Risk factors associated with delayed discharge following robotic assisted surgery for gynecologic malignancy.

BACKGROUND: The risk factors for extended length of stay (LOS) have not been examined in a cohort of patients with complex social and medical barriers who undergo robotic assisted (RA) surgery for gynecologic malignancies. We sought to identify those patients with a LOS > 24 h after robotic surgery and the risk factors associated with delayed discharge. Then we aimed to develop a predictive model for clinical care and identify modifiable pre-operative risk factors. METHODS: After IRB approval, data was abstracted from medical records of all patients with a gynecologic malignancy who underwent a RA laparoscopic surgery from 2010 to 2015. Univariable and multivariable logistic regression was performed to identify independent risk factors associated with delayed discharge defined as LOS > 24 h. A multi-variable logistic regression model was performed using a stepwise backward selection for the final prediction model. All testing was two-sided and a p-value < 0.05 was considered statistically significant. RESULTS: Of the 406 eligible and evaluable patients, 194 (48%) had a LOS > 24 h. Age ≥ 60 years, a higher usage of narcotic medication, a longer surgical time, and a larger estimated blood loss were all associated with LOS > 24 h (p < 0.05). Many of these women had a social work consultation and went home with home care services despite no surgical or post-operative complications. Our prediction model has the potential to correctly classified 75% of the patients discharged within 24 h. CONCLUSIONS: The development of a pre-hospitalization risk stratification and anticipating the possible need for home care services pre-operatively shows promise as a strategy to decrease LOS in patients classified as high-risk. These findings warrant prospective validation through the use of this prediction model in our institution.

Insulin-like growth factor 2: a poor prognostic biomarker linked to racial disparity in women with uterine carcinosarcoma.

The objective of this study was to investigate the relationship of insulin-like growth factor 2 (IGF2) expression and survival in women with uterine carcinosarcoma (UCS). Insulin-like growth factor 2 protein expression was determined by immunohistochemical staining of tumor tissues from 103 patients with UCS. The H-score (product of staining intensity and percentage positive cells) was quantified for the epithelial cytoplasmic (EC), epithelial nuclear (EN), and malignant stromal compartments. Multivariable Cox proportional hazard regression models were used to examine the relationship of IGF2 levels with progression-free survival (PFS) and overall survival (OS). Adjusting for stage, race, and adjuvant therapy, PFS and OS were reduced in patients with high IGF2 (H-score ≥ median) in the EC and EN compartments. Black race was independently associated with reduced PFS and OS in patients with early-stage disease, and IGF2 levels in the EC were higher in black than in white patients (P = 0.02, Wilcoxon test). In a race-stratified multivariable analysis, high IGF2 in the epithelial compartments more than doubled the risk of death in black women; HR = 2.43 (95% CI: 1.18-5.01, P = 0.02) for high IGF2 in the EC; and HR = 2.34 (95% CI: 1.25-4.39, P = 0.008) for high IGF2 in the EN. In conclusion, high tumor IGF2 expression is an independent risk factor for reduced PFS and OS in UCS. Black women have elevated tumor IGF2 compared with white women, and decreased survival associated with high IGF2. These findings identify IGF2 as a candidate biomarker for survival linked to racial disparity in women with UCS.