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Record W2333773964 · doi:10.1055/s-0034-1382017

Correlation between Acute and Chronic 24-Hour Blood Pressure Response to Resistance Training in Adult Women

2014· article· en· W2333773964 on OpenAlexaff
Ramires Alsamir Tibana, Nuno Manuel Frade de Sousa, Dahan da Cunha Nascimento, Guilherme Borges Pereira, Scott Thomas, S. Balsamo, Herbert Gustavo Simões, Jonato Prestes

Bibliographic record

VenueInternational Journal of Sports Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineBlood pressureInternal medicineResistance trainingDiastoleCardiologyEndocrinology

Abstract

fetched live from OpenAlex

The purpose of the present study was to correlate the acute and chronic decrease in blood pressure (BP) following resistance training (RT). 13 normotensive women (18-49 years) completed an acute whole body RT session with 3 sets of 10 repetitions at 60% 1RM and then 8 weeks of RT as follows: 3/week, 3 sets of 8-12 repetitions maximum. Systolic (SBP) and diastolic BP (DBP) were measured up to 60 min and 24 h following RT (acute and chronic). The greatest acute decrease of SBP (108.5±7.0 mmHg) and DBP (71.5±6.4 mmHg) values over the 60-min period were reduced compared to pre-exercise (117.3±11.7 and 79.3±8.2 mmHg, respectively; p<0.05). The chronic effect on resting BP was observed only for those presenting acute post-exercise hypotension (PEH). The change in both SBP and DBP following acute RT was correlated with the chronic change in resting SBP and DBP (r>0.5; p≤0.05). The change in 24 h BP after acute RT was correlated with the chronic reduction in SBP (r=0.74) and DBP (r=0.80). The magnitude of PEH is a promising candidate for the prediction of individual BP-related training efficacy.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.266
Teacher spread0.258 · 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

Citations60
Published2014
Admission routes1
Has abstractyes

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