|Title||Use of troponins in the classification of myocardial infarction from electronic health records. The Atherosclerosis Risk in Communities (ARIC) Study.|
|Publication Type||Journal Article|
|Year of Publication||2022|
|Authors||Kucharska-Newton AM, Loop MShane, Bullo M, Moore C, Haas SW, Wagenknecht L, Whitsel EA, Heiss G|
|Journal||Int J Cardiol|
|Date Published||2022 Feb 01|
|Keywords||Atherosclerosis, Bayes Theorem, Biomarkers, Electronic Health Records, Humans, Myocardial Infarction, Troponin I, Troponin T|
OBJECTIVE: Electronic health record (EHR) data are underutilized for abstracting classification criteria for heart disease. We compared extraction of EHR data on troponin I and T levels with human abstraction.
METHODS: Using EHR for hospitalizations identified through the Atherosclerosis Risk in Communities (ARIC) Study in four US hospitals, we compared blood levels of troponins I and T extracted from EHR structured data elements with levels obtained through data abstraction by human abstractors to 3 decimal places. Observations were divided randomly 50/50 into training and validation sets. Bayesian multilevel logistic regression models were used to estimate agreement by hospital in first and maximum troponin levels, troponin assessment date, troponin upper limit of normal (ULN), and classification of troponin levels as normal (2× ULN), or missing.
RESULTS: Estimated overall agreement in first measured troponin level in the validation data was 88.2% (95% credible interval: 65.0%-97.5%) and 95.5% (91.2-98.2%) for the maximum troponin level observed during hospitalization. The largest variation in probability of agreement was for first troponin measured, which ranged from 66.4% to 95.8% among hospitals.
CONCLUSION: Extraction of maximum troponin values during a hospitalization from EHR structured data is feasible and accurate.
|Alternate Journal||Int J Cardiol|
|PubMed Central ID||PMC8775766|
|Grant List||HHSN268201700002C / HL / NHLBI NIH HHS / United States |
HHSN268201700001I / HL / NHLBI NIH HHS / United States
HHSN268201700004I / HL / NHLBI NIH HHS / United States
HHSN268201700004C / HL / NHLBI NIH HHS / United States
HHSN268201700003I / HL / NHLBI NIH HHS / United States
HHSN268201700005C / HL / NHLBI NIH HHS / United States
HHSN268201700001C / HL / NHLBI NIH HHS / United States
HHSN268201700003C / HL / NHLBI NIH HHS / United States
HHSN268201700002I / HL / NHLBI NIH HHS / United States
HHSN268201700005I / HL / NHLBI NIH HHS / United States