Humanitarian cardiac care in Arequipa, Peru: experiences of a multidisciplinary Canadian cardiovascular team
Bibliographic record
Abstract
BACKGROUND: The prevalence of cardiovascular disease and its associated mortality continue to increase in developing countries despite unparalleled improvements in cardiovascular medicine over the last century. Cardiovascular care in developing nations is often constrained by limited resources, poor access, lack of specialty training and inadequate financial support. Medical volunteerism by experienced health care teams can provide mentorship, medical expertise and health policy advice to local teams and improve cardiovascular patient outcomes. METHODS: We report our experience from annual successive humanitarian medical missions to Arequipa, Peru, and describe the challenges faced when performing cardiovascular interventions with limited resources. RESULTS: Over a 2-year period, we performed a total of 15 cardiac repairs in patients with rheumatic, congenital and ischemic heart disease. We assessed and managed 150 patients in an outpatient clinic, including 7 patients at 1-year postoperative follow-up. CONCLUSION: Despite multiple challenges, we were able to help the local team deliver advanced cardiovascular care to many patients with few alternatives and achieve good early and 1-year outcomes. Interdisciplinary education at all levels of cardiac care, including preoperative assessment, intraoperative surgical and anesthetic details, and postoperative critical care management, were major goals for our medical missions.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".