ObjectiveThe choice between external ventricular drain (EVD) and intraparenchymal monitor (IPM) for managing intracranial pressure in moderate-to-severe traumatic brain injury (msTBI) patients... Show moreObjectiveThe choice between external ventricular drain (EVD) and intraparenchymal monitor (IPM) for managing intracranial pressure in moderate-to-severe traumatic brain injury (msTBI) patients remains controversial. This study aimed to investigate factors associated with receiving EVD versus IPM and to compare outcomes and clinical management between EVD and IPM patients.MethodsAdult msTBI patients at 2 similar academic institutions were identified. Logistic regression was performed to identify factors associated with receiving EVD versus IPM (model 1) and to compare EVD versus IPM in relation to patient outcomes after controlling for potential confounders (model 2), through odds ratios (ORs) and 95% confidence intervals (CIs).ResultsOf 521 patients, 167 (32.1%) had EVD and 354 (67.9%) had IPM. Mean age, sex, and Injury Severity Score were comparable between groups. Epidural hemorrhage (EDH) (OR 0.43, 95% CI 0.21–0.85), greater midline shift (OR 0.90, 95% CI 0.82–0.98), and the hospital with higher volume (OR 0.14, 95% CI 0.09–0.22) were independently associated with lower odds of receiving an EVD whereas patients needing a craniectomy were more likely to receive an EVD (OR 2.04, 95% CI 1.12–3.73). EVD patients received more intense medical treatment requiring hyperosmolar therapy compared to IPM patients (64.1% vs. 40.1%). No statistically significant differences were found in patient outcomes.ConclusionsWhile EDH, greater midline shift, and hospital with larger patient volume were associated with receiving an IPM, the need for a craniectomy was associated with receiving an EVD. EVD patients received different clinical management than IPM patients with no significant differences in patient outcomes. Show less
BACKGROUND: Robotic neurosurgery may improve the accuracy, speed, and availability of stereotactic procedures. We recently developed a computer vision and artificial intelligence-driven frameless... Show moreBACKGROUND: Robotic neurosurgery may improve the accuracy, speed, and availability of stereotactic procedures. We recently developed a computer vision and artificial intelligence-driven frameless stereotaxy for nonimmobilized patients, creating an opportunity to develop accurate and rapidly deployable robots for bedside cranial intervention. OBJECTIVE: To validate a portable stereotactic surgical robot capable of frameless registration, real-time tracking, and accurate bedside catheter placement. METHODS: Four human cadavers were used to evaluate the robot's ability to maintain low surface registration and targeting error for 72 intracranial targets during head motion, ie, without rigid cranial fixation. Twenty-four intracranial catheters were placed robotically at predetermined targets. Placement accuracy was verified by computed tomography imaging. RESULTS: Robotic tracking of the moving cadaver heads occurred with a program runtime of 0.111 +/- 0.013 seconds, and the movement command latency was only 0.002 +/- 0.003 seconds. For surface error tracking, the robot sustained a 0.588 +/- 0.105 mm registration accuracy during dynamic head motions (velocity of 6.647 +/- 2.360 cm/s). For the 24 robotic-assisted intracranial catheter placements, the target registration error was 0.848 +/- 0.590 mm, providing a user error of 0.339 +/- 0.179 mm. CONCLUSION: Robotic-assisted stereotactic procedures on mobile subjects were feasible with this robot and computer vision image guidance technology. Frameless robotic neurosurgery potentiates surgery on nonimmobilized and awake patients both in the operating room and at the bedside. It can affect the field through improving the safety and ability to perform procedures such as ventriculostomy, stereo electroencephalography, biopsy, and potentially other novel procedures. If we envision catheter misplacement as a "never event," robotics can facilitate that reality. Show less
OBJECTIVE A major obstacle to improving bedside neurosurgical procedure safety and accuracy with image guidance technologies is the lack of a rapidly deployable, real-time registration and tracking... Show moreOBJECTIVE A major obstacle to improving bedside neurosurgical procedure safety and accuracy with image guidance technologies is the lack of a rapidly deployable, real-time registration and tracking system for a moving patient. This deficiency explains the persistence of freehand placement of external ventricular drains, which has an inherent risk of inaccurate positioning, multiple passes, tract hemorrhage, and injury to adjacent brain parenchyma. Here, the authors introduce and validate a novel image registration and real-time tracking system for frameless stereotactic neuronavigation and catheter placement in the nonimmobilized patient.METHODS Computer vision technology was used to develop an algorithm that performed near- continuous, automatic, and marker-less image registration. The program fuses a subject's preprocedure CT scans to live 3D camera images (Snap-Surface), and patient movement is incorporated by artificial intelligence- driven recalibration (Real-Track). The surface registration error (SRE) and target registration error (TRE) were calculated for 5 cadaveric heads that underwent serial movements (fast and slow velocity roll, pitch, and yaw motions) and several test conditions, such as surgical draping with limited anatomical exposure and differential subject lighting. Six catheters were placed in each cadaveric head (30 total placements) with a simulated sterile technique. Postprocedure CT scans allowed comparison of planned and actual catheter positions for user error calculation.RESULTS Registration was successful for all 5 cadaveric specimens, with an overall mean (+/- standard deviation) SRE of 0.429 +/- 0.108 mm for the catheter placements. Accuracy of TRE was maintained under 1.2 mm throughout specimen movements of low and high velocities of roll, pitch, and yaw, with the slowest recalibration time of 0.23 seconds. There were no statistically significant differences in SRE when the specimens were draped or fully undraped (p = 0.336). Performing registration in a bright versus a dimly lit environment had no statistically significant effect on SRE (p = 0.742 and 0.859, respectively). For the catheter placements, mean TRE was 0.862 +/- 0.322 mm and mean user error (difference between target and actual catheter tip) was 1.674 +/- 1.195 mm.CONCLUSIONS This computer vision-based registration system provided real-time tracking of cadaveric heads with a recalibration time of less than one-quarter of a second with submillimetric accuracy and enabled catheter placements with millimetric accuracy. Using this approach to guide bedside ventriculostomy could reduce complications, improve safety, and be extrapolated to other frameless stereotactic applications in awake, nonimmobilized patients. Show less
OBJECTIVE Postoperative routine imaging is common after pediatric ventricular shunt revision, but the benefit of scanning in the absence of symptoms is questionable. In this study, the authors... Show moreOBJECTIVE Postoperative routine imaging is common after pediatric ventricular shunt revision, but the benefit of scanning in the absence of symptoms is questionable. In this study, the authors aimed to assess how often routine scanning results in a change in clinical management after shunt revision. METHODS The records of a large, tertiary pediatric hospital were retrospectively reviewed for all consecutive cases of pediatric shunt revision between July 2013 and July 2018. Postoperative imaging was classified as routine (i.e., in the absence of symptoms, complications, or other direct indications) or nonroutine. Reinterventions within 30 days were assessed in these groups. RESULTS Of 387 included shunt revisions performed in 232 patients, postoperative imaging was performed in 297 (77%), which was routine in 244 (63%) and nonroutine in 53 (14%). Ninety revisions (23%) underwent any shunt-related procedure after postoperative imaging, including shunt reprogramming (n = 35, 9%), shunt tap (n = 10, 3%), and a return to the operating room (OR; n = 58, 15%). Of the 244 cases receiving routine imaging, 241 did not undergo a change in clinical management solely based on routine imaging findings. The remaining 3 cases returned to the OR, accounting for 0.8% (95% CI 0.0%-1.7%) of all cases or 1.2% (95% CI 0.0%-2.6%) of cases that received routine imaging. Furthermore, 27 of 244 patients in this group returned to the OR for other reasons, namely complications (n = 12) or recurrent symptoms (n = 15); all arose after initial routine imaging. CONCLUSIONS The authors found a low yield to routine imaging after pediatric shunt revision, with only 0.8% of cases undergoing a change in management based on routine imaging findings without corresponding clinical findings. Moreover, routine imaging without abnormal findings was no guarantee of an uneventful postoperative course. Clinical monitoring can be considered as an alternative in asymptomatic, uncomplicated patients. Show less
Purpose Although standard-of-care has been defined for the treatment of glioblastoma patients, substantial practice variation exists in the day-to-day clinical management. This study aims to... Show morePurpose Although standard-of-care has been defined for the treatment of glioblastoma patients, substantial practice variation exists in the day-to-day clinical management. This study aims to compare the use of laboratory tests in the perioperative care of glioblastoma patients between two tertiary academic centers-Brigham and Women's Hospital (BWH), Boston, USA, and University Medical Center Utrecht (UMCU), Utrecht, the Netherlands. Methods All glioblastoma patients treated according to standard-of-care between 2005 and 2013 were included. We compared the number of blood drawings and laboratory tests performed during the 70-day perioperative period using a Poisson regression model, as well as the estimated laboratory costs per patient. Additionally, we compared the likelihood of an abnormal test result using a generalized linear mixed effects model. Results After correction for age, sex, IDH1 status, postoperative KPS score, length of stay, and survival status, the number of blood drawings and laboratory tests during the perioperative period were 3.7-fold (p < 0.001) and 4.7-fold (p < 0.001) higher, respectively, in BWH compared to UMCU patients. The estimated median laboratory costs per patient were 82 euros in UMCU and 256 euros in BWH. Furthermore, the likelihood of an abnormal test result was lower in BWH (odds ratio [OR] 0.75, p < 0.001), except when the prior test result was abnormal as well (OR 2.09, p < 0.001). Conclusions Our results suggest a substantially lower clinical threshold for ordering laboratory tests in BWH compared to UMCU. Further investigating the clinical consequences of laboratory testing could identify over and underuse, decrease healthcare costs, and reduce unnecessary discomfort that patients are exposed to. Show less
Glioblastoma is associated with a poor prognosis. Even though survival statistics are well-described at the population level, it remains challenging to predict the prognosis of an individual... Show moreGlioblastoma is associated with a poor prognosis. Even though survival statistics are well-described at the population level, it remains challenging to predict the prognosis of an individual patient despite the increasing number of prognostic models. The aim of this study is to systematically review the literature on prognostic modeling in glioblastoma patients. A systematic literature search was performed to identify all relevant studies that developed a prognostic model for predicting overall survival in glioblastoma patients following the PRISMA guidelines. Participants, type of input, algorithm type, validation, and testing procedures were reviewed per prognostic model. Among 595 citations, 27 studies were included for qualitative review. The included studies developed and evaluated a total of 59 models, of which only seven were externally validated in a different patient cohort. The predictive performance among these studies varied widely according to the AUC (0.58-0.98), accuracy (0.69-0.98), and C-index (0.66-0.70). Three studies deployed their model as an online prediction tool, all of which were based on a statistical algorithm. The increasing performance of survival prediction models will aid personalized clinical decision-making in glioblastoma patients. The scientific realm is gravitating towards the use of machine learning models developed on high-dimensional data, often with promising results. However, none of these models has been implemented into clinical care. To facilitate the clinical implementation of high-performing survival prediction models, future efforts should focus on harmonizing data acquisition methods, improving model interpretability, and externally validating these models in multicentered, prospective fashion. Show less
OBJECTIVE: Outcome prediction in severe traumatic brain injury (sTBI) has been studied using clinical and radiographic measurements and by using biomarkers such as glial fibrillary acidic protein,... Show moreOBJECTIVE: Outcome prediction in severe traumatic brain injury (sTBI) has been studied using clinical and radiographic measurements and by using biomarkers such as glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, and tau. Routine blood tests are regularly performed in patients with sTBI and could be used to predict outcomes. This study aims to investigate whether routine blood tests on admission can be predictive of outcome in patients with sTBI.METHODS: Patients with sTBI were selected from 2 institutional databases based on International Classification of Diseases Ninth and Tenth Revision codes for traumatic brain injury (TBI), ventilatory assistance >24 hours, intracranial pressure monitoring, and Glasgow Coma Score (GCS) score =8. Laboratory parameters included blood urea nitrogen, creatinine, glucose, hematocrit, hemoglobin, red blood cells, white blood cells, monocytes, lymphocytes, neutrophils, neutrophil lymphocyte ratio, platelets, international normalized ratio, prothrombin time, sodium, and potassium. Clinical outcome was measured as hospital length of stay, 30-day mortality, and favorable versus unfavorable outcome based on Glasgow Outcome Scale at 3 months.RESULTS: A total of 255 adult patients were selected. Median Injury Severity Score was 14.00 (interquartile range, 9.00-22.00). Of patients, 25.9% died within 30 days and 56.1% had an unfavorable outcome at 3 months. On multivariate analysis, low sodium level was significant for 30-day mortality and high sodium level was significant for unfavorable outcome at 3 months. However, after correction for multiple testing, no routine blood test remained significant.CONCLUSIONS: No routine blood tests measured on admission were significant predictors of outcome in patients with sTBI. Other clinical and radiologic factors may be better suited to predicting outcomes in this patient population. Show less
Solinge, T.S. van; Muskens, I.S.; Kavouridis, V.K.; Gormley, W.B.; Mekary, R.A.; Broekman, M.L.D.; Arnaout, O. 2020
Intraventricular hemorrhage (IVH) is an independent poor prognostic factor in subarachnoid and intra-parenchymal hemorrhage. The use of intraventricular fibrinolytics (IVF) has long been debated,... Show moreIntraventricular hemorrhage (IVH) is an independent poor prognostic factor in subarachnoid and intra-parenchymal hemorrhage. The use of intraventricular fibrinolytics (IVF) has long been debated, and its exact effects on outcomes are unknown. A systematic review and meta-analysis were performed in accordance with the PRISMA guidelines to assess the impact of IVF after non-traumatic IVH on mortality, functional outcome, intracranial bleeding, ventriculitis, time until clearance of third and fourth ventricles, obstruction of external ventricular drains (EVD), and shunt dependency. Nineteen studies were included in the meta-analysis, totaling 1020 patients. IVF was associated with lower mortality (relative risk [RR] 0.58; 95% confidence interval [CI] 0.47-0.72), fewer EVD obstructions (RR 0.41; 95% CI 0.22-0.74), and a shorter time until clearance of the ventricles (median difference [MD] - 4.05 days; 95% CI - 5.52 to - 2.57). There was no difference in good functional outcome, RR 1.41 (95% CI 0.98-2.03), or shunt dependency, RR 0.93 (95% CI 0.70-1.22). Correction for publication bias predicted an increased risk of intracranial bleeding, RR 1.67 (95% CI 1.01-2.74) and a lower risk of ventriculitis, RR 0.68 (95% CI 0.45-1.03) in IVH patients treated with IVF. IVF was associated with improved survival, faster clearance of blood from the ventricles and fewer drain obstructions, but further research is warranted to elucidate the effects on ventriculitis, long-term functional outcomes, and re-hemorrhage. Show less
PURPOSE The aim of this study was to develop an open-source natural language processing (NLP) pipeline for text mining of medical information from clinical reports. We also aimed to provide insight... Show morePURPOSE The aim of this study was to develop an open-source natural language processing (NLP) pipeline for text mining of medical information from clinical reports. We also aimed to provide insight into why certain variables or reports are more suitable for clinical text mining than others.MATERIALS AND METHODS Various NLP models were developed to extract 15 radiologic characteristics from free-text radiology reports for patients with glioblastoma. Ten-fold cross-validation was used to optimize the hyperparameter settings and estimate model performance. We examined how model performance was associated with quantitative attributes of the radiologic characteristics and reports.RESULTS In total, 562 unique brain magnetic resonance imaging reports were retrieved. NLP extracted 15 radiologic characteristics with high to excellent discrimination (area under the curve, 0.82 to 0.98) and accuracy (78.6% to 96.6%). Model performance was correlated with the inter-rater agreement of the manually provided labels (rho = 0.904; P<.001) but not with the frequency distribution of the variables of interest (rho = 0.179; P =.52). All variables labeled with a near perfect inter-rater agreement were classified with excellent performance (area under the curve > 0.95). Excellent performance could be achieved for variables with only 50 to 100 observations in the minority group and class imbalances up to a 9:1 ratio. Report-level classification accuracy was not associated with the number of words or the vocabulary size in the distinct text documents.CONCLUSION This study provides an open-source NLP pipeline that allows for text mining of narratively written clinical reports. Small sample sizes and class imbalance should not be considered as absolute contraindications for text mining in clinical research. However, future studies should report measures of inter-rater agreement whenever ground truth is based on a consensus label and use this measure to identify clinical variables eligible for text mining. Show less
OBJECTIVE Nonroutine discharge after elective spine surgery increases healthcare costs, negatively impacts patient satisfaction, and exposes patients to additional hospital-acquired complications.... Show moreOBJECTIVE Nonroutine discharge after elective spine surgery increases healthcare costs, negatively impacts patient satisfaction, and exposes patients to additional hospital-acquired complications. Therefore, prediction of nonroutine discharge in this population may improve clinical management. The authors previously developed a machine learning algorithm from national data that predicts risk of nonhome discharge for patients undergoing surgery for lumbar disc disorders. In this paper the authors externally validate their algorithm in an independent institutional population of neurosurgical spine patients.METHODS Medical records from elective inpatient surgery for lumbar disc herniation or degeneration in the Transitional Care Program at Brigham and Women's Hospital (2013-2015) were retrospectively reviewed. Variables included age, sex, BMI, American Society of Anesthesiologists (ASA) class, preoperative functional status, number of fusion levels, comorbidities, preoperative laboratory values, and discharge disposition. Nonroutine discharge was defined as postoperative discharge to any setting other than home. The discrimination (c-statistic), calibration, and positive and negative predictive values (PPVs and NPVs) of the algorithm were assessed in the institutional sample.RESULTS Overall, 144 patients underwent elective inpatient surgery for lumbar disc disorders with a nonroutine discharge rate of 6.9% (n = 10). The median patient age was 50 years and 45.1% of patients were female. Most patients were ASA class II (66.0%), had 1 or 2 levels fused (80.6%), and had no diabetes (91.7%). The median hematocrit level was 41.2%. The neural network algorithm generalized well to the institutional data, with a c-statistic (area under the receiver operating characteristic curve) of 0.89, calibration slope of 1.09, and calibration intercept of -0.08. At a threshold of 0.25, the PPV was 0.50 and the NPV was 0.97.CONCLUSIONS This institutional external validation of a previously developed machine learning algorithm suggests a reliable method for identifying patients with lumbar disc disorder at risk for nonroutine discharge. Performance in the institutional cohort was comparable to performance in the derivation cohort and represents an improved predictive value over clinician intuition. This finding substantiates initial use of this algorithm in clinical practice. This tool may be used by multidisciplinary teams of case managers and spine surgeons to strategically invest additional time and resources into postoperative plans for this population. Show less
