Predictive Validity of a QT<sub>c</sub> Interval Prolongation Risk Score in the Intensive Care Unit
Bibliographic record
Abstract
Background Torsade de pointes is a form of polymorphic ventricular tachycardia associated with heart rate–corrected QT (QTc) interval prolongation. With approximately 24–61% of critically ill patients experiencing QTc interval prolongation, a predictive tool to identify high‐risk patients could assist in the monitoring and management in the intensive care unit (ICU). The Tisdale et al. Risk Score (TRS) is a predictive tool that was developed and validated in a cardiac critical care unit. Objectives The objective of this study was to evaluate the predictive validity (sensitivity and specificity) and likelihood ratios of the TRS in a medical ICU. Methods This was a longitudinal, retrospective, cohort study of consecutive patients who met the inclusion criteria from October 2017 to June 2018 with a sample size of 264 patients. The sample size was derived based on the number of TRS covariates and an exploratory variable. Baseline characteristics and risk factors were documented from electronic health records. The first occurrence of QTc interval prolongation, defined as a QTc interval > 500 ms or an increase ≥ 60 ms above baseline, was the primary endpoint. Main Results The sensitivity and specificity of the TRS for low‐risk patients against the moderate‐risk and high‐risk patients were 97% (95% CI 91–99%) and 16% (95% CI 11–23%), respectively. These results corresponded to a positive likelihood ratio of 1.15 (95% CI 1.07–1.24) and a negative likelihood ratio of 0.20 (95% CI 0.06–0.65). Conclusions In conclusion, the TRS showed a high sensitivity, making it useful in identifying patients at risk of developing QTc interval prolongation. Furthermore, patients categorized as low risk by the tool can be considered as having minimal risk of developing QTc interval prolongation. Given the tool's low specificity, it does not reliably identify all patients at low risk of QTc interval prolongation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".