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Background: Hypoglycemia is the most common complication in insulin treated diabetes. Though mostly mild, it can be fatal in rare cases: It is hypothesized that hypoglycemia related QTc prolongation contributes to cardiac arrhythmia., Objective: To evaluate influence of nocturnal hypoglycemia on QTc and heart rate variability (HRV) in children with T1D., Methods: Children and adolescents with T1D for at least 6 months participated in an observational study using continuous glucose monitoring (CGM) and Holter electrocardiogram for five consecutive nights. Mean QTc was calculated for episodes of nocturnal hypoglycemia (<3.7 mmol/L) and compared to periods of the same duration preceding hypoglycemia. HRV (RMSSD, low and high frequency power LF and HF) was analyzed for different 15 min intervals: before hypoglycemia, onset of hypoglycemia, before/after nadir, end of hypoglycemia and after hypoglycemia., Results: Mean QTc during hypoglycemia was significantly longer compared to euglycemia (412 ± 15 vs. 405 ± 18 ms, p = 0.005). HRV changed significantly: RMSSD (from 88 ± 57 to 73 ± 43 ms) and HF (from 54 ± 17 to 47 ± 17nu) decreased from before hypoglycemia to after nadir, while heart rate (from 69 ± 9 to 72 ± 12 bpm) and LF (from 44 ± 17 to 52 ± 21 nu) increased (p = 0.04)., Conclusion: A QTc lengthening effect of nocturnal hypoglycemia in children with T1D was documented. HRV changes occurred even before detection of nocturnal hypoglycemia by CGM, which may be useful for hypoglycemia prediction., (© 2021 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Background: The impact of pre-transplant social determinants of health on post-transplant outcomes remains understudied. In the United States, poor clinical outcomes are associated with underprivileged status, as assessed by the Social Adaptability Index (SAI), a composite score of education, employment status, marital status, household income, and substance abuse. Using data from the Swiss Transplant Cohort Study (STCS), we determined the SAI's predictive value regarding two post-transplant outcomes: all-cause mortality and return to dialysis., Methods: Between 2012 and 2018, we included adult renal transplant patients (aged ≥ 18 years) with pre-transplant assessment SAI scores, calculated from a STCS Psychosocial Questionnaire. Time to all-cause mortality and return to dialysis were predicted using Cox regression., Results: Of 1238 included patients (mean age: 53.8 ± 13.2 years; 37.9% female; median follow-up time: 4.4 years [IQR: 2.7]), 93 (7.5%) died and 57 (4.6%) returned to dialysis. The SAI's hazard ratio was 0.94 (95%CI: 0.88-1.01; p = .09) for mortality and 0.93 (95%CI: 0.85-1.02; p = .15) for return to dialysis., Conclusions: In contrast to most published studies on social deprivation, analysis of this Swiss sample detected no significant association between SAI score and mortality or return to dialysis., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Introduction: Heart transplant (HTx) recipients need to follow a complex therapeutic regimen. We assessed the international prevalence and variability in nonadherence to six nonpharmacologic treatment components (physical activity, sun protection, diet, alcohol use, nonsmoking, and outpatient follow-up visits)., Methods: We used self-report data of 1397 adult HTx recipients from the 36-HTx-center, 11-country, 4-continent, cross-sectional BRIGHT study (ClinicalTrials.gov ID: NCT01608477). The nonadherence definitions used were as follows: Physical activity: <3 times/wk 20 minutes' vigorous activity, <5 times/wk 30 minutes' moderate activity, or <5 times/wk a combination of either intensity; Sun protection: not "always" applying any sun protection; Diet: not "often" or "always" following recommended diet(s); Alcohol use: >1 alcoholic drink/d (women) or >2 drinks/d (men); Smoking: current smokers or stopped <1 year before; Follow-up visits: missing ≥1 of the last 5 outpatient follow-up visits. Overall prevalence figures were adjusted to avoid over- or underrepresentation of countries. Between-country variability was assessed within each treatment component via chi-square testing., Results: The adjusted study-wide nonadherence prevalence figures were as follows: 47.8% for physical activity (95% CI [45.2-50.5]), 39.9% for sun protection (95% CI [37.3-42.5]), 38.2% for diet recommendations (95% CI [35.1-41.3]), 22.9% for alcohol consumption (95% CI [20.8-25.1]), 7.4% for smoking cessation (95% CI [6.1-8.7]), and 5.7% for follow-up visits (95% CI [4.6-6.9]). Significant variability was observed between countries in all treatment components except follow-up visits., Conclusion: Nonadherence to the post-HTx nonpharmacologic treatment regimen is prevalent and shows significant variability internationally, suggesting a need for tailored adherence-enhancing interventions., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Obesity and weight gain are serious concerns after solid organ transplantation (Tx); however, no unbiased comparison regarding body weight parameter evolution across organ groups has yet been performed. Using data from the prospective nationwide Swiss Transplant Cohort Study, we compared the evolution of weight parameters up to 3 years post-Tx in 1359 adult kidney (58.3%), liver (21.7%), lung (11.6%), and heart (8.4%) recipients transplanted between May 2008 and May 2012. Changes in mean weight and body mass index (BMI) category were compared to reference values from 6 months post-Tx. At 3 years post-Tx, compared to other organ groups, liver Tx recipients showed the greatest weight gain (mean 4.8±10.4 kg), 57.4% gained >5% body weight, and they had the highest incidence of obesity (38.1%). After 3 years, based on their BMI categories at 6 months, normal weight and obese liver Tx patients, as well as underweight kidney, lung and heart Tx patients had the highest weight gains. Judged against international Tx patient data, the majority of our Swiss Tx recipients' experienced lower post-Tx weight gain. However, our findings show weight gain pattern differences, both within and across organ Tx groups that call for preventive measures., (© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Introduction: In solid organ transplantation (TX), perceived health status (PHS) is a relevant patient-reported outcome. For patients on TX waiting lists, PHS information is limited. The aim of this study was therefore to compare PHS of heart, liver, lung, and renal TX candidates., Methods: We used a cross-sectional descriptive design, including consecutive heart, liver, lung and renal TX candidates listed at a university hospital in Belgium. PHS was evaluated using the generic EuroQoL instrument, assessing patients' perceptions of their general PHS, and evaluating the health-related domains of mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Data were analyzed using multivariable ordinal logistic regression., Results: The study included 314 TX candidates: 29 heart, 75 liver, 67 lung, and 143 renal. Analyses controlling for possible PHS-impacting variables (age, gender, marital status, education, comorbidities) yielded significantly disparate results between the four candidate groups. Renal candidates reported best PHS, followed by liver candidates, whereas heart and lung candidates, whose score differences were not significant, had worst PHS., Conclusion: The EQ-5D seems to be a valuable tool to identify differences in health-related problems in the four different organ candidate groups. The results can be used to create intervention programs focusing on effective clinical management for these patients pre- and post-transplant., (© 2009 John Wiley & Sons A/S.)

Background: Non-adherence to immunosuppressive medication is strongly associated with poor outcomes. Identifying the factors influencing it is a first step in developing adherence interventions. This study's objective was to investigate the prevalence of self-reported and collaterally-reported non-adherence to immunosuppressives, and, based on the Integrative Model of Behavioral Prediction, to explore the association between non-adherence, intention to adhere, attitudes, norms and self-efficacy., Methods: This cross-sectional study included a convenience sample of 114 renal transplant recipients in follow-up care, one to five yr post-transplant. Non-adherence was measured by self-reports and collateral reports. Factors of the Integrative Model of Behavioral Prediction were assessed using a self-report questionnaire., Results: Self-reports showed non-adherence of 23.7%; collateral reports showed 3.8%; and a combination of the two showed 26.4%. Logistic regression analysis showed that the attitude "Not all immunosuppressive drugs are necessary to prevent rejection" was less frequent in patients with higher intentions to adhere, with an odds ratio (OR) of 0.05 (95% CI 0.01-0.50). The barrier of "Forgetfulness/Interruption of daily routine" was associated with non-adherence, with an OR of 3.74 (95% CI 1.55-9.03)., Conclusions: Forgetfulness is the most powerful barrier against adherence. Intention to adhere plays a minor role in non-adherence in renal transplant recipients.

Background/significance: The use of complementary and alternative medicine (CAM) has increased considerably in the general population in recent decades. However, the prevalence of CAM use in renal transplant patients has not yet been assessed., Aim: To determine the prevalence and correlates of CAM use among renal transplant patients (RTX) who are more than one year post transplant., Methods: This secondary data analysis used data from Part 1 of the Supporting Medication Adherence in Renal Transplantation (SMART) study, which tested prevalence, determinants and consequences of non-adherence regarding immunosuppressive medication in kidney transplant (renal TX) patients. The study's convenience sample consisted of 356 patients recruited from two Swiss outpatient transplant clinics during their annual examination visits (mean age: 53+/-13; male: 58%). The use of CAM as well as the specific kind of CAM used was assessed through structured interviews. Assessed CAM use correlates were age, gender, education, depressive symptomatology, comorbidity and smoking status. Relationships between CAM use and candidate correlates were explored using multiple logistic regression., Results: The prevalence of CAM use in this sample of renal TX patients was 11.8%. Most frequently used alternative medicines were Homeopathy (42.9%) and Chinese medicine (23.8%). Two patients used St John's wort. The percentage of patients using Homeopathy (5.1%) and herbal medicine (2%) was similar to that of the general Swiss population (HO: 6.1% & HM: 2.6%). Significant correlates for CAM use were younger age (p=0.017; OR=0.96; 95%CI=0.93-0.99) and female gender (p=0.035; OR=2.13; 95%CI=1.05-4.3)., Conclusion: Every eighth renal transplant recipient in this sample used some form of CAM. Of these, some used herbal medicines, of which some are known to interfere with certain immunosuppressive treatment (St John's wort/Chinese medicines). These findings indicate that it is important for health care providers working in renal TX to assess CAM use.

Background: Although non-adherence to an immunosuppressive regimen (NAH) is a major risk factor for poor outcome after renal transplantation (RTx), very few studies have examined non-adherence intervention in this context. This pilot randomized controlled trial (RCT) tested the efficacy of an educational-behavioural intervention to increase adherence in non-adherent RTx patients. We also assessed how NAH evolves over time., Methods: Eighteen RTx non-adherent patients (age: 45.6 +/- 1.2 yr; 78.6% male) were randomly assigned to either an intervention group (IG) (n = 6) or an enhanced usual care group (EUCG) (n = 12), the latter receiving the usual clinical care. The IG received one home visit and three telephone interviews. We assessed NAH through electronic monitoring (EM) of medication intake during a nine-month period (three months intervention, six months follow-up)., Results: Five of 18 patients withdrew. Inclusion in the study resulted in a remarkable decrease in NAH in both groups over the first three months (IG chi(2) = 3.97, df = 1, p = 0.04; EUCG chi(2) = 3.40, df = 1, p = 0.06). The IG showed the greatest decrease in NAH after three months, although this did not reach statistical significance (at 90 d, chi(2) = 1.05, df = 1, p = 0.31). Thereafter, NAH increased gradually in both groups, reaching comparable levels at the end of the six-month follow-up (i.e. at nine months)., Conclusion: Our findings suggest an inclusion effect. Although the intervention in this pilot RCT appeared to add further benefit in medication compliance, a lack of statistical power prevented us from making a strong statistical statement.

Background: Severe alcohol use is recognized as a major public health concern, even though light to moderate alcohol use might have beneficial effects on health. Alcohol use has been studied to some extent in solid organ transplant populations, yet evidence is lacking on alcohol use and its correlates in the renal transplant population. The aim of this study was therefore to determine the prevalence, severity and correlates of alcohol use in renal transplant recipients., Methods: This cross-sectional study is a secondary analysis of the Supporting Medication Adherence in Renal Transplantation (SMART) study. Alcohol use was assessed by patient's self-report. At risk and binge drinkers were classified using World Health Organization criteria. The following correlates of alcohol use were explored: adherence with immunosuppression (Siegal questionnaire; electronic monitoring), smoking, coping style (UCL), depressive symptomatology (BDI) and busyness/routine in life style (ACQ Busyness Scale)., Results: Two hundred and eighty-four patients were included in this analysis, 58.1% male, with a mean age of 54 yr (range 20-84) and a median of seven (interquartile ranges [IQR] 8) yr post-transplantation. A total of 52.8% of study participants reported to drink alcohol at least once a week. Two hundred and eighty of 284 subjects (98.5%) were drinking at low risk, four at moderate risk (1.5%). None of the participants were drinking severely. Correlates of alcohol use were male gender and being professionally active., Conclusion: Alcohol use is less prevalent in renal transplant recipients than in the general population. Severe alcohol use does not seem to represent a serious problem in renal transplant patients.