Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic.

A positive correlation has been demonstrated between gross domestic product (GDP) per capita and COVID-19 tests per 1000 people. Although frequently used as an indicator of economic performance, GDP per capita does not directly reflect income distribution inequalities and imposed health costs. In this longitudinal ecological study, we aimed to determine if, besides GDP per capita, indicators relating to governance, public health measures enforcement, and health and research investment explain differences in RT-PCR testing rates among countries in Southeast Asia (SEA) during the first six months of the COVID-19 pandemic. Using open-access COVID-19 panel data, we estimated the effect of various indicators (GDP per capita, health expenditure per capita, number of researchers per one million population, corruption perceptions index, stringency index, regional authority index) on daily COVID-19 testing by performing fixed-effects negative binomial regression. After accounting for all indicators, the number of daily confirmed COVID-19 cases, and population density, the model provided a 2019 GDP per capita coefficient of 0.0046330 (95% CI: 0.0040171, 0.0052488; p <0.001), indicating that a rise in 2019 GDP per capita by 100 international dollars is associated with a 46.33% increase in the number of daily tests performed. Additionally, all indicators were significantly associated with the daily number of RT-PCR testing on multivariable analysis. In conclusion, we identified different country-level indicators significantly associated with differences in COVID-19 testing rates among SEA countries. Due to the study's ecological design, we caution on applying our results to the individual level given potential for systematic differences between the included countries. Additional investigation is likewise needed to understand how government expenditure on healthcare may have impacted COVID-19 testing capacity during the initial stages of the pandemic.

Examination performance with flipped classroom as instructional strategy in the carbohydrate metabolism course unit at a Philippine medical school: Estimation of average treatment effect from observational data.

While the innovativeness of the flipped classroom (FC) approach promotes active participation and higher-order thinking among students, there are concerns about its effectiveness in terms of knowledge retention. Currently, there are no studies involving medical school biochemistry that evaluate this aspect of effectiveness. Thus, we conducted a historical control study that analyzed observational data from two freshman batches of the Doctor of Medicine program in our institution. Class 2021 (n = 250) served as the traditional lecture (TL) group while Class 2022 (n = 264) served as the FC group. Data on relevant observed covariates (age, sex, National Medical Admission Test or NMAT score, undergraduate degree) and the outcome variable (carbohydrate metabolism course unit examination percentage scores, as indicator of knowledge retention) were included in the analysis. Propensity scores were calculated using logit regression conditional on these observed covariates. Afterwards, 1:1 nearest-neighbor propensity score matching (PSM) was performed to produce an estimated average treatment effect (ATE) measure afforded by FC (as adjusted mean difference in examination scores between the two batches), balancing on the covariates. Nearest-neighbor matching using the calculated propensity scores effectively balanced the two groups (standardized bias <10%), producing 250 matched student-pairs that received either TL or FC. Following PSM, the FC group was found to have a significantly higher adjusted mean examination score compared to the TL group (adjusted mean difference = 5.62%, 95% CI: 2.54%, 8.72%; p < 0.001). Using this approach, we were able to demonstrate benefit of FC over TL in terms of knowledge retention, as reflected by the estimated ATE.

Assessment of a proposed BMI formula in predicting body fat percentage among Filipino young adults.

Body mass index (BMI), while routinely used in evaluating adiposity, cannot distinguish between fat and lean mass, and thus can misclassify weight status particularly among athletic, physically active, and tall- and short-statured individuals, whose lean-to-fat ratios and body proportions vary considerably from average individuals. Believing that the traditional BMI formula divides weight by too much with short people and by too little with tall people, University of Oxford professor L. N. Trefethen proposed a modified formula in computing BMI. This study was conducted among a sample of Filipino young adults (n = 190) to assess the performance of the modified BMI formula against the traditional one in: (1) predicting body fat percentage (%BF) measured using bioelectric impedance analysis, and (2) diagnosing overweight/obesity. Using robust polynomial regression analysis (covariates: age, waist circumference, smoking history and alcohol intake), the BMI quadratic models had the highest adjusted R2 and the lowest AIC and BIC for both sexes compared to the linear models. The AuROCs of the traditional BMI were higher than those of the proposed BMI, albeit nonsignificant. In conclusion, both traditional and modified BMIs significantly predicted %BF, as well as adequately discriminated between %BF-defined normal and overweight-obese states using optimal BMI cutoff values.

Mitochondrial DNA variations are associated with recurrent pregnancy loss.

Cases with three or more consecutive spontaneous abortions before the 20th week of gestation are termed as recurrent pregnancy loss (RPL). Problems in implantation of the foetus and any retarded growth of the foetus in the uterus can be correlated to RPL. Possible causes of RPL would include the genetic variations in the regulatory enzymes of the crucial metabolic pathways, clotting factors, hormones and hormone receptors. This defect of the mitochondrial respiratory chain is recognized as a major cause of human disease. We investigated 73 women with RPL and 100 healthy normal controls. By using the direct sequencing method, the amplified products including the mtDNA complex I genes were analyzed. Overall, seven variations in mitochondrial complex I genes were found (T4216C, A5153G, C10142T, C12062T, A12662G, G14179A and T14263C) using direct sequencing technique. The RPL group had significantly higher proportions of the different variants than those observed of the control group. In conclusion, more research is essentially needed to understand the effect and role of the mitochondrial variations in the progress of RPL, which may vary among individuals and different ethnic groups.