A Meta‐Analysis of Prognostic Indicators to Predict Seizures, Arrhythmias or Death After Tricyclic Antidepressant Overdose
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Bibliographic record
Abstract
OBJECTIVES: To systematically review and summarize studies on the accuracy of ECG and tricyclic antidepressant (TCA) concentration as prognostic indicators of the risk of seizures, ventricular arrhythmia (VA) or death in patients with TCA overdose. METHODS: Articles were identified with MedLine and Cochrane register of controlled clinical trials searches and review of medical toxicology textbooks. Quality of the included studies was assessed. Pooled estimates of sensitivity, specificity, likelihood ratios and Summary Receiver Operating Characteristics (SROC) curves were generated. RESULTS: A total of 18 studies were included in the analysis. The pooled sensitivity (Se) and specificity (Sp) of the QRS for predicting seizures were 0.69 [95% CI 0.57-0.78] and 0.69 [95% CI 0.58-0.78] as compared to 0.75 [95% CI 0.61-0.85] and 0.72 [95% CI 0.61-0.81] for the TCA concentration. The Se and Sp of the QRS to predict VA were 0.79 [95% CI 0.58-0.91] and 0.46 [95% CI 0.35-0.59] compared to 0.78 [95% CI 0.56-0.90] and 0.57 [95% CI 0.46-0.67] for the TCA concentration. The Se and Sp of the QRS to predict death were 0.81 [95% CI 0.54-0.94] and 0.62 [95% CI 0.55-0.68] compared to 0.76 [95% CI 0.49-0.91] and 0.60 [95% CI 0.47-0.72] for the TCA concentration. Very few studies evaluated the accuracy of QTc, T 40 ms axis and the R/S ratio. CONCLUSIONS: Overall, the studies suggested that the ECG and TCA concentration have similar but relatively poor performance for predicting complications, such as seizures, VA or death, associated with TCA overdose.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.010 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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