BackgroundStroke patients requiring decompressive craniectomy are at high risk of prolonged mechanical ventilation and ventilator-associated pneumonia (VAP). Tracheostomy placement may reduce the duration of mechanical ventilation. Predicting which patients will require tracheostomy and the optimal timing of tracheostomy remains a clinical challenge. In this study, the authors compare key outcomes after early versus late tracheostomy and develop a useful pre-operative decision-making tool to predict post-operative tracheostomy dependence.MethodsWe performed a retrospective analysis of prospectively collected registry data. We developed a propensity-weighted decision tree analysis to predict tracheostomy requirement using factors present prior to surgical decompression. In addition, outcomes include probability functions for intensive care unit length of stay, hospital length of stay, and mortality, based on data for early (≤ 10 days) versus late (> 10 days) tracheostomy.ResultsThere were 168 surgical decompressions performed on patients with acute ischemic or spontaneous hemorrhagic stroke between 2010 and 2015. Forty-eight patients (28.5%) required a tracheostomy, 35 (20.8%) developed VAP, and 126 (75%) survived hospitalization. Mean ICU and hospital length of stay were 15.1 and 25.8 days, respectively. Using GCS, SOFA score, and presence of hydrocephalus, our decision tree analysis had 63% sensitivity and 84% specificity for predicting tracheostomy requirement. The early group had fewer ventilator days (7.3 versus 15.2, p < 0.001) and shorter hospital length of stay (28.5 versus 44.4 days, p = 0.014). VAP rates and mortality were similar between the two groups. Withdrawal of treatment interventions shortly post-operatively confounded mortality outcomes.ConclusionEarly tracheostomy shortens duration of mechanical ventilation and length of stay after surgical decompression for stroke, but it did not impact mortality or VAP rates. A decision tree is a practical tool that may be helpful in guiding pre-operative decision-making with patients’ families.Electronic supplementary materialThe online version of this article (10.1186/s40560-017-0269-1) contains supplementary material, which is available to authorized users.

Neurosurgery has been at the forefront of a paradigm shift from a localizationist perspective to a network-based approach to brain mapping. Over the last 2 decades, we have seen dramatic improvements in the way we can image the human brain and noninvasively estimate the location of critical functional networks. In certain patients with brain tumors and epilepsy, intraoperative electrical stimulation has revealed direct links between these networks and their function. The focus of these techniques has rightfully been identification and preservation of so-called “eloquent” brain functions (i.e., motor and language), but there is building momentum for more extensive mapping of cognitive and emotional networks. In addition, there is growing interest in mapping these functions in patients with a broad range of neurosurgical diseases. Resting-state functional MRI (rs-fMRI) is a noninvasive imaging modality that is able to measure spontaneous low-frequency blood oxygen level–dependent signal fluctuations at rest to infer neuronal activity. Rs-fMRI may be able to map cognitive and emotional networks for individual patients. In this review, the authors give an overview of the rs-fMRI technique and associated cognitive and emotional resting-state networks, discuss the potential applications of rs-fMRI, and propose future directions for the mapping of cognition and emotion in neurosurgical patients.

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.