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Record W2091920198 · doi:10.1016/j.pain.2010.03.012

Negative association between resting blood pressure and chest pain in people undergoing exercise stress testing for coronary artery disease

2010· article· en· W2091920198 on OpenAlexafffundabout
Blaine Ditto, Kim Lavoie, Tavis S. Campbell, Jennifer L. Gordon, André Arsenault, Simon Bacon

Bibliographic record

VenuePain · 2010
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsMontreal Heart InstituteUniversité de MontréalConcordia UniversityUniversity of CalgaryMcGill UniversityUniversité du Québec à Montréal
FundersInstitut de Cardiologie de Montréal
KeywordsMedicineBlood pressureAnginaCoronary artery diseaseCardiologyIschemiaInternal medicineChest painMyocardial infarction

Abstract

fetched live from OpenAlex

Sustained and acute increases in blood pressure can dampen pain in experimental animals and humans. The most important clinical implication of this relationship may be the phenomenon of silent cardiac ischemia. High blood pressure is common in people at risk for cardiac ischemia and may reduce angina, the key symptom of life-threatening ischemia. The relationship between resting blood pressure and angina was examined in 904 people undergoing exercise stress testing for coronary artery disease. The presence or absence of ischemia was documented with single photon emission computed tomography (SPECT). Participants with ischemia had higher scores on the McGill Pain Questionnaire (MPQ) following exercise though this was moderated significantly by diastolic blood pressure (DBP), especially in women. People with higher pre-exercise resting DBP who displayed SPECT-diagnosed ischemia had MPQ scores comparable to people who did not display ischemia, independent of age, exercise duration, medication, and cardiac history. Awareness of the potential association between blood pressure and angina may provide patients with coronary artery disease and their physicians' important guidance.

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)0.006
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.031
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)0.0000.000

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 head0.015
GPT teacher head0.244
Teacher spread0.228 · 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.

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

Citations4
Published2010
Admission routes3
Has abstractyes

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