Abstract
BackgroundWe aimed to generate and validate a nomogram to predict patients most likely to require intensive care unit (ICU) admission following gastric cancer surgery to improve postoperative outcomes and optimize the allocation of medical resources.MethodsWe retrospectively analyzed 3,468 patients who underwent gastrectomy for gastric cancer from January 2009 to June 2018. Here, 70.0% of the patients were randomly assigned to the training cohort, and 30.0% were assigned to the validation cohort. Least absolute shrinkage and selection operator (LASSO) method was performed to screen out risk factors for ICU-specific care using the training cohort. Then, based on the results of LASSO regression analysis, multivariable logistic regression analysis was performed to establish the prediction nomogram. The calibration and discrimination of the nomogram were evaluated in the training cohort and validated in the validation cohort. Finally, the clinical usefulness was determined by decision curve analysis (DCA).ResultsAge, the American Society of Anesthesiologists (ASA) score, chronic pulmonary disease, heart disease, hypertension, combined organ resection, and preoperative and/or intraoperative blood transfusions were selected for the model. The concordance index (C-index) of the model was 0.843 in the training cohort and 0.831 in the validation cohort. The calibration curves of the ICU-specific care risk nomogram suggested great agreement in both training and validation cohorts. The DCA showed that the nomogram was clinically useful.ConclusionsAge, ASA score, chronic pulmonary disease, heart disease, hypertension, combined organ resection, and preoperative and/or intraoperative blood transfusions were identified as risk factors for ICU-specific care after gastric surgery. A clinically friendly model was generated to identify those most likely to require intensive care.
Highlights
Intensive care units (ICUs) provide a limited number of specialized medical services and consume a significant portion of hospital resources for a minority of patients [1]
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to grow across the world, and it is estimated that approximately 15% of patients presenting with SARS-CoV-2 will require ICU admission based on studies from Italy and China [6, 7]
Risk factors for postoperative ICU admission have been identified for several surgeries, including colon cancer surgery [17], lung resection [15], and total joint arthroplasty [18]
Summary
Intensive care units (ICUs) provide a limited number of specialized medical services and consume a significant portion of hospital resources for a minority of patients [1]. Triage of high-risk surgical patients to ICUs may impact the outcomes of those with the highest probability of postoperative complications and deaths [2]. As the frequency of elderly gastric cancer patients with more preexisting comorbidities is increasing [13, 14], the number of patients requiring ICU-specific care may inevitably increase. For many patients who will be undergoing gastrectomy for gastric cancer, postoperative admission to an ICU is only planned for surveillance purposes. We aimed to generate and validate a nomogram to predict patients most likely to require intensive care unit (ICU) admission following gastric cancer surgery to improve postoperative outcomes and optimize the allocation of medical resources
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