GNRI and Rectus Femoris Muscle Thickness in Older Patients Undergoing Hip Fracture Surgery

Overview

This prospective observational study will evaluate whether nutritional risk and reduced muscle mass are associated with postoperative outcomes in adults aged 65 years or older undergoing surgery for hip fracture. Nutritional risk will be assessed using the Geriatric Nutritional Risk Index (GNRI), which is calculated from routine preoperative serum albumin, body weight, and ideal body weight. Rectus femoris muscle thickness will be measured before surgery using a brief, noninvasive ultrasound examination of the non-fractured thigh. Participants will receive routine clinical care, and no treatment or anesthesia method will be assigned by the study. Clinical information will be collected from hospital records, including postoperative length of hospital stay, surgical site infection, and mortality. Survival status will be evaluated at 30 and 90 days after surgery using hospital records and/or telephone follow-up.

This is a single-center, prospective observational cohort study involving consecutive patients aged 65 years or older who are scheduled to undergo surgical treatment for hip fracture at Fatih Sultan Mehmet Training and Research Hospital. The study will investigate the prognostic value of the Geriatric Nutritional Risk Index (GNRI) and ultrasonographic rectus femoris muscle thickness (RF-MT) for postoperative clinical outcomes. After informed consent is obtained, demographic and preoperative clinical data will be recorded, including age, sex, height, weight, body mass index, comorbidities, American Society of Anesthesiologists physical status, fracture type, serum albumin, hemoglobin, C-reactive protein, and creatinine. The GNRI will be calculated using the following formula: GNRI = \[1.489 × serum albumin (g/L)\] + \[41.7 × current body weight/ideal body weight\]. When the ratio of current body weight to ideal body weight is greater than 1, the ratio will be set to 1. Participants will be classified according to the original GNRI categories: no nutritional risk (GNRI greater than 98), low nutritional risk (GNRI 92 to 98), and moderate or severe nutritional risk (GNRI less than 92). Rectus femoris muscle thickness will be measured preoperatively on the non-fractured side using a high-frequency linear ultrasound probe. The measurement will be performed with the participant in the supine position at the midpoint between the anterior superior iliac spine and the upper border of the patella. Minimal probe pressure will be applied to avoid muscle compression. After the rectus femoris muscle is visualized in the transverse plane, muscle thickness will be measured as the greatest vertical distance between the superficial and deep fascia. Three measurements will be obtained, and their mean value will be used for analysis. All measurements will be performed by the same investigator experienced in ultrasonography. Perioperative and postoperative data will include surgical procedure, anesthesia technique, duration of surgery, estimated blood loss, blood transfusion, intensive care unit admission, postoperative hospital length of stay, surgical site infection, and all-cause mortality at 30 and 90 days. Postoperative hospital length of stay will be calculated as the number of days between surgery and hospital discharge. Prolonged postoperative hospital stay will be defined as a stay exceeding the 75th percentile of postoperative length of stay in the completed study cohort. Surgical site infections will be evaluated according to the Centers for Disease Control and Prevention criteria. Mortality status will be determined from hospital records and/or telephone follow-up. No study-specific medication, anesthesia technique, surgical treatment, or additional blood sampling will be administered. The only study-specific procedure will be the noninvasive preoperative ultrasound measurement. Associations between GNRI, RF-MT, and postoperative outcomes will be evaluated using multivariable regression and receiver operating characteristic curve analyses.