Reliability of electrocardiogram interpretation in critically ill patients*
Bibliographic record
Abstract
OBJECTIVE: To assess the intrarater and interrater reliability of electrocardiogram (ECG) interpretation in critically ill patients and to assess the effect of knowledge of cardiac troponin values on these reliability estimates. DESIGN: Prospective cohort study. SETTING: Fifteen-bed medical-surgical intensive care unit. PATIENTS: Consecutive adults admitted over a 2-month period. MEASUREMENTS AND RESULTS: All consecutive 12-lead ECGs were interpreted independently by two raters for the presence of myocardial ischemia or infarction and secondarily for specific ischemic ECG abnormalities. The ECGs were first interpreted blinded to the patient's troponin levels and reinterpreted on two separate occasions, blinded and unblinded to the troponin values. Results are reported using chance-independent agreement (phi) with associated 95% confidence intervals. For the presence of ischemia or infarction, the intrarater reliability ranged from fair to moderate (phi = 0.35 [95% confidence interval = 0.16, 0.52] and 0.59 [0.33, 0.77] for the two raters, respectively); interrater reliability was slight when blinded to troponin levels (phi = 0.18 [0.03, 0.32]) and increased to moderate when the raters were unblinded to troponin values (phi = 0.52 [0.33, 0.66], p value for the difference = .004). For specific ECG changes, the intrarater and interrater reliability were low for T-wave flattening, whereas detection of a left bundle branch block showed high reliability. CONCLUSIONS: ECG interpretation in critically ill patients for the presence of myocardial ischemia or infarction showed moderate reliability at best; however, there was high reliability for specific ECG changes. Knowledge of the patient's troponin values increased the reliability for all studied ECG changes and resulted in a statistically significant increase in the interrater reliability for diagnosing myocardial ischemia or infarction. Additional studies assessing the appropriate methods of diagnosing myocardial ischemia and infarction and assessing the reliability of these diagnostic tests in critically ill patients are required.
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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 | 0.021 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".