Outcomes for patients with rheumatic heart disease after cardiac surgery followed at rural district hospitals in Rwanda
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In sub-Saharan Africa, continued clinical follow-up, after cardiac surgery, is only available at urban referral centres. We implemented a decentralised, integrated care model to provide longitudinal care for patients with advanced rheumatic heart disease (RHD) at district hospitals in rural Rwanda before and after heart surgery. METHODS: We collected data from charts at non-communicable disease (NCD) clinics at three rural district hospitals in Rwanda to describe the outcomes of 54 patients with RHD who received cardiac valve surgery during 2007-2015. RESULTS: The majority of patients were adults (46/54; 85%), and 74% were females. The median age at the time of surgery was 22 years in adults and 11 years in children. Advanced symptoms-New York Heart Association class III or IV-were present in 83% before surgery and only 4% afterwards. The mitral valve was the most common valve requiring surgery. Valvular surgery consisted mostly of a single valve (56%) and double valve (41%). Patients were followed for a median of 3 years (range 0.2-7.9) during which 7.4% of them died; all deaths were patients who had undergone bioprosthetic valve replacement. For patients with mechanical valves, anticoagulation was checked at 96% of visits. There were no known bleeding or thrombotic events requiring hospitalisation. CONCLUSION: Outcomes of postoperative patients with RHD tracked in rural Rwanda health facilities were generally good. With appropriate training and supervision, it is feasible to safely decentralise follow-up of patients with RHD to nurse-led specialised NCD clinics after cardiac surgery.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it