Sriwijaya Journal of Forensic and Medicolegal

Clinical and Medicolegal Evidence Patterns in Granted and Rejected Medical Malpractice Claims in Indonesia: An Explainable Concept-Tagging Study

2026-10-09T07:13:32+00:00

Background. Medical malpractice judgments encode clinical standards, causation, professional evidence, and procedural constraints, but Indonesian decisions have rarely been analysed at the level of independent disputes.

Objective. To identify which judicially accepted or materially discussed clinical–medicolegal evidence patterns most clearly distinguished granted from rejected medical malpractice claims in a purposive corpus of Indonesian court decisions from 2006–2026.

Methods. This exploratory archival study purposively assembled 16 deduplicated medical malpractice disputes decided in Indonesia during 2006–2026. Eight prespecified, auditable concept tags captured judicially accepted or materially discussed clinical–medicolegal evidence. Granted and rejected claims were compared using risk differences, Haldane–Anscombe-corrected odds ratios (ORs), 95% confidence intervals (CIs), and two-sided Fisher exact tests; a sensitivity analysis excluded one low-confidence case.

Results. Six claims were granted and 10 rejected. Articulated breach linked to causation occurred in 6/6 versus 0/10 disputes (corrected OR 273.0, 95% CI 4.80–15515.67); adverse professional findings in 5/6 versus 0/10 (OR 77.0, 95% CI 2.67–2222.91); and organizational failure in 4/6 versus 0/10 (OR 37.8, 95% CI 1.49–956.48). Acceptance of a standard-of-care or medical-risk defence occurred in 0/6 versus 8/10 (OR 0.023, 95% CI 0.001–0.557). Severe harm was nearly universal (6/6 versus 9/10) and did not discriminate outcomes. Directions were unchanged after excluding the low-confidence case.

Conclusion. In this small purposive corpus, litigation outcomes aligned more closely with judicially accepted evidence connecting specific breach, causation, professional findings, and organizational responsibility than with injury severity alone. The findings are exploratory and support larger, independently coded studies rather than case prediction.

Human Blood Thanatotranscriptome Dynamics and Cross-Donor Generalisability of Postmortem Interval Prediction: A Longitudinal RNA-seq Reanalysis

2026-10-09T07:37:24+00:00

Background. Thanatotranscriptomic profiles may encode time-dependent molecular changes after death, but forensic utility requires temporal signals that generalise across individuals.

Objective. To characterise the genes and molecular pathways that change consistently with absolute postmortem interval (PMI) in serial human postmortem blood samples.

Methods. We reanalysed processed counts from 54 serial postmortem blood samples of seven individuals in GSE163207, spanning an absolute PMI of 2.35-37.83 h. After expression filtering and trimmed mean of M-values normalisation, limma-voom models included individual fixed effects and continuous absolute PMI. Eligible genes required a Benjamini-Hochberg false-discovery rate <0.05, an absolute log2 change >=0.10 per 10 h, and concordant direction in at least five individuals. Enrichment used the expressed-gene background. Nested leave-one-individual-out elastic-net validation kept feature selection and tuning within training donors.

Results. Among 12,633 expressed genes, 1,976 were eligible (954 increasing; 1,022 decreasing). Increasing genes were enriched for cytoskeletal, extracellular-matrix, oxidative-stress, and mitochondrial processes; decreasing genes were enriched for adaptive immune and antigen-presentation pathways. Sensitivity analysis produced an effect correlation of 0.987, with 1,645 genes retaining significance and direction. Cross-donor prediction yielded an RMSE of 10.03 h (95% CI 8.12-11.32), MAE of 8.63 h (95% CI 6.33-10.40), and R2 of -0.219, underperforming the training-mean baseline.

Conclusion. Human blood undergoes reproducible early postmortem molecular remodelling, but this seven-individual cohort does not support generalisable individual PMI prediction.

Disproportionate Reporting of Sudden Cardiac Death with Methadone in the FDA Adverse Event Reporting System (FAERS): A Case–Non-Case Study

2026-10-09T08:57:54+00:00

Background. Methadone can prolong cardiac repolarization, but outcome-specific reporting of sudden cardiac death has not, to our knowledge, been evaluated with contemporary data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS).

Objective. To quantify disproportionate reporting of sudden cardiac death with methadone in FAERS and to test its stability across exposure definitions, report clustering, and comparators.

Methods. We performed a report-level case–non-case disproportionality analysis of the openFDA Drug Adverse Event API. Methadone exposure was defined by a medicinal-product query and sudden cardiac death by its Medical Dictionary for Regulatory Activities (MedDRA) Preferred Term. Reporting odds ratios (RORs), proportional reporting ratios (PRRs), 95% confidence intervals (CIs), and Fisher exact tests were calculated. Four sensitivity analyses used harmonized and exact exposure definitions, an identical-signature clustering proxy, and exclusive buprenorphine reports as an active comparator.

Results. Among 20,692,690 searchable reports (52,462 mentioning methadone), 89 contained both methadone and sudden cardiac death. The primary ROR was 10.65 (95% CI 8.62–13.14) and the PRR was 10.63 (95% CI 8.61–13.12). Sensitivity RORs ranged from 6.82 to 9.29; every lower 95% CI bound exceeded 1. Fifty-six reports carried duplicate-related metadata, and 57 unique clinical signatures were identified.

Conclusion. Methadone and sudden cardiac death showed a consistent signal of disproportionate reporting in FAERS across exposure, clustering, and comparator assumptions. The signal supports focused pharmacovigilance and case review but does not estimate incidence, establish causality, or determine the cause of an individual death.

Development and Internal Technical Evaluation of a Transparent Dashboard for Indonesian Medical Malpractice Disputes: A Pilot Study

2026-10-12T04:25:49+00:00

Background. Judicial assessment of suspected medical malpractice requires simultaneous consideration of clinical facts, documentation, professional standards, causation, organizational responsibility, and procedural proof.

Objective. To develop and technically evaluate a transparent local dashboard that structures these elements for education and research without substituting for expert or judicial judgment.

Methods. Sixteen de-identified Indonesian disputes (2006–2026) were purposively assembled, one record per dispute. Eight prespecified concepts were manually coded and compared with a regular-expression dictionary, free of outcome terms, applied to evidence notes (dictionary-based natural language processing [NLP]). Five features entered a ridge logistic model (λ = 1) evaluated by leave-one-dispute-out cross-validation. Six families of deterministic software tests were run.

Results. The corpus contained six granted and ten rejected outcomes. Across 128 concept decisions, the dictionary produced 33 true positives, 2 false positives, and 13 false negatives (micro-precision 94.3%, micro-recall 71.7%, micro-F1 81.5%; macro-F1 87.9%). Severe injury was positive in 15 of 16 disputes and had the lowest recall (0.40). Out-of-fold sensitivity was 5/6 and specificity 10/10; the Brier score was 0.050 with manual features and 0.061 with NLP-derived features. All 49 software tests passed.

Conclusion. The prototype provides traceable exploration of a small medicolegal corpus. Because one abstractor produced the labels and notes, and the predictors restate the courts’ own grounds, the near-perfect internal separation is not evidence of prediction or external validity. Use should be limited to education, hypothesis generation, and abstraction quality assurance.