Risk Prediction Model for Older Adults Undergoing Noncardiac Surgery

Development of a Surgical Risk Prediction Model for Older Adults Undergoing Major Noncardiac Surgery: A Prospective Cohort Study

This prospective observational study aims to develop and evaluate predictive models for postoperative complications in patients aged 65 years or older scheduled for elective major surgery. The investigators will recruit 520 eligible patients visiting the preoperative assessment clinic.

The study involves the prospective collection of comprehensive preoperative data using specific validated tools:

• Physical Activity: Assessed using the Saltin-Grimby Physical Activity Scale (SGPAS) to categorize physical activity intensity.
• Nutritional Risk: Screened using the Nutritional Risk Screening 2002 (NRS-2002) tool.
• Psychological Status: Evaluated for anxiety and depression using the Hospital Anxiety and Depression Scale (HADS).
• Body Composition: Measured using a portable bioelectrical impedance analysis (BIA) device (BWA2.0S, InBody) to assess muscle mass, body fat/water, and phase angle.
• Physical Function: Assessed via the short physical performance battery (SPPB) using electronic measurement devices (AndanteFit, DYPHI) to calculate frailty index and physical age.

The primary endpoint is the occurrence and severity of postoperative complications within 30 days, evaluated using both the Clavien-Dindo Classification and the Comprehensive Complication Index (CCI). Using the collected dataset, the investigators will develop prediction models using both classical regression analysis and machine learning algorithms to compare their predictive performance.

Inclusion Criteria:

• Patients aged 65 years or older scheduled for elective surgery who visit the preoperative assessment clinic.
• Patients scheduled for major non-cardiac surgery.
• Patients who voluntarily provide written informed consent.

Exclusion Criteria:

• Patients unable to communicate.
• Patients unable to complete questionnaires or perform physical function tests.
• Patients with implanted electronic medical devices, such as cardiac pacemakers or implantable patient monitoring devices.
• Patients whose scheduled surgery is cancelled.
• Patients with underlying medical or psychiatric conditions that may affect the study outcomes.
• Any other reason that, in the opinion of the investigator, makes the patient unsuitable for participation.