The Association of Diabetes Mellitus with Premature Coronary Artery Disease: A Systematic Review of Pathophysiology, Biomarkers, and Clinical Outcomes
Bibliographic record
Abstract
Introduction: Premature Coronary Artery Disease (PCAD), defined as atherosclerotic cardiovascular disease in young adults, represents a significant and escalating public health challenge with profound socioeconomic consequences. Diabetes Mellitus (DM) is recognized as a principal and potent risk factor for cardiovascular disease, yet the full spectrum of its association with the aggressive phenotype of PCAD requires a comprehensive synthesis of the available evidence. This systematic review aims to elucidate the multifaceted relationship between DM and PCAD, spanning from pathophysiology to clinical outcomes. Methods: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search of PubMed, Google Scholar, Semantic Scholar, Springer, Wiley Online Library databases was performed to identify observational studies (cohort and case-control) examining the association between DM, prediabetes, or insulin resistance and PCAD. The methodological quality and risk of bias of included studies were rigorously assessed using the Newcastle-Ottawa Scale (NOS). A qualitative synthesis of the evidence was performed. Results: A total of 18 studies met the inclusion criteria. The evidence demonstrates a high prevalence of both diagnosed and previously undiagnosed DM in PCAD cohorts, often exceeding 30%. DM was significantly and consistently associated with increased angiographic severity, including a higher burden of multivessel disease and higher complexity scores. Clinically, DM emerged as a powerful independent predictor of adverse outcomes. Patients with PCAD and concomitant DM experience substantially higher rates of Major Adverse Cardiovascular Events (MACE), all-cause mortality, cardiovascular mortality, and recurrent myocardial infarction compared to their non-diabetic counterparts. Furthermore, novel biomarkers of insulin resistance, such as the Metabolic Score for Insulin Resistance (METS-IR) and the Triglyceride-Glucose (TyG) index, demonstrated superior predictive power for MACE over traditional metabolic markers. Discussion: The synthesized findings indicate that DM functions as a critical disease accelerator in the context of PCAD. The underlying pathophysiology, driven by insulin resistance and chronic hyperglycemia, fosters a systemic pro-inflammatory and pro-thrombotic state that promotes a more aggressive and diffuse atherosclerotic phenotype. The clinical implications are profound, highlighting a critical need for earlier risk stratification using novel biomarkers and more aggressive, multifactorial risk reduction strategies in young adults with metabolic dysfunction. Conclusion: The evidence robustly confirms that Diabetes Mellitus is a fundamental determinant of the risk, severity, and poor prognosis associated with Premature Coronary Artery Disease. This warrants a paradigm shift in clinical practice towards the early detection of insulin resistance and the implementation of intensive, secondary prevention-level care for young adults with DM to mitigate their substantial long-term cardiovascular risk.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".