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Record W2123416785 · doi:10.1139/h11-048

Evidence-based risk assessment and recommendations for exercise testing and physical activity clearance in apparently healthy individuals<sup>1</sup>This paper is one of a selection of papers published in this Special Issue, entitled Evidence-based risk assessment and recommendations for physical activity clearance, and has undergone the Journal’s usual peer review process.

2011· review· en· W2123416785 on OpenAlexafffundvenue
Jack M. Goodman, Scott Thomas, Jamie F. Burr

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2011
Typereview
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsMedicineAdverse effectCINAHLPopulationIncidence (geometry)MEDLINEMeta-analysisSystematic reviewInternal medicinePhysical therapyPsychological interventionEnvironmental health

Abstract

fetched live from OpenAlex

Increased physical activity (PA) is associated with improved health and quality of life in the general population. A dose-response effect is evident between increasing levels of PA participation and a lower relative risk for cardiovascular disease and all-cause mortality. However, there is also clear evidence that PA acutely increases the risk of an adverse cardiovascular (CV) event and sudden cardiac death (SCD) significantly above levels expected at rest. Adverse CV events during PA may be triggered acutely by the physiological stress of exercise. This investigation will review the available literature describing the CV risks of exercise testing and PA participation in apparently healthy individuals. A systematic review of the literature was performed using electronic databases, including Medline, CINAHL, SPORT discus, EMBASE, Cochrane DSR, ACP Journal Club, and DARE; additional relevant articles were hand-picked and the final grouping was used for the review using the AGREE process to assess the impact and quality of the selected articles. Six hundred and sixteen relevant articles were reviewed with 51 being identified as describing adverse CV events during exercise and PA. Data suggests the risks of fatal and nonfatal events during maximal exercise testing in apparently healthy individuals rarely occur (approximately <0.8 per 10 000 tests or 1 per 10 000 h of testing). The incidence of adverse CV events is extremely low during PA of varying types and intensities, with data limited almost exclusively to fatal CV events, as nonfatal events are rarely reported. However, this risk is reduced by 25%-50% in those individuals who have prior experience with increased levels of PA, particularly vigorous PA. Throughout a wide age range, the risk of SCD and nonfatal events during PA remain extremely low (well below 0.01 per 10 000 participant hours), but both increasing age and PA intensity are associated with greater risk. In most cases of exercise-related SCD, undetected pre-existing disease is present and SCD is typically the first clinical event. The risks of an adverse CV event during exercise testing and PA are rare and are outweighed by the health benefits. Given this risk-benefit relationship, the PAR-Q is an appropriate method to identify those at higher risk across a wide age span and should be used in conjunction with appropriate clinical guidelines for guiding individuals towards graduated PA. There are not adequate data to describe the risks of PA in those individuals considered to be at higher risk but without cardiovascular disease.

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 imitation

Not 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.

metaresearch head score (Codex)0.062
metaresearch head score (Gemma)0.250
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.062
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.250
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.010
Bibliometrics0.0160.008
Science and technology studies0.0010.001
Scholarly communication0.0080.006
Open science0.0070.004
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0090.004

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.

Opus teacher head0.108
GPT teacher head0.391
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations60
Published2011
Admission routes3
Has abstractyes

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