Simple bedside tests of muscle strength and function correlate with computed tomography-skeletal muscle index for assessment of sarcopenia in cirrhosis

BACKGROUND

Sarcopenia assessment can be done by skeletal muscle index (SMI) or bedside tests such as handgrip strength (HGS) and gait speed (GS).

GOALS

This study evaluated the correlations of HGS and GS with SMI, health-related quality of life (HRQOL) and cognition and assessed them as predictors of mortality.

STUDY

As many as 116 outpatients with cirrhosis were included in this prospective cohort study. Assessment for sarcopenia was done by SMI, HGS and GS. HRQOL was assessed using the chronic liver disease questionnaire (CLDQ) and fatigue severity scale (FSS). Cognition was assessed by mini-mental state examination (MMSE). Correlations of HGS and GS with SMI, HRQOL and cognition were analyzed. Area under the curve (AUCs) were calculated to compare them as predictors of mortality.

RESULTS

Alcoholic liver disease (47.4%) was the commonest etiology of cirrhosis followed by hepatitis C (12.9%). Sarcopenia was diagnosed in 64 (55.2%) patients. A strong correlation was seen between SMI and HGS (ρ = 0.78) and GS (ρ = 0.65). AUCs of GS (0.91 (95% confidence interval [CI], 0.85-0.96) was maximum, followed by HGS (95% CI, 0.86 [0.78-0.93] and SMI [95% CI, 0.8 0.71-0.88]) in predicting mortality (p > 0.05). CLDQ (3.2 vs. 5.6, p < 0.01) and MMSE scores (24.3 vs. 26.3, p < 0.01) were lower, whereas FSS score (5.7 vs. 3.1, p < 0.01) was higher in patients with sarcopenia. CLDQ (ρ = 0.83) and MMSE (ρ = 0.73) showed the strongest correlation with HGS, whereas FSS correlated well (ρ = 0.77) with GS.

CONCLUSIONS

Bedside tests of muscle strength and function, including HGS and GS, correlate strongly with SMI for sarcopenia assessment and prediction of mortality in patients with cirrhosis.

Clinical performance of lung ultrasound in predicting ARDS morphology

Background

To assess diagnostic performance of lung ultrasound (LUS) in identifying ARDS morphology (focal vs non-focal), compared with the gold standard computed tomography.

Methods

Mechanically ventilated ARDS patients undergoing lung computed tomography and ultrasound were enrolled. Twelve fields, were evaluated. LUS score was graded from 0 (normal) to 3 (consolidation) according to B-lines extent. Total and regional LUS score as the sum of the four ventral (LUS_V), intermediate (LUS_I) or dorsal (LUS_D) fields, were calculated. Based on lung CT, ARDS morphology was defined as (1) focal (loss of aeration with lobar distribution); (2) non-focal (widespread loss of aeration or segmental loss of aeration distribution associated with uneven lung attenuation areas), and diagnostic accuracy of LUS in discriminating ARDS morphology was determined by AU-ROC in training and validation set of patients.

Results

Forty-seven patients with ARDS (25 training set and 22 validation set) were enrolled. LUS_TOT, LUS_V and LUS_I but not LUS_D score were significantly lower in focal than in non-focal ARDS morphologies (p < .01). The AU-ROC curve of LUS_TOT, LUS_V, LUS_I and LUS_D for identification of non-focal ARDS morphology were 0.890, 0.958, 0.884 and 0.421, respectively. LUS_V value ≥ 3 had the best predictive value (sensitivity = 0.95, specificity = 1.00) in identifying non-focal ARDS morphology. In the validation set, an LUS_V score ≥ 3 confirmed to be highly predictive of non-focal ARDS morphology, with a sensitivity and a specificity of 94% and 100%.

Conclusions

LUS had a valuable performance in distinguishing ARDS morphology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00837-1.