Correction: Differential Changes in QTc Duration during In-Hospital Haloperidol Use
Bibliographic record
Abstract
Aims: To evaluate changes in QT duration during low-dose haloperidol use, and determine associations between clinical variables and potentially dangerous QT prolongation. Methods:In a retrospective cohort study in a tertiary university teaching hospital in The Netherlands, all 1788 patients receiving haloperidol between 2005 and 2007 were studied; ninety-seven were suitable for final analysis.Rate-corrected QT duration (QTc) was measured before, during and after haloperidol use.Clinical variables before haloperidol use and at the time of each ECG recording were retrieved from hospital charts.Mixed model analysis was used to estimate changes in QT duration.Risk factors for potentially dangerous QT prolongation were estimated by logistic regression analysis.Results: Patients with normal before-haloperidol QTc duration (male #430 ms, female #450 ms) had a significant increase in QTc duration of 23 ms during haloperidol use; twenty-three percent of patients rose to abnormal levels (male $450 ms, female $470 ms).In contrast, a significant decrease occurred in patients with borderline (male 430-450 ms, female 450-470 ms) or abnormal before-haloperidol QTc duration (15 ms and 46 ms, respectively); twenty-three percent of patients in the borderline group, and only 9% of patients in the abnormal group obtained abnormal levels.Potentially dangerous QTc prolongation was independently associated with surgery before haloperidol use (OR adj 34.9, p = 0.009) and beforehaloperidol QTc duration (OR adj 0.94, p = 0.004).Conclusion: QTc duration during haloperidol use changes differentially, increasing in patients with normal beforehaloperidol QTc duration, but decreasing in patients with prolonged before-haloperidol QTc duration.Shorter beforehaloperidol QTc duration and surgery before haloperidol use predict potentially dangerous QTc prolongation.
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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 | 0.003 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.067 | 0.023 |
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".