METHODS: This study involved developing a questionnaire and was conducted in Kuala Lumpur, Malaysia from July 2021 until June 2022. The questionnaire was developed based on a literature review and expert consultation. The first phase includes a systematic literature review to generate the items for the questionnaire. A group of five panels was then invited to perform content validity for the questionnaire. Face validity was conducted among ten parents to get feedback for the questionnaire. Construct validity and reliability of the questionnaire were measured by which the questionnaire was administered to a total of 134 parents and 64 parents for reliability test.
RESULT: The final PEPC-KAPQ consists of four main sections: demographic, knowledge, attitude, and practice with 52 items. The content validity index was 0.85 for all domains of KAP. Modified kappa showed excellent value for most items for all domains. The Kaiser-Meyer-Olkin sampling adequacy showed acceptable scores of 0.84, and Bartlett's Test of Sphericity was significant (x2 = 3172.09, p<0.0001). Kuder-Richardson-2 of the domain knowledge was 0.95. Cronbach's α coefficient of domain attitude and practice were 0.92 and 0.88, respectively and the intraclass correlation of domain attitude and practice were 0.93 and 0.94 respectively. Bland and Altman's plots show that majority of the data fell within the limits of agreement.
CONCLUSION: The findings of this validation and reliability study show that the developed questionnaire has a satisfactory psychometric property for measuring the KAP of parents regarding eye problems among children.
METHODS: Pkdhps were amplified and sequenced from 28 P. knowlesi samples collected in 2008 and 2020 from nine provinces across Thailand. Combining pkdhfr sequencing data from previous work with pkdhps data to analyze polymorphisms of pkdhfr and pkdhps haplotype. Protein modeling and molecular docking were constructed using two inhibitors, sulfadoxine and sulfamethoxazole, and further details were obtained through analyses of protein-ligand interactions by using the Genetic Optimisation for Ligand Docking program. A phylogenetic tree cluster analysis was reconstructed to compare the P. knowlesi Malaysia isolates.
RESULTS: Five nonsynonymous mutations in the pkdhps were detected outside the equivalence of the binding pocket sites to sulfadoxine and sulfamethoxazole, which are at N391S, E421G, I425R, A449S, and N517S. Based on the modeling and molecular docking analyses, the N391S and N517S mutations located close to the enzyme-binding pocket demonstrated a different docking score and protein-ligand interaction in loop 2 of the enzyme. These findings indicated that it was less likely to induce drug resistance. Of the four haplotypes of pkdhfr-pkdhps, the most common one is the R34L pkdhfr mutation and the pkdhps quadruple mutation (GRSS) at E421G, I425R, A449S, and N517S, which were observed in P. knowlesi in southern Thailand (53.57%). Based on the results of neighbor-joining analysis for pkdhfr and pkdhps, the samples isolated from eastern Thailand displayed a close relationship with Cambodia isolates, while southern Thailand isolates showed a long branch separated from the Malaysian isolates.
CONCLUSIONS: A new PCR protocol amplification and evaluation of dihydropteroate synthase mutations in Knowlesi (pkdhps) has been developed. The most prevalent pkdhfr-pkdhps haplotypes (53.57%) in southern Thailand are R34L pkdhfr mutation and pkdhps quadruple mutation. Further investigation requires additional phenotypic data from clinical isolates, transgenic lines expressing mutant alleles, or recombinant proteins.
METHODS: This study followed the PRISMA 2020 Checklist. Relevant studies were searched in health-related databases. The Newcastle-Ottawa Scale criteria were used to evaluate the studies quality. Pooled odds ratio (OR) and its 95% confidence interval (CI) were used to determine the strength of association between each polymorphism and hepatocellular carcinoma using five genetic models. Stratification was done by ethnic groups. Trial sequential analysis (TSA) was performed to determine the required information size.
RESULTS: Fifteen case-control studies (n = 8182) were identified. Overall, the heterozygous model showed a marginal significant association only between IL-10 (-1082 A/G) and hepatocellular carcinoma risk (OR: 0.82, 95% CI: 0.67-1.00, 9 studies). On stratification, IL-10 (-1082 A/G) was significantly associated with hepatocellular carcinoma risk in the non-Asian population under dominant (OR: 0.62, 95% CI: 0.45-0.86, 4 studies), heterozygous (OR: 0.60, 95% CI: 0.43-0.85) and allelic models (OR: 0.79, 95% CI: 0.64-0.99). IL-10 (-819 T/C) was significantly associated with hepatocellular carcinoma risk only among non-Asians under the dominant (OR: 1.47, 95% CI: 1.02-2.13, 8 studies), recessive (OR: 1.99, 95% CI: 1.03-3.86, and homozygous models (OR: 2.18, 95% CI: 1.13-4.23). For IL-10 (-592 A/C) with 11 studies, there was no significant association with hepatocellular carcinoma in all five genetic models (P values > 0.5). TSA plots indicated that the information size for firm evidence of effect was sufficient only for the analysis of IL-10 (-592 A/C), but not for the - 1082 A/G or -819 T/C.
CONCLUSIONS: Findings suggest that IL-10 (-1082 A/G and - 819 T/C) polymorphisms are associated with hepatocellular carcinoma in ethnic-specific manner. However, this evidence is not conclusive because the sample size was insufficient. IL-10 (-592 A/C) polymorphism was not associated with hepatocellular carcinoma albeit with sufficient information size. Future well-designed large case-control studies on IL-10 (-1082 A/G and - 819 T/C) with different ethnicities are recommended.
METHODS: A parallel, open-label, 2-arm prospective, pilot randomised controlled trial was conducted at a long-term stroke service at a university based primary care clinic. All stroke caregivers aged ≥ 18 years, proficient in English or Malay and smartphone operation were invited. From 147 eligible caregivers, 76 participants were randomised to either SRA™ intervention or conventional care group (CCG) after receiving standard health counselling. The intervention group had additional SRA™ installed on their smartphones, which enabled self-monitoring of modifiable and non-modifiable stroke risk factors. The Stroke Riskometer app (SRATM) and Life's Simple 7 (LS7) questionnaires assessed stroke risk and lifestyle practices. Changes in clinical profile, lifestyle practices and calculated stroke risk were analysed at baseline and 3 months. The trial was registered in the Australia-New Zealand Clinical Trial Registry, ACTRN12618002050235.
RESULTS: The demographic and clinical characteristics of the intervention and control group study participants were comparable. Better improvement in LS7 scores were noted in the SRA™ arm compared to CCG at 3 months: Median difference (95% CI) = 0.88 (1.68-0.08), p = 0.03. However, both groups did not show significant changes in median stroke risk and relative risk scores at 5-, 10-years (Stroke risk 5-years: Median difference (95% CI) = 0.53 (0.15-1.21), p = 0.13, 10-years: Median difference (95% CI) = 0.81 (0.53-2.15), p = 0.23; Relative risk 5-years: Median difference (95% CI) = 0.84 (0.29-1.97), p = 0.14, Relative risk 10-years: Median difference (95% CI) = 0.58 (0.36-1.52), p = 0.23).
CONCLUSION: SRA™ is a useful tool for familial stroke caregivers to make lifestyle changes, although it did not reduce personal or relative stroke risk after 3 months usage.
TRIAL REGISTRATION: No: ACTRN12618002050235 (Registration Date: 21st December 2018).
METHODS: PubMed, IEEE Xplore, Google Scholar, and Scopus were searched for relevant studies. All studies that used ML/DL to detect or early-predict the onset of sepsis in the adult population using EHRs were considered. Data were extracted and analyzed from all studies that met the criteria and were also evaluated for their quality.
RESULTS: This systematic review examined 1942 articles, selecting 42 studies while adhering to strict criteria. The chosen studies were predominantly retrospective (n = 38) and spanned diverse geographic settings, with a focus on the United States. Different datasets, sepsis definitions, and prevalence rates were employed, necessitating data augmentation. Heterogeneous parameter utilization, diverse model distribution, and varying quality assessments were observed. Longitudinal data enabled early sepsis prediction, and quality criteria fulfillment varied, with inconsistent funding-article quality correlation.
CONCLUSIONS: This systematic review underscores the significance of ML/DL methods for sepsis detection and early prediction through EHR data.