Effects of exogenous factors on spatial accuracy in neurosurgery

The study aimed to assess the effect of exogenous factors such as surgeon posture, surgical instrument length, fatigue after a night shift, exercise and caffeine consumption on the spatial accuracy of neurosurgical manipulations. For the evaluation and simulation of neurosurgical manipulations, a testing device developed by the authors was used. The experimental results were compared using nonparametric analysis (Wilcoxon test) and multivariate analysis, which was performed using mixed models. The results were considered statistically significant at p < 0.05. The study included 11 first-year neurosurgery residents who met the inclusion criteria. Hand support in the sitting position (Wilcoxon test p value = 0.0033), caffeine consumption (p = 0.0058) and the length of the microsurgical instrument (p = 0.0032) had statistically significant influences on the spatial accuracy of surgical manipulations (univariate analysis). The spatial accuracy did not significantly depend on the type of standing position (Wilcoxon test p value = 0.2860), whether the surgeon was standing/sitting (p = 0.1029), fatigue following a night shift (p = 0.3281), or physical exertion prior to surgery (p = 0.2845).When conducting the multivariate analysis, the spatial accuracy significantly depended on the test subject (p < 0.0001), the use of support during the test (p = 0.0001), and the length of the microsurgical instrument (p = 0.0397). To increase the spatial accuracy of microsurgical manipulations, hand support and shorter tools should be used. Caffeine consumption in high doses should also be avoided prior to surgery.     

A Perioperative Care Display for Understanding High Acuity Patients

Background  The data visualization literature asserts that the details of the optimal data display must be tailored to the specific task, the background of the user, and the characteristics of the data. The general organizing principle of a concept-oriented display is known to be useful for many tasks and data types. Objectives  In this project, we used general principles of data visualization and a co-design process to produce a clinical display tailored to a specific cognitive task, chosen from the anesthesia domain, but with clear generalizability to other clinical tasks. To support the work of the anesthesia-in-charge (AIC) our task was, for a given day, to depict the acuity level and complexity of each patient in the collection of those that will be operated on the following day. The AIC uses this information to optimally allocate anesthesia staff and providers across operating rooms. Methods  We used a co-design process to collaborate with participants who work in the AIC role. We conducted two in-depth interviews with AICs and engaged them in subsequent input on iterative design solutions. Results  Through a co-design process, we found (1) the need to carefully match the level of detail in the display to the level required by the clinical task, (2) the impedance caused by irrelevant information on the screen such as icons relevant only to other tasks, and (3) the desire for a specific but optional trajectory of increasingly detailed textual summaries. Conclusion  This study reports a real-world clinical informatics development project that engaged users as co-designers. Our process led to the user-preferred design of a single binary flag to identify the subset of patients needing further investigation, and then a trajectory of increasingly detailed, text-based abstractions for each patient that can be displayed when more information is needed.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

Personal characteristics and school contextual variables associated with student self-determination in Spanish context

Background: Most theoretical models of self-determination suggest that both environmental and personal factors influence the development of self-determination. The design and implementation of interventions must be conducted with foreknowledge of such mediating and moderating factors if the intervention is to be successful.

Methods: The purpose of this study was to examine the degree to which several personal factors and school characteristics affect and explain students’ self-determination. A total of 232 students with intellectual disability from Spain participated. Their self-determination level was assessed by the ARC-INICO Scale.

Results: Students with moderate levels of intellectual disability obtained significantly lower scores on self-determination than their peers with mild intellectual disability. There were significant differences in relation to the level of support needs and their experience with transition programs. The level of support needs was a significant predictor.

Conclusion: These findings contribute to current research in this field and practical implications were discussed.     

ONRAB® oral rabies vaccine is shed from,but does not persist in,captive mammals

ONRAB® is a human adenovirus rabies glycoprotein recombinant vaccine developed to control rabies in wildlife. To support licensing and widespread use of the vaccine, safety studies are needed to assess its potential residual impact on wildlife populations. We examined the persistence of the ONRAB® vaccine virus in captive rabies vector and non-target mammals. This research complements work on important rabies vector species (raccoon, striped skunk, and red fox) but also adds to previous findings with the addition of some non-target species (Virginia opossum, Norway rats, and cotton rats) and a prolonged period of post vaccination monitoring (41 days). Animals were directly inoculated orally with the vaccine and vaccine shedding was monitored using quantitative real-time PCR applied to oral and rectal swabs. ONRAB® DNA was detected in both oral and rectal swabs from 6 h to 3 days post-inoculation in most animals, followed by a resurgence of shedding between days 17 and 34 in some species. Overall, the duration over which ONRAB® DNA was detectable was shorter for non-target mammals, and by day 41, no animal had detectable DNA in either oral or rectal swabs. All target species, as well as cotton rats and laboratory-bred Norway rats, developed robust humoral immune responses as measured by competitive ELISA, with all individuals being seropositive at day 31. Similarly, opossums showed good response (89% seropositive; 8/9), whereas only one of nine wild caught Norway rats was seropositive at day 31. These results support findings of other safety studies suggesting that ONRAB® does not persist in vector and non-target mammals exposed to the vaccine. As such, we interpret these data to reflect a low risk of adverse effects to wild populations following distribution of ONRAB® to control sylvatic rabies.     

健康支持性环境对四川农村人群的不同血压水平的影响分析

目的 探讨健康支持性环境中的不同特征变量对四川省农村人群的不同血压水平的影响。方法 采用多阶段整群抽样的方法，随机抽取四川省7个县（区）8400名的18岁以上常住居民为调查对象。问卷调查一般人口学特征、身体活动行为特征和环境等信息。采用标准方法测量身高、体重、腰围和血压。采用无序多分类logistic回归分析。结果 本调查人群中共检出正常高值血压者4270例，检出率为50.83%，标化率为37.02%，平均年龄（56.22±14.89）岁；高血压患者1498例，检出率为17.83%，标化率为7.92%，平均年龄（65.26±11.28）岁。无序多分类logistic回归结果显示，住宿环境好、获得运动方面的健康信息和参与中等强度活动150Symbol~A@300min/周是正常高值血压和高血压人群的共同保护因素；住宿便利（OR=0.789, 95%CI:0.649~0.958, P=0.017）、医疗服务可及性便利（OR=0.686, 95%CI:0.509~0.924, P=0.013）、对健身步道和健身广场满意为高血压人群的保护因素。结论 多途径合理构建健康支持性环境，对农村正常高值血压者和高血压患者具有保护作用，对遏制农村高血压的流行现状起到一定作用。