Epidemiology of drug-related liver injury among the elderly: a systematic review and meta-analysis of incidence, and risk factors
Bibliographic record
Abstract
BACKGROUND: With increasing global ageing and spreading trend of polypharmacy, it is crucial to systematically analyze the disease burden and risk factors of DILI in the elderly. The aim of this study was to systematically assess the incidence and risk factors of drug-induced liver injury (DILI) in the elderly. METHODS: PubMed, Embase and Web of Science databases from 1 January 2000 to 24 March 2025 were systematically searched. Two independent reviewers selected studies, extracted data and assessed risk of bias. The quality of included studies was assessed using the Newcastle-Ottawa scale. Meta-analyses were conducted to quantify the incidence and risk factors of DILI in elderly. RESULTS: A total of 16 studies including 8,847 elderly patients with DILI were included. Overall, the incidence of DILI in the elderly population was 25% (95% CI: 18%-31%). In addition, risk factors for DILI in older adults included being female (OR = 1.35, 95% CI: 1.12–1.63; P = 0.003), alcohol use (OR = 2.10, 95% CI: 1.50–2.94; P < 0.001), diabetes mellitus (OR = 1.30. 95% CI: 1.10–1.54; P = 0.008), chronic liver disease (OR = 3.25, 95% CI: 2.20–4.80; P < 0.001), malignancy (OR = 1.80, 95% CI: 1.20–2.70; P = 0.004), antimicrobials (OR = 2.50, 95% CI: 1.90–3.30; P < 0.001), immunosuppressants (OR = 2.20, 95% CI: 1.60-3.00; P < 0.001), and antineoplastics (OR = 3.00, 95% CI: 2.10–4.30; P < 0.001), non-steroidal anti-inflammatory drugs (OR = 1.70, 95% CI: 1.25–2.30; P < 0.001), and antiviral drugs (OR = 1.90, 95% CI: 1.30–2.80; P < 0.001). CONCLUSION: This study systematically quantified the prevalence and risk factors of DILI in the elderly population, highlighting the high risk of chronic liver disease, antineoplastic drugs and antimicrobials. TRIAL REGISTRATION: Not applicable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".