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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Jun 2, 2020
Open Peer Review Period: Jun 2, 2020 - Jun 29, 2020
Date Accepted: Jul 14, 2020
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation

Li Y

Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation

JMIR Med Inform 2020;8(8):e20974

DOI: 10.2196/20974

PMID: 32795995

PMCID: 7455869

Development and External Validation of Diagnostic Model for in-Hospital Bleeding in Patients with Acute ST Elevation Myocardial Infarction: Algorithm Development and Validation

  • Yong Li

ABSTRACT

Background:

Bleeding complications in patients with acute ST segment elevation myocardial infarction (STEMI) were associated with an increased risk of subsequent adverse consequences.

Objective:

The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding.

Methods:

Design: Multivariate logistic regression of a cohort for hospitalized patients with acute STEMI . Setting: Emergency department ward of a university hospital. Participants: Diagnostic model development: A total of 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. External validation: A total of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019. Outcomes: All-cause in-hospital bleeding not related to coronary artery bypass graft surgery or catheterization. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram.We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA).

Results:

In-hospital bleeding occurred in 112 out of 4,262 participants (2.6%) patients in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed that the differences between two group with and without in-hospital bleeding in age( odds ratios (OR)1.047; 95% confidence interval(CI), 1.029 ~1.066 ; P <.001), Killip III (OR 3.265;95% CI, 2.008~ 5.31 ; P <.001) , and Killip IV (OR 5.133; 95% CI, 3.196~ 8.242 ; P <.001).We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was .777±.021, 95% CI= .73576 ~ .81823. We constructed a nomogram based on age , and Killip classification. In-hospital bleeding occurred in 117 out of 6,015 participants (1.9%)patients in the validation data set. The AUC was .7234±.0252, 95% CI= .67392 ~ .77289 .Discrimination, calibration, and DCA were satisfactory. Date of approved by ethic committee:18 November 2019. Date of data collection start: 26 November 2019. Numbers recruited as of submission of the manuscript:10,277.

Conclusions:

We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI . Clinical Trial: We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027578; registered date: 19 Novmober 2019). http://www.chictr.org.cn/edit.aspx?pid=45926&htm=4.


 Citation

Please cite as:

Li Y

Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation

JMIR Med Inform 2020;8(8):e20974

DOI: 10.2196/20974

PMID: 32795995

PMCID: 7455869

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