An Exploration of the Incorporation of Prediction Models in (inter) national clinical practice guidelines in cardiology

Abstract

Cardiovascular diseases (CVDs) significantly impact survival and quality of life, highlighting the necessity for prompt and effective prevention and treatment strategies. Healthcare providers rely on guidelines from authoritative bodies like the ESC, AHA, and ACC to manage CVDs. These guidelines incorporate prediction models crucial for evaluating patient outcomes. This study assessed the integration of such models into international clinical practice guidelines. For example, a review of 146 guidelines part of ESC and AHA/ASCVD revealed 17 that described at least 23 distinct models predicting CVD progression, focusing on long-term risk, mortality, disease development likelihood, etc. While these models are referenced as predictive tools in the guidelines, there is a lack of detailed explanation about their development and predictive accuracy within the guidelines. The study emphasizes the need for scientific progress in the guidelines to fully understand these models' applications, advantages, limitations, and outcome calculation methodologies. It recommends that guidelines offer various predictive models with comprehensive usage details, equipping healthcare professionals with a broad spectrum of tools for outcome evaluation and informed decision-making in patient care. The guidelines discussed did not endorse a particular prognostic model but referred to models from other guidelines or studies. Further research is required to provide clear recommendations on using various predictive models in a specific guideline, which will assist healthcare providers in making definitive choices for particular cardiovascular disease (CVD) cases.