Risk of Stroke Among HIV Patients: A Systematic Review and Meta-analysis of Global Studies and Associated Comorbidities
Bibliographic record
Abstract
BACKGROUND: Despite advancements in the management of HIV infection, the factors contributing to stroke development among HIV-positive individuals remain unclear. This systematic review and meta-analysis aim to identify and evaluate the relative risk factors associated with stroke susceptibility in the HIV population. METHODS: A comprehensive search was conducted in PubMed, Scopus, and Web of Science databases to identify studies investigating the risk of stroke development in HIV patients and assessing the role of different risk factors, including hypertension, diabetes, dyslipidemia, smoking, sex, and race. The quality assessment of case-control studies was conducted using the Newcastle-Ottawa Scale, whereas cohort studies were assessed using the National Institute of Health tool. Meta-analyses were performed using a random-effects model to determine pooled hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: A total of 18 observational studies involving 116,184 HIV-positive and 3,184,245 HIV-negative patients were included. HIV-positive patients exhibited a significantly higher risk of stroke compared with HIV-negative patients [OR (95% CI): 1.31 (1.20 to 1.44)]. Subgroup analyses revealed increased risks for both ischemic stroke [OR (95% CI): 1.32 (1.19 to 1.46)] and hemorrhagic stroke [OR (95% CI): 1.31 (1.09 to 1.56)]. Pooled adjusted HRs showed a significant association between stroke and HIV positivity (HR: 1.37, 95% CI: 1.22 to 1.54). Among HIV-positive patients with stroke, hypertension [OR (95% CI): 3.5 (1.42 to 8.65)], diabetes [OR (95% CI): 5 (2.12 to 11.95)], hyperlipidemia, smoking, male gender, and black race were associated with an increased risk. DISCUSSION: Our study revealed a significant increased risk of stroke development among people with HIV. A multitude of factors, encompassing sociodemographic characteristics, racial background, underlying health conditions, and personal behaviors, significantly elevate the risk of stroke in individuals living with HIV. The use of observational studies introduces inherent limitations, and further investigations are necessary to explore the underlying mechanisms of stroke in people with HIV for potential treatment strategies. CONCLUSION: HIV patients face a higher risk of stroke development, either ischemic and hemorrhagic strokes. Hypertension, diabetes, hyperlipidemia, smoking, male gender, and black race were identified as significant risk factors. Early identification and management of these risk factors are crucial in reducing stroke incidence among patients living with HIV.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".