The role of anticoagulation for superior sagittal sinus thrombosis following craniotomy for resection of parasagittal/parafalcine meningiomas.

OBJECTIVE: The safety and efficacy of anticoagulation in managing superior sagittal sinus (SSS) thrombosis remains unclear. The present study investigated the relationship between anticoagulation and cerebrovascular complications in parasagittal/parafalcine meningioma patients presenting with post-surgical SSS thrombosis. METHODS: We analyzed 266 patients treated at a single institution between 2005 and 2020. Bivariate analysis was conducted using the Mann-Whitney U test and Fisher's exact test. Multivariate analysis was conducted using a logistic regression model. Blood thinning medications investigated included aspirin, warfarin, heparin, apixaban, rivaroxaban, and other novel oral anticoagulants (NOACs). A symptomatic SSS thrombosis was defined as a radiographically apparent thrombosis with new headaches, seizures, altered sensorium, or neurological deficits. RESULTS: Our patient cohort was majority female (67.3%) with a mean age ([Formula: see text] SD) of 58.82 [Formula: see text] 13.04 years. A total of 15 (5.6%) patients developed postoperative SSS thrombosis and 5 (1.9%) were symptomatic; 2 (0.8%) symptomatic patients received anticoagulation. None of these 15 patients developed cerebrovascular complications following observation or anticoagulative treatment of asymptomatic SSS thrombosis. While incidence of any other postoperative complications was significantly associated with SSS thrombosis in bivariate analysis (p = 0.015), this association was no longer observed in multivariate analysis (OR = 2.15, p = 0.16) when controlling for patient age, sex, and anatomical location of the tumor along the SSS. CONCLUSIONS: Our single-institution study examining the incidence of SSS thrombosis and associated risk factors highlights the need for further research efforts better prognosticate this adverse outcome. Conservative management may represent a viable treatment strategy for patients with SSS thrombosis.

A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors.

PURPOSE: Establishing predictors of hospital length of stay (LOS), discharge deposition, and total hospital charges is essential to providing high-quality, value-based care. Though previous research has investigated these outcomes for patients with metastatic brain tumors, there are currently no tools that synthesize such research findings and allow for prediction of these outcomes on a patient-by-patient basis. The present study sought to develop a prediction calculator that uses patient demographic and clinical information to predict extended hospital length of stay, non-routine discharge disposition, and high total hospital charges for patients with metastatic brain tumors. METHODS: Patients undergoing surgery for metastatic brain tumors at a single academic institution were analyzed (2017-2019). Multivariate logistic regression was used to identify independent predictors of extended LOS (> 7 days), non-routine discharge, and high total hospital charges (> $ 46,082.63). p < 0.05 was considered statistically significant. C-statistics and the Hosmer-Lemeshow test were used to assess model discrimination and calibration, respectively. RESULTS: A total of 235 patients were included in our analysis, with a mean age of 62.74 years. The majority of patients were female (52.3%) and Caucasian (76.6%). Our models predicting extended LOS, non-routine discharge, and high hospital charges had optimism-corrected c-statistics > 0.7, and all three models demonstrated adequate calibration (p > 0.05). The final models are available as an online calculator ( https://neurooncsurgery.shinyapps.io/brain_mets_calculator/ ). CONCLUSIONS: Our models predicting postoperative outcomes allow for individualized risk-estimation for patients following surgery for metastatic brain tumors. Our results may be useful in helping clinicians to provide resource-conscious, high-value care.

Predicting High-Value Care Outcomes After Surgery for Skull Base Meningiomas.

BACKGROUND: Although various predictors of adverse postoperative outcomes among patients with meningioma have been established, research has yet to develop a method for consolidating these findings to allow for predictions of adverse health care outcomes for patients diagnosed with skull base meningiomas. The objective of the present study was to develop 3 predictive algorithms that can be used to estimate an individual patient's probability of extended length of stay (LOS) in hospital, experiencing a nonroutine discharge disposition, or incurring high hospital charges after surgical resection of a skull base meningioma. METHODS: The present study used data from patients who underwent surgical resection for skull base meningiomas at a single academic institution between 2017 and 2019. Multivariate logistic regression analysis was used to predict extended LOS, nonroutine discharge, and high hospital charges, and 2000 bootstrapped samples were used to calculate an optimism-corrected C-statistic. The Hosmer-Lemeshow test was used to assess model calibration, and P < 0.05 was considered statistically significant. RESULTS: A total of 245 patients were included in our analysis. Our cohort was mostly female (77.6%) and white (62.4%). Our models predicting extended LOS, nonroutine discharge, and high hospital charges had optimism-corrected C-statistics of 0.768, 0.784, and 0.783, respectively. All models showed adequate calibration (P>0.05), and were deployed via an open-access, online calculator: https://neurooncsurgery3.shinyapps.io/high_value_skull_base_calc/. CONCLUSIONS: After external validation, our predictive models have the potential to aid clinicians in providing patients with individualized risk estimation for health care outcomes after meningioma surgery.

Predictors of Nonroutine Discharge Disposition Among Patients with Parasagittal/Parafalcine Meningioma.

OBJECTIVE: Discharge disposition is an important outcome for neurosurgeons to consider in the context of high-quality, value-based care. There has been limited research into how the unique anatomic considerations associated with parasagittal/parafalcine meningioma resection may influence discharge disposition. We investigated the effects of various predictors on discharge disposition within a cohort of patients with parasagittal/parafalcine meningioma. METHODS: A total of 154 patients treated at a single institution were analyzed (2016-2019). Bivariate analysis was conducted using the Mann-Whitney U and Fisher exact tests. Multivariate analysis was conducted using logistic regression. An optimism-corrected C-statistic was calculated using 2000 bootstrap samples to assess logistic regression model performance. RESULTS: Our cohort was mostly female (67.5%) and white (72.7%), with a mean age of 57.29 years. Most patients had tumors associated with the middle third of the superior sagittal sinus (SSS) (60.4%) and had tumors that were not fully occluding the SSS (74.0%). In multivariate analysis, independent predictors of nonroutine discharge disposition included 5-factor Modified Frailty Index score (odds ratio [OR], 2.06; P = 0.0088), Simpson grade IV resection (OR, 4.22; P = 0.0062), and occurrence of any postoperative complication (OR, 2.89; P = 0.031). The optimism-corrected C-statistic of our model was 0.757. CONCLUSIONS: In our single-institution experience, neither extent of SSS invasion nor location along the SSS predicted nonroutine discharge, suggesting that tumor invasion and posterior location along the SSS are not necessarily contraindications to surgery. Our results also highlight the importance of frailty and tumor size in stratifying patients at risk of nonroutine discharge disposition.