Commentary to QTc prolongation associated with atypical antipsychotic use in the treatment of adolescent-onset anorexia nervosa.
Bibliographic record
Abstract
In this paper, Ritchie & Norris remind us of the need to remain vigilant for drug-induced adverse reactions while treating patients with anorexia nervosa (AN). The authors are to be commended for their submission, as some recent studies show adverse reactions may be underreported by 80–95%, even for serious events (Hazell & Shakir, 2006). In other words, for every adverse event reported, it is reasonable to think that from 4–19 similar incidents have occurred elsewhere, but have not been formally reported. Drug-induced QTc interval prolongation has become a prominent issue as clinicians struggle with decision making around drug therapy in an era which has seen multiple drugs either restricted in their use or removed from the market due to QTc prolongation (Roden, 2004). A recent publication in a prominent journal demonstrated an increased rate of sudden cardiac death in an adult cohort for patients receiving atypical antipsychotics (Ray et al., 2009). A meta-analysis of AN patients showed that QTc interval was within normal range, though significantly longer than in controls. Electrocardiogram (ECG) data appears to have been collected at baseline prior to starting any drug therapy (Lesinskiene et al., 2008). Diurnal variation in QTc interval, controversy over choice of QT interval correction method and a relative lack of information in the literature about QTc effects of psychotropic drugs, especially in specific patient subgroups which may be at greater risk for sudden cardiac death further muddy the waters. There is hope, however, as the currently underway Canadian trial investigating the efficacy and safety of adjunctive olanzapine in patients with AN will obtain ECG data at baseline and on treatment (Spettigue et al., 2008). Hopefully the trial (one of the trial investigators is a co-author of this case report) and others like it will shed more light on this complex issue.
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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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.043 | 0.032 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".