Skeletal Muscle Mass on Prognosis and Recovery in Clinical Trial

Comprehensive Interpretation of the Importance of Skeletal Muscle Mass on Prognosis and Recovery in Cardiac Arrest Survivors: From Machine Learning to Clinical Trial

The objective of this research project is to develop an automated muscle mass measurement system based on computed tomography (CT) images using deep learning and artificial intelligence, and to construct a prognostic prediction model for patients who have experienced cardiac arrest and undergone resuscitation. The model will be validated using multicenter registry data and medical imaging. Furthermore, a clinical trial involving core muscle rehabilitation for post-resuscitation patients will be conducted to evaluate both short-term and long-term outcomes, aiming to comprehensively understand the impact of muscle mass on the prognosis of patients after cardiac arrest.

Inclusion Criteria:

• Non-traumatic adult patients who experienced sudden cardiac arrest
• Achieved sustained return of spontaneous circulation (ROSC) for more than five minutes following successful resuscitation
• Admitted to the ICU
• Survived beyond 72 hours without successful weaning from mechanical ventilation

Exclusion Criteria:

• Age under 18 years
• Pregnancy
• Expected to be weaned from mechanical ventilation within 48 hours
• Terminal-stage cancer or unwillingness to receive aggressive treatment
• Unavailability of ICU care due to overcrowding in the emergency intensive care unit
• Refusal to participate in the study by the patient or family members
• Presence of an implanted pacemaker or defibrillator
• Open wounds, severe edema, or deep vein thrombosis in the lower limbs
• Pre-arrest status limited to wheelchair use or bedridden, unable to ambulate