A new index, Respiratory Insufficiency index and Modified Early Warning Scores predict extubation failure
Bibliographic record
Abstract
Background: Extubation failure occurs in 5%-20% of patients and is associated with poor clinical outcomes. The primary aim of this project was to determine the predictive ability of the Respiratory Insufficiency (RI) index, Respiratory Oxygenation (ROX) index and Modified Early Warning Score (MEWS) in identifying extubation failure. Methods: fold cross validation. Nomogram was constructed based on the final model. Results: Of 216 enrolled subjects, 46 (21.3%) experienced extubation failure. The median RI index 1-h post extubation was 20 [interquartile range [IQR] 16.33-24.24] for success group and 27.02 [IQR 22.42-33.83] for the failure group (P<0.001). The median ROX index 1-h post extubation was 16.66 [IQR 12.57-19.84] for success group and 11.11 [IQR 8.09-14.67] for failure group (P<0.001). The median MEWS 1-h post extubation was 2 [IQR 1-3] for the success group and 4 [IQR 3-5] for the failure group (P<0.001). In multivariable analysis, age >60 years [OR 3.89 (95% CI 1.56-9.73); P=0.004], MEWS >4 [OR 4.01 (95% CI (1.59-10.14); P=0.003] and, RI index >20 [OR 4.50 (95% CI 1.43-14.21); P=0.010] were independently associated with extubation failure. Conclusion: In the present study, RI index and MEWS were independently associated with predicting extubation failure within 1 h of extubation. A prospective validation study is warranted to establish the role of these indices in predicting extubation outcome.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".