutive HIV-RNA > 50 cp/ mL both during the study period and at the end of the clinical observation (42 months).

Safety assessments included lipid profiles defined as changes in total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL) and triglycerides (TG) as well as hepatic toxicity: aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TB), gamma glutamyl transferase (γGT). Lipid levels were defined according to the reference by age and gender in adolescents [16,17].

Lipodistrophy was annually assessed using a checklist of standard clinical signs for fat redistribution completed by the pediatrician for each child [18]. Children were considered to have fat redistribution if they had one or more of major clinical signs. A combined subtype of fat redistribution was defined as showing at least one sign of peripheral lipoatrophy and at least one of central lipohypertrophy.

Homeostatic Model Assessment (HOMA) index was evaluated in this cohort by an oral glucose tolerance test (OGTT) during the annual follow up visit to check for insulin resistance. The HOMA index was calculated as the product of the fasting plasma insulin level (μU/mL) and the fasting plasma glucose level (mmol/L), divided by 22.5. HOMA index cut-offs, from the 5 th to the 95 th percentile.

Categorical variables are given as the number or percentage of subject with the characteristic of interest. Continuous variables are reported as median, lower (25 th percentile), and upper quartile (75 th percentile). The comparison between the baseline and 42 month time-point was conducted with the Wilcoxon non-parametric test. The level of statistical significance was set at P <0.05. SPSS 15 for Windows was the statistical software package used for the analyses (SPSS, Chicago, IL, USA).

A formal approval from the Ethical Committee was not required. Our institution's IRB does not require approval for therapeutic interventions which are part of the regular clinical practice. The children were started on this treatment as part of their standard care prescribed by their physician and no treatment was given for the purposes of this study.

Results

The cases, 5 males and 2 females, showed the following CDC stage: A1 (1 patient), A2 (1), A3 (1), B3 (2), C2 (1). The median age of the patients was 15.96 years and the interquartile range was 10.82 to 18.93 years. One patient was co-infected with Hepatitis C virus, but his condition was clinically stable and no laboratory evidence of decreased hepatic function was evident. All patients presented the inclusion criteria as previously specified. Prior to the introduction of the new regimen, 5/7 patients were taking a N(n)RTI-based antiretroviral regimen and 2/7 an antiretroviral regimen including 2 N(n)RTIs and 1 PI.

The double boosted-PI regimen plus 3TC achieved an excellent virological and immunological response. As shown in Figure 1, CD4 absolute number increased over time in all subjects. At baseline, the median and the interquartile range for the CD4 absolute number and the percentage were 364 (217-478)/μL and 18 (16.9-21.2) %, respectively, whereas at month 42 the values were 618 (534-684)/μL and 26.6 (21.4-28.3) %, respectively. This increase was statistically significant (p < 0.05).

At baseline the median and HIV-RNA was 6562 cp/ml, ranging from 1048 to 102772 cp/ mL. Viral load showed a rapid decrease below the detection limit (50 cp/ mL) after 2 months of the new treatment in all subjects and remained undetectable in all cases throughout of study period.

The results of the genotype resistance tests are shown in Table 1. As shown, all pediatric subjects but 1 exhibited resistance to the majority of N(n)RTI and this was the main reason that promted us to use a dual boosted PI-based regimen. The only child without resistance mutations received a dual boosted PI-based regimen due to hematologic and metabolic toxicities.

Liver enzymes showed a certain degree of variation, but did not cause any treatment interruption during the study period. At baseline, the median and range for ALT were 40

Discussion

This study showed that at month 42 a combination regimen of fAVP + ATV/r obtained an excellent virological (100% of subjects with HIV-RNA <50 copies/ml) and a good immunological (9% median CD4 increase) outcome in HIV-infected children and adolescents although there was an association of a worsening lipid profile. Our results showed a similar efficacy compared to the other two available studies of double-boosted PI in experienced HIVinfected children. These two studies assessed the efficacy of the combination of SQV and LPV/r in a cohort of 50 HIV-infected children; the first and the second assessment were performed at week 48 and 96 respectively [13,14].At week 48 the median CD4 increase was 9% (IQR 5-16) and the percentage of patients with HIV-RNA < 400 and < 50 copies/ml were 78 and 64, respectively. At week 96 the median CD4 increased by 14% (IQR: [7][8][9][10][11][12][13][14][15][16][17][18][19] and the percentage of patients with HIV-RNA < 50 copies/ml was 64.

The dual-PI regimen in our study was chosen due to the genotypic resistance profile and the ongoing virological failure. The highly resistant genotypic profile was mainly due to an extensive exposure to the N(n)RTI class that has been considered the backbone of antiretroviral regimens. The presence of NAMs has been demonstrated to be highly correlated with reduced susceptibility to all N(n) RTIs [19], thus a therapeutic switch was fully justified.

Moreover, when this study began, new PIs as tipranavir and darunavir, the new NNRTI etravirine, and entry inhibitors were not yet available. Raltegravir had not been licensed even for adult populations. In addition, this dual boostedPI-based regimen significantly and rapidly decreased HIV-RNA and led to an improved prognosis for the patients as well as preventing a worsening of the genotypic resistance.

The regimen was well tolerated and none of the patients discontinued the therapy due to side effects. Hepatic parameters remained stable overtime apart from TB, as expected. Lipids increased over 36-42 months of observation without causing therapeutic interruptions.

Hyperlipidemia is a well-know complication of ARV therapy in pediatric patients. The European Pediatric Lipodistrophy Group showed that PI use, specifically ritonavir, was associated with dyslipidemia [18]. Hypercholesterolemia showed a prevalence of 38% in children that took ritonavir vs 24% in those without ritonavir use. Recently, Alam et al showed a prevalence of 31% of metabolic abnormalities in a cohort of 385 HIV-infected children: 4 out of 5 of these children had hypertriglyceridemia and 2 out of 5 of these children had hypercholesterolemia. The use  of ritonavir-boosted PI regimens was associated with a consistent risk factor for all metabolic abnormality outcomes [20]. Other two studies showed an association of the use of a double-PI regimen consisting of LPV/r and SQV in HIV-infected children with a percentage of patients with a median serum cholesterol and triglyceride significantly increased compared to the baseline value. Similarly, our results showed that almost 57% of children treated with ATV/r + fAVP developed hypercholesterolemia and hypertriglyceridemia. These data may be considered more serious than those observed in the previous studies and this could be related to the type of analysis used. In fact, we did not define dyslipidemia using a single cut-off value but lipid values were categorized according to age and gender reference values. Our study is somehow limited by the small number of subjects assessed. Since this observation was carried out in a small number of subjects within the out-patients clinic, we did not decide to conduct a case-control study.

Moreover, we did not have the possibility to obtain pK data, thus the relationship between drug exposure and toxicity could not be assessed. We understand that TDM studies are of pivotal importance when using drug regimens which include compounds with a potential interaction, e.g. 2 PIs.

In this study, we have proposed a therapeutic strategy that could be considered obsolete and most likely is not being used in most pediatric Infectious Disesase divisions. Nevertheless, in the presence of multiple failures, particularly with N (n)RTIs and NNRTIs, this strategy has overcome the complexity of the resistance pattern. This double-boosted protease regimen with ATV/r and fAVP was effective in suppressing HIV viremia and improving immunological outcome. During the study duration, hypercholesterolmia and hypertriglyceridemia were commonly observed and need close follow-up. The impact on bilirubin level and lipid profile suggests caution in using this regimen in the pediatric population. Thus, this regimen should only be considered as a possible option for a rescue treatment in HIV-infected children and adolescents who failed N(n)RTIs and more so in those with an extensive N(n)RTI resistance.

Conclusions

The main contribution of this study lies in the clinical efficacy of a regimen composed by ATV/r and fAVP in effectively maintaining the viral suppression together with a good immunological outcome. An increase in lipid levels was demonstrated in the majority of children included in our study although none of them discontinued HAART. In the future, safer therapeutic strategies, with the same effectiveness, will ameliorate the performance status of our patients. In the meantime, these children will be safely followed to that point.

(18-78) U/L, whereas they were 33 (30-40) U/L at month 42. AST resulted 37 (22-70) U/L and 32 (29-38) U/L and γGT was 27 (18-42) U/L and 28 (18-34) U/L, at baseline and month 42, respectively. All hepatic enzymes remained quite stable during the entire observation time without any statistical difference. As shown in Figure 2, TB varied more extensively at different time intervals. Overall one subject maintained a normal level, whereas the other 4 subjects showed a grade 2. One patient showed a grade 3 toxicity at month 12, while a single patient reached the grade 4 of toxicity at month 12, 30 and 42 [17]. At baseline, the TB median and range values were 0.65 (0.30-0.80) mg/dL and reached 3.37 (3.27-3.96) mg/ dL at month 42; this result was statistically significant (P = 0.046). Fasting lipid profiles (TC, HDL, LDL, and TG) are shown in Figure 3. TC showed a significant increase (p < 0.05) from baseline to month 42, 143 (112-157) mg/dL and 194 (160-203) mg/dL, respectively. TC values > 97 th cent.le for males and 94 th cent.le for females were detected in 4/7 patients (57%). TG increased from baseline (78 mg/dL [59-106]) to month 42 (175 mg/dL [135-194]) with a significant difference (P < 0.05). TG values >97 th percentile were detected in 4/7 patients. (57 %) LDL cholesterol remained stable over-time, with baseline values of 75 (64-105) mg/dl and 106 (92-116) at month 42. LDL values > 97 th cent.le for males and >95 th cent.le for females were detected in patients 4/7 patients (57%). HDL exhibited protective values during the follow up. At baseline, one out of 7 patients had lipohypertrophy consisting in truncal fat accumulation, "buffalo hump" and breast enlargement. In this single patient, lipohypertrophy remained stable during the follow up. No other patients developed signs of lipodistrophy during the double-boosted PI therapy. At baseline all patients had a normal HOMA index (3.8 [1.2-10.1)], which was maintained stable during the follow up.

Figure 1
1CD4 cell count profiles in HIV-infected children and adolescents treated with double-boosted protease inhibitors during the study period.

Figure 2
2Total bilirubin profile in HIV-infected children and adolescents treated with double-boosted protease inhibitors during the study period.

Figure 3
3Mean values of lipids (TC, HDL, TG, LDL) in HIVinfected children and adolescents treated with double-boosted protease inhibitors during the study period.

Table 1
1Genotypic resistance mutations before switching to a double-boosted protease inhibitors regimenNNRTI
PI
Resistant Drugs

Patient
98 (G)
103 (R/N)
108 (I)
135 (L/I/V)
283 (I)

P1
G
L
63 P, 71 V, 77 wt/I, 93 L
NVP L-lR

P2
N
I
N
I
10 V, 35 D
EFV and NVP L-lR

P3
wt/I
77I
none

P4
No mutations
63 P, 93 L
none

P5
V
V
35 D, 60 E, 63 P
none

P6
No mutations
No mutations
none

P7
R
T
10 V, 13 wt/V, 63 P, 77 I
none

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AcknowledgementsWe wish to acknowledge the precious help of Elizabeth L. Kaplan, MSW in preparing the manuscript.Competing interestAuthors declared no conflict of interest.Authors' contributions SR, VG and CM composed the manuscript. FA and OV analized the data. AV, GZ and MG revised the manuscript. All authors read and approved the final manuscript.Submit your next manuscript to BioMed Central and take full advantage of:
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Efficacy and safety of a dual boosted protease inhibitor-based regimen, atazanavir and fosamprenavir/ ritonavir, against HIV: experience in a pediatric population. Rusconi, BMC Infectious Diseases. 12179Cite this article asCite this article as: Rusconi et al.: Efficacy and safety of a dual boosted protease inhibitor-based regimen, atazanavir and fosamprenavir/ ritonavir, against HIV: experience in a pediatric population. BMC Infectious Diseases 2012 12:179.


Cardiovascular Ultrasound Persistent left superior vena cava: a case report and review of literature

Sandeep K Goyal
Department of Medicine
Boston University School of Medicine
BostonMAUSA

Sujeeth R Punnam email@example.com
Division of Cardiology
Michigan State University
East LansingMIUSA

Gita Verma
Maulana Azad Medical College
New DelhiIndia

Frederick L Ruberg firstname.lastname@example.com
Department of Medicine
Section of Cardiology
Boston University School of Medicine
BostonMAUSA

Department of Radiology
Boston University School of Medicine
BostonMAUSA

Cardiovascular Ultrasound Persistent left superior vena cava: a case report and review of literature
10.1186/1476-7120-6-50BioMed Central Page 1 of 4 (page number not for citation purposes) Case report * Corresponding author
Persistent left superior vena cava is rare but important congenital vascular anomaly. It results when the left superior cardinal vein caudal to the innominate vein fails to regress. It is most commonly observed in isolation but can be associated with other cardiovascular abnormalities including atrial septal defect, bicuspid aortic valve, coarctation of aorta, coronary sinus ostial atresia, and cor triatriatum. The presence of PLSVC can render access to the right side of heart challenging via the left subclavian approach, which is a common site of access utilized when placing pacemakers and Swan-Ganz catheters. Incidental notation of a dilated coronary sinus on echocardiography should raise the suspicion of PLSVC. The diagnosis should be confirmed by saline contrast echocardiography.

Background

Persistent left superior vena cava (PLSVC) is an uncommon vascular anomaly; however, it is the most common congenital anomaly of thoracic venous system. It is usually asymptomatic and is detected when cardiovascular imaging is performed for unrelated reasons. When a left subclavian approach is used for vascular access, its presence can complicate catheter placement within the right side of heart. Here we present a case that highlights the practical implications PLSVC. Further, we review a diagnostic approach and provide insight into the embryonic basis of this anomaly.

Case presentation

A 19-year-old male was admitted to the hospital after sustaining multiple injuries, including sternal fracture, in a motor vehicle accident. An admission echocardiogram revealed a dilated coronary sinus ( Figure 1) with normal right sided filling pressures, raising the suspicion for the presence of a persistent left sided superior vena cava (PLSVC). A follow-up agitated saline ("bubble") study was recommended but not immediately performed. A Swan-Ganz catheter was subsequently placed via the left subclavian approach, and on routine post-procedural chest X-ray, an unusual course of the catheter was identified ( Figure 2). PLSVC was suspected, and a follow-up echocardiogram demonstrated the catheter passing through the coronary sinus ( Figure 3) (See additional file 1). A Contrast enhanced computed tomography study of thorax was performed to assess the bony and vascular injuries associated with motor vehicle accident, which also revealed PLSVC as an incidental finding ( Figure 4).

As, the diagnosis was well established on an echocardiogram showing catheter traversing the coronary sinus, a saline contrast echocardiography was deemed unnecessary and was not performed.

Discussion

Persistent left SVC is the most common congenital thoracic venous anomaly with a prevalence of 0.3-0.5% in general population [1]. The thoracic embryonic venous system is composed of two large veins (the superior cardinal veins) which return blood from cranial aspect of embryo, and the inferior cardinal vein, which returns blood from the caudal aspect. Both pairs of veins join to Transthoracic echocardiogram, parasternal long axis view, illustrating a dilated coronary sinus (CS) Figure 1 Transthoracic echocardiogram, parasternal long axis view, illustrating a dilated coronary sinus (CS). Other chambers visible are the left ventricle (LV), aorta (Ao), and left atrium (LA).

Chest-x-ray demonstrating unusual course of Swan-Ganz catheter (arrows) with its distal end in the proximal pulmo-nary artery Figure 2 Chest-x-ray demonstrating unusual course of Swan-Ganz catheter (arrows) with its distal end in the proximal pulmonary artery. Note the course of the catheter into the heart on the left side of the spine, rather than the right side via the normal anatomic position of the superior vena cava.

Echocardiogram demonstrating the Swan-Ganz catheter (seen in cross section and indicated by the small arrow) pass-ing via dilated coronary sinus The most common subtype of PLSVC results in the presence of both left and right SVCs. A bridging innominate vein may or may not be present. Webb et al [2] reported that a PLSVC is associated with absence of the innominate vein in 65% cases. More rarely, the caudal right superior cardinal vein regresses leading to an absent right SVC with PLSVC. In this case, the left SVC returns all the blood from cranial aspect of the body. Variations have also been reported in the insertion of left SVC. In 80-90% of individuals, the persistent LSVC drains into the right atrium via the coronary sinus and is of no hemodynamic consequence. In the remaining cases, it may drain in left atrium resulting in a right to left sided shunt.

Diagnosis of left SVC is usually made as an incidental finding during cardiovascular imaging or surgery. Placement of Swan-Ganz catheter via the left subclavian approach as in this case of PLSVC demonstrates an unusual course of the catheter on chest X-ray [Fig 1]. Transthoracic echocardiography reveals a dilated coronary sinus and diagnosis can be confirmed by use of saline contrast ("bubble study") echocardiography. PLSVC is not the only cause of a dilated coronary sinus, however, with other etiologies including elevated right atrial pressure (most common), coronary arterio-venous fistula, partial anomalous pulmonary venous return, or an "unroofed" coronary sinus affording shunt flow between the left atrium and coronary sinus. The following diagnostic criteria can be used with echocardiography: (1) the presence of a dilated coronary sinus on two-dimensional echocardiography in the absence of evidence of elevated right sided filling pressures; (2) enhancement of the dilated coronary sinus before the right atrium (RA) after contrast material infusion into a left arm vein; (3) normal transit of contrast with RA opacification before the coronary sinus with contrast injected from the right arm. Multislice computed tomography [Fig 4] or magnetic resonance venography can also be employed to establish the diagnosis, and is useful to rule out variations in the typical anomalous venous course. Single or multiplane transesophageal echocardiography [3] and radionuclide angiocardiography have also been used to establish diagnosis.

Almost 40% of patients with PLSVC can have a variety of associated cardiac anomalies, [4,5] such as atrial septal defect, bicuspid aortic valve, coarctation of aorta, coronary sinus ostial atresia, and cor triatriatum. The presence of associated anomalies is more common with concomitant absence of right SVC the notation of which warrants appropriate investigation to rule out other anomalies. The PLSVC has been associated with anatomical and architectural abnormalities of the sinus node and conduction tissues. Both sinus and AV node can have persistent fetal dispersion in the central fibrous body in subjects with PLSVC [6].

PLSVC has various practical implications when the left subclavian vein is used for access to the right side of the heart or pulmonary vasculature. Swan-Ganz catheter placement can be challenging as it is performed without imaging under many circumstances, such as at the bedside. PLSVC can also complicate permanent pacemaker and implantable cardioverter defibrillator (ICD) placement (the latter of which is always done under fluoroscopic guidance thus the anomaly is typically detected during the procedure). Serious complications such as arrhythmia, cardiogenic shock, cardiac tamponade, and coronary sinus thrombosis have been reported when pacemaker leads or catheters have been inserted via PLSVC. Fortunately, the incidence of such complications is relatively low, and permanent pacemaker leads for single chamber pacing have been successfully placed via PLSVC as early as 1971 [7]. Improvements in catheter types and technique over time have permitted the successful placement of right atrial and right ventricular leads for dual-chamber pacing [8]. In addition, cardiac resynchronization therapy for advanced chronic heart failure requires the placement of third pacing lead in left posterolateral vein of the heart. Several operators have successfully placed a cardiac resynchronization system, and therefore a lead via the coronary sinus, in individuals with PLSVC with good intermediate term results [9].

During cardiac surgery, the presence of PLSVC is a relative contraindication to the administration of retrograde cardioplegia. It may be possible to clamp the PLSVC to prevent the cardioplegia solution from perfusing retrograde up the PLSVC and its branches with inadequate myocardial protection [10]. However, there is a possibility that there may be some steal of cardioplegia solution through an accessory vein. During heart transplantation in a patient with PLSVC, the coronary sinus must be dissected carefully to permit reanastomosis of PLSVC to right atrium [11].

Conclusion

Presence of a dilated coronary sinus on echocardiography should alert the clinician towards the possibility of PLSVC. The diagnosis should be confirmed by saline contrast echocardiography. Cardiologists and critical care physicians should consider presence of PLSVC whenever a catheter or guide wire inserted via left subclavian vein takes an unusual left-sided downward course. A PLSVC certainly presents technical difficulties with right heart access via the left subclavian, but does not preclude insertion of catheters; however, the additional associated risks should be discussed with the patient if the diagnosis of PLSVC is already established, and alternative access sites should be considered.

Figure 3
3Echocardiogram demonstrating the Swan-Ganz catheter (seen in cross section and indicated by the small arrow) passing via dilated coronary sinus. CT thorax showing left sided superior vena Cava (large arrow) Figure 4 CT thorax showing left sided superior vena Cava (large arrow). form right and left common cardinal veins before entering the embryological heart. The left common cardinal vein persists to form coronary sinus and oblique vein of left atrium. During the 8 th week of gestation, an anastomosis forms between right and left superior cardinal veins resulting in the innominate (or brachiocephalic) vein. The cephalic portion of superior cardinal veins form the internal jugular veins. The caudal portion of right superior vein forms the normal right-sided superior vena cava, while the portion of the left superior cardinal vein caudal to the innominate vein normally regresses to become "ligament of Marshall". If this normal regression of the left superior cardinal vein fails to occur, a persistent left-sided vascular structure that empties into the coronary sinus, results (the PLSVC). The innominate vein may or may not degenerate in these cases leading to variations in anatomy.
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AcknowledgementsWe would like to thanks the patient and her family for giving us permission to publish this case report.ConsentWritten informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.Competing interestsThe authors declare that they have no competing interests.Authors' contributionsSKG collection of data, patient care and preparation of manuscript. SRP, GV preparation of manuscript. FLR final revision of manuscript and guidance. All authors read and approved the final manuscript.Additional materialAdditional file 1Echocardiographic movie of parasternal long axis view showing Swan-Ganz catheter traversing the dilated coronary sinus.Click here for file [http://www.biomedcentral.com/content/supplementary/1476-7120-6-50-S1.avi]
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Diagnosis of persistent left superior vena cava by multiplane transesophageal echocardiography. Cardiologia. P Voci, G Luzi, L Agati, 40Voci P, Luzi G, Agati L: Diagnosis of persistent left superior vena cava by multiplane transesophageal echocardiography. Car- diologia 1995, 40(4):273-275.

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Persistent fetal dispersion of the atrioventricular node and His bundle within the central fibrous body. T James, T: Marshall, Xviii, Circulation. 536James T, Marshall T: XVIII. Persistent fetal dispersion of the atrioventricular node and His bundle within the central fibrous body. Circulation 1976, 53(6):1026-1034.

Transvenous pacemaker implantation by way of an anomalous left superior vena cava. M Rose, L Gross, A Protos, J Thorac Cardiovasc Surg. 626Rose M, Gross L, Protos A: Transvenous pacemaker implanta- tion by way of an anomalous left superior vena cava. J Thorac Cardiovasc Surg 1971, 62(6):965-966.

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open heart surgery in a case associated with persistent left superior vena cava: a method of simple occlusion of L-SVC using an alternative extra-pericardial approach and retrograde cardioplegia. M Oosawa, A Sakai, M Abe, N Hanayama, Z Lin, K Kodera, RepeatOosawa M, Sakai A, Abe M, Hanayama N, Lin Z, Kodera K: [Repeat open heart surgery in a case associated with persistent left superior vena cava: a method of simple occlusion of L-SVC using an alternative extra-pericardial approach and retro- grade cardioplegia].

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Pathogenesis of persistent left superior vena cava with a coronary sinus connection. E Nsah, G Moore, G Hutchins, Pediatr Pathol. 112Nsah E, Moore G, Hutchins G: Pathogenesis of persistent left superior vena cava with a coronary sinus connection. Pediatr Pathol 1991, 11(2):261-269.


Self-monitoring of health data by patients with a chronic disease: does disease controllability matter?

Martine W J Huygens
Ilse C S Swinkels
Judith D De Jong
Monique J W M Heijmans
Roland D Friele
Onno C P Van Schayck
Luc P De Witte
Self-monitoring of health data by patients with a chronic disease: does disease controllability matter?
10.1186/s12875-017-0615-3R E S E A R C H A R T I C L E Open Access
Background: There is a growing emphasis on self-monitoring applications that allow patients to measure their own physical health parameters. A prerequisite for achieving positive effects is patients' willingness to self-monitor. The controllability of disease types, patients' perceived self-efficacy and health problems could play an essential role in this. The purpose of this study is to investigate the relationship between patients' willingness to self-monitor and a range of disease and patient specific variables including controllability of disease type, patients' perceived self-efficacy and health problems. Methods: Data regarding 627 participants with 17 chronic somatic disease types from a Dutch panel of people with chronic diseases have been used for this cross-sectional study. Perceived self-efficacy was assessed using the general self-efficacy scale, perceived health problems using the Physical Health Composite Score (PCS). Participants indicated their willingness to self-monitor. An expert panel assessed for 17 chronic disease types the extent to which patients can independently keep their disease in control. Logistic regression analyses were conducted. Results: Patients' willingness to self-monitor differs greatly among disease types: patients with diabetes (71.0%), asthma (59.6%) and hypertension (59.1%) were most willing to self-monitor. In contrast, patients with rheumatism (40.0%), migraine (41.2%) and other neurological disorders (42.9%) were less willing to self-monitor. It seems that there might be a relationship between disease controllability scores and patients' willingness to self-monitor. No evidence is found of a relationship between general self-efficacy and PCS scores, and patients' willingness to self-monitor. Conclusions: This study provides the first evidence that patients' willingness to self-monitor might be associated with disease controllability. Further research should investigate this association more deeply and should focus on how disease controllability influences willingness to self-monitor. In addition, since willingness to self-monitor differed greatly among patient groups, it should be taken into account that not all patient groups are willing to self-monitor.

Background

In recent decades there has been a growing emphasis on self-monitoring applications in primary care. These applications allow patients to measure their own physical health parameters, such as blood pressure, blood glucose level and lung function [1][2][3]. Self-monitoring is a key aspect of patients' self-management [4], especially in diseases like diabetes, asthma and heart failure. It offers the potential to create awareness of symptoms, bodily sensations, daily activities and cognitive processes and to provide information for action [5]. The effects of self-monitoring look promising: literature shows that it could improve self-management, symptom management and disease regulation, and could lead to reductions in complications, improved patients' coping and attitudes toward their disease, realistic goal setting and an enhanced quality of life [6]. Self-monitoring is a broad term, including the monitoring of clinical parameters, symptom measures and daily activities [5]. In the current study we focus on individual self-monitoring of clinical parameters (such as: weight, blood pressure, blood glucose level and lung function) with the use of technical equipment.

With the introduction of new technologies, selfmonitoring has become more convenient and accessible for patients. However, a prerequisite for achieving the positive effects of self-monitoring is the willingness of patients to self-monitor. Patients' willingness to use technologies in health care is often studied with the Technology Acceptance Model (TAM) [7,8]. This model theorizes that beliefs about perceived ease of use and perceived usefulness are the main constructs predicting user intention. A recent review study shows that the TAM is still the most important model used to identify the factors that influence the adoption of information technologies in health care [9]. This model had been extended and modified in recent years, such as in the Unified Theory of Acceptance and Use of Technology (UTAUT) [10]. Besides ease of use and perceived usefulness two other key constructs are included in the UTAUT model: social influence and facilitating conditions. However, we suggest that there are other underlying disease-specific and patient-specific factors that play an essential role in patients' willingness to self-monitor.

For instance, the relevance of self-monitoring may not be the same for each disease type. For patients with diabetes and hypertension, for example, self-management goals are easy to define, such as optimizing blood glucose level and blood pressure, which are parameters that can easily be monitored by the patient. For patients with a disease like arthritis these goals are less concrete [11]. Moreover, other researchers suggest that in disease types such as diabetes, the feedback between action and change is rather direct and can clearly be observed by the patient, which can trigger the sensemaking process of performing self-management behaviour. For disease types such as cancer there are less direct and easily captured indicators that can activate this process [12].

Hence, it would seem that disease types differ in the extent to which they are controllable by the patients' behaviour (e.g., using medication, nutrition and physical activity), which could be related to patients' willingness to self-monitor. Some support for this was found in a recently performed focus group study [13]. In this study we found that patients with diabetes were more interested in the use of self-monitoring than patients with a Chronic Obstructive Pulmonary Disease (COPD) and a cardiovascular condition, because they mentioned that their own behaviour (nutrition, weight loss and medication) directly influenced their health, and that selfmonitoring support could help them to influence their behaviour.

However, disease controllability does not only differ between disease types, but can also differ between individuals. Patients' belief that they are capable of managing and controlling their disease is better known as self-efficacy [14]. This plays an important role in performing selfmanagement behaviour [15] and might likewise influence patients' willingness to self-monitor. Previous research found that higher perceived self-efficacy was associated with better blood glucose monitoring in patients with diabetes [16,17].

Besides self-efficacy, the benefits that patients experience from self-monitoring might play an important role in their willingness to self-monitor. According to the Health Belief Model [18], perceiving higher benefits in relation to costs improves the performance of health behaviour. This is also found to be related to adherence to self-monitoring in patients with diabetes [19]. Experienced benefits regarding self-monitoring could be the reduction or prevention of disease symptoms. In our focus group study we found that patients with a chronic disease who experienced minimal health complaints were less willing to self-monitor because they expected fewer benefits. They did not expect improvements in their health, because their disease had little impact on their life, and were more focused on the perceived costs; the time it takes to do the self-monitoring [13]. Therefore in terms of selfmonitoring we argue that patients who experience more severe health problems perceive higher benefits from selfmonitoring (improvements in their health) in relation to the costs (doing the self-monitoring) and might likewise be more willing to self-monitor.

Up until now self-monitoring is often not yet integrated in standard care procedures. Moreover, the role of the patient and health care professional regarding the provision of self-monitoring is not yet defined. This study aimed to get more insight in willingness to selfmonitor by patients with different chronic disease types. In this study our hypotheses which were based on the results of the focus group study are tested in a wider range of disease types to answer the following research question: what is the relationship between the controllability of disease types (disease specific) and patients' perceived self-efficacy and health problems (patient specific) on the one hand, and patients' willingness to self-monitor on the other. In addition, the influence of patients' characteristics (gender, age, level of education and multimorbidity) on patients' willingness to self-monitor will be investigated. Based on the previously performed focus group study we generated three hypotheses:

Disease-specific hypothesis: 1. The controllability of a certain type of chronic disease is related to patients' willingness to self-monitor; patients with a chronic disease that can be, in general, properly kept under control by the patient will be more interested in self-monitoring than patients that have a disease that is less controllable by the patient.

Patient-specific hypotheses: 2. Patient's perceived self-efficacy is related to their willingness to self-monitor; patients with high perceived self-efficacy are more interested in self-monitoring than patients that perceive low self-efficacy.

3. The severity of problems that patients experience with daily functioning is related to their willingness to self-monitor; patients that have moderate problems with daily functioning are more interested in self-monitoring than patients who perceive no problems with daily functioning. This holds to a certain extent; patients who experience many problems with daily functioning might not be able to do the monitoring anymore.

We investigated these hypotheses in a Dutch nationwide study of patients with the most prevalent chronic diseases.

Methods

Design and participants

Data from 1294 participants of the National Panel of people with Chronic illness or Disability (NPCD) were used for this cross-sectional study [20]. This panel was established by NIVEL (the Netherlands Institute for Health Services Research) and is a nationwide prospective panel study in the Netherlands. Participants with a chronic disease are recruited from random samples of general practices in the Netherlands. The following criteria were used for recruitment of the NPCD: being diagnosed with a somatic chronic disease (using the International Classification of Primary Care (ICPC)) by a certified medical doctor, being aged 15 or older, not being permanently institutionalized, being aware of the diagnosis, not being terminally ill (a life expectancy of more than six months according to their general practitioner), being mentally capable of participating, and having sufficient mastery of the Dutch language. Every year 500 new panel members are selected to replace panel members who have withdrawn or who have participated for the maximum term of four years. The NPCD can be considered to be representative of the chronic disease population in the Netherlands of aged 15 years and older. The NPCD is registered with the Dutch Data Protection Authority. All data are collected and handled in accordance with the privacy protection guidelines of the Dutch authority.

Patients voluntarily participate in the NPCD. Participation has no influence on their care. Twice a year (spring and autumn) the panel members voluntarily fill out a questionnaire. The panel members could choose whether they wanted to receive questionnaires by post, email or phone. Some items used in this study were issued in the spring questionnaire of 2014, others in the autumn questionnaire of 2014. The questionnaire can be found in Additional file 1.

In addition, to test our hypothesis regarding selfmonitoring of health data by people with different chronic disease types an expert panel of 16 medical doctors and physiotherapists was invited to participate in a questionnaire study in February and March 2016.

Measurements

Participant characteristics

The background characteristics of the members of the NPCD had already been gathered using a questionnaire that was completed at inclusion in the panel. For this study, the following characteristics were used: gender (1 = male, 2 = female), age and level of education (1 = low (primary school or preparatory vocational training), 2 = middle (intermediate or advanced general education or intermediate vocational training), 3 = high (high vocational education or university)). In addition, information regarding participants' chronic disease(s) was provided at inclusion by their general practitioner.

Self-monitoring of health data

The following question regarding self-monitoring of health data was asked to participants in autumn 2014: "Did you measure certain health data by yourself in the past year, for example blood pressure, blood glucose values or lung function?" Participants could answer: 1) yes; 2), no, but I would like to do this (independently); 3), no, but I would like to do this together with a care professional; or 4), no, and I do not want to do this.

Self-efficacypatient specific

Patients' perceived self-efficacy was collected using the Dutch version of the general self-efficacy scale [21] in spring 2014 (Cronbach's alpha was 0.92). This questionnaire consists of ten questions with a four-point Likert scale ranging from 1) completely wrong to 4) completely right. For example: "When I am confronted with a problem, I can usually find several solutions" and "It is easy for me to stick to my aims and accomplish my goals". Participants with four or more missing values were excluded. Mean values were used in further analyses, in which a higher mean score indicates a higher level of self-efficacy.

Problems in daily functioningpatient specific

The Dutch version of the Physical Health Composite Score (PCS) of the SF-12 [22] was used to investigate patients' experienced problems in daily functioning in autumn 2014 (Cronbach's alpha was 0.88). The SF-12 has shown adequate validity and reliability in multiple studies [23]. PCS scores were collected in spring 2014. Mean scores were calculated using QualityMetric Health Outcomes™ Scoring Software 5.0 and could range from 0 to 100, in which 100 indicates the highest level of health.

Disease controldisease specific

To test the hypothesis, based on literature and experiences regarding self-monitoring of health data by people with different disease types (disease-specific hypothesis), nine care professionals from the expert panel (six medical doctors and three physiotherapists) out of sixteen experts who were invited, answered the following question for 17 different chronic diseases: "To what extent can people with a chronic disease, in general, independently keep their disease under control (by means of nutrition, physical activity, medication etc.)?" Participants could respond with: 1) not at all; 2) to some extent; or 3) to a large extent. Mean scores per disease type were used in the analyses.

Statistical analyses

Descriptive analyses were conducted to study participants' characteristics per disease group. Participants were divided into 17 different disease-type categories based on the diagnosis of their first chronic disease (ischaemic heart disease, hypertension, other cardiovascular disorders, cancer, asthma, COPD, other respiratory diseases, diabetes, thyroid disorder, chronic back pain, rheumatism, osteoarthritis, other musculoskeletal disorders, migraine, other neurological disorders, digestive disorder and skin disease). The most common diseases per disease category can be found in Additional file 2.

Univariate logistic regression analyses were conducted to test the relationship between patient-and diseasespecific characteristics, and patients' willingness to selfmonitor health data (dependent variable: 1 = participants who did measure certain health data by themselves + participants who would like to do that (independently), 0 = participants who would like to do that together with a care professional + participants who did not want to do that at all). The univariate logistic regression analyses were conducted with the following independent variables: mean scores of the expert panel regarding disease controllability, mean score of the general self-efficacy scale, PCS score of the SF-12 and age, gender (1 = male, 2 = female), level of education (1 = low, 2 = middle, 3 = high) and multimorbidity (0 = one disease, 1 = two or more diseases). Assumptions for logistic regression were checked. We adjusted for clustering of data within chronic disease types (patients within one disease group have the same disease control score). Finally, multivariate logistic regression analyses were performed with all the above-mentioned concepts (dependent variable: willingness to self-monitor). Statistical analyses were performed using STATA 14.0. Figure 1 shows a flow chart of the process of the inclusion of participants in this study. Out of 1294 participants of the NPCD, 979 responded to the questionnaire that was issued in spring 2014. Of these 979 participants, 2 had no chronic disease or a disease that did not fit in one of the 17 most prevalent chronic disease types (n = 67). Subsequently 101 participants were excluded because of incomplete data regarding the self-monitoring question (n = 44), PCS (n = 39) and level of education (n = 18). In addition 160 participants were excluded because they did not fill out the questionnaire at spring (n = 160) or because of incomplete data in the general self-efficacy scale (n = 22). This resulted in a total sample of 627 participants. Non response analyses showed no differences in Fig. 1 Flow chart of participants included in the study characteristics between the non-responders (including people who responded but did not fill out the entire questionnaire) and the final sample, except for age (non-responders: M = 63.5, SE = 0.55; final sample: M = 65.1, SE = 0.46, t(1292) = −2.15, p = 0.03). So except for a sampling bias of age the sample is representative of the chronic disease population in the Netherlands. Table 1 shows the characteristics of the study sample. Diabetes (19.8%), other cardiovascular disorders (8.9%), ischaemic heart disease/heart failure (8.6%) and asthma (8.3%) were the most common chronic disease types within the sample. Almost 4% of the participants were diagnosed less than three years ago, 16.1% three to five years ago, 31.9% six to ten years ago and almost half (48.1%) longer than ten years ago. More than half (51.2%) had been diagnosed with two or more chronic diseases. All characteristics per disease group can be found in Additional file 3.

Results

Participants

Relationship of disease controllability with willingness to self-monitor Figure 2 represents the association between disease controllability scores (assessed by the expert panel) and the percentage of participants that is willing to self-monitor health data per disease type. Patients' willingness to selfmonitor differs greatly among disease types: patients with diabetes (71.0%), asthma (59.6%) and hypertension (59.1%) were most willing to self-monitor. In contrast, patients with rheumatism (40.0%), migraine (41.2%) and other neurological disorders (42.9%) were less willing to self-monitor. In addition, the expert panel assessed diabetes (3.0), hypertension (2.7) and COPD and asthma (2.6) as diseases that can be kept well under control by the patient, and cancer (1.1), thyroid disorder (1.4), and other neurological disorders and migraine (1.6) as the diseases that are most difficult for the patient to keep under control. The scores of the expert panel can be found in Additional file 4.

A relationship is found between disease controllability scores and patients' willingness to self-monitor. The correlation between disease controllability scores and the percentage of participants that is willing to self-monitor is significant (r = 0.547, p < 0.05). In addition, looking at the univariate and multivariate logistic association of disease controllability with patients' willingness to self-monitor (first column Tables 2 and 3 respectively), a significant association is found (univariate: OR = 1.589, 95% CI = 1.142-2.210; multivariate: OR = 1.639, 95% CI = 1.129-2.380).

Diabetes groupdisease controllability and willingness to self-monitor

As can be seen in Fig. 2, all experts assessed diabetes as a disease that can, to a large extent, be kept under control by the patient (the maximum mean score of 3.0). In addition, the diabetes group scored remarkably high on willingness to self-monitor (71.0%). Therefore, we decided to look more deeply into the diabetes group only (n = 124).

Of the 124 people with diabetes, 9 participants have type I diabetes and 103 type II (for 12 participants it is unknown what type of diabetes they have). 41 participants with diabetes use insulin (33.1%), 65 do not use insulin (52.4%) and for 18 participants this is unknown (14.5%). Of the 41 participants using insulin, 95.1% are willing to self-monitor health data. In contrast, among patients who are not using insulin 46.2% are willing to do so. In Tables 2 and 3 (second column) it can be seen that by excluding the entire diabetes group in the univariate and multivariate logistic regression analyses to investigate the relationship between disease controllability and patients' willingness to self-monitor (n = 503), no significant association is found (univariate: OR = 1.169, 95% CI = 0.942-1.451; multivariate: OR = 1.164, 95% CI = 0.908-1.491).

Relationship of patient characteristics with willingness to self-monitor

Patients' perceived problems in daily functioning (PCS) and self-efficacy have no significant association with their willingness to self-monitor (see Tables 2 and 3). Age and multimorbidity also have no relationship with willingness to self-monitor. In contrast, males and more highly educated people are significantly more willing to self-monitor their health data.

Looking at the diabetes sample only (Tables 2 and 3  third column), there was no significant association between gender and education level, and patients' willingness to self-monitor.

Discussion

Principal results

This study provides the first evidence of an association between disease controllability and patients' willingness to self-monitor health data. Against our expectations, no  evidence is found for a relationship between self-efficacy and the severity of problems that patients experience with daily functioning, and patients' willingness to selfmonitor. In addition, it is found that males and more highly educated people are more willing to self-monitor their health data. The scores of the diabetes group regarding disease controllability and patients' willingness to self-monitor were remarkably high. Patients with diabetes using insulin were particularly willing to self-monitor (95.1%). The difference between diabetes and other chronic disease types regarding self-monitoring could be explained by the fact that for diabetes patients self-monitoring is recommended as an integral component of their treatment (particularly for patients using insulin) [24,25]. So for many persons with diabetes, their "willingness" to selfmonitor is beyond question, because they have to monitor their blood glucose level for their (optimal) treatment. Hence, as we found in this study, this is also independent of the patient characteristics they have. For other chronic disease types self-monitoring is often not yet integrated into the standard treatment. For these chronic disease types males and more highly educated people were more willing to self-monitor, which is in line with some, but not all, self-management research [26][27][28]. Interestingly, we did not find a relationship between multimorbidity (having two or more chronic conditions) and willingness to self-monitor. Although many research found that performing optimal self-management behaviour may be more challenging for people with multiple chronic diseases [29,30], this study suggest that this does not influence willingness to self-monitor.

Contrary to our expectations no effect of self-efficacy on patients' willingness to self-monitor was found in this study. However, in other studies that did find an association between self-efficacy and self-monitoring, questionnaires were used to investigate self-efficacy regarding patients' chronic disease, such as how participants assessed their capability to monitor, plan and carry out activities for their disease (for example nutrition, physical exercises and medication) [16,17]. In the current study the general self-efficacy scale [21] was used, which consists of generic questions such as "When I am confronted with a problem, I can usually find several solutions" and "It is easy for me to stick to my aims and accomplish my goals". It appears that patients' general self-efficacy is not related to their willingness to self-monitor. In future research it might be interesting to investigate if a chronic disease self-efficacy scale, e.g., the Chronic Diseases Self-Efficacy Scale of Lorig and colleagues [31] is related to willingness to self-monitor.

No relationship was found between patients' perceived problems in daily functioning and self-monitoring, which is not in line with our hypothesis. Again, participants were asked to assess all their general health problems in daily functioning, and not only the physical problems related to their specific chronic disease. Although we found some support for this possible relationship in our recently performed focus group study [13], other research regarding eHealth did not find a relationship between health needs and patients' acceptance and interests of eHealth as well [32,33]. It seems that patients' willingness to self-monitor health data is not directly related to their perceived health problems. In future research it might be interesting to investigate if a disease specific health scale (such as Quality of life Disease Impact Scale [34]) has an influence on patients' willingness to self-monitor. In addition, although we did not ask participants to indicate their expected or perceived benefits of self-monitoring health data, it might be expected that willingness to self-monitor is more related to the overall concepts of "perceived benefits" and "perceived usefulness", which are well-studied concepts in care technology acceptance research [8,19,[35][36][37]. It might be that patients are more willing to self-monitor when they believe that self-monitoring can convey (health) benefits.

This study provides the first evidence that patients' willingness to self-monitor might be associated with

Strengths and limitations

The strength of this study is its general focus on patients' willingness to self-monitor health data in a broad sample (n = 627) of people with the most common chronic somatic disease types (17 chronic disease types). The panel used for this study was representative of the Dutch chronic disease population (except for age). The overall response of this panel is high and participants were not recruited for the specific topic of this study which minimizes selection bias; items used for this study were a part of a panel questionnaire. In addition, this study is conducted to test our hypotheses, which were based on the results of a recently performed focus group study [13]. Moreover, to the best of our knowledge, this is the first study to investigate the relationship between the controllability of certain chronic disease types and patients' willingness to self-monitor.

As mentioned before, one limitation of this study is that data from general questionnaires have been used to investigate patients' self-efficacy and physical problems that were not specifically related to patients' chronic disease. In addition, the dependent variable 'patients' willingness to self-monitor' was based on one non-validated question. Furthermore, patients' willingness to self-monitor and their Physical health Composite Scores (PCS) were collected in autumn 2014, in contrast to general self-efficacy scores, which were investigated in spring 2014. However, it is expected that these scores did not significantly change within six months. In addition, the number of people within a disease type highly differed from n = 6 (chronic back pain) to n = 124 (diabetes). Five chronic disease types had only 20 or less participants. In addition, in the analyses with the diabetes group only, no relationships were found between gender and education level, and patients' willingness to self-monitor. This might be explained by the lower number of participants compared with the entire sample (n = 124 vs n = 627). Moreover, no relationship between multimorbidity and patients' willingness to self-monitor was found in this study. We defined multimorbidity as having two or more chronic conditions. It might be that this does not reflect the complexity of this problem, in particular not for people with a high number of conditions.

Another limitation is that people that had done selfmonitoring in the previous year and those that wanted to do so independently were recoded as being willing to self-monitor. Additional separate analyses were performed to investigate differences between the association of the actual self-monitoring group or the willing to self-monitor group on the one hand, and disease controllability on the other. Although similar positive associations between the actual and willing to self-monitor group, and disease controllability were found, no valid statements could be made due to the small number of people in each (disease) group. In addition, it is assumed that the actual self-monitoring group were also willing to self-monitor in the first place. Moreover, participants that wanted to do self-monitoring with the help of a care professional and participants that did not want to do self-monitoring at all were recoded as being not willing to self-monitor, because we were particularly interested in people that were willing to self-monitor independently. This because we consider self-monitoring as a core element of self-management and by monitoring independently the required effects of self-monitoring (improving symptom management, disease regulation, patients' coping and attitudes toward their disease, realistic goal setting and an enhanced quality of life [6]) will be most effective.

Conclusion

This study provides the first evidence that patients' willingness to self-monitor might be associated with disease controllability. Further research should investigate this association more deeply and should focus on how disease controllability influences willingness to self-monitor. In addition, it should be investigated what other disease-and patient specific factors play a role in patients' willingness to self-monitor. No evidence is found of a relationship between self-efficacy and the severity of problems that patients experience with daily functioning, and patients'

Fig. 2
2Mean disease controllability score (expert panel: 1 = not at all; 2 = to some extent; 3 = to a large extent) plotted against the percentage of participants that is willing to monitor independently

Table 1
1Characteristics of the study sampleCharacteristics

Table 2
2Univariate logistic regression analyses with the dependent variable: willingness to monitor health dataEntire sample (n = 627)
Sample without diabetes (n = 503)
Diabetes only (n = 124)

Independent variable
OR (95% CI)
p
OR (95% CI)
p
OR (95% CI)
p

Age
0.994 (0.979-1.010)
0.453
0.994 (0.977-1.012)
0.519
0.973 (0.934-1.014)
0.193

Gender (ref = male)
0.728 (0.533-0.993)
0.045
0.669 (0.488-0.916)
0.012
1.800 (0.774-4.187)
0.172

Level of education (ref = low)
-
-
-
-
-
-

Intermediate
1.308 (0.863-1.983)
0.206
1.611 (1.158-2.240)
0.005
0.741 (0.308-1.784)
0.503

High
1.908 (1.300-2.801)
0.001
2.254 (1.603-3.170)
<0.001
1.256 (0.435-3.627)
0.673

Multimorbidity (ref = one disease)
1.076 (0.816-1.420)
0.604
1.192 (0.902-1.577)
0.217
0.849 (0.390-1.850)
0.681

Disease control score (expert panel)
1.589 (1.142-2.210)
0.006
1.169 (0.942-1.451)
0.156
-
-

Physical Health Composite Score (PCS)
1.005 (0.989-1.020)
0.567
1.002 (0.984-1.020)
0.823
1.003 (0.966-1.041)
0.874

Self-efficacy patient
0.994 (0.747-1.322)
0.968
1.062 (0.760-1.483)
0.724
0.747 (0.374-1.492)
0.408

Table 3
3Multivariate logistic regression analyses with the dependent variable: willingness to monitor health data To what extent can people with a chronic disease, in general, independently keep their disease under control (by means of nutrition, physical activity, medication etc.) for the following chronic diseases?"). It is recommended to first define the concept of disease controllability and to investigate what factors and mechanisms play a role in this. Secondly, it should be investigated how disease controllability influences patients' willingness to self-monitor, for example by using qualitative methodology focusing on behavioural and motivational aspects of patients. Thirdly, it should be investigated how self-monitoring applications for different disease types can be adapted to improve this. In addition, it should be investigated what other disease-and patient specific factors play a role in patients' willingness to self-monitor, such as disease effects, patients' perceived controllability of symptoms and patients' coping and attitudes toward their disease. This study shows that the percentage of participants that is willing to self-monitor health data differed greatly between disease types. Hence, while developing and offering self-monitoring applications it should be kept in mind that not all patient groups are willing to self-monitor their health data.Entire sample (n = 627)
Sample without diabetes (n = 503)
Diabetes only (n = 124)

Independent variable
OR (95% CI)
p
OR (95% CI)
p
OR (95% CI)
p

Age
0.992 (0.976-1.008)
0.312
0.993 (0.974-1.012)
0.468
0.972 (0.929-1.018)
0.229

Gender (ref = male)
0.792 (0.522-1.203)
0.274
0.655 (0.468-0.916)
0.013
1.934 (0.783-4.776)
0.153

Level of education (ref = low)
-
-
-
-
-
-

Intermediate
1.491 (0.973-2.284)
0.067
1.804 (1.256-2.590)
0.001
0.652 (0.250-1.701)
0.382

High
2.042 (1.415-2.950)
<0.001
2.344 (1.645-3.341)
<0.001
1.217 (0.398-3.724)
0.730

Multimorbidity (ref = one disease)
1.170 (0.868-1.576)
0.303
1.278 (0.903-1.809)
0.167
0.876 (0.386-1.988)
0.751

Disease control score (expert panel)
1.639 (1.129-2.380)
0.009
1.164 (0.908-1.491)
0.230
-
-

Physical Health Composite Score (PCS)
1.001 (0.984-1.019)
0.916
0.999 (0.979-1.020)
0.934
1.008 (0.962-1.057)
0.726

Self-efficacy patient
0.862 (0.655-1.134)
0.288
0.881 (0.636-1.221)
0.448
0.757 (0.346-1.656)
0.486

AcknowledgementsThe authors would like to thank Geeke Waverijn for her help in setting up the data set and Lucas van der Hoek for his statistical advice.FundingFor this study data is used from the National Panel of people with Chronic illness or Disability (NPCD), which is financed by the Netherlands Ministry of Public Health, Welfare and Sports and the Netherlands Ministry of Social Affairs and Employment. In addition, this study is part of a PhD project, which is partly funded by a grant from the Netherlandswillingness to self-monitor. Since the percentage of participants that is willing to self-monitor health data differed greatly between disease types, it should be taken into account that not all patient groups are willing to self-monitor their health data. Availability of data and materials For this study data from the NPCD is used. The dataset analysed in the current study is not publicly available because it will be used for further studies, but is available from the corresponding author on reasonable request.Authors' contributions JJ and MJH are responsible for setting up the questionnaire and data collection. MH, IS, JJ, MJH, RF, OS and LP conceived the study. MH is responsible for data analyses and the interpretation of the data. MH wrote the draft of the manuscript with the help of IS, JJ, MH, RF, OS and LW. All authors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.Consent for publicationNot applicable.Ethics approval and consent to participateThe National Panel of people with Chronic illness or Disability (NPCD) is registered with the Dutch Data Protection Authority. According to the Dutch legislation, neither obtaining informed consent nor approval by a medical ethics committee is obligatory for doing research within the panel, because panel members only participate in questionnaire studies (http://www.ccmo.nl/ en/questionnaire-research). Panel members voluntarily participate in the NPCD. Participation has no influence on their care and questionnaires were not detailed, burdensome or intimate. No participants under the age of 16 participated in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.Publisher's NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Submit your next manuscript to BioMed Central and we will help you at every step:
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