MétaCan
Menu
Back to cohort

Alternative Methods To Quantify Baroreflex Sensitivity Following Resistance Exercise

2023· article· en· W4387054981 on OpenAlexaffabout
Foster Wynne, Jeeva Gill, Olivia Mclennan, Mark Rakobowchuk

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsThompson Rivers UniversityUniversity of British Columbia
Fundersnot available
KeywordsBaroreflexBlood pressureMedicineLinear regressionBaroreceptorAnalysis of varianceResistance trainingCardiologyInternal medicineAnesthesiaHeart rateMathematicsStatistics

Abstract

fetched live from OpenAlex

Most studies assess baroflex sensitivity (BRS) assuming a linear relationship between R-R inteval (RRI) and systolic blood pressure (SBP). However, exponential models may be more appropriate and provide timings of baroreflex responses. PURPOSE: Resistance exercise induces substantial BRS alterations, and was used here to examine the utility of exponential modelling. METHODS: Eight healthy participants completed a resistance exercise bout lasting 1 hour that involved 8 exercises (3 sets, 10 repetitions to failure). BRS was determined from continuous arterial blood pressure, and ECG during phase II and phase IV of a series of 6-10 Valsalva maneuvers (VM) completed before, immediately after, and 1 hour after the bout. We determined traditional BRS as the slope of the linear regression between RRI and SBP during phase II and phase IV, and we modelled the phase IV RRI response. The time delay (TD) and time constant (tau) quantified the baroreflex response latency. Response magnitude was determined as the gain and normalized gain (gain/deltaSBP). Time comparisons were made using 1-way repeated measures ANOVA. RESULTS: Phase II traditional BRS decreased significantly immediately following exercise (Post: 4.9 ± 2.6 vs. Pre: 12.5 ± 6.0 ms/mmHg p < 0.01) but returned to baseline by 1H (p = 0.43). Whilst the phase IV BRS tended to decrease (p = 0.09). Gain was significantly increased immediately following (Post: 361 ± 195 vs. Pre: 269 ± 132 ms p < 0.01) and remained elevated but not significantly at 1H (p = 0.07). The deltaSBP followed this same response (Post: 41 ± 22 vs. Pre: 23 ± 12 mmHg p = <0.01) but remained elevated at 1H (28 ± 12 mmHg, p = 0.03). The normalized gain tended to decrease immediately after the bout (p = 0.09). Exponential modelling was less sensitive to the bout of resistance exercise with tau, and TD, not significantly altered (p > 0.05). CONCLUSION: Our finding of a reduced PII BRS is novel and not previously reported. Whereas, both the normalized gain and the traditional PIV BRS showed a similar decreasing trend suggesting high methodological similarity. Gain increased after the exercise bout indicating a more pronounced heart rate response to VMs but the latency and kinetics of the baroreflex response were not altered. Supported by the Canada Foundation for Innovation John R Evans Leaders Fund.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.040
GPT teacher head0.383
Teacher spread0.343 · 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 designBench or experimental
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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & ExerciseSame topicHeart Rate Variability and Autonomic ControlFrench-language works237,207