Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study

BMC Geriatrics

Table 3 Diagnostic value of BMI, GCA, and skeletal muscle index for predicting low lean mass

Sensitivity, Specificity, Positive and Negative Predictive Values and Receiver Operating Curve Model of the BMI, GCA, L3SMI, MSMI and combination of BMI, GCA and skeletal muscle index (either L3SMI or MSMI).
Variable¹	Sensitivity	Specificity	PPV	NPV	+LR	-LR	Accuracy	SE	AUC (95%CI)
BMI	0.790	0.628	0.722	0.733	2.121	0.335	0.704	0.051	0.777 (0.672, 0.863)
GCA	0.684	0.837	0.788	0.750	4.203	0.377	0.765	0.046	0.820 (0.713, 0.892)
L3SMI	0.622	0.791	0.719	0.708	2.970	0.479	0.713	0.054	0.757 (0.654, 0.851)
MSMI	0.865	0.707	0.844	0.778	2.955	0.191	0.782	0.049	0.827 (0.732, 0.908)
Model 1^a	0.919	0.837	0.829	0.923	5.645	0.097	0.875	0.028	0.926 (0.844, 0.972)
Model 2^b	0.919	0.830	0.853	0.917	6.279	0.095	0.885	0.029	0.931 (0.857,0.979)

Abbreviations: AUC Area under the curve, BMI Body mass index, GCA Global cortical atrophy, L3SMI L3 skeletal muscle index, MSMI Masseter skeletal muscle index, NPV Negative predictive values, PPV Positive predictive values, SE Standard error, +LR Positive likelihood ratio, −LR Negative likelihood ratio
¹Significantly different with all variables (p < 0.05)
^aModel 1: combination of BMI, GCA and L3SMI
^bModel 2: combination of BMI, GCA and MSMI

ISSN: 1471-2318