Table 1.

Demographics and Comorbidities Added Into a Nonparsimonious Propensity Model to Predict Dialysis at Index Hospitalization^*

	OR	Lower 95% CI	Upper 95% CI	P Value
Male	1.11	1.04	1.18	<0.001
Age (per year)	1.02	1.02	1.02	<0.001
Premorbid risk
Charlson score	1.25	1.21	1.29	<0.001
Congestive heart failure	1.87	1.67	2.08	<0.001
Dementia	0.67	0.54	0.82	<0.001
COPD	0.55	0.50	0.61	<0.001
Rheumatologic disease	2.23	1.73	2.83	<0.001
Hemiplegia	0.69	0.52	0.91	0.009
Tumor	0.82	0.69	0.98	0.030
Diabetes mellitus	2.28	2.10	2.48	<0.001
Moderate or severe liver disease	2.64	2.10	3.28	<0.001
Chronic kidney disease	5.37	4.72	6.11	<0.001
Index hospital comobidity
Respiratory	2.69	2.46	2.94	<0.001
Neurologic	2.41	1.89	3.04	<0.001
Hematologic	2.99	2.30	3.84	<0.001
Metabolic	14.08	11.27	17.51	<0.001
Operative categories
Cardiothoracic	1.23	1.02	1.48	0.027
Upper GI	0.49	0.35	0.67	<0.001
Hepatobiliary	0.56	0.43	0.72	<0.001
ICU admission during index hospitalization	19.79	18.48	21.20	<0.001

The propensity score in an attempt to make an unbiased estimated of all the confounders to balance study and control groups and further add to the Cox regression model. AKI indicates acute kidney injury; COPD, chronic obstructive pulmonary disease; ESRD, end‐stage renal disease; GI, gastrointestinal; ICU, intensive care unit.

^*The propensity model for predicting the need for dialysis during index hospitalization in both groups had a high discrimination power (estimated area under the receiver operating characteristic curve: 0.937), and it fit well with the observed binary data (adjusted generalized R²=0.35).