Faith C. Robertson, Laura Lippa and Marike L. D. Broekman
Marike L. D. Broekman, Janneke van Beijnum, Wilco C. Peul and Luca Regli
Many neurosurgeons remove their patients' hair before surgery. They claim that this practice reduces the chance of postoperative surgical site infections, and facilitates planning, attachment of the drapes, and closure. However, most patients dread this procedure. The authors performed the first systematic review on shaving before neurosurgical procedures to investigate whether this commonly performed procedure is based on evidence. They systematically reviewed the literature on wound infections following different shaving strategies. Data on the type of surgery, surgeryrelated infections, preoperative shaving policy, decontamination protocols, and perioperative antibiotics protocols were collected. The search detected 165 articles, of which 21 studies—involving 11,071 patients—were suitable for inclusion. Two of these studies were randomized controlled trials. The authors reviewed 13 studies that reported on the role of preoperative hair removal in craniotomies, 14 on implantation surgery, 5 on bur hole procedures, and 3 on spine surgery. Nine studies described shaving policies in pediatric patients. None of these papers provided evidence that preoperative shaving decreases the occurrence of postoperative wound infections. The authors conclude that there is no evidence to support the routine performance of preoperative hair removal in neurosurgery. Therefore, properly designed studies are needed to provide evidence for preoperative shaving recommendations.
Ken R. Winston
Liang Wu, Yunwei Ou and Weiming Liu
Enrico Martin, Joeky T. Senders, Aislyn C. DiRisio, Timothy R. Smith and Marike L. D. Broekman
Ideal timeframes for operating on traumatic stretch and blunt brachial plexus injuries remain a topic of debate. Whereas on the one hand spontaneous recovery might occur, on the other hand, long delays are believed to result in poorer functional outcomes. The goal of this review is to assess the optimal timeframe for surgical intervention for traumatic brachial plexus injuries.
A systematic search was performed in January 2017 in PubMed and Embase databases according to the PRISMA guidelines. Search terms related to “brachial plexus injury” and “timing” were used. Obstetric plexus palsies were excluded. Qualitative synthesis was performed on all studies. Timing of operation and motor outcome were collected from individual patient data. Patients were categorized into 5 delay groups (0–3, 3–6, 6–9, 9–12, and > 12 months). Median delays were calculated for Medical Research Council (MRC) muscle grade ≥ 3 and ≥ 4 recoveries.
Forty-three studies were included after full-text screening. Most articles showed significantly better motor outcome with delays to surgery less than 6 months, with some studies specifying even shorter delays. Pain and quality of life scores were also significantly better with shorter delays. Nerve reconstructions performed after long time intervals, even more than 12 months, can still be useful. All papers reporting individual-level patient data described a combined total of 569 patients; 65.5% of all patients underwent operations within 6 months and 27.4% within 3 months. The highest percentage of ≥ MRC grade 3 (89.7%) was observed in the group operated on within 3 months. These percentages decreased with longer delays, with only 35.7% ≥ MRC grade 3 with delays > 12 months. A median delay of 4 months (IQR 3–6 months) was observed for a recovery of ≥ MRC grade 3, compared with a median delay of 7 months (IQR 5–11 months) for ≤ MRC grade 3 recovery.
The results of this systematic review show that in stretch and blunt injury of the brachial plexus, the optimal time to surgery is shorter than 6 months. In general, a 3-month delay appears to be appropriate because while recovery is better in those operated on earlier, this must be considered given the potential for spontaneous recovery.
Brittany M. Stopa, Joeky T. Senders, Marike L. D. Broekman, Mark Vangel and Alexandra J. Golby
Functional MRI (fMRI) is increasingly being investigated for use in neurosurgical patient care. In the current study, the authors characterize the clinical use of fMRI by surveying neurosurgeons’ use of and attitudes toward fMRI as a surgical planning tool in neurooncology patients.
A survey was developed to inquire about clinicians’ use of and experiences with preoperative fMRI in the neurooncology patient population, including example case images. The survey was distributed to all neurosurgical departments with a residency program in the US.
After excluding incomplete surveys and responders that do not use fMRI (n = 11), 50 complete responses were included in the final analysis. Responders were predominantly from academic programs (88%), with 20 years or more in practice (40%), with a main area of practice in neurooncology (48%) and treating an adult population (90%). All 50 responders currently use fMRI in neurooncology patients, mostly for low- (94%) and high-grade glioma (82%). The leading decision factors for ordering fMRI were location of mass in dominant hemisphere, location in a functional area, motor symptoms, and aphasia. Across 10 cases, language fMRI yielded the highest interrater reliability agreement (Fleiss’ kappa 0.437). The most common reasons for ordering fMRI were to identify language laterality, plan extent of resection, and discuss neurological risks with patients. Clinicians reported that fMRI results were not obtained when ordered a median 10% of the time and were suboptimal a median 27% of the time. Of responders, 70% reported that they had ever resected an fMRI-positive functional site, of whom 77% did so because the site was “cleared” by cortical stimulation. Responders reported disagreement between fMRI and awake surgery 30% of the time. Overall, 98% of responders reported that if results of fMRI and intraoperative mapping disagreed, they would rely on intraoperative mapping.
Although fMRI is increasingly being adopted as a practical preoperative planning tool for brain tumor resection, there remains a substantial degree of discrepancy with regard to its current use and presumed utility. There is a need for further research to evaluate the use of preoperative fMRI in neurooncology patients. As fMRI continues to gain prominence, it will be important for clinicians to collectively share best practices and develop guidelines for the use of fMRI in the preoperative planning phase of brain tumor patients.
Matthew E. Eagles and Rajiv Midha
Marike L. D. Broekman, Eelco W. Hoving, Kuan H. Kho, Lucienne Speleman, K. Sen Han and Patrick W. Hanlo
✓ Beckwith–Wiedemann syndrome (BWS) is a rare congenital syndrome characterized by gigantism, macroglossia, exophthalmos, postpartum hypoglycemia, and multiple midline defects such as omphalocele. The authors describe, to the best of their knowledge, the first case of a child in whom BWS was diagnosed and who was subsequently treated for a nasal encephalocele.
Because the authors believe that this feature might not be an incidental finding in patients with BWS, intranasal masses in these patients should be carefully differentiated, as complications might be severe.
Predicting nonroutine discharge after elective spine surgery: external validation of machine learning algorithms
Presented at the 2019 AANS/CNS Joint Section on Disorders of the Spine and Peripheral Nerves
Brittany M. Stopa, Faith C. Robertson, Aditya V. Karhade, Melissa Chua, Marike L. D. Broekman, Joseph H. Schwab, Timothy R. Smith and William B. Gormley
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.
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.
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.
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.