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Caffeine Attenuates Early Post-Exercise Hypotension in Middle-Aged Subjects

2006· article· en· W1998892346 on OpenAlexaff
Catherine F. Notarius, Billah Morris, John S. Floras

Bibliographic record

VenueAmerican Journal of Hypertension · 2006
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineCaffeineBlood pressureCardiologyAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Sustained hypotension after an acute dynamic exercise bout is due primarily to peripheral vasodilation. We tested the hypothesis that adenosine-mediated vasodilation contributes to hypotension after exercise, by determining the effect of blocking its actions with caffeine. METHODS: Fourteen healthy middle-aged subjects (mean age = 51 +/- 3 years), cycled to peak effort on 2 study days, after a randomized double-blind intravenous infusion of caffeine (4 mg/kg) selective for adenosine receptor blockade, or vehicle. Both studies were performed after 72 h of caffeine abstinence. RESULTS: Infusion achieved 52.0 +/- 6.1 mumol/L caffeine in plasma. Significant reductions in mean and diastolic blood pressure (BP) were elicited by prior exercise on the vehicle day (from 93 +/- 2 to 85 +/- 2 mm Hg v from 79 +/- 2 to 73 +/- 3 mm Hg, respectively; both P < .05), but not after caffeine infusion. Systolic and mean BP, 10 min after exercise, were higher on the caffeine than on the vehicle day (by 9 +/- 3 and 6 +/- 2 mm Hg, respectively; P < .05), as was heart rate (HR) (100 +/- 5 v 93 +/- 4 beats/min; P < .05). CONCLUSIONS: These data suggest that endogenous adenosine contributes to early hypotension after exercise in healthy middle-aged subjects and underscore the importance of caffeine abstinence if BP or HR immediately after exercise is used to infer cardiovascular risk.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.249
Teacher spread0.224 · 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

Citations38
Published2006
Admission routes1
Has abstractyes

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