New Study Reveals Heart Health Indicators and COPD Symptom Severity Predict Major Future Heart and Lung Events in COPD

A new study from the Observational and Pragmatic Research Institute has shown that long-term heart and lung risks can be predicted in people with chronic obstructive pulmonary disease (COPD), a common lung condition, using information already captured in primary care.  

This research responds to a long‑standing need for better ways to assess combined heart and lung risks in this patient group, as traditional cardiac risk tools are not optimised for people with COPD – a key evidence gap identified by the International Cardiovascular and Respiratory Alliance in 2025.  

Real-world primary care data, collected as part of routine clinical consultations, provides an excellent opportunity for deriving and validating a statistical model predicting the future risk of serious heart and lung events, tailored to patients with COPD.  

Using data from the UK’s Optimum Patient Care Research Database (OPCRD), researchers developed a COPD-specific model to forecast the risk of these events – collectively called Major Adverse Cardiovascular and Respiratory Events (MACRE) – including heart attacks, severe COPD flareups, and deaths from any cause.  

The study found sixty-one demographic and clinical factors that helped predict a patient’s MACRE risk over both five- and ten-year periods. Importantly, heart-health indicators (or a patient's cardiovascular risk profile) and COPD symptom severity (based on a patient’s reported breathlessness score) were found to predict future risk of MACRE in five years (Figure 1).    

When tested in a large nationwide cohort, the model showed that these events were common: half of patients went on to experience a major heart or lung related event over the study period, which spanned a median of 10.5 years. However, importantly our model found that some patients were at much higher risk and may benefit most from preventative interventions.

Figure 1: Risk classification heatmap, showing the predicted risks of MACRE in the overall study cohort at five years, stratified by cardiovascular risk profile and the modified Medical Research Council (mMRC) score. Numbers on the right represent the predicted risks in percentages.  

Reflecting on the study, Professor Chris Gale, lead author and Professor at the University of Leeds, commented: “People living with COPD face a much higher risk of both heart and lung complications, yet clinicians do not have the tools to reliably assess that combined risk. Our study shows that information already collected during routine appointments can identify who is most vulnerable. This opens the door to earlier intervention, better monitoring, and ultimately improved outcomes for patients.” 

As one of the first models to use electronic medical records alone to predict combined cardiopulmonary risk in COPD, this study lays the groundwork for more refined tools to support earlier identification of high-risk patients.  

Further studies are now needed to build on this work, to facilitate the establishment of clinically actionable thresholds that guide cardiopulmonary interventions in COPD patients to prevent MACRE in real-world care.  

To view, read the full publication in the Pragmatic and Observational Research. 

Reference: Chris P. Gale, Mohit Bhutani, Jeffrey Shi Kai Chan, John Townend, Mehul S Patel, Mohsen Sadatsafav, William Henley, Cono Ariti, Victoria Carter, Amy Couper, Richard Hubbard, Janwillem W.H. Kocks, Rachel Pullen, Derek Skinner and David Price. Development and internal validation of a prediction model for major cardiovascular and respiratory events in chronic obstructive pulmonary disease: nationwide primary care electronic medical records cohort study. Pragmatic and Observational Research. 2026:17 551291. https://doi.org/10.2147/POR.S551291  

This study was part funded by AstraZeneca, conducted by the Observational and Pragmatic Research Institute, and involved committee members of the International Cardiovascular and Respiratory Alliance (ICRA).