Bibliographic record
Abstract
We were very interested to see the rather surprisingly poor outcomes for patients admitted to two intensive ICUs in Leeds following out-of-hospital cardiac arrest [1]. Of the 100 patients reviewed, only 14 (14%) survived to discharge from ICU and just 5 (5%) survived to leave hospital. We have a particular interest in patients admitted to our ICU after cardiac arrest and we collect data continuously for all these patients using a modified Utstein template. Between February 1998 and March 2007, 158 patients have been admitted to our ICU after out-of-hospital cardiac arrest. Seventy-nine (50%) of these were discharged from ICU and 70 (44.3%) survived to leave hospital. Of the survivors, 62 (85.7%) returned to their normal residence. We have previously published data on outcomes for these patients up until 2004 [2]. A recent study from Canada reported that 537 (36.4%) of 1474 patients admitted to ICU after out-of-hospital cardiac arrest survived to hospital discharge [3]. There could be several reasons for these dramatically different outcomes and in the absence of more detailed data it would be inappropriate to speculate on these. Based on an analysis of the Intensive Care National Audit and Research Centre Case Mix Programme (ICNARC CMP) 42.9% of 24 132 patients admitted to ICU after out-of-hospital cardiac arrest survived to leave ICU and 28.6% survived to hospital discharge (unpublished data). Of those discharged from hospital alive, 79.9% went directly back to their normal place of residence. We are undertaking another analysis of the CMP to define the variability in process and outcome among ICUs for patients admitted after cardiac arrest. These more detailed data might provide some explanations for any significant differences in outcome between ICUs.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".