Table 6.

Results of linear regression analysis between predicted and observed BMI 1 year after surgery for prediction models in SG group

Model	B	95% CI	p-value	R	R2	adjusted R2	SE	RMSE
Baltasar_1	1.22	1.00–1.44	<0.0001	0.44	0.19	0.19	5.31	5.30
Baltasar_2	1.00	0.82–1.19	<0.0001	0.44	0.19	0.19	5.31	5.30
Baltasar_3	0.21	0.17–0.24	<0.0001	0.44	0.19	0.19	5.49	5.49
Baltasar_4	0.93	0.77–1.10	<0.0001	0.44	0.19	0.19	5.31	5.30
Wood	0.58	0.48–0.69	<0.0001	0.45	0.20	0.20	5.28	5.27
Wise	0.29	0.23–0.34	<0.0001	0.41	0.17	0.17	5.39	5.38
Goulard	0.63	0.52–0.73	<0.0001	0.46	0.21	0.21	5.24	5.23
Seyssel	0.70	0.58–0.81	<0.0001	0.48	0.23	0.23	5.19	5.18
Cottam 1	0.56	0.46–0.66	<0.0001	0.45	0.20	0.20	5.29	5.27
Cottam 2	0.51	0.42–0.60	<0.0001	0.45	0.20	0.20	5.27	5.26
Janik	0.51	0.43–0.59	<0.0001	0.48	0.23	0.23	5.18	5.17
Velázquez-Fernández	0.67	0.55–0.79	<0.0001	0.45	0.20	0.20	5.27	5.26

p-value refers to linear regression coefficient

Embolden p-values indicate statistically significant result

Abbreviations: B regression coefficient, 95% CI, 95% confidence interval, R Pearson’s correlation coefficient, SE standard error of the estimate, RMSE root mean square error