MétaCan
Menu
Back to cohort
Record W2954816013 · doi:10.3233/wor-192952

Impact of applying different resting blood pressure cut-points to clear for maximal exercise

2019· article· en· W2954816013 on OpenAlexaff
Elizabeth B. Yee, Alison Macpherson, Norman Gledhill, Scott Gledhill, Veronica Jamnik

Bibliographic record

VenueWork · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsYork University
Fundersnot available
KeywordsClearanceMedicineBlood pressureVO2 maxPhysical therapyCardiologyInternal medicineHeart rate

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to examine the impact of applying six commonly-used and two proposed resting blood pressure (BP) cut-points to clear individuals for maximal exercise in non-clinical health, wellness, commercial fitness agencies and physically demanding occupation test sites. METHODS: Participants (n = 1670) completed the Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) and had their resting BP measured. Individuals with a BP >160/90 mmHg were further screened for contraindications to exercise using the ePARMed-X+ (www.eparmedx.com), all 1670 were cleared. There were no adverse events during or post exercise. RESULTS: The percentages of participants cleared for each BP cut-point were: <130/80 mmHg (85.3%), <140/90 mmHg (93.4%), <144/90 mmHg (94.6%), <144/94 mmHg (96.3%), <150/100 mmHg (98.6%), <160/90 mmHg (95.6%), <160/94 mmHg (97.8%) and <160/100 mmHg (99.5%). Individuals who would not have been cleared without further screening were significantly older, had a higher BMI, or had a lower maximal oxygen consumption. CONCLUSIONS: Conservative or lower resting BP cut-points currently applied to clear individuals for maximal exercise provide an unnecessary barrier. For individuals categorized as low-to- moderate risk by evidence-based screening tools such as the PAR-Q+ and ePARmed-X+, we recommend a resting BP cut-point of <160/94 mmHg to clear for maximal exercise until sufficient evidence is amassed to support the increase to <160/100 mmHg.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.276
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueWorkSame topicCardiovascular and exercise physiologyFrench-language works237,207