Table 3.

Predictors of Hospital LOS following Periprosthetic Hip Fracture

Predictor	Change in LOS (%)	95% CI	P-value
Race
Black	9.1	4.3-13.9	<0.001
Comorbidity
Paralysis	35.4	24.1-46.6	<0.001
Fluid and electrolyte disorders	30.6	28.4-32.7	<0.001
Weight loss	25.9	22.1-29.7	<0.001
Blood loss anemia	21.5	14.2-28.7	<0.001
Psychoses	21.2	11.7-30.7	<0.001
Metastatic cancer	20.9	11.0-30.7	<0.001
Neurological disorders	18.1	15.1-21.0	<0.001
Obesity	13.8	11.0-16.7	<0.001
Pulmonary circulation disorders	13.6	8.8-18.5	<0.001
Coagulopathy	13.5	9.7-17.2	<0.001
Lymphoma	13.2	1.9-24.5	0.027
Liver disease	12.8	7.0-18.6	<0.001
Congestive heart failure	12.2	8.7-15.6	<0.001
Cardiac arrhythmias	10.3	8.1-12.5	<0.001
Deficiency anemia	9.8	5.6-14.0	<0.001
Drug abuse	9.5	3.4-15.6	0.003
Renal failure	5.5	1.8-9.2	0.005
Primary payment source
Other	12.9	5.7-20.0	<0.001
Medicaid	9.3	3.8-14.8	0.001
Median income quartile
1	4.4	1.5-7.3	0.003
2	3.6	0.9-6.3	0.010
Hospital bed size
Medium	3.6	0.8-6.5	0.013
Large	12.8	10.1-15.4	<0.001
Hospital type
Urban teaching	6.3	2.3-10.3	0.002

Data derived from the NIS (National Inpatient Sample).

All adult patients diagnosed with a hip periprosthetic fracture between 2016 and 2019 were included.

Linear regression was used with hospital length of stay as the outcome variable. The length of stay was log-transformed prior to analysis and reversed for interpretation. Only statistically significant variables (P<0.05) are shown in the table. In addition to significant predictors, the final model included admission day, sex, and comorbidities, including AIDS, alcohol abuse, chronic pulmonary disease, depression, diabetes, hypertension, peptic ulcer disease, peripheral vascular disease, solid tumor, and valvular disease.

Reference variables were white race, absence of comorbidity, Medicare as a primary payment source, fourth median income quartile, small hospital bed size, and rural hospital type.

LOS: length of stay, CI: confidence interval.