Subarachnoid Hemorrhage from Ruptured Aneurysm in the Middle Cerebral Artery and Anterior Cerebral Artery Trunk: A Single-Center Study

Objective: Ruptured anterior cerebral artery (ACA) trunk aneurysms and middle cerebral artery (MCA) trunk aneurysms are rare, and little is known about them. This study was conducted to determine the difference between these and other types of aneurysms.Methods: We performed a retrospective review of patients diagnosed with subarachnoid hemorrhage over an 8-year period at a single institution. We analyzed the characteristics, clinical factors, and radiological components of aneurysms at the trunk portion of A-1 and M-1. Descriptive analysis and univariate analysis for factors were performed to determine the differences of ACA A-1 portion trunk and MCA M-1 portion trunk aneurysms from other ACA and MCA aneurysms, respectively.Results: Univariate logistic regression modeling showed that trunk aneurysms in MCA M-1 had a smaller dome size (p=0.026) and dome/neck ratio (p=0.048) than other MCA aneurysms. Likewise, through univariate logistic regression modeling, the ACA group showed differences in dome size including age (p=0.001) as well as dome size (p=0.038) and dome neck ratio (p=0.041) in the A1 region.Conclusion: MCA M-1 and ACA A-1 trunk aneurysms are likely to have several different characteristics such as small in size and a lower dome/neck ratio. Also, due to their close locations to the perforator arteries, there is a high possibility of perforator artery injury when treating these aneurysms. Thus, careful attention is required when setting the treatment methods, and further studies about these aneurysms are needed.

Disordered eating among adolescents with chronic pain: the experience of a pediatric rheumatology subspecialty pain clinic

Background Disordered eating and chronic pain often co-occur in adolescents, but the relationship between these conditions is not well understood. We aimed to determine the prevalence of and to identify the clinical characteristics associated with the presence of disordered eating among adolescents with chronic musculoskeletal pain (CMP) presenting to a pediatric rheumatology subspecialty pain clinic. Methods This was a retrospective cohort study of pediatric patients presenting to a pediatric rheumatology subspecialty pain clinic for an initial consultation from March 2018 to March 2019. We complemented data from an existing patient registry with secondary chart review for patients identified with disordered eating. We compared patient characteristics based on the presence or absence of disordered eating among adolescents with CMP. Logistic regression modeling was used to determine factors associated with disordered eating. Results Of the 228 patients who were seen for an initial consultation in the pain clinic in 1 year, 51 (22.4%) had disordered eating. Only eight (15.7%) of the 51 patients identified with disordered eating had a previously documented formal eating disorder diagnosis. Through multivariate logistic regression modeling, we found that disordered eating was associated with older age, higher functional disability, presence of abdominal pain, presence of gastrointestinal comorbidities, and presence of anxiety (all p < 0.05). Conclusions Adolescents with chronic pain, especially those who experience gastrointestinal issues, anxiety, and greater functional disability, should be evaluated for disordered eating by the treating clinician in order to ensure timely and appropriate treatment.

Proximate and Underlying Deforestation Causes in a Tropical Basin through Specialized Consultation and Spatial Logistic Regression Modeling

The present study focuses on identifying and describing the possible proximate and underlying causes of deforestation and its factors using the combination of two techniques: (1) specialized consultation and (2) spatial logistic regression modeling. These techniques were implemented to characterize the deforestation process qualitatively and quantitatively, and then to graphically represent the deforestation process from a temporal and spatial point of view. The study area is the North Pacific Basin, Mexico, from 2002 to 2014. The map difference technique was used to obtain deforestation using the land-use and vegetation maps. A survey was carried out to identify the possible proximate and underlying causes of deforestation, with the aid of 44 specialized government officials, researchers, and people who live in the surrounding deforested areas. The results indicated total deforestation of 3938.77 km2 in the study area. The most important proximate deforestation causes were agricultural expansion (53.42%), infrastructure extension (20.21%), and wood extraction (16.17%), and the most important underlying causes were demographic factors (34.85%), economics factors (29.26%), and policy and institutional factors (22.59%). Based on the spatial logistic regression model, the factors with the highest statistical significance were forestry productivity, the slope, the altitude, the distance from population centers with fewer than 2500 inhabitants, the distance from farming areas, and the distance from natural protected areas.

Antibiotic Use in Lateral Skull Base Surgery: A Survey of the North American Skull Base Society

Objectives Antibiotic use in lateral skull base surgery (LSBS) has not been thoroughly investigated in the literature. There is wide variability in antibiotic use and insufficient data to guide management. This study aims to describe the factors and patterns influencing antibiotic use in LSBS among the membership of the North American Skull Base Society (NASBS). Design An online-based survey was designed and distributed to the membership of the NASBS. Data was analyzed using bivariate analysis and logistic regression modeling. Setting Online-based questionnaire. Participants NASBS membership. Main Outcome Measures Use of intraoperative antibiotics and use of postoperative antibiotics. Results The survey response rate was 26% (208 respondents). Of the 208 total respondents, 143 (69%) respondents performed LSBS. Most respondents are neurosurgeons (69%) with the remaining being otolaryngologists (31%). The majority of respondents (79%) are fellowship-trained in skull base surgery. Academic or government physicians make up 69% of respondents and 31% are in private practice with or without academic affiliations. Bivariate analysis showed that practice setting significantly influenced intraoperative antibiotic use (p = 0.01). Geographic location significantly affected postoperative antibiotic use (p = 0.01). Postoperative antibiotic duration was significantly affected by presence of chronic otitis media, cerebrospinal fluid leak, and surgeon training (p = 0.02, p = 0.01, and p = 0.006, respectively). Logistic regression modeling showed that the motivation to reduce infection significantly impacted postoperative antibiotic use (p = 0.03). Conclusion This study demonstrates significant variations in intraoperative and postoperative antibiotic use in LSBS among the NASBS membership. Appropriate guidelines for optimal perioperative antibiotic use patterns should be determined with randomized studies in the future.

Predicting Diagnosis of Australian Canine and Feline Urinary Bladder Disease Based on Histologic Features

Anatomic pathology is a vital component of veterinary medicine but as a primarily subjective qualitative or semiquantitative discipline, it is at risk of cognitive biases. Logistic regression is a statistical technique used to explain relationships between data categories and outcomes and is increasingly being applied in medicine for predicting disease probability based on medical and patient variables. Our aims were to evaluate histologic features of canine and feline bladder diseases and explore the utility of logistic regression modeling in identifying associations in veterinary histopathology, then formulate a predictive disease model using urinary bladder as a pilot tissue. The histologic features of 267 canine and 71 feline bladder samples were evaluated, and a logistic regression model was developed to identify associations between the bladder disease diagnosed, and both patient and histologic variables. There were 102 cases of cystitis, 84 neoplasia, 42 urolithiasis and 63 normal bladders. Logistic regression modeling identified six variables that were significantly associated with disease outcome: species, urothelial ulceration, urothelial inflammation, submucosal lymphoid aggregates, neutrophilic submucosal inflammation, and moderate submucosal hemorrhage. This study demonstrated that logistic regression modeling could provide a more objective approach to veterinary histopathology and has opened the door toward predictive disease modeling based on histologic variables.

Crash Risk Assessment for Heterogeneity Traffic and Different Vehicle-Following Patterns Using Microscopic Traffic Flow Data

This paper investigates the impacts of heavy vehicles (HV) on speed variation and assesses the rear-end crash risk for four vehicle-following patterns in a heterogeneous traffic flow condition using three surrogate safety measures: speed variation, time-to-collision (TTC), and deceleration rate to avoid a crash (DRAC). A video-based data collection approach was employed to collect the speed of each individual vehicle and vehicle-following headway; a total of 3859 vehicle-following pairs were identified. Binary logistic regression modeling was employed to assess the impacts of HV percentage on crash risk. TTCs and DRACs were calculated based on the collected traffic flow data. Analytical models were developed to estimate the minimum safe vehicle-following headways for the four vehicle-following patterns. Field data revealed that the variation of speed first increased with HV percentage and reached the maximum when HV percentage was at around 0.35; then, it displayed a decreasing trend with HV percentage. Binary logistic regression modeling results suggest that a high risk of rear-end collision is expected when HV percentage is between 0.19 and 0.5; while, when HV percentage is either below 0.19 or exceed 0.5, a low risk of rear-end collision is anticipated. Analytical modeling results show that the passenger car (PC)-HV vehicle-following pattern requires the largest minimum safe space headway, followed by HV-HV, PC-PC, and HV-PC vehicle-following patterns. Findings from this research present insights to transportation engineers regarding the development of crash mitigation strategies and have the potential to advance the design of real-time in-vehicle forward collision warnings to minimize the risk of rear-end crash.