Machine Learning Prediction of Respiratory Muscle Changes and Ventilatory Responses After Incretin-Based Therapy in Obesity

Prediction of Changes in Pulmonary Function, Respiratory Muscle Performance, and Ventilatory Responses Following Incretin-Based Therapy in Individuals With Obesity Using Machine Learning

This study aims to evaluate changes in respiratory function, respiratory muscle performance, and ventilatory responses following incretin-based therapy in individuals with obesity, and to identify predictors of these changes through the application of machine learning methods.

Inclusion Criteria:

• Individuals aged 25-60 years
• Individuals with a body mass index (BMI) ≥ 30 kg/m² according to the World - Health Organization (WHO) classification of obesity
• Individuals who voluntarily agree to participate in the study

Exclusion Criteria:

Charlson Comorbidity Index (CCI) score ≥ 3 Uncontrolled arrhythmia, hypertension, heart failure, diabetes mellitus, or unstable angina pectoris Cognitive, orthopedic, or neurological conditions that may interfere with study assessments or treatment procedures History of lower extremity injury or surgery within the previous 6 months Diagnosis of diabetes mellitus with complications such as nephropathy, retinopathy, or neuropathy Presence of chronic respiratory disease Acute infection at the time of assessment Middle ear pathologies (e.g., tympanic membrane rupture or otitis) History of spontaneous or traumatic pneumothorax Current smoking Pregnancy STOP-Bang score ≥ 3 Participation in a structured weight-loss diet program or receipt of medical treatment for weight reduction during the assessment period History of endoscopic weight-loss procedures and/or bariatric surgery within the previous 12 months