Prevalence, Risk Factors, and Mortality of Infective Endocarditis in HIV+Positive Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
This systematic review and meta-analysis examines the epidemiology, risk factors, clinical characteristics, microbiological profiles, and mortality outcomes of infective endocarditis (IE) in HIV-positive and HIV-negative patients, drawing from observational studies. The study aims to compare the burden and presentation of IE between these groups, exploring the roles of HIV-related immunosuppression, intravenous drug use (IVDU), and other behavioral and immunological factors. Employing a random-effects meta-analysis, it synthesizes data on IE prevalence, odds ratios for HIV status, valve involvement patterns, IVDU prevalence, causative pathogens, and survival outcomes. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) and GRADE checklist to evaluate methodological rigor and evidence certainty. The work investigates differences in disease manifestation, such as right- versus left-sided IE, and variations in microbial etiology, alongside their implications for clinical management. By addressing these aspects, this research seeks to clarify the complex interplay of HIV and IE, identify gaps in current knowledge, and provide a foundation for tailored prevention and treatment strategies in high-risk populations. Its findings are intended to inform healthcare providers and guide future investigations into this evolving infectious disease challenge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.036 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".