OBJECTIVE: To develop an adherence prediction model for CKD patients.
METHODS: This multi-centre, cross-sectional study was conducted in 10 tertiary hospitals in Malaysia using simple random sampling of CKD patients with ≥1 medication (sample size = 1012). A questionnaire-based collection of patient characteristics, adherence (defined as ≥80% consumption of each medication for the past one month), and knowledge of each medication (dose, frequency, indication, and administration) was performed. Continuous data were converted to categorical data, based on the median values, and then stratified and analysed. An adherence prediction model was developed through multiple logistic regression in the development group (n = 677) and validated on the remaining one-third of the sample (n = 335). Beta-coefficient values were then used to determine adherence scores (ranging from 0 to 7) based on the predictors identified, with lower scores indicating poorer medication adherence.
RESULTS: Most of the 1012 patients had poor medication adherence (n = 715, 70.6%) and half had good medication knowledge (n = 506, 50%). Multiple logistic regression analysis determined 4 significant predictors of adherence: ≤7 medications (constructed score = 2, p
METHODS: This retrospective study was performed on all KTRs ≥18 years of age at our center from January 1, 2006 to December 31, 2015, who were prescribed diltiazem as tacrolimus-sparing agent. Blood tacrolimus trough level (TacC0) and other relevant clinical data for 70 eligible KTRs were reviewed.
RESULTS: The dose of 1 mg tacrolimus resulted in a median TacC0 of 0.83 ± 0.52 ng/mL. With the introduction of a 90-mg/d dose diltiazem, there was a significant TacC0 increase to 1.39 ± 1.31 ng/mL/mg tacrolimus (P < .01). A further 90-mg increase in diltiazem to 180 mg/d resulted in a further increase of TacC0 to 1.66 ± 2.58 ng/mL/mg tacrolimus (P = .01). After this, despite a progressive increment of every 90-mg/d dose diltiazem to 270 mg/d and 360 mg/d, there was no further increment in TacC0 (1.44 ± 1.15 ng/mL/mg tacrolimus and 1.24 ± 0.94 ng/mL/mg tacrolimus, respectively [P < .01]). Addition of 180 mg/d diltiazem reduced the required tacrolimus dose to 4 mg/d, resulting in a cost-savings of USD 2045.92 per year (per patient) at our center. Adverse effects reported within 3 months of diltiazem introduction were bradycardia (1.4%) and postural hypotension (1.4%), which resolved after diltiazem dose reduction.
CONCLUSION: Coadministration of tacrolimus and diltiazem in KTRs appeared to be safe and resulted in a TacC0 increment until reaching a 180-mg/d total diltiazem dose, at which point it began to decrease. This approach will result in a marked savings in immunosuppression costs among KTRs in Malaysia.
METHODS: The ADR reports recorded between 2000 and 2017 were retrospectively analysed to identify hepatic ADR reports. The trend and characteristics of hepatic ADR cases were described. Multivariate disproportionality analysis of the causative agents was performed to generate signals of hepatic ADRs.
RESULTS: A total of 2090 hepatic ADRs (1.77% of all ADRs) were reported with mortality rate of 12.7% among cases with known clinical outcomes. The incidence of hepatic ADR reporting in Malaysia increased significantly over 18 years from 0.26 to 9.45 per million population (P
METHODS: Hospital admissions for selected diagnoses between 1 February 2021 and 30 September 2021 were linked to the national COVID-19 immunisation register. We conducted self-controlled case-series study by identifying individuals who received COVID-19 vaccine and diagnosis of thrombocytopenia, venous thromboembolism, myocardial infarction, myocarditis/pericarditis, arrhythmia, stroke, Bell's Palsy, and convulsion/seizure. The incidence of events was assessed in risk period of 21 days postvaccination relative to the control period. We used conditional Poisson regression to calculate the incidence rate ratio (IRR) and 95% confidence interval (CI) with adjustment for calendar period.
RESULTS: There was no increase in the risk for myocarditis/pericarditis, Bell's Palsy, stroke, and myocardial infarction in the 21 days following either dose of BNT162b2, CoronaVac, and ChAdOx1 vaccines. A small increased risk of venous thromboembolism (IRR 1.24; 95% CI 1.02, 1.49), arrhythmia (IRR 1.16, 95% CI 1.07, 1.26), and convulsion/seizure (IRR 1.26; 95% CI 1.07, 1.48) was observed among BNT162b2 recipients. No association between CoronaVac vaccine was found with all events except arrhythmia (IRR 1.15; 95% CI 1.01, 1.30). ChAdOx1 vaccine was associated with an increased risk of thrombocytopenia (IRR 2.67; 95% CI 1.21, 5.89) and venous thromboembolism (IRR 2.22; 95% CI 1.17, 4.21).
CONCLUSION: This study shows acceptable safety profiles of COVID-19 vaccines among recipients of BNT162b2, CoronaVac, and ChAdOx1 vaccines. This information can be used together with effectiveness data for risk-benefit analysis of the vaccination program. Further surveillance with more data is required to assess AESIs following COVID-19 vaccination in short- and long-term.