OBJECTIVE: We aimed to identify the prevalence and risk factors of genitourinary C.trachomatis infection among patients attending STD clinics in northern Peninsular Malaysia.
METHODS: A hospital-based cross-sectional study was conducted in STD clinics of Hospital Pulau Pinang and Hospital Sultanah Bahiyah, Kedah from January to November 2014. Participants were individually interviewed using a structured data collection form followed by a physical examination and laboratory tests. Nucleic Acid Amplification Test (NAAT) was used to detect C.trachomatis infection. Analysis was carried out using SPSS Version 15.
RESULTS: Eighty-three sexually active patients were enrolled, consisting of 51 males and 32 females. The median age was 28.0 years. In general, 32.5% patients were asymptomatic, the remaining presented with genital discharge (41.0%), genital warty lesion (25.3%), genital ulcer (13.3%), dysuria (13.3%), dyspareunia (2.4%), urine hesistancy (1.2%) and genital swelling (1.2%). The prevalence of genitourinary C.trachomatis infection was 21.7% in the study population; 17.6% in males and 28.1% in females. Among the infected females, 44.4% were pregnant. Of those infected 56.6% did not show any symptoms of genital infection, and 77.8% were aged between 18 and 30 years, of which most were females. Among newly diagnosed HIV patients, the prevalence was 14.3%. From multivariable logistic regression analysis, age under 28 years, being married and engagement in oral sex had significantly increased odds of C.trachomatis infection.
CONCLUSIONS: C.trachomatis infection was common among patients attending STD clinics in northern Penisular Malaysia especially in the younger age groups. Majority of the infected patients were asymptomatic.
METHODS: This is a quasi-experimental study conducted in 20 intervention and 20 matched control clinics. We surveyed all HCPs who were directly involved in patient management. A self-administered questionnaire which included six questions on job satisfaction were assessed on a scale of 1-4 at baseline (April and May 2017) and post-intervention phase (March and April 2019). Unadjusted intervention effect was calculated based on absolute differences in mean scores between intervention and control groups after implementation. Difference-in-differences analysis was used in the multivariable linear regression model and adjusted for providers and clinics characteristics to detect changes in job satisfaction following EnPHC interventions. A negative estimate indicates relative decrease in job satisfaction in the intervention group compared with control group.
RESULTS: A total of 1042 and 1215 HCPs responded at baseline and post-intervention respectively. At post-intervention, the intervention group reported higher level of stress with adjusted differences of - 0.139 (95% CI -0.266,-0.012; p = 0.032). Nurses, being the largest workforce in public clinics were the only group experiencing dissatisfaction at post-intervention. In subgroup analysis, nurses from intervention group experienced increase in work stress following EnPHC interventions with adjusted differences of - 0.223 (95% CI -0.419,-0.026; p = 0.026). Additionally, the same group were less likely to perceive their profession as well-respected at post-intervention (β = - 0.175; 95% CI -0.331,-0.019; p = 0.027).
CONCLUSIONS: Our findings suggest that EnPHC interventions had resulted in some untoward effect on HCPs' job satisfaction. Job dissatisfaction can have detrimental effects on the organisation and healthcare system. Therefore, provider experience and well-being should be considered before introducing healthcare delivery reforms to avoid overburdening of HCPs.
RESULTS: Two fungal isolates (UM 1400 and UM 1020) from human specimens were identified as Daldinia eschscholtzii by morphological features and ITS-based phylogenetic analysis. Both genomes were similar in size with 10,822 predicted genes in UM 1400 (35.8 Mb) and 11,120 predicted genes in UM 1020 (35.5 Mb). A total of 751 gene families were shared among both UM isolates, including gene families associated with fungus-host interactions. In the CAZyme comparative analysis, both genomes were found to contain arrays of CAZyme related to plant cell wall degradation. Genes encoding secreted peptidases were found in the genomes, which encode for the peptidases involved in the degradation of structural proteins in plant cell wall. In addition, arrays of secondary metabolite backbone genes were identified in both genomes, indicating of their potential to produce bioactive secondary metabolites. Both genomes also contained an abundance of gene encoding signaling components, with three proposed MAPK cascades involved in cell wall integrity, osmoregulation, and mating/filamentation. Besides genomic evidence for degrading capability, both isolates also harbored an array of genes encoding stress response proteins that are potentially significant for adaptation to living in the hostile environments.
CONCLUSIONS: Our genomic studies provide further information for the biological understanding of the D. eschscholtzii and suggest that these wood-decaying fungi are also equipped for adaptation to adverse environments in the human host.
Method: We used pharmacy dispensing data of 1461 eligible T2DM patients from public primary care clinics in Malaysia treated with oral antidiabetic drugs between January 2018 and May 2019. Adherence rates were calculated during the period preceding the HbA1c measurement. Adherence cut-off values for the following conditions were compared: adherence measure (MPR versus PDC), assessment period (90-day versus 180-day), and HbA1c target (⩽7.0% versus ⩽8.0%).
Results: The optimal adherence cut-offs for MPR and PDC in predicting HbA1c ⩽7.0% ranged between 86.1% and 98.3% across the two assessment periods. In predicting HbA1c ⩽8.0%, the optimal adherence cut-offs ranged from 86.1% to 92.8%. The cut-off value was notably higher with PDC as the adherence measure, shorter assessment period, and a stricter HbA1c target (⩽7.0%) as outcome.
Conclusion: We found that optimal adherence cut-off appeared to be slightly higher than the conventional value of 80%. The adherence thresholds may vary depending on the length of assessment period and outcome definition but a reasonably wise cut-off to distinguish good versus poor medication adherence to be clinically meaningful should be at 90%.