Abstract
Background:
Bedside ultrasound is increasingly utilized to assess muscle mass in critically ill patients, providing a noninvasive and real-time tool for early risk stratification. Muscle wasting is known to be associated with adverse outcomes in septic shock, but its prognostic value using ultrasound in this population remains underexplored. This study aimed to investigate the association between changes in rectus femoris cross-sectional area (CSA), assessed by bedside ultrasound, and 28-day mortality in patients with septic shock.
Methods:
This prospective observational study enrolled adult patients (≥18 years) with septic shock admitted to the intensive care unit (ICU), diagnosed according to Sepsis-3 criteria. Ultrasound assessments of rectus femoris CSA were performed at baseline (day 0), day 4, and day 7 using a linear transducer. The primary outcome was 28-day mortality. Percentage change in CSA was calculated, and its association with mortality was evaluated using multivariable logistic regression and receiver operating characteristic (ROC) analysis.
Results:
A total of 116 patients were included. The 28-day mortality rate was 20.7%. Rectus femoris CSA decreased significantly over time, with a median reduction of −0.35 cm² (IQR: −0.62 to −0.21) by day 7. The percentage decrease in CSA was significantly greater in non-survivors at both day 4 (−10.0% vs −8.5%, P = .041) and day 7 (−15.4% vs −13.5%, P = .044). In multivariable analysis, percentage CSA loss at day 7 was independently associated with 28-day mortality (OR 0.94, 95% CI 0.88-0.99, P = .036). ROC analysis yielded an area under the curve (AUC) of 0.65 (95% CI 0.52-0.78) for %CSA reduction at day 7, with a −15.28% cut-off showing 66.7% sensitivity and 61.9% specificity.
Conclusions:
Serial ultrasound assessment of rectus femoris CSA is a feasible and reproducible method for monitoring muscle wasting in septic shock. While the predictive performance was modest, serial ultrasound measurements may serve as a valuable adjunct in early mortality risk stratification in critically ill patients.
Keywords
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