Guidelines for reporting case studies and series on drug-induced QT interval prolongation and its complications following acute overdose
Bibliographic record
Abstract
Background: The assessment and management of patients with QT interval prolongation in poisoning requires an appropriate method of measuring and adjusting the QT interval for the heart rate (HR) in order to decide if the patient is at risk of life-threatening dysrhythmias, notably torsade de pointes (TdP). As the Clinical Toxicology Collaborative (CTC) workgroup reviewed the published literature on drug-induced QT interval prolongation in poisoning, it became obvious that many publications were missing essential data that were necessary to thoroughly assess and compare the evidence. The aim of this guidance document is to identify essential and ideal criteria required when reporting a case of drug-induced QT interval prolongation and/or TdP in poisoning.Methods: We employed a mixed methods approach as follows. Initially, we reviewed 188 cases of available published case reports and series in the literature regarding drug-induced QT interval prolongation and/or TdP in poisoning as the first step to another project. Common features and deficiencies were identified. Given the large gaps in reporting quality, we conducted an iterative consultative process involving all 23 members of the CTC to identify essential and ideal criteria to analyse publications of QT interval prolongation in poisoning. A priori standards were developed for acceptance or rejection of individual criteria.Results: Survey response was 100%. A minimum set of essential criteria for reporting cases of QT interval prolongation and drug-induced TdP in overdose setting are provided and a 35-item checklist is presented.Conclusions: We report a QT reporting checklist to ensure published case reports and series describing drug-induced QT interval prolongation in poisoning can contribute to the fund of knowledge of QT interval prolongation, TdP and other malignant dysrhythmias.
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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 | 0.169 | 0.341 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.039 | 0.017 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.013 | 0.008 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.009 |
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".