The Impact of Frailty on All-Cause Mortality in Patients with HIV Infection: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The aim of this study was to conduct a systematic review and meta-analysis of cohort studies that have examined the association between frailty and all-cause mortality in patients with HIV infection. We searched Embase, Medline through the Ovid interface, PubMed, Cochrane Library, and Web of Science to identify potential studies. Cohort studies of death outcomes in HIV patients under debilitating conditions were included and other ineligible or inadequate data were excluded. Data related to all-cause mortality in patients with HIV were extracted. The quality of the included studies was assessed using the Newcastle–Ottawa Scale for cohort studies. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were pooled to estimate the association between frailty and all-cause mortality using Stata, version 12.0. We identified 845 unduplicated citations. Of these, six cohort studies were eligible for inclusion in the review after applying our inclusion and exclusion criteria. Pooled results demonstrated that patients with HIV experiencing frailty were at an increased risk of all-cause mortality (pooled HR = 2.69, 95% CI = 1.83–3.97, p < .001) compared with those without frailty. Frailty was significantly associated with an increased risk of all-cause mortality among patients with HIV, indicating that frailty is an important predictor of adverse clinical outcomes. Therefore, more attention should be paid to screen patients with HIV for frailty and adopt appropriate interventions and personalized treatment plans to prevent the occurrence of adverse events. However, these results need to be validated in further prospective cohort studies in ethnically or geographically diverse populations.
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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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".