Mortality predictions in the intensive care unit: Comparing physicians with scoring systems*
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Risk-prediction models offer potential advantages over physician predictions of outcomes in the intensive care unit (ICU). Our systematic review compared the accuracy of ICU physicians' and scoring system predictions of ICU or hospital mortality of critically ill adults. DATA SOURCE: MEDLINE (1966-2005), CINAHL (1982-2005), Ovid Healthstar (1975-2004), EMBASE (1980-2005), SciSearch (1980-2005), PsychLit (1985-2004), the Cochrane Library (Issue 1, 2005), PubMed "related articles," personal files, abstract proceedings, and reference lists. STUDY SELECTION: We considered all studies that compared physician predictions of ICU or hospital survival of critically ill adults to an objective scoring system, computer model, or prediction rule. We excluded studies if they focused exclusively on the development or economic evaluation of a scoring system, computer model, or prediction rule. DATA EXTRACTION AND ANALYSIS: We independently abstracted data and assessed study quality in duplicate. We determined summary receiver operating characteristic curves and areas under the summary receiver operating characteristic curves+/-se and summary diagnostic odds ratios. DATA SYNTHESIS: We included 12 observational studies of moderate methodological quality. The area under the summary receiver operating characteristic curves for seven studies was 0.85+/-0.03 for physician predictions compared with 0.63+/-0.06 for scoring system predictions (p=.002). Physicians' summary diagnostic odds ratios derived from the area under the summary receiver operating characteristic curves were significantly higher (12.43; 95% confidence interval 5.47, 27.11) than scoring systems' summary diagnostic odds ratios (2.25; 95% confidence interval 0.78, 6.52, p=.001). Combined results of all 12 studies indicated that physicians predict mortality more accurately than do scoring systems: ratio of diagnostic odds ratios (95% confidence interval) 1.92 (1.19, 3.08) (p=.007). CONCLUSIONS: Observational studies suggest that ICU physicians discriminate between survivors and nonsurvivors more accurately than do scoring systems in the first 24 hrs of ICU admission. The overall accuracy of both predictions of patient mortality was moderate, implying limited usefulness of outcome prediction in the first 24 hrs for clinical decision making.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it