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J Am Heart Assoc. 2019 Aug 6;8(15):e012811. doi: 10.1161/JAHA.119.012811. Epub 2019 Jul 31.

Angina Severity, Mortality, and Healthcare Utilization Among Veterans With Stable Angina.

Author information

1
Leon H. Charney Division of Cardiology Department of Medicine New York University School of Medicine New York NY.
2
Department of Population Health New York University School of Medicine New York NY.
3
Department of Population Health Sciences University of Utah Salt Lake City UT.
4
Department of Pharmacy Kaiser Permanente Colorado Aurora CO.
5
George E. Wahlen Department of Veterans Affairs Medical Center Salt Lake City UT.
6
Department of Clinical Pharmacy University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences Aurora CO.
7
Cardiology Section Veterans Affairs Medical Center Manhattan NY.
8
Department of Internal Medicine University of Utah Salt Lake City UT.
9
Department of Pharmacotherapy University of Utah Salt Lake City UT.

Abstract

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.

KEYWORDS:

angina pectoris; healthcare utilization; myocardial revascularization; natural language processing

PMID:
31362569
DOI:
10.1161/JAHA.119.012811
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