Deep-learning-based risk stratification for mortality of patients with acute myocardial infarction


Autoři: Joon-myoung Kwon aff001;  Ki-Hyun Jeon aff002;  Hyue Mee Kim aff003;  Min Jeong Kim aff003;  Sungmin Lim aff003;  Kyung-Hee Kim aff002;  Pil Sang Song aff003;  Jinsik Park aff003;  Rak Kyeong Choi aff003;  Byung-Hee Oh aff003
Působiště autorů: Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, Korea aff001;  Artificial intelligence and big data center, Sejong medical research institute, Gyeonggi, Korea aff002;  Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224502

Souhrn

Objective

Conventional risk stratification models for mortality of acute myocardial infarction (AMI) have potential limitations. This study aimed to develop and validate deep-learning-based risk stratification for the mortality of patients with AMI (DAMI).

Methods

The data of 22,875 AMI patients from the Korean working group of the myocardial infarction (KorMI) registry were exclusively divided into 12,152 derivation data of 36 hospitals and 10,723 validation data of 23 hospitals. The predictor variables were the initial demographic and laboratory data. The endpoints were in-hospital mortality and 12-months mortality. We compared the DAMI performance with the global registry of acute coronary event (GRACE) score, acute coronary treatment and intervention outcomes network (ACTION) score, and the thrombolysis in myocardial infarction (TIMI) score using the validation data.

Results

In-hospital mortality for the study subjects was 4.4% and 6-month mortality after survival upon discharge was 2.2%. The areas under the receiver operating characteristic curves (AUCs) of the DAMI were 0.905 [95% confidence interval 0.902–0.909] and 0.870 [0.865–0.876] for the ST elevation myocardial infarction (STEMI) and non ST elevation myocardial infarction (NSTEMI) patients, respectively; these results significantly outperformed those of the GRACE (0.851 [0.846–0.856], 0.810 [0.803–0.819]), ACTION (0.852 [0.847–0.857], 0.806 [0.799–0.814] and TIMI score (0.781 [0.775–0.787], 0.593[0.585–0.603]). DAMI predicted 30.9% of patients more accurately than the GRACE score. As secondary outcome, during the 6-month follow-up, the high risk group, defined by the DAMI, has a significantly higher mortality rate than the low risk group (17.1% vs. 0.5%, p < 0.001).

Conclusions

The DAMI predicted in-hospital mortality and 12-month mortality of AMI patients more accurately than the existing risk scores and other machine-learning methods.

Klíčová slova:

Antiplatelet therapy – Blood pressure – Cardiac arrest – Creatinine – Death rates – Forecasting – Myocardial infarction – Prognosis


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