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Development and validation of nomogram for unplanned ICU admission in patients with dilated cardiomyopathy

Xiao-Lei Li1,2, Dilare Adi1,2, Qian Zhao1,2

  • 1State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

Frontiers in Cardiovascular Medicine
|April 3, 2023
PubMed

Insights

Unplanned intensive care unit (ICU) admissions in dilated cardiomyopathy (DCM) patients can be predicted using a new nomogram. This tool helps identify high-risk DCM patients for timely intervention.

Area of Science:

  • Cardiology
  • Clinical Medicine
  • Predictive Analytics

Background:

  • Unplanned intensive care unit (ICU) admission is a significant adverse event for patients with dilated cardiomyopathy (DCM).
  • Effective risk stratification is crucial for managing DCM patients and preventing critical care escalation.

Purpose of the Study:

  • To develop and validate a nomogram for predicting individualized risk of unplanned ICU admission in DCM patients.
  • To provide a clinical tool for early identification of high-risk DCM inpatients.

Main Methods:

  • Retrospective analysis of 2,214 DCM patients from a single tertiary hospital.
  • Development of a nomogram using least absolute shrinkage and selection operator and multivariable logistic regression.
  • Model evaluation using receiver operating characteristic curves, calibration plots, and decision curve analysis (DCA).

Main Results:

  • A nomogram incorporating emergency admission, prior stroke, NYHA class, heart rate, neutrophil count, and NT-proBNP levels was developed.
  • The model demonstrated good discrimination (C-index 0.76) and calibration in the training set.
  • The nomogram showed sustained performance in the validation cohort, with DCA confirming its clinical utility.

Conclusions:

  • This study presents the first risk prediction model for unplanned ICU admission in DCM patients based on readily available clinical data.
  • The developed nomogram can assist clinicians in identifying DCM inpatients at elevated risk for unplanned ICU admission, facilitating proactive management.
Abstract

Keywords:
dilated cardiomyopathynomogramprediction modelprognosisunplanned ICU admission

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