Bibliographic record
Abstract
Introduction: The goal of this study was to establish a local low-cost rapid response team to improve the early recognition of decompensating patients and to reduce delays in treatment initiation. Hypothesis: We have previously demonstrated that there is a marked delay between patient deterioration to time of critical care consultation and initiation of appropriate therapy on our medical wards.This delay was associated with increased mortality(PMID22699035).We anticipated that creation of a ward-based MET would decrease time from patient decompensation to initial intervention,decrease ICU transfers,and reduce cardiac arrest(Code Blue)calls. Methods: A 6-month educational project was undertaken (Jan-Jun 2011).Ward nurses,residents,and Clinical Teaching Unit (CTU)attending doctors were taught MET calling criteria.The afferent and efferent limbs of the MET were defined,with the afferent limb comprised of bedside nurses and the efferent limb comprised of senior residents.Transfers from CTU to ICU between Jul 2011-Jun 2012 were examined.We reviewed baseline patient characteristics,time from MET call to intervention,and time of ICU transfer.We also collected 30-and 90-day mortality data for ICU transfers and compared medical ward cardiac arrest rates pre-and post-MET implementation. Results: During the study period,4.2patients/1000patient days were transferred from CTU to ICU,compared to 5.0patients/1000patient days pre-MET implementation(p=NS).55 MET calls were placed for 47 patients,with an average 1.57calls/week.The median time from MET activation to intervention was 5min(IQR1-10)compared to 3.4hrs(IQR0.6-12.4)in historical controls.Code blue rates on the CTU fell from 2.4/1000patient days to 1.2/1000patient days(p=0.03).In contrast,code blue rates outside our medical wards remained stable(1.2/1000patient days to 1.0/1000patient days(p=0.18)).The 30-day mortality for ICU transfers was 37%(n=15) compared to 32%(n=15) pre-MET(p=NS). Conclusions: Our local low-cost program reduced time from patient decompensation to intervention by 3.3 hours.The number of code blue calls from the CTU was reduced post-MET.However, the number of unexpected ICU transfers and 30-day mortality of patients transferred to ICU remained unchanged.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.645 | 0.527 |
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".