Prediction of Postoperative ICU Requirement in Oncologic Surgery

Comparison of ASA, SORT, CACI, and P-POSSUM Scores for Predicting Postoperative Intensive Care Unit Requirement in Patients Undergoing Oncologic Surgery

This prospective observational cohort study aims to compare the performance of commonly used perioperative risk scoring systems in predicting postoperative intensive care unit (ICU) requirement among adult patients undergoing oncologic surgery. Accurate prediction of postoperative ICU admission is essential for optimizing patient safety and efficient allocation of limited critical care resources, particularly in high-risk oncologic surgical populations.

A total of 500 adult patients scheduled for elective or emergency oncologic surgery will be prospectively enrolled at a single tertiary oncology center. Preoperative clinical and demographic data, intraoperative variables, and perioperative characteristics will be recorded using a standardized data collection form. Risk assessment will include the American Society of Anesthesiologists (ASA) Physical Status classification, Surgical Outcome Risk Tool (SORT), Age-adjusted Charlson Comorbidity Index (CACI), Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (P-POSSUM), Eastern Cooperative Oncology Group (ECOG) performance status, Nutritional Risk Screening 2002 (NRS-2002), and preoperative serum albumin levels.

The primary outcome is the need for postoperative ICU admission within the first 24 hours after surgery. Secondary outcomes include unplanned ICU admission, duration of ICU stay, need for mechanical ventilation, hospital length of stay, and 30-day mortality. The predictive performance of each scoring system will be evaluated using receiver operating characteristic (ROC) analysis and multivariable logistic regression models.

Postoperative intensive care unit (ICU) admission represents a critical component of perioperative management, particularly in patients undergoing oncologic surgery who frequently present with advanced age, multiple comorbidities, impaired functional capacity, and increased perioperative risk. Accurate preoperative identification of patients requiring postoperative critical care is essential to improve patient outcomes, optimize perioperative planning, and ensure appropriate allocation of limited ICU resources.

Several perioperative risk assessment tools are routinely used in clinical practice, including the American Society of Anesthesiologists (ASA) Physical Status classification, the Surgical Outcome Risk Tool (SORT), and the Age-adjusted Charlson Comorbidity Index (CACI). However, comparative prospective evidence regarding their ability to predict postoperative ICU requirement remains limited. The Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (P-POSSUM), which incorporates both physiological and operative variables, may provide additional prognostic value beyond traditional preoperative scoring systems. Furthermore, functional status and nutritional condition are increasingly recognized as important determinants of surgical outcomes in oncology patients. Therefore, inclusion of Eastern Cooperative Oncology Group (ECOG) performance status, Nutritional Risk Screening 2002 (NRS-2002), and preoperative serum albumin levels may enhance predictive accuracy.

This study is designed as a single-center prospective observational cohort study enrolling adult patients undergoing elective or emergency oncologic surgery. Eligible patients aged 18 years or older will be consecutively included and followed throughout the perioperative period. Preoperative demographic and clinical characteristics, intraoperative variables, and perioperative management data will be recorded using a standardized data collection system.

The primary objective of the study is to evaluate and compare the predictive performance of ASA, SORT, CACI, P-POSSUM, ECOG performance status, and NRS-2002 scores for postoperative ICU requirement within the first 24 hours after surgery. Secondary objectives include assessment of unplanned ICU admission, mechanical ventilation requirement, ICU length of stay, hospital length of stay, and 30-day mortality.

Predictive performance will be evaluated using receiver operating characteristic (ROC) curve analysis with calculation of area under the curve (AUC) values. Differences between scoring systems will be assessed using appropriate statistical comparison methods, and multivariable logistic regression analysis will be performed to determine independent predictors of postoperative ICU requirement while adjusting for potential confounding variables.

The findings of this study are expected to support evidence-based perioperative risk stratification and contribute to improved clinical decision-making regarding postoperative critical care planning in oncologic surgical patients.

Inclusion Criteria:

• Patients aged 18 years and older.
• Patients scheduled for elective or emergency oncologic surgery.
• Patients who are able to provide written informed consent.
• Patients whose data will be analyzed for both planned and unplanned intensive care unit (ICU) admissions.

Exclusion Criteria:

• Patients under 18 years of age.
• Patients requiring continuous ICU follow-up due to a pre-existing critical illness prior to the current surgery.
• Patients who do not provide consent to participate in the study.