Replantation Surgery in Quebec: The Bottlenecks to Rapid Care
Bibliographic record
Abstract
INTRODUCTION: Time delays resulting in prolonged ischemia have a significant impact on the successful reattachment of amputated body parts. No studies have addressed the issues surrounding delays from the time of the accident to the start of replantation surgery. The present paper identifies the bottlenecks that prolong the time before patients are able to gain access to a replant team. METHODS: A total of 50 patients underwent microsurgical replantation, because of traumatic amputation, at a university-based hospital from 1996 to 2003. The charts were analyzed to ascertain individual time intervals from the onset of injury until the beginning of replant surgery. RESULTS: The average length of time for patients who came directly to the replant centre was 3 h 40 min before surgery began. In contrast, for those referred from outlying hospitals, the elapsed time was 6 h 21 min. CONCLUSIONS: Two major bottlenecks were found. First, for patients who were referred from other health centres, delays were due to a lack of information as to where patients could receive appropriate replant surgery. Second, delays at the replant centre were primarily due to insufficient physical and human resources in the operating room.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".