Practice and clinical outcomes of valvular surgery for rheumatic heart disease in africa: a scoping review
Bibliographic record
Abstract
BACKGROUND: Rheumatic heart disease is prevalent in Africa, but advanced cardiac care for the condition, which includes valve surgery, is limited. This study examined rheumatic heart disease surgical management and clinical outcomes in Africa. METHODS: This study followed the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. We conducted a comprehensive search of PubMed, Embase, Scopus, and Web of Science for keywords related to “rheumatic heart disease,” “valve surgery,” and “Africa.” Clinical studies published in African countries on valve surgery for rheumatic heart disease were included. RESULTS: The review included 17 studies from 10 countries. The prevalence of rheumatic heart disease had a female predominance (n = 1313/2367, 55.5%). Mitral valve procedures were universally reported. 7 studies highlighted moderate to severe valve disease severity. Clinical improvement was noted in two studies, with patients in NYHA Class I or II. Reoperation rates varied from 1.45% to 17%, and mortality rates from 3.85% to 22.67%. Hospital stays ranged from 5 to 16 days, and ICU stays from 2 to 3 days. Post-operative complications included thromboembolic disease, hypertrophic scars, infective endocarditis, left ventricular dysfunction, bioprosthetic valve dysfunction, arrhythmias, and neurological events such as stroke. CONCLUSION: Valve surgery for rheumatic heart disease in Africa shows promising clinical outcomes but faces challenges like outcome variability, postoperative complications, and limited infrastructure. Addressing diagnostic issues, enhancing follow-up care, and building healthcare capacity are essential for expanding effective surgical interventions and improving patient outcomes.
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 | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".