Bibliographic record
Abstract
It is unfortunate, but true, that mortality gaps between psychiatric patients and the general population remain considerably wide. While the data are not always consistent, it appears that life expectancy may be about 10 to 20 years shorter among patients with psychiatric conditions, compared with healthy people.1 Previous data have identified numerous factors contributing to the shorter life expectancy, which, apart from suicide, plausibly include increased physical morbidities.1–3 Among them, cardiac sudden death is one of the major causes of premature mortality. For example, CVDs accounted for as many as 62.8% of sudden death in 51 patients with schizophrenia in an autopsy-based study.4 Depression was also associated with a higher hazard of 3-year mortality from heart disease, with an adjusted hazard ratio of 1.155 among 5 078 082 patients who were treated in Veterans Health Administration settings.5 Issues in lifestyle, such as smoking, substance use, an unbalanced diet, and reduced physical activities following the onset of psychiatric illnesses may result in metabolic abnormalities, which could ultimately lead to increased risks of CVDs. In addition, various psychotropics, even newer ones, have cardiac toxicity.6,7 Those drugs more or less prolong QT intervals by blocking potassium channel, which, in turn, can result in life-threatening ventricular arrhythmias, such as torsade de pointes although the risk differs substantially among the medications. In light of the risk of this potentially lethal side effect, major treatment guidelines recommend routine assessment with an ECG for patients receiving drugs with such a risk,8–10 which, however, is not always followed in clinical practice.11 Such ignorance may be attributable, at least to some extent, to a lack of knowledge and experiences with this highly important but possibly unfamiliar issue, which is a serious concern. What does QT interval represent? What is the difference between QT interval and QTc interval? Is there any difference in QT intervals between the sexes? How about the impact of age on QT intervals? It is very likely that many of us cannot promptly and accurately answer those questions, although they are all clinically relevant. Another concern is the potential impact of the concurrent use of 2 or more psychotropics or polypharmacotherapy on QT intervals. This is highly pertinent as recent prescription surveys have been consistent in demonstrating a prevalent use of psychotropic polypharmacy, irrespective of geographical regions.12–16 While polypharmacy for bipolar disorders generally seems to be supported by empirical data,17 data in favour of polypharmacy for other psychiatric conditions are still scarce and controversial at best.18 Moreover, those previous data have mainly focused on the therapeutic effects of psychotropic polypharmacy; conversely, its negative effects have not garnered wide attention thus far. In light of the possible pharmacokinetic and pharmacodynamic interactions of drugs concurrently prescribed, potentially increased risks of adverse consequences of combination therapy, including QT prolongation, should be prudently considered. In the 2 In Review articles19,20 in this issue of The Canadian Journal of Psychiatry, the authors have provided thorough reviews of QTc prolongation among patients with psychiatric conditions. In the first article,19 Dr Rabkin examined the impact of age and sex on QTc intervals. Dr. Rabkin is one of the most distinguished expert cardiologists and has served on many consensus conferences for the development of the best practice guidelines for physicians. First, he shares the basic knowledge on QTc, including correction methods and its association with sudden death, with which many psychiatrists may not be familiar. Then, he reviews current evidence on the effects of age and sex as well as frequently prescribed antipsychotics and antidepressants on QTc intervals in an easy-to-understand manner. In the second article,20 Dr Takeuchi and colleagues conducted a systematic review of the current literature on any potential association between antipsychotic polypharmacy and QTc prolongation. They conclude that the currently available evidence fails to unequivocally show that antipsychotic polypharmacy worsens QTc prolongation in general. However, in light of scarce and inconsistent evidence, clinicians are advised to remain conservative in resorting to antipsychotic polypharmacy as the combination of some QTc-prolongation liable antipsychotics has the potential to further prolong QTc interval. Both reviews clearly emphasize potentially serious consequences of QTc prolongation and underscore the need of timely and regular ECG assessments. This is especially true for senior patients, whose QTc is already longer than their younger counterparts. Moreover, they are likely to receive a greater number of medications for psychiatric and somatic conditions; the percentage taking more than 1 medication was 70% in people aged 65 to 79 and 3% in those aged 6 to 14, according to the Canadian Health Measures Survey that was conducted from 2007 to 2011.21 Drug-induced QTc prolongation depends on drug concentrations, which is longest at peak and shortest at trough. Given the well-described and uncharacterized risks of elevation of drug concentrations owing to interactions, polypharmacy of any sort should be avoided if at all possible unless there is a clear medical indication. While QTc intervals should be assessed in a timely and regular manner in real-world practice, psychiatrists are advised to pay attention to other well-established somatic risk factors, such as smoking, substance use, obesity, and glucose intolerance, that are detrimental to the morbidity and mortality of cardiac diseases.9 Such a comprehensive and holistic viewpoint, albeit with some realistic challenges, is useful to reduce CVDs and undesired outcomes among patients with serious mental illnesses.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".