METHODS: MEDLINE and Embase databases were searched from inception up to September 2019 to identify all studies that compared the predictive performance of cystatin C- and/or creatinine-based eGFR in predicting the clearance of vancomycin. The prediction errors (PEs) (the value of eGFR equations minus vancomycin clearance) were quantified for each equation and were pooled using a random-effects model. The root mean squared errors were also quantified to provide a metric for imprecision.
RESULTS: This meta-analysis included evaluations of seven different cystatin C- and creatinine-based eGFR equations in total from 26 studies and 1,234 patients. The mean PE (MPE) for cystatin C-based eGFR was 4.378 mL min-1 (95% confidence interval [CI], -29.425, 38.181), while the creatinine-based eGFR provided an MPE of 27.617 mL min-1 (95% CI, 8.675, 46.560) in predicting clearance of vancomycin. This indicates the presence of unbiased results in vancomycin clearance prediction by the cystatin C-based eGFR equations. Meanwhile, creatinine-based eGFR equations demonstrated a statistically significant positive bias in vancomycin clearance prediction.
CONCLUSION: Cystatin C-based eGFR equations are better than creatinine-based eGFR equations in predicting the clearance of vancomycin. This suggests that utilising cystatin C-based eGFR equations could result in better accuracy and precision to predict vancomycin pharmacokinetic parameters.
METHODS: This was a prospective cohort study conducted in the neonatal intensive care units of two public hospitals in Malaysia. Neonates with a gestational age greater than 34 weeks who were started on empiric antibiotics within 72 h of life were screened. The data were then stratified according to de-escalation and non-de-escalation practices, where de-escalation practice was defined as narrowing down or discontinuation of empiric antibiotic within 72 h of treatment.
RESULTS: A total of 1045 neonates were screened, and 429 were included. The neonates were then divided based on de-escalation (n = 207) and non-de-escalation (n = 222) practices. Neonates under non-de-escalation practices showed significantly longer durations of antibiotic use compared to those under de-escalation practices (p
METHODS: A total of 6221 tweets related to breast cancer posted between 2018 and 2022 were collected. An oncologist and two pharmacists coded the tweets to differentiate between true information and misinformation, and to analyse the misinformation content. Binary logistic regression was conducted to identify determinants of misinformation.
RESULTS: There were 780 tweets related to breast cancer prevention and treatment, and 456 (58.5%) contain misinformation, with significantly more misinformation in Malay compared to English tweets (OR = 6.18, 95% CI: 3.45-11.07, p
METHODS: A Markov model of a Malaysian hypothetical cohort aged ≥30 years (N = 14,589,900) was used to estimate the total and per-member-per-month (PMPM) costs of RAS uptake. This involved an incidence and prevalence rate of 9.0% and 10.53% of patients with diabetes and hypertension respectively. Transition probabilities of health stages and costs were adapted from published data.
RESULTS: An increasing uptake of RAS drugs would incur a projected total treatment cost ranged from MYR 4.89 billion (PMPM of MYR 27.95) at Year 1 to MYR 16.26 billion (PMPM of MYR 92.89) at Year 5. This would represent a range of incremental costs between PMPM of MYR 0.20 at Year 1 and PMPM of MYR 1.62 at Year 5. Over the same period, the care costs showed a downward trend but drug acquisition costs were increasing. Sensitivity analyses showed the model was minimally affected by the changes in the input parameters.
CONCLUSION: Mild impact to the overall healthcare budget has been reported with an increased utilization of RAS. The long-term positive health consequences of RAS treatment would reduce the cost of care in preventing deterioration of kidney function, thus offsetting the rising costs of purchasing RAS drugs. Optimizing and increasing use of RAS drugs would be considered an affordable and rational strategy to reduce the overall healthcare costs in Malaysia.
PURPOSE: The study aimed to evaluate the budget impact of increasing the uptake of denosumab for the management of postmenopausal osteoporosis in Malaysia.
METHODS: A Markov budget impact model was developed to estimate the financial impact of osteoporosis treatment. We modelled a scenario in which the uptake of denosumab would increase each year compared with a static scenario. A 5-year time horizon from the perspective of a Malaysian MOH healthcare provider was used. Model inputs were based on Malaysian sources where available. Sensitivity analyses were performed to examine the robustness of the modelled results.
RESULTS: An increase in denosumab uptake of 8% per year over a 5-year time horizon would result in an additional budget impact, from MYR 0.26 million (USD 0.06 million) in the first year to MYR 3.25 million (USD 0.78 million) in the fifth year. When expressed as cost per-member-per-month (PMPM), these were less than MYR 0.01 across all five years of treatment. In sensitivity analyses, the acquisition cost of denosumab and medication persistence had the largest impact on the budget.
CONCLUSION: From the perspective of a Malaysian MOH healthcare provider, moderately increasing uptake of denosumab would have a minimal additional budget impact, partially offset by savings in fracture treatment costs. Increasing the use of denosumab appears affordable to reduce the economic burden of osteoporosis in Malaysia.
METHODS AND ANALYSIS: This is a prospective direct observational study that will be conducted in five neonatal intensive care units. A minimum sample size of 820 drug preparations and administrations will be observed. Data including patient characteristics, drug preparation-related and administration-related information and other procedures will be recorded. After each round of observation, the observers will compare his/her observations with the prescriber's medication order, hospital policies and manufacturer's recommendations to determine whether MAE has occurred. To ensure reliability, the error identification will be independently performed by two clinical pharmacists after the completion of data collection for all study sites. Any disagreements will be discussed with the research team for consensus. To reduce overfitting and improve the quality of risk predictions, we have prespecified a priori the analytical plan, that is, prespecifying the candidate predictor variables, handling missing data and validation of the developed model. The model's performance will also be assessed. Finally, various modes of presentation formats such as a simplified scoring tool or web-based electronic risk calculators will be considered.
METHODS: Study subjects include patients with various levels of renal function recruited from the nephrology clinic and wards of a tertiary hospital. The blood samples collected were analyzed for serum cystatin C and creatinine levels by particle-enhanced turbidimetric immunoassay and kinetic alkaline picrate method, respectively. DNA was extracted using a commercially available kit. -Polymerase chain reaction results were confirmed by direct DNA Sanger sequencing.
RESULTS: The genotype percentage (G/G = 73%, G/A = 24.1%, and A/A = 2.9%) adhere to the Hardy-Weinberg equilibrium. The dominant allele found in our population was CST3 73G allele (85%). The regression lines' slope of serum cystatin C against creatinine and cystatin C-based eGFR against creatinine-based eGFR, between G and A allele groups, showed a statistically significant difference (z-score = 3.457, p < 0.001 and z-score = 2.158, p = 0.015, respectively). Patients with A allele had a lower serum cystatin C level when the values were extrapolated at a fixed serum creatinine value, suggesting the influence of genetic factor.
CONCLUSION: Presence of CST3 gene G73A polymorphism affects serum cystatin C levels.
METHODS: This research was conducted following the PRISMA guidelines. The databases that had been searched included Web of Science, PubMed, Scopus, Cochrane Library and Ovid from 2017 to 2022. Study characteristics were retrieved and study outcomes such as adherence status and diabetes control were extracted and quantitatively analysed through meta-analysis.
RESULTS: Eight studies met the final inclusion criteria and were included in the analysis, contributing to a total of 884 subjects. The methodological quality of the included studies was variable. Three studies reported statistically significant improvement in medication adherence through mobile apps intervention. Additionally, the mobile apps intervention proved effective in reducing glycaemic outcomes. As compared to non-mobile apps users, glycated haemoglobin (HbA1c) significantly decreased by 0.36% (95% CI -0.47% to -0.25%), whereas fasting plasma glucose (FPG) significantly decreased by 16.75 mg/dL (95% CI -17.60 mg/dL to -15.80 mg/dL).
CONCLUSION: Mobile apps intervention had beneficial impacts on medication adherence and glycaemic parameters. Future research should explore the best practical approach for real-world settings.
METHODS: Relevant articles were identified from Medline, Embase, AMED, PsycINFO, International Pharmaceutical Abstracts, and APA PsycArticles. Studies that measured patient adherence in the implementation or persistence phase for a period of at least five years using objective or multiple measures of adherence and investigated correlates of adherence were included. The titles, abstracts and full articles were screened and reviewed by two authors and any discrepancies were discussed with a third author.
RESULTS: Twenty-six studies were included. Mean rate of adherence at five-year for implementation phase was 66.2% (SD = 17.3%), and mean persistence was 66.8% (SD = 14.5%). On average, adherence decreased by 25.5% (SD = 9.3%) from the first to fifth year. Higher rate of adherence was observed through self-report in comparison to database or medical record. Older age, younger age, higher comorbidity index, depression and adverse effects were associated with lower adherence. Treatment with aromatase inhibitors, received chemotherapy, and prior medication use were associated with improved adherence.
CONCLUSION: Adherence to adjuvant endocrine therapy decreased from the first to fifth year of treatment. On average, one-third of patients were not adherent to treatment by the fifth year. Nineteen recurring factors were found to be significantly associated with long-term adherence in multiple studies. Further research using objective or multiple measures of adherence are needed to improve validity of results.