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Role of absolute muscle strength in determining the blood pressure response to static and dynamic knee extension

2020· article· en· W3016495348 on OpenAlexaffabout
Jordan Brandon Lee, William Lutz, Lucas James Omazic, Mitchell Alexander Jordan, Joseph Cacoilo, Geoffrey A. Power, Philip J. Millar

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHeart rateMedicineBlood pressurePhotoplethysmogramCardiologyHemodynamicsPhysical therapyIsometric exercisePhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

Relative contraction intensity is considered the primary factor determining the hemodynamic response to exercise, though premenopausal women still commonly present with lower blood pressure (BP) and heart rate responses. Our group has shown that within‐ and between‐sex differences in BP responses during static handgrip are abolished when controlling for maximal voluntary effort (MVE). Whether these findings apply to static contractions in the lower limb, dynamic contractions, or are affected by differences in contraction intensity remain untested. 27 young healthy men and women (23±3 years [mean ±SD]; 10 women) performed static and dynamic single leg knee extensor exercise on 2 separate visits, with one modality being tested during a single visit. Both contraction types were performed at 3 separate intensities, 10% MVC, 30% MVC, and 25 nM as an absolute intensity, with 20 minutes of recovery between bouts. All static contractions were held for 2 minute bouts, whereas the dynamic tasks were performed for 3 minutes. Dynamic contractions were performed at a 1:2 second work‐to‐rest ratio at a velocity of 60□/second. The intensities were tested in order from lowest to highest. At baseline and during exercise, continuous BP and heart rate were measured using finger photoplethysmography and single‐lead electrocardiography, respectively. MVC was measured from the left knee extensors on a dynamometer (HUMAC‐norm) at 80□ of knee flexion, and voluntary activation was assessed using the interpolated twitch technique, with ≥90% voluntary activation of the knee extensors set as the acceptable activation threshold. To compare those with HIGH and LOW muscle strength, we split males and females separately by the median MVC. BP and heart rate responses were assessed as the difference from baseline to the last minute of exercise. The groups were matched for baseline characteristics aside from the HIGH group having a higher body mass (78±13 vs. 67±9 kg, p=0.02). By design, knee extensor MVC was different between groups (169±57 vs. 114±38 Nm, p=0.009). During the second minute of the 10% static contractions, diastolic BP responses were larger in HIGH compared to LOW participants (Δ10±4 vs. 6±3 mmHg, p=0.01). The changes in systolic BP (Δ16±9 vs. 10±7 mmHg, p=0.06) and heart rate (Δ11±8 vs 6±4 beats/minute, p=0.07) were also trending towards being larger in HIGH participants. In contrast, the changes in BP and heart rate were not statistically different during the 30% static MVC contraction or the absolute intensity contraction between groups (all p=0.17). During 10% dynamic contractions, systolic BP responses were trending towards being larger in HIGH participants (Δ8±6 vs. 4±4 mmHg, p=0.06), while heart rate responses were greater during 30% dynamic contractions in HIGH participants (Δ14±5 vs. 9±6 beats/minute, p=0.02). In conclusion, our data suggest that absolute torque affects BP and heart rate responses during lower limb static and dynamic knee extension exercise. The mechanisms responsible for how absolute torque influences BP and heart rate warrants future investigation. Support or Funding Information Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant; Canada Foundation for Innovation

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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 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
Published2020
Admission routes2
Has abstractyes

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