High Temperatures and Cardiovascular-Related Morbidity: A Scoping Review
Bibliographic record
Abstract
The primary objective of this review was to synthesize studies assessing the relationships between high temperatures and cardiovascular disease (CVD)-related hospital encounters (i.e., emergency department (ED) visits or hospitalizations) in urban Canada and other comparable populations, and to identify areas for future research. Ovid MEDLINE, EMBASE, CINAHL, Cochrane Database of Systematic Reviews, and Scopus were searched between 6 April and 11 April 2020, and on 21 March 2021, to identify articles examining the relationship between high temperatures and CVD-related hospital encounters. Studies involving patients with pre-existing CVD were also included. English language studies from North America and Europe were included. Twenty-two articles were included in the review. Studies reported an inconsistent association between high temperatures and ischemic heart disease (IHD), heart failure, dysrhythmia, and some cerebrovascular-related hospital encounters. There was consistent evidence that high temperatures may be associated with increased ED visits and hospitalizations related to total CVD, hyper/hypotension, acute myocardial infarction (AMI), and ischemic stroke. Age, sex, and gender appear to modify high temperature-CVD morbidity relationships. Two studies examined the influence of pre-existing CVD on the relationship between high temperatures and morbidity. Pre-existing heart failure, AMI, and total CVD did not appear to affect the relationship, while evidence was inconsistent for pre-existing hypertension. There is inconsistent evidence that high temperatures are associated with CVD-related hospital encounters. Continued research on this topic is needed, particularly in the Canadian context and with a focus on individuals with pre-existing CVD.
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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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".