California Cardiovascular Screening Tool: Findings from Initial Implementation.
Elizabeth A BlumenthalBrian A CroslandDana Senderoff BergerKathryn SanturinoNisha GargMegan BernsteinDiana WolfeAfshan HameedPublished in: AJP reports (2020)
Objective American College of Obstetricians and Gynecologists (ACOG) recently published the California (CA) cardiovascular disease (CVD) screening algorithm for pregnant and postpartum women. We aim to prospectively determine screen-positive and true-positive rates of CVD among women across two populations. Study Design This is a prospective cohort study of obstetrical patients from April 2018 to July 2019 at academic medical centers in CA and New York (NY). We attempted to screen all patients at least once during their pregnancy care (prenatal or postpartum). Women who screened positive ("Red Flags," >3-4 moderate risk factors, abnormal physical examination, and persistent symptoms) underwent further testing. The primary outcome was the screen-positive rate. Secondary outcomes included the true-positive rate and the strength of each moderate factor in predicting a positive CVD screen. Results We screened 846 women. The overall screen-positive rate was 8% (5% in CA vs. 19% in NY). The sites differed in ethnicity, that is, African American women (2.7% in CA vs. 35% in NY, p < 0.01) and substance use (2.7 vs. 5.6%, p < 0.04). The true-positive rate was 1.5% at both sites. The percentage of screen-positive patients who did not complete follow-up studies was higher in NY (70%) than in CA (27%). CVD was confirmed in 30% with positive screens with complete follow-up. Combinations of moderate factors were the main driver of screen-positive rates in both populations. Conclusion This is the first data describing the performance of the CVD screening algorithm in a general obstetric population. Factors, such as proportion of African American women affect the likelihood of a positive screen. The screening algorithm highlights patients at higher lifetime risk of CVD and may identify a group that could be targeted for more direct care transitions postpartum. Data may be used to design a larger validation study.
Keyphrases
- high throughput
- polycystic ovary syndrome
- african american
- cardiovascular disease
- healthcare
- risk factors
- machine learning
- pregnancy outcomes
- pregnant women
- palliative care
- randomized controlled trial
- quality improvement
- gene expression
- depressive symptoms
- ejection fraction
- systematic review
- genome wide
- drug delivery
- artificial intelligence
- cervical cancer screening
- preterm birth
- health insurance
- prognostic factors