The ethics of pacemaker reuse: might the best be the enemy of the good?
Bibliographic record
Abstract
Symptomatic bradycardia contributes significantly to mortality and decreased functional status in many low and middle income countries (LMIC). In contrast to the developed world, where bradycardia often results from sinus node dysfunction, patients requiring pacemakers in LMIC more commonly present with complete heart block.1–3 Yet many patients in LMIC have little to no access to electrophysiological therapies, as the cost of one device often exceeds the annual income of the average citizen.4 Several countries—including Sweden, India and Canada—have previously explanted and resterilised pacemakers from deceased donors for reutilisation.5–7 With increasing global disparities in medical care, post mortem explantation and reuse of pacemakers presents a potential means for mitigating the rising burden of cardiovascular disease in LMIC. Recent survey data indicate that almost 45% of deceased pacemaker patients in the USA have their devices extracted for reasons including family request and risk of device explosion during cremation. Notably, over 80% of these extracted devices are discarded or stored as waste. The vast majority of funeral directors, device patients and the general population support donation of explanted pacemakers to LMIC.8 ‘Project My Heart–Your Heart’ is a proof of concept pacemaker donation initiative that allows funeral directors to send explanted devices to an academic centre for evaluation and resterilisation before donation to underserved patients in LMIC.9 A recent case study of 12 resterilised pacemakers donated through this …
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".