Muhammad Habiburrahman

Objective: To describe clinical outcomes and inflammatory profiles in patients with culture-positive sepsis identified using Sepsis-3 criteria and to explore their association with bacterial Gram stain status. Methods: A retrospective cohort study was conducted in adult patients with sepsis hospitalized at a single-center hospital in East Java, Indonesia, in 2023. Patients were identified using Sepsis-3 criteria and included if blood cultures were obtained at admission. Data collected included blood culture results, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, comorbidities, length of hospital stay, and in-hospital mortality. Patients were grouped according to bacterial Gram stain status. Group differences were analyzed using the chi-square test for categorical variables and the Mann–Whitney U test for continuous variables. Multivariate logistic regression was performed to identify factors associated with mortality. Results: Among 172 patients clinically diagnosed with sepsis, blood culture was positive in 46 cases (26.7%), indicating that most patients (73.3%) had culture-negative sepsis. Among culture-positive cases, gram-positive organisms predominated (n = 37), whereas gram-negative pathogens were less frequently isolated (n = 9). Increased inflammatory burden, reflected by a higher admission neutrophil-to-lymphocyte ratio, was associated with worse clinical outcomes. In multivariate analysis, gram-negative infection (adjusted odds ratio = 4.00, 95% confidence interval: 1.05–15.30), higher neutrophil-to-lymphocyte ratio (adjusted odds ratio = 1.06 per unit; 95% confidence interval: 1.01–1.11), and acute kidney injury (adjusted odds ratio = 5.30, 95% confidence interval: 1.73–16.50) were independently associated with in-hospital mortality. Conclusion: Culture-negative sepsis was common, likely influenced by early antibiotic use. Gram-positive pathogens predominated among culture-positive cases, whereas gram-negative infections were associated with worse clinical outcomes. Elevated neutrophil-to-lymphocyte ratio and acute kidney injury independently predicted in-hospital mortality. These findings support the need for multimodal sepsis assessment integrating clinical judgment and laboratory markers rather than relying solely on culture results.

Background: Although health indicators have improved across ASEAN, RHD burden remains uneven and its decline relative to socioeconomic development is unclear. This study aimed to assess temporal trends, burden typologies, and development-adjusted inequities in RHD across ASEAN countries from 2000 to 2023. Methods: Data from the Global Burden of Disease (GBD) 2023 study including age-standardised rates of RHD-attributable disability-adjusted life years (DALYs), deaths, and prevalence were used for 11 ASEAN countries from 2000 to 2023. Average annual percentage change (AAPC), derived from generalised additive model (GAM) predictions, was used as the primary trend metric to summarise nonlinear trajectories. Estimated annual percentage change (EAPC) was additionally reported as a uniform log-linear measure for cross-country clustering. Socio-demographic Index (SDI) frontier analysis was performed using a GAM with a country-level random-effect term to evaluate development-adjusted performance. Results: Across ASEAN, the age-standardised RHD DALY rate declined by 41.0%, from 185.20 [95% uncertainty interval (UI): 126.22–260.25] in 2000 to 109.27 (95% UI: 72.17–159.80) per 100,000 in 2023. Age-standardised death rates fell by 46.6%, from 3.42 to 1.83 per 100,000, while prevalence declined only marginally by 2.1%, indicating persistent prevalent burden despite reductions in mortality and DALYs. GAM-derived AAPCs ranged from −1.80% in Timor-Leste to −4.63% in Cambodia, while EAPCs ranged from −0.95% to −4.67%. Joint EAPC–DALY clustering identified Cambodia and Singapore as less concerning, Brunei Darussalam, Indonesia, Malaysia, the Philippines, Thailand, and Viet Nam as moderately concerning, and Lao People's Democratic Republic (PDR), Myanmar, and Timor-Leste as highly concerning. In the SDI-adjusted analysis, the largest higher-than-expected DALY burdens were observed in Myanmar (+80.6 DALYs per 100,000) and Lao PDR (+76.2), whereas Thailand showed the largest lower-than-expected burden (−77.1). In 2023, the highest DALY rates were observed in Lao PDR (298.12 per 100,000), Timor-Leste (281.03), and Myanmar (238.76). Conclusion: All ASEAN countries made substantial progress in reducing RHD burden, with most showing nonlinear declining trajectories. However, progress remained uneven and major disparities persisted. Countries classified as highly concerning require prioritised investment in primary prevention, early detection, secondary prophylaxis, and long-term RHD care.

Objectives: The low uptake of cervical cancer screening (CCS) in rural areas is mainly related to the lack of awareness regarding cervical cancer. Using educational interventions has been shown to substantially improve knowledge and attitude towards cervical cancer, which are important determinants of undergoing CCS. The aim of this study was to analyse the impact of different educational intervention methods on knowledge, attitudes and willingness to undergo CCS among women in rural Indonesia. Design: A quasi-experimental study with a non-equivalent control group design. Setting: The study was conducted in North Tobelo, a rural district in North Halmahera Regency. Participants: Sample size was calculated using Power and Sample Size Calculations software (V.3.1.2). 150 women were recruited via convenience sampling from 12 Integrated Health Service Posts, cluster-randomised into three arms: control (n=50), flipchart (n=50) and video (n=50). A per-protocol approach was applied; all participants completed pre-intervention and post-intervention assessments within a single visit with no loss to follow-up. Continuous outcomes were analysed using the Kruskal-Wallis and Wilcoxon tests; categorical outcomes using χ² or Fisher’s exact tests with Bonferroni correction. Non-parametric analysis of covariance (Quade’s method) controlled for baseline scores, age at first sexual intercourse and household income, with partial eta-squared reported as the effect size. Interventions: All study arms received identical educational content presented in simple Indonesian language and avoiding the use of medical terminology. The educational content included cervical cancer epidemiology, aetiology, risk factors, clinical symptoms, prevention methods, various CCS methods, visual inspection with acetic acid screening procedures, benefits and side effects of getting human papillomavirus vaccination and CCS, as well as a brief explanation regarding cervical cancer treatment. Knowledge, attitude and willingness were assessed using a structured pre-intervention and post-intervention questionnaire comprising both dichotomous items and Likert-scale questions. Results: Although knowledge improved significantly in all intervention groups (p<0.001), only the video group showed a significant improvement in attitude after the intervention (p=0.016). The median change scores of knowledge and attitude were only significantly higher in the video group when compared with the control group (p=0.041 and p=0.013, respectively), but not significantly different in other pairwise comparisons. Moreover, the proportion of participants who were willing to undergo CCS after the intervention was also increased significantly in the video group when compared with the control group (52% vs 22%; p=0.006) and flipchart group (52% vs 24%; p=0.012). Conclusions: In conclusion, the video-based educational intervention demonstrated the greatest improvements in knowledge, attitude, and willngness to undergo CCS compared to other methods.

Introduction: α-Glucosidase inhibitors (AGIs) are essential for controlling postprandial hyperglycemia, with flavonoids representing a major class of natural AGIs. However, conventional quantitative structure–activity relationship (QSAR) models trained on structurally diverse datasets often exhibit limited predictive reliability for natural flavonoids due to chemical space mismatch. This study aimed to develop and optimize Random Forest–based QSAR models derived from ChEMBL AGIs and to evaluate their chemotype-specific applicability to natural flavonoids.Methods: ChEMBL-derived inhibitors were curated into two datasets: (i) a general scaffold-diverse dataset and (ii) a flavonoid-specific dataset. A custom RDKit-based pipeline employing SMARTS pattern recognition and fingerprint similarity automatically classified flavonoid chemotypes while excluding nonphenolic compounds. Molecular descriptors were calculated using Mordred. Regression and classification models were constructed with 10-fold cross-validation. External validation was performed using 15 literature-reported natural flavonoids categorized into flavones/flavonols (aglycones), flavonol glycosides, isoflavones, and flavan-3-ols.Results: The general model (n = 563) demonstrated strong regression performance (R2 = 0.837) and classification accuracy (0.915). The flavonoid-specific model showed moderate regression (R2 = 0.564) and classification accuracy (0.880). However, external validation revealed superior predictive reliability of the flavonoid-specific model, particularly for catechins (MAE = 0.182) and aglycones (MAE = 0.233). Predictive performance decreased for glycosides and isoflavones.Conclusion: Chemotype-focused QSAR modeling enhances predictive reliability for natural flavonoids. The optimized flavonoid-specific model is suitable for predicting pIC50 of flavones and flavonols but should be applied cautiously to glycosylated or structurally divergent subclasses.

Individuals with hypertension are at risk to reduced quality of life (QoL). Explainable machine learning (ML) can be used for domain-specific risk stratification and prioritization of modifiable determinants of low QoL. To train ML classifier algorithms for QoL risk stratification in hypertension, where meaningful determinants were explored through Shapley additive explanations (SHAP). Data from hypertensive individuals (n = 534) completed WHOQOL BREF, Quick Physical Activity Rating, Morisky Medication Adherence Scale 8, and standardized questionnaires for acceptance and knowledge were analyzed utilizing Decision Tree, Gradient Boosting, XGBoost, AdaBoost, Random Forest, and Naive Bayes ML classifiers. The trained ML algorithms were evaluated using stratified 10-fold cross-validation, where the stability was examined using rank-based metrics. SHAP were applied to the gradient boosting, as the most stable model. For physical QoL, Random Forest (AUC 0.850; sensitivity 0.835; specificity 0.738) and Gradient Boosting (AUC 0.850; sensitivity 0.801; specificity 0.764) showed good reduced QoL identification. For psychological domain, best classifications were obtained from Gradient Boosting performed best (AUC 0.833; sensitivity 0.818; specificity 0.651) and XGBoost (AUC 0.831; sensitivity 0.824; specificity 0.660), with the former observed as the most stable SHAP analysis identified acceptance and medication adherence as the dominant shared drivers of risk across both QoL domains. Physical QoL risk was further influenced by physical activity-related factors, whereas Psychological QoL risk showed additional contributions from age and educational attainment. Ensemble tree-based classifiers, particularly Gradient Boosting, had the most optimal performance in discriminating reduced and good QoL. Acceptance and medication adherence are the most influential shared drivers of risk, while physical activity, age, and educational attainment contributed to domain-specific heterogeneity.

Introduction: Timely identification of sepsis patients at elevated risk for in-hospital mortality or prolonged hospitalization remains a clinical imperative. This study aimed to assess the prognostic utility of two readily available hematological biomarkers, namely the neutrophil-to-lymphocyte count ratio (NLCR) and platelet-to-lymphocyte count ratio (PLCR), for their association with mortality and length of stay (LOS) among sepsis patients, including high-risk subgroups with acute kidney injury (AKI) or type 2 diabetes mellitus (T2DM). Methodology: This retrospective 1-year cohort study included 202 adult sepsis patients. NLCR and PLCR were derived from admission complete blood counts. Receiver operating characteristic (ROC) curve analysis was used to evaluate discriminative performance, with optimal thresholds determined using Youden’s index. Kaplan–Meier and log-rank tests assessed survival differences, while LOS comparisons were analyzed using Mann–Whitney and Chi-square tests. Results: NLCR demonstrated limited overall prognostic value for mortality (AUC 0.560; sensitivity 53.68%; specificity 63.55%) but showed improved discrimination in patients with T2DM (AUC 0.603). PLCR was not associated with mortality in any subgroup (AUCs: 0.438–0.539). Diabetic patients with low NLCR had significantly higher survival (62.4% vs. 32.8%; p = 0.039). No significant survival differences were observed in the overall or AKI cohorts. Both NLCR and PLCR had poor association with LOS (AUC < 0.55). However, AKI patients with elevated NLCR had significantly prolonged hospitalization (11.5 ± 4.9 vs. 7.83 ± 4.5 days; p = 0.039). PLCR was not significantly associated with LOS. Conclusions: NLCR may provide modest, preliminary prognostic value in specific sepsis subgroups, particularly those with T2DM or AKI, and may serve as a low-cost adjunct for early risk stratification.

Background: Congenital heart anomalies (CHAs) are a leading cause of premature childhood mortality and contribute substantially to years of life lost (YLL). Despite overall improvements in child survival in Southeast Asia, progress in reducing CHA-attributed mortality has been uneven. Examining how trends in CHA-related YLL align with socioeconomic development is critical for informing targeted health system investments. This study assesses trends and projections of CHA-attributed premature mortality in ASEAN countries from 2000 to 2030 in relation to development levels. Methods: Data from the Global Burden of Disease Study 2021 were used to extract CHA-attributed YLL rates, including all-age and age-stratified estimates ( 600 per 100,000). The estimated trends in Singapore and Brunei Darussalam exceeded those expected under the SDI-adjusted projections, with projected YLLs of 17.35 and 131.67 per 100,000 population, respectively. Conclusion: CHA-attributed premature mortality is largely preventable but not assured by development alone. Greater YLL reductions occur when investment in pediatric cardiac care keep pace with socioeconomic progress, highlighting the need for targeted interventions in countries with rising SDI but limited mortality reduction.

Vulvar cancer (VC) is a rare malignancy with limited data in Southeast Asia. This 6-year retrospective cohort study aims to characterize temporal trends in VC cases in Indonesia, describe patients’ sociodemographic, obstetric, and clinicopathological features, and identify predictors of advanced stage and distant metastasis (DM). We analyzed 86 VC cases diagnosed between 2015 and 2020 at a tertiary hospital in Indonesia. Patients’ sociodemographic and obstetric characteristics were described, and clinicopathological and treatment-related features were compared by stage and DM status. Temporal trends were assessed using Joinpoint regression, expressed as annual percentage change (APC). Subgroup analyses were conducted by age (<60 vs ≥60 years), residential status (rural vs urban), and DM presence (negative vs positive). Univariate and multivariate logistic regression identified predictors of advanced-stage VC and DM, with model performance evaluated using the area under the receiver operating characteristic curve (AUC). The number of VC cases increased significantly over six years (APC +21.43%, p=0.034), with the highest growth observed among older patients, rural residents, and cases without DM (+25.53% vs +19.61%; +22.25% vs +19.08%; +30.50% vs +9.95%, respectively). Multivariate analysis identified urban residence (OR 5.12), right-sided lesion (OR 7.93), bilateral lesions (OR 10.25), and tumor volume ≥70 cm³ (OR 10.88) as independent predictors of advanced-stage VC (AUC 0.81, p<0.001). Predictors of DM included normal/underweight nutritional status (OR 5.50), presence of pain (OR 4.88), right-sided lesion (OR 13.80), and non-keratinized tumor subtype (OR 5.72) (AUC 0.80, p<0.001). The experience from an Indonesian referral hospital shows that the number of VC cases treated is rising, particularly among older adults, rural populations, and patients without DM. Specific clinicopathological features, including tumor laterality, bilaterality, volume, nutritional status, pain, and histological subtype, predict adverse outcomes, providing a foundation for improved risk stratification, early detection, and targeted management in underrepresented populations.