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Short-Term Global Cardiovascular Disease Risk Prediction in Older Adults.

TitleShort-Term Global Cardiovascular Disease Risk Prediction in Older Adults.
Publication TypeJournal Article
Year of Publication2018
AuthorsSaeed A, Nambi V, Sun W, Virani SS, Taffet GE, Deswal A, Selvin E, Matsushita K, Wagenknecht LE, Hoogeveen RC, Coresh JJ, de Lemos JA
Secondary AuthorsBallantyne CM
JournalJ Am Coll Cardiol
Volume71
Issue22
Pagination2527-2536
Date Published2018 06 05
ISSN1558-3597
KeywordsAge Factors, Aged, Aged, 80 and over, Biomarkers, Cardiovascular Diseases, Cohort Studies, Female, Global Health, Humans, Male, Predictive Value of Tests, Prospective Studies, Risk Factors, Time Factors
Abstract

BACKGROUND: Current prevention guidelines recommend using the Pooled Cohort Equation (PCE) for 10-year atherosclerotic cardiovascular disease (CVD) risk assessment. However, the PCE has serious limitations in older adults: it excludes heart failure (HF) hospitalization, estimates 10-year risk, which may not be the most relevant time frame, and is not indicated for individuals age >79 years.

OBJECTIVES: This study sought to determine whether adding biomarkers to PCE variables improves global CVD (coronary heart disease, stroke, and HF) risk prediction in older adults over a shorter time period.

METHODS: Atherosclerosis Risk in Communities study participants without prevalent CVD including HF (n = 4,760; age 75.4 ± 5.1 years) were followed for incident global CVD events. Adding N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, and high-sensitivity C-reactive protein to the PCE and a "lab model" with the biomarkers, age, race, and gender were assessed for prediction improvement. Area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were calculated.

RESULTS: Over median follow-up of ∼4 years, incident HF was the leading CVD event (n = 193 vs. 118 coronary heart disease and 81 stroke events). Compared to the PCE, each biomarker improved risk prediction. The largest improvement in risk prediction metrics was with the addition of all 3 biomarkers (ΔAUC 0.103; continuous NRI 0.484). The lab model also performed better than the PCE model (ΔAUC 0.091, continuous NRI 0.355).

CONCLUSIONS: Adding biomarkers to the PCE or a simpler "lab model" improves short-term global CVD risk prediction and may be useful to inform short-term preventive strategies in older adults.

DOI10.1016/j.jacc.2018.02.050
Alternate JournalJ Am Coll Cardiol
PubMed ID29535064
PubMed Central IDPMC5984171
Grant ListR01 DK089174 / DK / NIDDK NIH HHS / United States
HHSN268201700001I / HL / NHLBI NIH HHS / United States
K24 DK106414 / DK / NIDDK NIH HHS / United States
HHSN268201700004I / HL / NHLBI NIH HHS / United States
HHSN268201700002I / HL / NHLBI NIH HHS / United States
HHSN268201700005I / HL / NHLBI NIH HHS / United States
R01 HL134320 / HL / NHLBI NIH HHS / United States
HHSN268201700003I / HL / NHLBI NIH HHS / United States