Accuracy Of Stroke Prediction Using The Predicting Risk Of CVD Events Equation Among Diverse Adults Of The Northern Manhattan Study
Abstract Body (Do not enter title and authors here): Background: The Predicting Risk of CVD EVENTs (PREVENT) equations are a new set of sex-specific and race-free equations developed by the American Heart Association to calculate risk of cardiovascular disease, including stroke as an independent outcome.
Objective: To describe the ten-year risk of stroke (ischemic and hemorrhagic) using the PREVENT equation and assess its validity in predicting stroke among racially and ethnically diverse adults.
Methods: The Northern Manhattan Study is a community-based observational cohort of male and female participants who are of non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic background. Participants were aged 40 years or older and without a history of stroke at the baseline visit between 1993 and 2001. Information was collected on blood lipids, systolic blood pressure, body mass index, estimated glomerular filtration rate, smoking status, diabetes status, and anti-hypertensive or lipid lowering medication use. Using the base model PREVENT equation for stroke, we calculated the ten-year risk of stroke and categorized participants based on levels of risk. Participants were followed and stroke events occurring within ten years were adjudicated by an independent panel of clinicians. We calculated the stroke discordance rate by comparing the predicted to observed number of strokes overall, by sex, and by race/ethnicity.
Results: Among 2,229 participants, mean age was 65 years, with 61% female, 17% NHW, 20% NHB, 60% Hispanic, and 2% Other. Overall, 25% had a <2.5% risk of stroke; 34% had a 2.5 to <5.0% risk of stroke, 25% had a 5.0 to <7.5% risk of stroke, 11% had a 7.5 to <10.0%, and 5% had a ≥10% risk of stroke. Men compared with women and NHB compared with NHW adults had a higher risk of stroke, p<0.05. Over ten years, 106 strokes were predicted, and 136 strokes were observed (discordance rate: 22%). Stroke was more likely to be underpredicted among females (discordance rate: 24%) than males (discordance rate: 20%), p<0.01 and among NHB (discordance rate: 42%) or Hispanic adults (discordance rate: 18%) compared with NHW adults (discordance rate: 0%), p <0.01.
Conclusion: In this sample of urban dwelling adults, the base model PREVENT equation for stroke was most accurate in predicting stroke among NHW adults but performed with less accuracy among NHB and Hispanic adults. Additional factors, such as the social deprivation index, may be important for estimating stroke risk in NHB and Hispanic populations.
Mesa, Robert
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Veledar, Emir
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Levin, Bonnie
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Agudelo, Christian
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Elfassy, Tali
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Gardener, Hannah
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Rundek, Tatjana
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Brown, Scott
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Yang, Eugene
( University of Washington School of Medicine
, Seattle
, Washington
, United States
)
Elkind, Mitchell
( Columbia University Mailman School of Public Health
, New York
, New York
, United States
)
Gutierrez, Jose
( Columbia University Vagelos College of Physicians and Surgeons
, New York
, New York
, United States
)
Besser, Lilah
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Gutierrez, Carolina
( University of Miami Miller School of Medicine
, Miami
, Florida
, United States
)
Author Disclosures:
Robert Mesa:DO NOT have relevant financial relationships
| Emir Veledar:DO NOT have relevant financial relationships
| Bonnie Levin:No Answer
| Christian Agudelo:DO NOT have relevant financial relationships
| Tali Elfassy:DO NOT have relevant financial relationships
| Hannah Gardener:No Answer
| Tatjana Rundek:DO NOT have relevant financial relationships
| Scott Brown:DO NOT have relevant financial relationships
| Eugene Yang:DO have relevant financial relationships
;
Consultant:Genentech:Active (exists now)
; Other (please indicate in the box next to the company name):American College of Cardiology (honoraria):Active (exists now)
; Research Funding (PI or named investigator):Microsoft Research:Active (exists now)
; Advisor:TenPoint7:Active (exists now)
; Individual Stocks/Stock Options:Measure Labs:Active (exists now)
; Consultant:Mineralys:Active (exists now)
; Advisor:Qure.ai:Past (completed)
; Advisor:Sky Labs:Active (exists now)
| Mitchell Elkind:DO have relevant financial relationships
;
Employee:AHA:Active (exists now)
| Jose Gutierrez:DO NOT have relevant financial relationships
| Lilah Besser:DO NOT have relevant financial relationships
| Carolina Gutierrez:DO NOT have relevant financial relationships
Cho So Mi, Natarajan Pradeep, Rivera Rachel, Koyama Satoshi, Kim Min Seo, Honigberg Michael, Bhattacharya Romit, Paruchuri Kaavya, Allen Norrina, Hornsby Whitney