Dataset Information

Development and validation of a prognostic nomogram for myocardial infarction patients in intensive care units: a retrospective cohort study.

ABSTRACT:

Objectives

We aimed to develop and validate a prognostic nomogram and evaluate the discrimination of the nomogram model in order to improve the prediction of 30-day survival of critically ill myocardial infarction (MI) patients.

Design

A retrospective cohort study.

Setting

Data were collected from the Medical Information Mart for Intensive Care (MIMIC)-III database, consisting of critically ill participants between 2001 and 2012 in the USA.

Participants

A total of 2031 adult critically ill patients with MI were enrolled from the MIMIC-III database.

Primary and secondary outcome

Thirty-day survival.

Results

Independent prognostic factors, including age, heart rate, white blood cell count, blood urea nitrogen and bicarbonate, were identified by Cox regression model and used in the nomogram. Good agreement between the prediction and observation was indicated by the calibration curve for 30-day survival. The nomogram exhibited reasonably accurate discrimination (area under the receiver operating characteristic curve, 0.765, 95% CI, 0.716 to 0.814) and calibration (C-index, 0.758, 95% CI, 0.712 to 0.804) in the validation cohort. Decision curve analysis demonstrated that the nomogram was clinically beneficial. Additionally, participants could be classified into two risk groups by the nomogram, and the 30-day survival probability was significantly different between them (p<0.001).

Conclusion

This five-factor nomogram can achieve a reasonable degree of accuracy to predict 30-day survival in critically ill MI patients and might be helpful for risk stratification and decision-making for MI patients.

SUBMITTER: Guo Q

PROVIDER: S-EPMC7747593 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a prognostic nomogram for myocardial infarction patients in intensive care units: a retrospective cohort study.

Guo Qi Q Wu Maoxiong M Li Hongwei H Ouyang Huijun H Sun Runlu R Wang Junjie J Liu Zhaoyu Z Wang Jingfeng J Zhang Yuling Y

BMJ open 20201217 12

<h4>Objectives</h4>We aimed to develop and validate a prognostic nomogram and evaluate the discrimination of the nomogram model in order to improve the prediction of 30-day survival of critically ill myocardial infarction (MI) patients.<h4>Design</h4>A retrospective cohort study.<h4>Setting</h4>Data were collected from the Medical Information Mart for Intensive Care (MIMIC)-III database, consisting of critically ill participants between 2001 and 2012 in the USA.<h4>Participants</h4>A total of 20 ...[more]

PMID: 33334835

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Project description:BackgroundSepsis-associated encephalopathy (SAE) is a critical and common problem in elderly patients with sepsis, which is still short of efficient predictive tools. Therefore, this study aims to screen the risk factors and establish a useful predictive nomogram for SAE in elderly patients with sepsis in the intensive care unit (ICU).Patients and methodsElderly patients (age ≥ 65 years) with sepsis were selected from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Data from demographics and laboratory examinations were collected on the first day of admission to the ICU. SAE was defined by two criteria in the presence of sepsis: ① a Glasgow Coma Scale (GCS) score of < 15 or ② delirium. Differences in demographics and laboratory tests were calculated between SAE and non-SAE groups. Participants were randomly divided into a training set and a validation set without replacement at a ratio of 6:4. A predictive nomogram was constructed in the training set by logistic regression analysis and then validated. The predictive capability of the nomogram was demonstrated by receiver operating characteristic (ROC) analysis and calibration curve analysis.ResultsA total of 22,361 patients were selected, of which 2,809 patients (12.7%) died in the hospital and 8,290 patients (37.1%) had SAE. In-hospital mortality in the SAE group was higher than that in the non-SAE group (18.8 vs. 8.9%, p < 0.001). Based on the results of logistic regression analysis, a nomogram integrating age, Na+, Sequential Organ Failure Assessment (SOFA) score, heart rate, and body temperature were constructed. The area under the curve (AUC) of the nomogram was 80.2% in the training set and 80.9% in the validation set. Calibration curve analysis showed a good predictive capacity of the nomogram.ConclusionSAE is an independent risk of in-hospital mortality in elderly patients in the intensive care unit. The nomogram has an excellent predictive capability of SAE and helps in clinical practice.

Dataset Information

Development and validation of a prognostic nomogram for myocardial infarction patients in intensive care units: a retrospective cohort study.

Objectives

Design

Setting

Participants

Primary and secondary outcome

Results

Conclusion

Publications

Development and validation of a prognostic nomogram for myocardial infarction patients in intensive care units: a retrospective cohort study.

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