Abstract 340: Improved Patterns for Advanced Non-Invasive Diagnostic Testing Using a Personalized Gene Expression Score among Patients Presenting to Primary Care Clinicians with Symptoms of Suspected Obstructive Coronary Artery Disease: Results from the IMPACT-PCP (Investigation of a Molecular Personalized Coronary Gene Expression Test on Primary Care Practice Pattern) Trial
Bibliographic record
Abstract
Introduction: Chest pain is the chief complaint in ~10,000 visits/day in the primary care provider (PCP) office and results in approximately $5 billion/yr in testing costs. Better methods are needed to more accurately assess the CAD risk of patients (pts) in an office-based, non-invasive fashion and to optimize referrals to advanced non-invasive testing for further evaluation and care planning. Hypothesis: We hypothesized that gene expression score (GES) results would lead to a change in the PCP’s diagnostic evaluation of stable pts presenting in the ambulatory setting with symptoms suggestive of obstructive CAD. Methods: The IMPACT-PCP Trial was a multi-center, prospective study which enrolled 251 consecutive pts with no history of CAD seen by nine clinicians for evaluation of chest pain and related symptoms. All patients underwent GES testing: the clinician’s diagnostic strategy was evaluated before and after the GES result was known. The GES is a blood-based molecular diagnostic test with a 96% NPV for excluding the diagnosis of obstructive CAD (defined as at least one vessel with ≥50% coronary artery stenosis by quantitative coronary angiography or core-lab CT-angiography) in symptomatic patients. The primary outcome of interest was the decision change in the diagnostic testing pattern pre/post GES testing as measured by McNemar’s test and logistic regression modeling. Results: Characteristics of the 251 pts eligible for primary endpoint analysis included 140 (56%) women, mean age of 56.2 years (SD± 13.0), average BMI of 29.7 (SD± 6.7), and mean GES of 16 (SD± 10). Following GES, a decision change in treatment plan (e.g. MPI, CTA, and cardiac catheterization) was noted in 145 pts (58% observed vs 10% expected change, p<0.001). More patients had a decreased (n=93, 37%) versus increased (n=52, 21%) intensity of testing (p<0.001). In particular, among the 127 low GES pts (51% of study pts), 60% (76/127) had decreased testing and only 2% (3/127) had increased testing. Follow-up is ongoing, with 233 (93%) pts having completed 30-day follow-up. There has been one MACE event (stroke) reported. Conclusion: The GES was associated with a statistically significant and clinically relevant change in clinical decision making among pts evaluated for suspected symptomatic CAD. In conclusion, the addition of the GES showed clinical utility above and beyond conventional decision-making by optimizing the pt’s diagnostic evaluation, particularly around the reduction in the intensity of diagnostic testing among low GES patients.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".