Key result
CCS class IV angina is linked to ~48% higher all-cause mortality risk versus class I.
Why the study?
Although Canadian Cardiovascular Society angina severity is tied to adverse outcomes in trial and registry data, its association with all-cause mortality and healthcare utilization using natural language processing-extracted classifications from clinical notes remained to be determined.
Does higher Canadian Cardiovascular Society (CCS) angina severity class predict increased all-cause mortality and healthcare utilization in veterans with stable angina?
Cohort (n=14,216)
Does higher Canadian Cardiovascular Society (CCS) angina severity class predict increased all-cause mortality and healthcare utilization in veterans with stable angina?
Effect estimate: HR 1.48 (95% CI 1.25-1.76)
Absolute Event Rate: 6.83% vs 4.58%
Higher CCS angina severity class extracted via natural language processing is independently associated with increased all-cause mortality and healthcare utilization in veterans with stable angina.
Higher CCS class was associated with mortality in veterans; supports NLP extraction for stratification but leaves open prospective validation.
Background Canadian Cardiovascular Society ( CCS ) angina severity classification is associated with mortality, myocardial infarction, and coronary revascularization in clinical trial and registry data. The objective of this study was to determine associations between CCS class and all‐cause mortality and healthcare utilization, using natural language processing to extract CCS classifications from clinical notes. Methods and Results In this retrospective cohort study of veterans in the United States with stable angina from January 1, 2006, to December 31, 2013, natural language processing extracted CCS classifications. Veterans with a prior diagnosis of coronary artery disease were excluded. Outcomes included all‐cause mortality (primary), all‐cause and cardiovascular‐specific hospitalizations, coronary revascularization, and 1‐year healthcare costs. Of 299 577 veterans identified, 14 216 (4.7%) had ≥1 CCS classification extracted by natural language processing. The mean age was 66.6±9.8 years, 99% of participants were male, and 81% were white. During a median follow‐up of 3.4 years, all‐cause mortality rates were 4.58, 4.60, 6.22, and 6.83 per 100 person‐years for CCS classes I, II , III , and IV , respectively. Multivariable adjusted hazard ratios for all‐cause mortality comparing CCS II , III , and IV with those in class I were 1.05 (95% CI, 0.95–1.15), 1.33 (95% CI, 1.20–1.47), and 1.48 (95% CI, 1.25–1.76), respectively. The multivariable hazard ratio comparing CCS IV with CCS I was 1.20 (95% CI, 1.09–1.33) for all‐cause hospitalization, 1.25 (95% CI, 0.96–1.64) for acute coronary syndrome hospitalizations, 1.00 (95% CI, 0.80–1.26) for heart failure hospitalizations, 1.05 (95% CI, 0.88–1.25) for atrial fibrillation hospitalizations, 1.92 (95% CI, 1.40–2.64) for percutaneous coronary intervention, and 2.51 (95% CI, 1.99–3.16) for coronary artery bypass grafting surgery. Conclusions Natural language processing–extracted CCS classification was positively associated with all‐cause mortality and healthcare utilization, demonstrating the prognostic importance of anginal symptom assessment and documentation.
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Owlia et al. (2019) conducted a cohort in stable angina (n=14,216). Canadian Cardiovascular Society (CCS) angina severity classification (Classes II-IV) vs. CCS Class I was evaluated on all-cause mortality (HR 1.48, 95% CI 1.25-1.76). Higher Canadian Cardiovascular Society angina severity class was associated with increased all-cause mortality, with CCS class IV having an HR of 1.48 (95% CI, 1.25-1.76) compared to class I.
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