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Record W2766364055 · doi:10.1161/jaha.117.007019

Impact of Diabetes Mellitus on the Evaluation of Stable Chest Pain Patients: Insights From the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) Trial

2017· article· en· W2766364055 on OpenAlexaff
Abhinav Sharma, Nishant K. Sekaran, Adrian Coles, Neha J. Pagidipati, Udo Hoffmann, Daniel B. Mark, Kerry L. Lee, Hussein R. Al‐Khalidi, Michael T. Lu, Patricia A. Pellikka, Quynh A. Truong, Pamela S. Douglas

Bibliographic record

VenueJournal of the American Heart Association · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineDiabetes mellitusChest painCoronary artery diseaseInternal medicineOdds ratioProspective cohort studyLogistic regressionCardiology

Abstract

fetched live from OpenAlex

Background The impact of diabetes mellitus on the clinical presentation and noninvasive test ( NIT ) results among stable outpatients presenting with symptoms suggestive of coronary artery disease ( CAD ) has not been well described. Methods and Results The PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial enrolled 10 003 patients with known diabetic status, of whom 8966 were tested as randomized and had interpretable NIT results (1908 with diabetes mellitus, 21%). Differences in symptoms and NIT results were evaluated using logistic regression. Patients with diabetes mellitus (versus without) were similar in age (median 61 versus 60 years) and sex (female 54% versus 52%), had a greater burden of cardiovascular comorbidities, and had a similar likelihood of nonchest pain symptoms (29% versus 27%). The Diamond‐Forrester/Coronary Artery Surgery Study score predicted that patients with diabetes mellitus (versus without) had similar likelihood of obstructive CAD (low 1.8% versus 2.7%; intermediate 92.3% versus 92.6%; high 5.9% versus 4.7%). Physicians estimated patients with diabetes mellitus to have a higher likelihood of obstructive CAD (low to very low: 28.3% versus 40.1%; intermediate 63.9% versus 55.9%; high to very high 7.8% versus 4.0%). Patients with diabetes mellitus (versus without) were more likely to have a positive NIT result (15% versus 11%; adjusted odds ratio, 1.23; P =0.01). Conclusions Stable chest pain patients with and without diabetes mellitus have similar presentation and pretest likelihood of obstructive CAD ; however, physicians perceive that patients with diabetes mellitus have a higher pretest likelihood of obstructive CAD , an assessment supported by increased risk of a positive NIT . Further evaluation of diabetes mellitus's influence on CAD assessment is required. Clinical Trial Registration URL : https://www.clinicaltrials.gov . Unique identifier: NCT 01174550.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.034
GPT teacher head0.356
Teacher spread0.322 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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