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  11. Construction And Validation Of A Risk Prediction Model For Postoperative Icu Admission In Patients With Colorectal Cancer: Clinical Prediction Model Study

Construction and validation of a risk prediction model for postoperative ICU admission in patients with colorectal cancer: clinical prediction model study

Lu Wang1, Yanan Wu1, Liqin Deng2

  • 1Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, China.

BMC Anesthesiology
|July 4, 2024

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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View abstract on PubMed

Summary
This summary is machine-generated.

A new nomogram predicts intensive care unit (ICU) admission after colorectal cancer (CRC) surgery. Key predictors include age, nutritional status, and comorbidities, aiding clinical decisions for postoperative care.

Area of Science:

  • Oncology
  • Surgical Critical Care
  • Medical Informatics

Background:

  • Intensive care unit (ICU) admission is frequent after major non-cardiac surgeries, particularly radical colorectal cancer (CRC) resection.
  • Optimizing the use of critical care resources and postoperative management is essential for patient outcomes.
  • A predictive tool for mandatory ICU admission post-CRC surgery is needed.

Purpose of the Study:

  • To develop and validate a nomogram predicting the necessity of ICU admission immediately after radical CRC resection.
  • To provide clinicians with a tool for informed decision-making regarding postoperative care intensity.

Main Methods:

  • A retrospective analysis of 1003 patients undergoing CRC surgery was performed.
  • Patients were divided into training (70%) and validation (30%) cohorts.
Keywords:
Intensive care unitNomogramPredictive modelRadical colorectal cancer surgery

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  • The least absolute shrinkage and selection operator (LASSO) and logistic regression identified predictors to build the nomogram, which was validated using decision curve analysis (DCA).

    • Main Results:

    • The final nomogram incorporated age, Nutritional Risk Screening 2002 (NRS2002), serum albumin (ALB), atrial fibrillation, chronic obstructive pulmonary disease (COPD), forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC), and surgical method.
    • The model demonstrated strong discriminative ability (Area Under Curve = 0.865) and excellent calibration.
    • Decision curve analysis confirmed the clinical utility of the nomogram for predicting ICU admission.

    Conclusions:

    • Age, preoperative nutritional status (NRS2002), serum albumin, atrial fibrillation, COPD, FEV1/FVC ratio, and surgical approach are significant predictors of ICU admission after radical CRC surgery.
    • The developed nomogram and its online tool effectively support clinical decision-making for postoperative ICU admission in CRC patients.
    Risk factors