[Establish the nomogram prediction model of septic cardiomyopathy based on the afterload-corrected cardiac

Lili Tao1, Xing Wei, Qi Xu

  • 1Department of Critical Care Medicine, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou 510260, Guangdong, China. Corresponding author: Chen Weiyan,

Insights

This study developed a nomogram to predict 30-day mortality in septic cardiomyopathy (SCM) patients. The model, incorporating age, APACHE II score, VIS score, CRRT, and afterload-corrected cardiac performance (ACP), shows good predictive accuracy.

Area of Science:

  • Critical Care Medicine
  • Cardiology
  • Septic Shock Research

Background:

  • Septic cardiomyopathy (SCM) is a serious complication of sepsis, characterized by impaired cardiac function.
  • Accurate prognosis prediction is crucial for timely intervention and improved patient outcomes in SCM.

Purpose of the Study:

  • To develop and validate a nomogram prediction model for 30-day mortality in patients with septic cardiomyopathy (SCM).
  • To identify key predictors of poor prognosis in SCM patients using afterload-corrected cardiac performance (ACP).

Main Methods:

  • Retrospective analysis of 102 SCM patients monitored with PiCCO.
  • Univariate and multivariate Cox regression analyses to identify independent risk factors for 30-day mortality.
  • Nomogram construction based on significant predictors including age, APACHE II, VIS, CRRT, and ACP.

Main Results:

  • The 30-day mortality rate for SCM patients was 60.8%.
  • Afterload-corrected cardiac performance (ACP) was a significant independent predictor of mortality (HR=0.952, P<0.001).
  • Other independent predictors included APACHE II score, vasoactive inotropic score (VIS), and continuous renal replacement therapy (CRRT).
  • The nomogram demonstrated good discrimination (AUC=0.865) and calibration (C-index=0.797).

Conclusions:

  • The developed nomogram effectively predicts 30-day mortality in SCM patients.
  • The model integrates clinical variables and cardiac performance (ACP) for enhanced prognostic accuracy.
  • Further external validation is recommended to confirm the model's generalizability.
Abstract

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