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All Journal Natural Sciences Engineering and Technology Journal Indonesian Community Empowerment Journal Sriwijaya Journal of Forensic and Medicolegal Sriwijaya Journal of Internal Medicine Sriwijaya Journal of Obstetrics and Gynecology Sriwijaya Journal of Otorhinolaryngology
Muhammad Yoshandi
Department of Health Sciences, Tembilahan Community Health Center, Tembilahan, Indonesia
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Efficacy of a Specialist Tele-Mentoring Triage System on Severe Maternal Morbidity and Mortality in High-Risk Pregnancies: A Stepped-Wedge Cluster Randomized Trial Muhammad Yoshandi; Rheina Weisch Fedre; Desiree Montesinos
Sriwijaya Journal of Obstetrics and Gynecology Vol. 3 No. 2 (2025): Sriwijaya Journal of Obstetrics & Gynecology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjog.v3i2.280

Abstract

Introduction: Maternal deaths in low- and middle-income settings are driven largely by delays in recognising and treating obstetric emergencies at the primary-care frontline. Real-time specialist tele-mentoring may compress these delays, yet trial evidence on hard maternal and neonatal endpoints remains scarce in Indonesia. We evaluated whether a specialist tele-mentoring triage system reduces severe maternal morbidity and mortality in high-risk pregnancies. Methods: In a closed-cohort stepped-wedge cluster randomized trial, ten primary-to-referral facility clusters across two Indonesian metropolitan regions sequentially crossed from conventional referral to a 24/7 tele-mentoring triage system (audiovisual specialist consultation, portable cardiotocography/vital-sign telemetry, and a Maternal Early Warning Score [MEWS] algorithm) over six two-month periods. The primary outcome was a composite of maternal death and WHO-defined severe maternal morbidity. Intention-to-treat analysis used generalized linear mixed models adjusting for secular trend and cluster random effect. Results: Among 1,858 high-risk women, the composite outcome fell from 7.97% (95% CI 6.39–9.88) during control person-time to 4.41% (95% CI 3.27–5.93) during tele-mentoring (adjusted OR 0.51, 95% CI 0.36–0.73, p<0.001; absolute risk reduction 3.55%; number-needed-to-treat 28). Door-to-treatment time shortened by 85.6 minutes (Cohen's d 1.77, p<0.001). MEWS discriminated the composite outcome well (AUC 0.84, 95% CI 0.80–0.88). NICU admission (OR 0.66, NNT 19, p=0.003) and 5-minute Apgar <7 (OR 0.58, p=0.002) also improved. Conclusion: A specialist tele-mentoring triage system roughly halved the odds of severe maternal morbidity and mortality in high-risk pregnancies and improved neonatal outcomes. Scaling specialist-guided digital triage could meaningfully strengthen obstetric emergency referral in Indonesia.
Enhancing 'First 1,000 Days' Nutrition Literacy via a Posyandu Kader 'Train-the-Trainer' Model: A Mixed-Methods Impact Evaluation on Child Nutritional Status in Eastern Indonesia Fatimah Mursyid; Novalika Kurnia; Sana Ullah; Lestini Wulansari; Muhammad Yoshandi
Indonesian Community Empowerment Journal Vol. 5 No. 1 (2025): Indonesian Community Empowerment Journal
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/icejournal.v5i1.53

Abstract

The 'First 1,000 Days' (HPK) period is critical for preventing stunting, a significant public health challenge in Indonesia, particularly in Eastern provinces. Posyandu kader (community health volunteers) are pivotal, but their effectiveness is often hampered by inadequate and unstandardized training. This study evaluates the impact of a structured 'Train-the-Trainer' (ToT) model on kader nutrition literacy and, subsequently, on child nutritional status. We conducted a quasi-experimental, convergent parallel mixed-methods study in two districts of East Nusa Tenggara (NTT) province, Indonesia. The intervention district (n=50 kader, n=312 mother-child dyads) received the ToT intervention, while the control district (n=50 kader, n=309 mother-child dyads) continued standard practices. The ToT model involved training Puskesmas (health center) staff as 'Master Trainers' who then cascaded structured training and mentorship to kader over 12 months. Quantitative data (kader literacy scores, child anthropometry [Height-for-Age Z-score, HAZ]) were collected at baseline and 12-month follow-up, analyzed using Difference-in-Differences (DiD) and linear mixed-effects models (LMM). Qualitative data (n=24 in-depth interviews, n=6 focus group discussions) explored the intervention's mechanisms, fidelity, and contextual facilitators. At 12 months, kader nutrition literacy in the intervention group increased significantly (mean score change: +29.8 points) compared to the control group (+2.1 points, p < 0.001). The LMM analysis, controlling for covariates, showed a significant 'time × group' interaction effect on child HAZ (β = 0.28, 95% CI [0.15, 0.41], p < 0.001), indicating a meaningful improvement in child growth attributable to the intervention. Stunting prevalence (HAZ < -2 SD) in the intervention group decreased by 8.7 percentage points, while it remained stagnant in the control group. Qualitative themes revealed that the ToT model enhanced kader self-efficacy, shifted their role from passive data collectors to active counselors, and provided mechanisms to address local socio-cultural barriers to nutrition. In conclusion, the 'Train-the-Trainer' model is an effective and scalable strategy for enhancing kader nutrition literacy and precipitating measurable improvements in child nutritional status in high-burden settings. This model provides a sustainable framework for strengthening community health systems to combat stunting, aligning with Indonesia's national strategy and Sustainable Development Goal 3.
Cross-Cohort Transcriptomic Analysis Identifies an ECM–CAF Stromal Program but Does Not Validate a Seven-Gene Prognostic Score in Head and Neck Squamous Cell Carcinoma Reisha Notonegoro; Bjorka Alma; Patricia Wulandari; Muhammad Yoshandi
Sriwijaya Journal of Otorhinolaryngology Vol. 3 No. 2 (2025): Sriwijaya Journal of Otorhinolaryngology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjorl.v3i2.307

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) is biologically heterogeneous, and many public-data gene signatures lack cross-platform replication and unbiased evaluation. Objective: We sought reproducible tumor–normal expression programs and tested the transportability of a derived seven-gene score. Methods: TCGA-HNSC RNA-sequencing defined differentially expressed genes (DEGs) between 520 tumors and 44 normal tissues using TMM normalization and voom–limma, with paired sensitivity analysis. Concordant genes were replicated in 22 GSE6631 matched pairs and analyzed for GO and KEGG enrichment. A seven-gene overall-survival score was developed in event-stratified TCGA training data (n=361), evaluated in held-out TCGA (n=156), repeated nested resampling, and examined in GSE65858 (n=253). ESTIMATE and marker scores characterized tumor-microenvironment features. Results: Among 5,657 TCGA and 168 GSE6631 DEGs, 151 replicated. Upregulated genes were enriched for extracellular-matrix organization, ECM–receptor interaction, integrin signaling, focal adhesion, and PI3K–Akt signaling. The score was associated with survival in training (HR per SD=1.68; C-index=0.642) but not held-out TCGA (HR=1.02; C-index=0.546) or unadjusted GSE65858 (HR=1.15; C-index=0.548). Median nested C-index was 0.564. HPV adjustment attenuated the GSE65858 association. The score correlated with CAF/fibroblast (ρ=0.269) and stromal scores (ρ=0.228). Conclusion: Replicated expression changes support an ECM–CAF program, but the seven-gene score did not generalize and is not a validated prognostic model.
Glycated Hemoglobin (HbA1c) as a Predictor of Periodontal Disease Progression in Patients with Type 2 Diabetes: A Longitudinal Study in Surabaya, Indonesia Alexander Mulya; Muhammad Ashraf; Muhammad Yoshandi; Ayesh Mahmood; Daphne Marshall
Sriwijaya Journal of Internal Medicine Vol. 3 No. 1 (2025): Sriwijaya Journal of Internal Medicine
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjim.v2i2.178

Abstract

Introduction: Periodontal disease is a prevalent complication of type 2 diabetes mellitus (T2DM), and poor glycemic control is a known risk factor. This longitudinal study aimed to investigate the predictive value of glycated hemoglobin (HbA1c) for periodontal disease progression in a cohort of T2DM patients in Surabaya, Indonesia. Methods: A prospective cohort study was conducted at private hospital, Surabaya, Indonesia, from January 2021 to January 2023. 180 patients with T2DM and pre-existing chronic periodontitis were enrolled. Periodontal parameters, including probing pocket depth (PPD), clinical attachment loss (CAL), bleeding on probing (BOP), and plaque index (PI), were assessed at baseline, 12 months, and 24 months. HbA1c was measured at each visit. Multivariate linear regression and mixed-effects models were used to analyze the association between HbA1c and changes in periodontal parameters over time, adjusting for potential confounders. Results: The mean age of participants was 58.5 ± 8.2 years, and 55% were female. Baseline mean HbA1c was 8.2 ± 1.5%. After adjusting for age, gender, smoking status, diabetes duration, and baseline periodontal parameters, higher baseline HbA1c was significantly associated with greater increases in PPD (β = 0.15 mm per 1% HbA1c increase, 95% CI: 0.08-0.22, p < 0.001) and CAL (β = 0.18 mm per 1% HbA1c increase, 95% CI: 0.10-0.26, p < 0.001) over 24 months. Furthermore, sustained elevation of HbA1c (average HbA1c over 24 months) was a stronger predictor of periodontal disease progression than baseline HbA1c alone. A significant interaction between HbA1c and time was observed (p < 0.001), indicating that the effect of HbA1c on periodontal parameters increased over time. Conclusion: HbA1c is a significant independent predictor of periodontal disease progression in patients with T2DM. Sustained glycemic control is crucial for preventing and managing periodontal complications in this population. These findings highlight the importance of interdisciplinary collaboration between internists and dentists in the comprehensive care of T2DM patients.
An In-Silico Investigation of Machine Learning for Integrating Genomic and Digital Biomarker Data in Cardiovascular Risk Stratification Immanuel Simbolon; Cindy Susanti; Gayatri Putri; Karina Chandra; Muhammad Yoshandi; Daniel Hilman Maulana
Natural Sciences Engineering and Technology Journal Vol. 5 No. 2 (2025): Natural Sciences Engineering and Technology Journal
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/nasetjournal.v5i2.71

Abstract

Conventional models for stratifying cardiovascular disease (CVD) risk have limitations. The integration of static genomic data and dynamic digital biomarkers from wearable technology holds theoretical promise, but its potential quantitative impact remains poorly defined. This study aimed to develop and validate an in-silico framework to quantify the theoretical maximum predictive gain of an integrated risk model under idealized conditions. We developed a sophisticated data generating process (DGP) to create a synthetic dataset of 5,000 individuals. The DGP incorporated demographic and clinical variables with distributions and correlations based on epidemiological literature. It included a simulated polygenic risk score (PRS) for coronary artery disease and advanced digital biomarkers derived from wireless health monitoring data, such as heart rate variability (HRV) and time in moderate-to-vigorous physical activity (MVPA). The 10-year risk of Major Adverse Cardiovascular Events (MACE) was generated via a defined logistic function incorporating these variables plus stochastic noise. We compared the performance of the ACC/AHA Pooled Cohort Equations (PCE) against several machine learning models (Logistic Regression, Random Forest, XGBoost) using the area under the receiver operating characteristic curve (AUC-ROC), precision, recall, and F1-score. In this simulated environment, the integrated XGBoost model achieved near-optimal predictive performance with an AUC-ROC of 0.92 (95% CI, 0.90-0.94), significantly outperforming the benchmark PCE model (AUC-ROC 0.76; 95% CI, 0.73-0.79; p < 0.001). The inclusion of the PRS and, most notably, dynamic digital biomarkers like HRV, provided substantial incremental improvements in risk discrimination over traditional factors alone. In conclusion, this in-silico study demonstrates the substantial theoretical potential of integrating genomic and advanced digital biomarker data through machine learning for CVD risk stratification. While these idealized results are not directly generalizable, they provide a quantitative rationale for pursuing real-world data collection and validation studies. This work establishes a methodological proof-of-concept and highlights the potential for a paradigm shift toward more dynamic and personalized cardiovascular risk assessment.
Age and Sex Associations With Body Mass Index in an Audited Postmortem CT Metadata Cohort Rachmat Hidayat; Muhammad Yoshandi
Sriwijaya Journal of Forensic and Medicolegal Vol. 3 No. 2 (2025): Sriwijaya Journal of Forensic and Medicolegal
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjfm.v3i2.326

Abstract

Introduction: Open postmortem computed tomography (PMCT) repositories support forensic research, but record duplication and incomplete metadata can distort anthropometric inference. This study examined age- and sex-related variation in body mass index (BMI) after curator-informed audit of VSDFullBody. Methods: We performed a retrospective secondary analysis of 105 metadata rows. A calibration phantom was excluded; seven concordant duplicate pairs were collapsed; both records from four duplicate pairs with conflicting metadata were excluded; curator data reconciled six sex labels and recovered 13 BMI values. The primary cohort comprised 89 decedents, including 83 complete cases. BMI was regressed on age per 10 years and audited biological sex using HC3 standard errors; bootstrap, duplicate-choice, robust-regression, leave-one-out, head-coverage, and missing-outcome sensitivity analyses assessed stability. Results: Mean BMI was 24.2 kg/m2. Each 10-year age increment was associated with 0.49 kg/m2 higher BMI (95% confidence interval [CI], 0.05-0.93; p=0.029). Adjusted BMI was 2.58 kg/m2 higher in male than female decedents (95% CI, 0.18-4.99; p=0.036); the bootstrap 95% CI was 0.34-4.88. Sensitivity estimates retained the same direction. Conclusion: In this audited PMCT metadata cohort, age and male sex were associated with modestly higher BMI. Curator companion files materially increased analyzable completeness, supporting explicit metadata audit before reuse of open forensic imaging collections.
Co-Authors Alexander Mulya Ayesh Mahmood Bjorka Alma Cindy Susanti Daniel Hilman Maulana Daphne Marshall Desiree Montesinos Fatimah Mursyid Gayatri Putri Immanuel Simbolon Karina Chandra Lestini Wulansari Muhammad Ashraf Novalika Kurnia Patricia Wulandari RACHMAT HIDAYAT Reisha Notonegoro Rheina Weisch Fedre Sana Ullah