Associação de eventos adversos cardiovasculares e o uso de agentes antipsicóticos em pacientes esquizofrênicos: revisão sistemática de estudos observacionais
Bibliographic record
Abstract
There are controversies about the association of cardiovascular adverse events and the use of antipsychotic agents in schizophrenia patients. Cardiovascular diseases are responsible for the main causes of mortality in the world. And it has been observed high mortality rates in patients with schizophrenia. Thus, the objective of this research was to determine whether there is an association between the risk of cardiovascular adverse events and the use of antipsychotic agents in schizophrenia patients. Were surveyed on LILACS from 1982 to November 2015, PUBMED (public version of MEDLINE) de1962 to November 2015, The Cochrane Controlled Clinical Trials Database (CENTRAL) 2015 volume 10 and PsycINFO until November 2015. Two reviewers selected and accessed from independently observational studies reporting associations between cardiovascular adverse events and the use of antipsychotic agents. Three observational cohort items were included to assess quality. The quality of the articles was assessed using the Newcastle-Ottawa Scale, in which two articles received three stars and an article won four stars, indicating high risk of bias. Clinical heterogeneity was evident and there is no meta-analysis. Data best quality articles were used to estimate preliminary results. This systematic review shows a preliminary result of the variables: arrhythmia and mortality. When analyzed arrhythmia demonstrated that there was a significant increase in patients with schizophrenia which makes use of antipsychotic agents with compared to people without psychotic diagnosis. Mortality from cardiovascular disease, demonstrating a significant increase in the group of participants who received antipsychotics and schizophrenia were compared to the general population not taking antipsychotics. The evidence found so far were insufficient to demonstrate or rule out the existence of the association between the use of neuroleptic drugs for the treatment of patients with schizophrenia and adverse cardiovascular events.
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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 | 0.039 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".