Coronary Artery Disease Prevalence in an Executive Population at a Tertiary Medical Center: Protocol for a Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Coronary artery disease (CAD) is a leading cause of global morbidity and mortality. Although CAD prevalence in the general population is well-documented, its occurrence among executive patients remains largely unexplored. An executive is an individual in a major leadership role, such as a C-suite officer, senior manager, board member, trustee, founder, or business owner, responsible for high-level decision-making and strategic direction. These roles often involve demanding schedules and significant stress. Despite their influence and better access to health care, this demographic faces unique challenges such as demanding work schedules, chronic stress, frequent travel, and reduced control over lifestyle. To address executives' unique health needs, many health care organizations offer specialized programs emphasizing preventive cardiovascular care, using advanced tools such as lipid panels, stress tests, and coronary calcium scans not typically included in primary care, to detect risks early and to promote long-term wellness. OBJECTIVE: This protocol aims to design a study to determine the prevalence of CAD in executive patients and compare it to the established prevalence in the US general population with the overarching goal of improving screening and care of CAD among executive patients. METHODS: This protocol proposes a retrospective review of medical records for patients with CAD seen at the Mayo Clinic's Executive Health Program from January 1, 2020, to December 31, 2023, with the aim of determining the prevalence of CAD in executive patients. The primary outcome is CAD prevalence, which will be identified through clinical diagnoses in the electronic medical records. Secondary outcomes include demographics, cardiovascular medications, social determinants of health, laboratory and diagnostic results, coronary calcium scores, and treatment interventions. The prevalence of CAD will be calculated as the proportion of patients with a documented CAD diagnosis relative to the total number of patients in the study cohort. RESULTS: A total of 24,272 patients were seen in the executive health clinic between January 1, 2020, and December 31, 2023. After applying the inclusion criteria, 6466 executive patients were eligible, with 3290 identified as having a potential CAD diagnosis pending confirmation through a detailed chart review. CONCLUSIONS: In this protocol, we outline a research design and methodology to address a critical gap in understanding the prevalence of CAD among executive patients. This demographic is often overlooked despite their unique risk factors such as high stress and lifestyle choices. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72451.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".