Predictive modelling for optimization of preoperative care in multimorbid patients undergoing major surgery

Abstract

Introduction: Preoperative optimization programs are effective interventions to improve postoperative outcomes in patients undergoing major surgery. However, customization of these programs to multimorbid patients’ is an unmet need. The current study aims to identify factors associated to program completion, and to postoperative complications, in multimorbid patients undergoing major surgery.

Methods: Inclusion criteria: 1) Undergoing to major surgery; 2) high-risk for surgical complications defined by age≥ 70 and/or American Society of Anesthesiologists risk scale 3-4. The program included 6 interventions: 1) Cardiorespiratory training; 2) Promotion of physical activity; 3) Volumetric inspirometer teaching; 4) Cognitive behavioural therapy; 5) Nutritional optimization; 6) Mindfulness. Program completion was defined as attending ≥80% of appointments.

Results: From 200 patients, 120 (60%) completed the program. Among completers, 62 did not suffer from postoperative complications (52%). Undergoing oncologic surgery (24.5[3.9-153.8];p=0.001), suffering from endocrine and metabolic diseases (3.8[1.2-12.3];p=0.025) and willingness to participate in mindfulness sessions (3.1[1.03-9.15];p=0.044) were associated with program completion, while being older (0.93[0.88-0.97];p=0.002) was related to lower probability of completion. Among completers, higher baseline fitness (Duke Activity Status Index) (0.95[0.91-0.999];p=0.019) and higher risk of malnutrition (Malnutrition Universal Screening Tool) (1.8[1.1-3.1];p=0.023) were related to postoperative morbidity.

Conclusions: The current study identifies actionable factors useful to personalize these programs which may facilitate its effectiveness.