Methods: Primary data were collected through a standardized survey, and secondary data analysis was used to derive estimates of the ESRD expenditure.
Results: Total annual expenditure of ESRD by the public sector has grown 94% within a span of 7 years, from Malaysian Ringgit [MYR] 572 million (US dollars [USD] 405 million, purchasing power parity [PPP] 2010) in 2010 to MYR 1.12 billion (USD 785 million, PPP 2016) in 2016. The total ESRD expenditure in 2010 constituted 2.95% of the public sector's total health expenditure, whereas in 2016, the proportion has increased to 4.2%. Only 6% of ESRD expenditure was spent on renal transplantation, and the remaining 94% was spent on dialysis.
Conclusion: The share of ESRD expenditure in total health expenditure for the public sector is considered substantial given only a small proportion of the population is affected by the disease. The rapid increase in expenditure relative to the national total health expenditure should warrant the relevant authorities about sustainability of the existing financing mechanism of ESRD and the importance to institutionalize more drastic preventive measures.
METHODS: Via cross sectional approach, the current study collected data using a validated questionnaire to obtain information on the awareness of UNHS program among the health practitioners and to test the formulated hypotheses. 51, representing 81% response rate, out of 63 questionnaires distributed to the health professionals were returned and usable for statistical analysis. The survey instruments involving healthcare practitioners' awareness, human resource, program layout, screening instrument, and screening techniques instruments were adapted and scaled with 7-point Likert scale ranging from 1 (little) to 7 (many). Partial Least Squares (PLS) algorithm and bootstrapping techniques were employed to test the hypotheses of the study.
RESULTS: With the result involving beta values, t-values and p-values (i.e. β=0.478, t=1.904, p<0.10; β=0.809, t=3.921, p<0.01; β= -0.436, t=1.870, p<0.10), human resource, measured with training, functional equipment and program layout, are held to be significant predictors of enhanced knowledge of health practitioners. Likewise, program layout, human resource, screening technique and screening instrument explain 71% variance in health practitioners' awareness. Health practitioners' awareness is explained by program layout, human resource, and screening instrument with effect size (f2) of 0.065, 0.621, and 0.211 respectively, indicating that program layout, human resource, and screening instrument have small, large and medium effect size on health practitioners' awareness respectively. However, screening technique has zero effect on health practitioners' awareness, indicating the reason why T-statistics is not significant.
CONCLUSION: Having started the UNHS program in 2003, non-public hospitals have more experienced and well-trained employees dealing with the screening tools and instrument, and the program layout is well structured in the hospitals. Yet, the issue of homogeneity exists. Non-public hospitals charge for the service they render, and, in turn, they would ensure quality service, given that they are profit-driven and/or profit-making establishments, and that they would have no option other than provision of value-added and innovative services. The employees in the non-public hospitals have less screening to carry out, given the low number of babies delivered in the private hospitals. In addition, non-significant relationship between screening techniques and healthcare practitioners' awareness of UNHS program is connected with the fact that the techniques that are practiced among public and non-public hospital are similar and standardized. Limitations and suggestions were discussed.
METHODS: We carried out a prospective analysis based on the DFI samples collected from 2016 till 2018. Specimens were cultured with optimal techniques in addition to antibiotic susceptibility based on recommendations from The Clinical and Laboratory Standards Institute (CLSI). A total of 1040 pathogens were isolated with an average of 1.9 pathogens per lesion in 550 patients who were identified with having DFIs during this interval.
RESULTS: A higher percentage of Gram-negative pathogens (54%) were identified as compared with Gram-positive pathogens (33%) or anaerobes (12%). A total of 85% of the patients were found to have polymicrobial infections. Pseudomonas aeruginosa (19%), Staphylococcus aureus (11%) and Bacteroides species (8%) appeared to be the predominant organisms isolated. In the management of Gram-positive bacteria, the most efficacious treatment was seen with the use of Vancomycin, while Imipenem and Amikacin proved to be effective in the treatment of Gram-negative bacteria.
CONCLUSION: DFI's are common among Malaysians with diabetes, with a majority of cases displaying polymicrobial aetiology with multi-drug resistant isolates. The data obtained from this study will be valuable in aiding future empirical treatment guidelines in the treatment of DFIs. This study investigated the microbiology of DFIs and their resistance to antibiotics in patients with DFIs that were managed at a Tertiary Care Centre in Malaysia.
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.