Predictive validity and reliability of the Poisoning Severity Score in a pediatric poisoned population: a multicenter retrospective study
Bibliographic record
Abstract
Abstract Background: The Poisoning Severity Score (PSS) aims to assess the severity of poisoned patients based on their clinical presentation. In the absence of a validated severity score for assessing pediatric intoxications in clinical toxicology, we aimed to evaluate the predictive validity and reliability of the PSS in measuring poisoning severity and toxicity progression in poisoned children. Methods: We conducted a multicenter retrospective cohort study using health records data from children aged 0 to 17 years poisoned by a carbo-adsorbable substance and managed in the emergency department at three academic centers in Québec, Canada. Logistic regression was used to estimate the accuracy of the initial PSS and the 12-hour delta PSS to predict hospital admission, intensive care unit admission, a hospital stay ≥ 12 hours, and the need for follow-up after discharge. Its performances were compared to that of the Pediatric Logistic Organ Dysfunction Score (PELODS) using the DeLong test for paired data. Inter-rater reliability of the PSS was measured using weighted Kappa coefficients. Results: Of the 469 subjects included in the study, an initial PSS of 0 was observed for 97% of non-admitted subjects versus 58% of admitted subjects (p<0.05). The AUC-ROC of the PSS ranged from 0.626 (95% CI 0.581-0.670) to 0.690 (95% CI 0.649-0.506) for hospital admission. The AUC-ROC of the PSS were < 0.75 for all outcomes in the unadjusted models but significantly superior or equivalent to those of the PELODS (p≤0.05). Inter-rater reliability was good for the initial PSS (Kappa 82%) and moderate for the 12-hour delta PSS (Kappa 77%). Conclusion: The Poisoning Severity Score appears to be a valid and reliable score to measure the severity of poisoning and the toxicity progression in poisoned children presenting to the Emergency Department within 12 hours of ingestion of a carbo-adsorbable substance, even if its discrimination remains poor.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".