Does Biological Sex Determine the Natural History and Management of Infective Endocarditis?
Bibliographic record
Abstract
Sex and gender are important determinants of health. Despite growing recognition of their relevance, women remain under-represented in clinical trials and cardiovascular research. Infective endocarditis (IE) is a complex cardiovascular condition in which emerging evidence reveals sex-based disparities that extend beyond demographic differences. This narrative review aims to synthesize current evidence from large population-based studies, national registries, meta-analyses, and cohort studies to elucidate the epidemiologic landscape of sex differences in IE, including variations in clinical presentation, management, and outcomes. Women with IE are generally older and have more comorbidities than men. They more frequently exhibit mitral-valve involvement and present less often with perivalvular complications. Staphylococcus aureus infections appear to be more common in women, whereas streptococcal and enterococcal infections are reported less frequently. Although findings are not entirely consistent, most studies suggest higher short-term mortality in women, with female sex identified as an independent risk factor in several analyses. In addition, there has been an increase of 26% in cases of IE related to injection drug use among women. Of particular concern are cases occurring during pregnancy, which may or may not be associated with substance use. The underlying causes of these sex-based disparities in IE remain unclear and warrant further investigation. Future research must adopt a sex- and gender-informed perspective to improve our understanding and guide more equitable clinical management.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".