Predictors of Prolonged Length of Stay After Pituitary Adenoma Resection: A Large Cohort Analysis Using the National...

In this nationwide retrospective study, the authors aimed to identify demographic, clinical, and baseline health risk factors predictive of a prolonged length of stay (PLOS) for patients with pituitary adenomas (PAs).

The National Inpatient Sample dataset from 2016 to 2019 was utilized to identify all included hospitalizations for PA resection as identified by the appropriate diagnosis-related group code. Comorbidities were classified based on the Charlson Comorbidity Index mapping of ICD-10 codes, and PLOS was identified as any stay longer than 3 days. Univariable and multivariable logistic regression models, accounting for the sample design, were built to determine factors associated with PLOS and emergent surgery.

Overall, 30 945 patients were included in this study with 10 535 patients having PLOS. Female patients experienced an increased odds of PLOS (odds ratio [OR]: 1.29; P < .001). Black patients (OR: 1.49; P < .001) and Hispanic patients (OR: 1.30; P = .003) had 1.49 times and 1.30 times the odds of PLOS compared to White patients, respectively. Compared to patients insured by Medicare, patients insured by Medicaid had an increased odds of PLOS (OR: 1.36; P = .007) as well as emergent surgery (OR: 5.40; P < .001). When stratified by emergent surgeries, Black patients (OR: 1.89; P < .001), Hispanic patients, (OR: 2.14; P < .001), and patients on Medicaid insurance (OR: 1.71; P < .001) were at an increased risk of emergent procedures. However, female sex (OR: 0.65; P < .001), upper third quartile (OR: 0.73; P = .017), and fourth quartile (OR: 0.69; P = .014) of patients categorized by zip code income were at decreased odds of an emergent procedure.

Black and Hispanic patients, patients with Medicaid insurance, and patients of low socioeconomic status patients are at significantly higher risk of emergent PA resection and PLOS. Efforts to prevent emergent surgeries and shorten hospitalization after pituitary surgery may need to primarily focus on patient groups with select sociodemographic characteristics.