SETTING: Five medical and cardiology wards of a tertiary care center in Malaysia.

SUBJECTS: Five hundred cardiac inpatients, who received ACEIs concomitantly with other interacting drugs.

METHOD: This was a prospective cohort study of 500 patients with cardiovascular diseases admitted to Penang Hospital between January to August 2006, who received ACEIs concomitantly with other interacting drugs. ACEI-drug interactions of clinical significance were identified using available drug information resources. Drug Interaction Probability Scale (DIPS) was used to assess the causality of association between ACEI-drug interactions and the adverse outcome (hyperkalemia).

MAIN OUTCOME MEASURE: Hyperkalemia as an adverse clinical outcome of the interaction was identified from laboratory investigations.

RESULTS: Of the 489 patients included in the analysis, 48 (9.8%) had hyperkalemia thought to be associated with ACEI-drug interactions. Univariate analysis using binary logistic regression revealed that advanced age (60 years or more), and taking more than 15 medications were independent risk factors significantly associated with hyperkalemia. However, current and previous smoking history appeared to be a protective factor. Risk factors identified as predictors of hyperkalemia secondary to ACEI-drug interactions by multi-logistic regression were: advanced age (adjusted OR 2.3, CI 1.07-5.01); renal disease (adjusted OR 4.7, CI 2.37-9.39); hepatic disease (adjusted OR 5.2, CI 1.08-25.03); taking 15-20 medications (adjusted OR 4.4, CI 2.08-9.19); and taking 21-26 medications (adjusted OR 9.0, CI 1.64-49.74).

METHOD: Outcomes derived from a systematic review, multi-disciplinary expert panel and patient input were included in a multilanguage online survey. Participants rated the absolute importance of outcomes using a 9-point Likert scale (7-9 being critically important). The relative importance was determined by a best-worst scale using multinomial logistic regression. Open text responses were analysed thematically.

RESULTS: The survey was completed by 873 participants [224 (26%) patients/caregivers and 649 (74%) health professionals] from 58 countries. Vascular access function was considered the most important outcome (mean score 7.8 for patients and caregivers/8.5 for health professionals, with 85%/95% rating it critically important, and top ranked on best-worst scale), followed by infection (mean 7.4/8.2, 79%/92% rating it critically important, second rank on best-worst scale). Health professionals rated all outcomes of equal or higher importance than patients/caregivers, except for aneurysms. We identified six themes: necessity for HD, applicability across vascular access types, frequency and severity of debilitation, minimizing the risk of hospitalization and death, optimizing technical competence and adherence to best practice and direct impact on appearance and lifestyle.

METHODS AND STUDY DESIGN: A cross-sectional study was conducted among 184 Malaysian HD patients. Anthropometric measurements and handgrip strength (HGS) were obtained using standardized protocols. Relevant biochemical indicators were retrieved from patients' medical records. Nutritional status was assessed using the dialysis malnutrition score. The sleep quality of patients was determined using the Pittsburgh Sleep Quality Index questionnaire on both dialysis and non-dialysis days.

RESULTS: Slightly more than half of the HD patients were poor sleepers, with approximately two-third of them having a sleep duration of <7 hours per day. Sleep latency (1.5±1.2) had the highest sleep component score, whereas sleep medicine use (0.1±0.6) had the lowest score. Significantly longer sleep latency and shorter sleep duration were observed in the poor sleepers, regardless of whether it was a dialysis day or not (p<0.001). Poor sleep quality was associated with male sex, old age, small triceps skinfold, hypoproteinemia, hyperkalemia, hyperphosphatemia, and poorer nutritional status. In a multivariate analysis model, serum potassium (β=1.41, p=0.010), male sex (β=2.15, p=0.003), and HGS (β=-0.088, p=0.021) were found as independent predictors of sleep quality.

METHODOLOGY: This is a retrospective cohort study recruiting all kidney transplant recipients in South Australia from January 2010 till December 2018. Following that, the incidence of blood transfusion within one week post-operatively were traced (transfusion group). The outcomes were compared with all other transplant recipients (non-transfusion group). Recipient's demographic, donor characteristics and immunological risk profiles were obtained from the transplant unit database, while the biopsy report, history of blood transfusion, latest serum creatinine and follow-up status was gathered from the electronic medical system (OASIS). The HLA-DSA and HLA-Ab results were collected from the NOMS database. Finally, the survival data were merged with the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry for South Australia recipients graft survival.

RESULTS: A total of 699 patients were eligible for analysis. The mean age was 50.64 ± 13.23 years old. There were more elderly (>65 years old) and females who needed transfusion. The majority had glomerulonephritis as the primary disease. There was no statistical difference in donor characteristics, cold ischemic time and immunological risk between the transfusion and non-transfusion group. There was no difference in the development of de novo HLA-DSA, HLA-Ab and rejection episodes between the group and the results were consistent in a model adjusted for all potential confounders. Median graft survival in days between the transfusion vs non-transfusion group was 1845 IQR (961,2430) and 1250 IQR (672,2013).