Predictors of Nonroutine Discharge Disposition Among Parasagittal/Parafalcine Meningioma Patients

2020 
Abstract 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 anatomical considerations associated with parasagittal/parafalcine meningioma resection may influence discharge disposition. We investigated the effects of various predictors upon discharge disposition within a cohort of parasagittal/parafalcine meningioma patients. Methods 154 patients treated at a single institution were analyzed (2016-2019). Bivariate analysis was conducted using the Mann-Whitney U and Fisher’s 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 majority female (67.5%) and Caucasian (72.7%), with a mean age of 57.29 years. The majority of 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 mFI-5 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.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    29
    References
    3
    Citations
    NaN
    KQI
    []