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Bharath Raju, Fareed Jumah, Vinayak Narayan, Anika Sonig, Hai Sun, and Anil Nanda

The earliest evidence of man’s attempts in communicating ideas and emotions can be seen on cave walls and ceilings from the prehistoric era. Ingenuity, as well as the development of tools, allowed clay tablets to become the preferred method of documentation, then papyrus and eventually the codex. As civilizations advanced to develop structured systems of writing, knowledge became a power available to only those who were literate. As the search to understand the intricacies of the human brain moved forward, so did the demand for teaching the next generation of physicians. The different methods of distributing information were forced to advance, lest the civilization falls behind. Here, the authors present a historical perspective on the evolution of the mediums of illustration and knowledge dissemination through the lens of neurosurgery. They highlight how the medium of choice transitioned from primitive clay pots to cutting-edge virtual reality technology, aiding in the propagation of medical literature from generation to generation across the centuries.

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Bharath Raju, Fareed Jumah, Omar Ashraf, Vinayak Narayan, Gaurav Gupta, Hai Sun, Patrick Hilden, and Anil Nanda

Big data has transformed into a trend phrase in healthcare and neurosurgery, becoming a pervasive and inescapable phrase in everyday life. The upsurge in big data applications is a direct consequence of the drastic boom in information technology as well as the growing number of internet-connected devices called the Internet of Things in healthcare. Compared with business, marketing, and other sectors, healthcare applications are lagging due to a lack of technical knowledge among healthcare workers, technological limitations in acquiring and analyzing the data, and improper governance of healthcare big data. Despite these limitations, the medical literature is flooded with big data–related articles, and most of these are filled with abstruse terminologies such as machine learning, artificial intelligence, artificial neural network, and algorithm. Many of the recent articles are restricted to neurosurgical registries, creating a false impression that big data is synonymous with registries. Others advocate that the utilization of big data will be the panacea to all healthcare problems and research in the future. Without a proper understanding of these principles, it becomes easy to get lost without the ability to differentiate hype from reality. To that end, the authors give a brief narrative of big data analysis in neurosurgery and review its applications, limitations, and the challenges it presents for neurosurgeons and healthcare professionals naive to this field. Awareness of these basic concepts will allow neurosurgeons to understand the literature regarding big data, enabling them to make better decisions and deliver personalized care.

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Bharath Raju, Fareed Jumah, Omar Ashraf, Vinayak Narayan, Gaurav Gupta, Hai Sun, Patrick Hilden, and Anil Nanda

Big data has transformed into a trend phrase in healthcare and neurosurgery, becoming a pervasive and inescapable phrase in everyday life. The upsurge in big data applications is a direct consequence of the drastic boom in information technology as well as the growing number of internet-connected devices called the Internet of Things in healthcare. Compared with business, marketing, and other sectors, healthcare applications are lagging due to a lack of technical knowledge among healthcare workers, technological limitations in acquiring and analyzing the data, and improper governance of healthcare big data. Despite these limitations, the medical literature is flooded with big data–related articles, and most of these are filled with abstruse terminologies such as machine learning, artificial intelligence, artificial neural network, and algorithm. Many of the recent articles are restricted to neurosurgical registries, creating a false impression that big data is synonymous with registries. Others advocate that the utilization of big data will be the panacea to all healthcare problems and research in the future. Without a proper understanding of these principles, it becomes easy to get lost without the ability to differentiate hype from reality. To that end, the authors give a brief narrative of big data analysis in neurosurgery and review its applications, limitations, and the challenges it presents for neurosurgeons and healthcare professionals naive to this field. Awareness of these basic concepts will allow neurosurgeons to understand the literature regarding big data, enabling them to make better decisions and deliver personalized care.

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Shyamal C. Bir, Anil Nanda, Hugo Cuellar, Hai Sun, Bharat Guthikonda, Cesar Liendo, Alireza Minagar, and Oleg Y. Chernyshev

OBJECTIVE

Obstructive sleep apnea (OSA) is associated with the progression of abdominal and thoracic aortic aneurysms. However, the role of OSA in the overall outcome of intracranial aneurysms (IAs) has not yet been established. Authors of this report investigated the role of OSA in the overall outcome of IAs.

METHODS

Radiological and clinical data on patients (from 2010 through 2015) with confirmed IA were retrospectively reviewed. Significant differences between the OSA and non-OSA groups were determined using a chi-square test. Logistic regression analysis was performed to identify the predictors of an unfavorable IA outcome.

RESULTS

Among the 283 patients with confirmed IAs, 45 patients (16%) were positively screened for OSA, a proportion that was significantly higher than the prevalence of OSA in nonaneurysmal neurosurgical patients (4%, p = 0.008). The percentage of patients with hypertension (p = 0.018), a body mass index ≥ 30 kg/m2 (p < 0.0001), hyperlipidemia (p = 0.034), diabetes mellitus (p = 0.005), chronic heart disease (CHD; p = 0.024), or prior stroke (p = 0.03) was significantly higher in the OSA group than in the non-OSA group. Similarly, the percentage of wide-necked aneurysms (p = 0.00001) and patients with a poor Hunt and Hess Grade IV–V (p = 0.01) was significantly higher in the OSA group than in the non-OSA group. In addition, the percentage of ruptured aneurysms (p = 0.03) and vasospasms (p = 0.03) was significantly higher in the OSA group. The percentage of patients with poor modified Rankin Scale (mRS) scores (3–6) was significantly higher in the OSA group (p = 0.03). A separate cohort of patients with ruptured IAs showed similar results. In both univariate (p = 0.01) and multivariate (p = 0.04) regression analyses, OSA was identified as an individual predictor of an unfavorable outcome. In addition, hypertension and prior stroke were revealed as predictors of a poor IA outcome.

CONCLUSIONS

Complications of IA such as rupture and vasospasm are often the consequence of uncontrolled OSA. Overall outcome (mRS) of IAs is also affected by the co-occurrence of OSA. Therefore, the coexistence of OSA with IA affects the outcome of IAs. Obstructive sleep apnea is a risk factor for a poor outcome in IA patients.

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Devi Prasad Patra, Shyamal C. Bir, Tanmoy K. Maiti, Piyush Kalakoti, Hugo Cuellar, Bharat Guthikonda, Hai Sun, Christina Notarianni, and Anil Nanda

OBJECTIVE

Despite significant advances in the medical field and shunt technology, shunt malfunction remains a nightmare of pediatric neurosurgeons. In this setting, the ability to preoperatively predict the probability of shunt malfunction is quite compelling. The authors have compared the preoperative radiological findings in obstructive hydrocephalus and the subsequent clinical course of the patient to determine any association with overall shunt outcome.

METHODS

This retrospective study included all pediatric patients (age < 18 years) who had undergone ventriculoperitoneal shunt insertion for obstructive hydrocephalus. Linear measurements were taken from pre- and postoperative CT or MRI studies to calculate different indices and ratios including Evans' index, frontal horn index (FHI), occipital horn index (OHI), frontooccipital horn ratio (FOHR), and frontooccipital horn index ratio (FOIR). Other morphological features such as bi- or triventriculomegaly, right-left ventricular symmetry, and periventricular lucency (PVL) were also noted. The primary clinical outcomes that were reviewed included the need for shunt revision, time interval to first shunt revision, frequency of shunt revisions, and revision-free survival.

RESULTS

A total of 121 patients were eligible for the analysis. Nearly half of the patients (47.9%) required shunt revision. The presence of PVL was associated with lower revision rates than those in others (39.4% vs 58.2%, p = 0.03). None of the preoperative radiological indices or ratios showed any correlation with shunt revision. Nearly half of the patients with shunt revision required early revision (< 90 days of primary surgery). The reduction in the FOHR was high in patients who required early shunt revision (20.16% in patients with early shunt revision vs 6.4% in patients with late shunt revision, p = 0.009). Nearly half of the patients (48.3%) requiring shunt revision ultimately needed more than one revision procedure. Greater occipital horn dilation on preoperative images was associated with a lower frequency of shunt revision, as dictated by a high OHI and a low FOIR in patients with a single shunt revision as compared with those in patients who required multiple shunt revisions (p = 0.029 and 0.009, respectively). The mean follow-up was 49.9 months. Age was a significant factor affecting shunt revision–free survival. Patients younger than 6 months of age had significantly less revision-free survival than the patients older than 6 months (median survival of 10.1 vs 94.1 months, p = 0.004).

CONCLUSIONS

Preoperative radiological linear indices and ratios do not predict the likelihood of subsequent shunt malfunction. However, patients who required early shunt revision tended to have greater reductions in ventricular volumes on postoperative images. Therefore a greater reduction in ventricular volume is not actually desirable, and a ventricular volume high enough to reduce intracranial pressure is instead to be aimed at for long-term shunt compliance.

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Shyamal C. Bir, Devi Prasad Patra, Tanmoy K. Maiti, Hai Sun, Bharat Guthikonda, Christina Notarianni, and Anil Nanda

OBJECTIVE

Adult-onset hydrocephalus is not commonly discussed in the literature, especially regarding its demographic distribution. In contrast to pediatric hydrocephalus, which is related to a primary CSF pathway defect, its development in adults is often secondary to other pathologies. In this study, the authors investigated the epidemiology of adult-onset hydrocephalus as it pertains to different etiologies and in reference to age, sex, and race distributions.

METHODS

The authors retrospectively reviewed the clinical notes of 2001 patients with adult-onset hydrocephalus who presented to Louisiana State University Health Sciences Center within a 25-year span. Significant differences between the groups were analyzed by a chi-square test; p < 0.05 was considered significant.

RESULTS

The overall mean (± SEM) incidence of adult hydrocephalus in this population was 77 ± 30 per year, with a significant increase in incidence in the past decade (55 ± 3 [1990–2003] vs 102 ± 6 [2004–2015]; p < 0.0001). Hydrocephalus in a majority of the patients had a vascular etiology (45.5%) or was a result of a tumor (30.2%). The incidence of hydrocephalus in different age groups varied according to various pathologies. The incidence was significantly higher in males with normal-pressure hydrocephalus (p = 0.03) or head injury (p = 0.01) and higher in females with pseudotumor cerebri (p < 0.0001). In addition, the overall incidence of hydrocephalus was significantly higher in Caucasian patients (p = 0.0002) than in those of any other race.

CONCLUSIONS

Knowledge of the demographic variations in adult-onset hydrocephalus is helpful in achieving better risk stratification and better managing the disease in patients. For general applicability, these results should be validated in a large-scale meta-analysis based on a national population database.