Identification of Patients With Stable Chest Pain Deriving Minimal Value From Noninvasive Testing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Importance: Guidelines recommend noninvasive testing for patients with stable chest pain, although many subsequently have normal test results and no adverse clinical events. Objective: To describe a risk tool developed to use only pretest clinical data to identify patients with chest pain with normal coronary arteries and no clinical events during follow-up (minimal-risk cohort). Design, Setting, and Participants: This secondary analysis of a randomized, pragmatic comparative effectiveness trial (Prospective Multicenter Imaging Study for Evaluation of Chest Pain [PROMISE]) includes stable, symptomatic outpatients without known coronary artery disease referred for noninvasive testing at 193 sites in North America. Interventions: Patients were randomized to receive coronary computed tomography angiography (CCTA) vs functional testing. Main Outcomes and Measures: A low-risk tool was developed and internally validated from July 27, 2010, to September 19, 2013, in 4631 patients receiving CCTA as their initial test, with a median follow-up of 25 months. Logistic regression analysis was used to evaluate pretest variables to determine factors associated with minimal risk using a two-thirds random sample for model derivation (n = 3087) and a one-third sample for testing and validation (n = 1544). The model was then applied to the CCTA and functional testing arms, and test results and event rates were ascertained. Results: A total of 1243 of 4631 patients (26.8%) were in the minimal-risk cohort. The final minimal-risk model included 10 clinical variables that together were correlated with normal CCTA results and no clinical events (C statistic = 0.725 for the derivation and validation subsets; 95% CI, 0.705-0.746): younger age; female sex; racial or ethnic minority; no history of hypertension, diabetes, or dyslipidemia; family history of premature coronary artery disease; never smoking; symptoms unrelated to physical or mental stress; and higher high-density lipoprotein cholesterol level. Across the entire PROMISE cohort, this model was associated with the lowest rates of severely abnormal test results (1.3% for CCTA; 5.6% for functional) and cardiovascular death or myocardial infarction (0.5% for a median of 25 months) among patients at the highest probability (10th decile) of minimal risk. Conclusions and Relevance: In contemporary practice, more than 25% of patients with stable chest pain referred for noninvasive testing will have normal coronary arteries and no long-term clinical events. A clinical tool using readily available pretest variables discriminates such minimal-risk patients, for whom deferred testing may be considered. Trial Registration: clinicaltrials.gov Identifier: NCT01174550.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it