Table 5.

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

Model	B	95% CI	p-value	R	R2	adjusted R2	SE	RMSE
Baltasar_1	1.21	0.95–1.47	<0.0001	0.49	0.24	0.24	4.72	4.71
Baltasar_2	1.00	0.78–1.22	<0.0001	0.49	0.24	0.24	4.72	4.71
Baltasar_3	0.93	0.73–1.13	<0.0001	0.49	0.24	0.24	4.72	4.71
Baltasar_4	0.93	0.73–1.13	<0.0001	0.49	0.24	0.24	4.72	4.71
Wood	0.57	0.45–0.69	<0.0001	0.49	0.24	0.24	4.72	4.71
Wise	0.29	0.22–0.35	<0.0001	0.45	0.20	0.20	4.84	4.82
Goulard	0.59	0.45–0.72	<0.0001	0.47	0.22	0.22	4.78	4.76
Seyssel	0.66	0.52–0.80	<0.0001	0.50	0.25	0.25	4.70	4.69
Cottam 1	0.56	0.42–0.69	<0.0001	0.46	0.21	0.21	4.82	4.80
Cottam 2	0.50	0.38–0.61	<0.0001	0.47	0.22	0.22	4.79	4.77
Janik	0.50	0.39–0.61	<0.0001	0.49	0.24	0.24	4.72	4.71
Velázquez-Fernández	0.66	0.52–0.81	<0.0001	0.50	0.25	0.25	4.70	4.68

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