Conclusions There is considerable variability in the type of measures utilized to measure physical impairments and limitations in survivors of critical illness .
Purpose To identify measures used to evaluate the broad constructs of functional impairment and limitations in the critically ill across the continuum of recovery , and to evaluate , synthesis e and compare the clinimetric properties of the measures identified .
Assessment of body cell mass at bedside in critically ill patients.
Critical illness affects body composition profoundly , especially body cell mass ( BCM ) . BCM loss reflects lean tissue wasting and could be a nutritional marker in critically ill patients . However , BCM assessment with usual isotopic or tracer methods is impractical in intensive care units ( ICUs ) . We aim ed to modelize the BCM of critically ill patients using variables available at bedside . Fat-free mass ( FFM ) , bone mineral ( Mo ) , and extracellular water ( ECW ) of 49 critically ill patients were measured prospect ively by dual-energy X-ray absorptiometry and multifrequency bioimpedance .  BCM was estimated according to the four-compartment cellular level : BCM = FFM - ( ECW/0.98 ) - ( 0.73 × Mo ) . Variables that might influence the BCM were assessed , and multivariable analysis using fractional polynomials was conducted to determine the relations between BCM and these data . Bootstrap resampling was then used to estimate the most stable model predicting BCM . BCM was 22.7 ± 5.4 kg . The most frequent model included height ( cm ) , leg circumference ( cm ) , weight shift ( Δ ) between ICU admission and body composition assessment ( kg ) , and trunk length ( cm ) as a linear function : BCM ( kg ) = 0.266 × height + 0.287 × leg circumference + 0.305 × Δweight - 0.406 × trunk length - 13.52 . The fraction of variance explained by this model ( adjusted r(2 ) ) was 46 % . Including bioelectrical impedance analysis variables in the model did not improve BCM prediction . In summary , our results suggest that BCM can be estimated at bedside , with an error lower than ±20 % in 90 % subjects , on the basis of static ( height , trunk length ) , less stable ( leg circumference ) , and dynamic biometric variables ( Δweight ) for critically ill patients
Conclusions There is considerable variability in the type of measures utilized to measure physical impairments and limitations in survivors of critical illness .
Purpose To identify measures used to evaluate the broad constructs of functional impairment and limitations in the critically ill across the continuum of recovery , and to evaluate , synthesis e and compare the clinimetric properties of the measures identified .