Influence of Olanzapine on QT Variability and Complexity Measures of Heart Rate in Patients With Schizophrenia
Bibliographic record
Abstract
Previous studies have shown that untreated patients with acute schizophrenia present with reduced heart rate variability and complexity as well as increased QT variability. This autonomic dysregulation might contribute to increased cardiac morbidity and mortality in these patients. However, the additional effects of newer antipsychotics on autonomic dysfunction have not been investigated, applying these new cardiac parameters to gain information about the regulation at sinus node level as well as the susceptibility to arrhythmias. We have investigated 15 patients with acute schizophrenia before and after established olanzapine treatment and compared them with matched controls. New nonlinear parameters (approximate entropy, compression entropy, fractal dimension) of heart rate variability and also the QT-variability index were calculated. In accordance with previous results, we have observed reduced complexity of heart rate regulation in untreated patients. Furthermore, the QT-variability index was significantly increased in unmedicated patients, indicating increased repolarization lability. Reduction of the heart rate regulation complexity after olanzapine treatment was seen, as measured by compression entropy of heart rate. No change in QT variability was observed after treatment. This study shows that unmedicated patients with acute schizophrenia experience autonomic dysfunction. Olanzapine treatment seems to have very little additional impact in regard to the QT variability. However, the decrease in heart rate complexity after olanzapine treatment suggests decreased cardiac vagal function, which may increase the risk for cardiac mortality. Further studies are warranted to gain more insight into cardiac regulation in schizophrenia and the effect of novel antipsychotics.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".