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Record W1968242732 · doi:10.1160/th08-10-0630

The impact of acute and chronic exercise on thrombosis in cardiovascular disease

2009· article· en· W1968242732 on OpenAlexaff
Roxanne Pelletier, Kim Lavoie, Simon Bacon

Bibliographic record

VenueThrombosis and Haemostasis · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsConcordia University
Fundersnot available
KeywordsMedicineAerobic exerciseDiseaseThrombosisIntensive care medicinePhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

There is now a large and impressive literature showing that people who engage in chronic aerobic exercise or who have better cardiovascular fitness levels, tend to live longer and have lower levels of cardiovascular disease (CVD). However, there is a paradox, as acute aerobic exercise has been associated with an increased risk of CVD events. There are now a number of review articles suggesting that the differential benefits of chronic, relative to acute, exercise might be due to thrombotic changes, though the majority of this data is derived from healthy individuals. However, acute exercise is of greater concern and chronic exercise of greater benefit to patient populations. In addition, these higher risk groups tend to present with more complex profiles, e.g. they may be taking medications that influence thrombotic pathways. As such, the current review has focused on newer information relating to exercise, physical activity and thrombosis in patient populations, and highlights some of the growing area's in the field. For example, the impact of warm-up exercise, the interaction of medications, and issues surrounding the optimal volume and intensity of exercise.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.322
Teacher spread0.292 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

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