Selecting patients for early interdisciplinary rehabilitation during neurointensive care after moderate to severe traumatic brain injury

Background

Early interdisciplinary rehabilitation (EIR) in neurointensive care is a limited resource reserved for patients with moderate to severe traumatic brain injury (TBI) believed to profit from treatment. We evaluated how key parameters related to injury severity and patient characteristics were predictive of receiving EIR, and whether these parameters changed over time.

Methods

Among 1003 adult patients with moderate to severe TBI admitted over 72 h to neurointensive care unit during four time periods between 2005 and 2020, EIR was given to 578 and standard care to 425 patients. Ten selection criteria thought to best represent injury severity and patient benefit were evaluated (Glasgow Coma Scale, Head Abbreviated Injury Scale, New-Injury-Severity-Scale, intracranial pressure monitoring, neurosurgery, age, employment, Charlson Comorbidity Index, severe psychiatric disease, and chronic substance abuse).

Results

In multivariate regression analysis, patients who were employed (adjOR 1.99 [95% CI 1.41, 2.80]), had no/mild comorbidity (adjOR 3.15 [95% CI 1.72, 5.79]), needed neurosurgery, had increasing injury severity and were admitted by increasing time period were more likely to receive EIR, whereas receiving EIR was less likely with increasing age (adjOR 0.97 [95% CI 0.96, 0.98]) and chronic substance abuse. Overall predictive ability of the model was 71%. Median age and comorbidity increased while employment decreased from 2005 to 2020, indicating patient selection became less restrictive with time.

Conclusion

Injury severity and need for neurosurgery remain important predictors for receiving EIR, but the importance of age, employment, and comorbidity have changed over time. Moderate prediction accuracy using current clinical criteria suggest unrecognized factors are important for patient selection.     

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.     

胞饮突评估子宫内膜容受性的研究进展

胚胎植入是一个复杂且受到高度调控的过程,需要囊胚与母体子宫内膜的发育精确同步。胞饮突作为表达于子宫内膜上的一种特殊膜状突起,随月经周期变化表现为不同形态,可分为发育期、成熟期及退化期。目前已有一系列研究证实,胞饮突的数量、覆盖面积及发育阶段等在预测不孕女性种植窗及评估子宫内膜容受性中具有临床价值。胞饮突评分较高、覆盖面积较广且成熟期胞饮突占比较高的女性妊娠结局更佳。其机制可能包括胞饮突通过调节宫腔内容物影响子宫内膜容受性、通过表达植入相关蛋白参与囊胚-子宫内膜相互作用等。然而,对胞饮突精准且客观的评估手段仍待进一步探索,胞饮突评估子宫内膜容受性的精确度也待进一步验证。     

胸部CT指导冠脉造影（治疗）术导管选择的价值研究

目的探讨胸部CT 指导冠脉造影（治疗）术导管选择的价值。方法 选择2018 年1 月～2019 年1 月我院收治的300 例行冠状动脉造影（治疗）术的患者作为研究对象，采用单双号法分组，单号为对照组，双号为研究组，每组各150 例，对照组采用超声指导造影导管选择，研究组采用胸部CT 指导造影导管选择，对比两组患者导管选型、大小合适率、导管选择花费时间、手术总耗时、治疗总有效率及手术过程中动脉管壁损伤发生率。结果 研究组患者导管选型合适率（98.00%）、大小合适率（98.67%）均显著高于对照组（85.33%、86.67%），研究组患者导管选择花费时间为（13.76±1.73）min、手术总耗时为（37.18±2.72）min 均显著短于对照组的（21.23±2.15）min、（58.96±3.44）min，研究组患者治疗总有效率（96.67%）显著高于对照组（77.33%），研究组患者手术过程中动脉管壁损伤发生率（0.67%）显著低于对照组（15.33%），差异均有统计学意义（P＜0.05）。结论 在冠状动脉造影术中采用胸部CT指导临床患者选择造影导管，不仅能有效提高患者导管选型、大小合适率、缩短导管选择花费时间和降低其脉管壁损伤发生率，还能有效提高手术整体治疗效果，提高患者预后质量。     

运用彭静山教授“一点二穴三线四面取穴法”针刺治疗难治性面瘫

彭静山教授提出“一点二穴三线四面”八字取穴法。笔者运用此八字取穴法指导针灸临床取穴治疗难治性面瘫,临床效果显著。本文列举临床典型病例,详细阐述取穴和针刺治疗方法,并对治疗机理进行论述。对于难治性面瘫,单纯毫针针刺治疗效果有一定局限性,以“一点二穴三线四面”八字取穴法为基础,取穴点以透刺连接构成线、面,以芒针联合透刺法为主要治疗方法,可强化治疗效果、提高临床效应。     

基于复杂网络技术对电针治疗乳腺增生病处方分析

目的基于复杂网络技术分析电针治疗乳腺增生病的核心穴位及配伍穴相关性,并对电针波型进行探讨。方法检索中国期刊全文数据库(CNKI)、万方数据库、维普网数据库(VIP)中从1954年1月1日到2018年12月31日公开发表的电针治疗乳腺增生病的临床中文文献,利用Excel表格工具建立电针治疗乳腺增生病数据库,利用Matlab2014a软件进行节点中心性分析和聚类分析,利用Gephi0.9.1软件制作复杂网络示意图对分析结果进行描述和展示,利用Excel表格工具制作电针治疗乳腺增生病不同波形比例饼状图并分析其规律。结果选定43条电针处方:电针治疗乳腺增生病主穴核心度前三位依次为膻中穴、足三里、肩井穴;配伍穴位核心度前三位依次为太冲穴、太溪穴、脾俞穴;经络核心度前三位依次为足阳明胃经、任脉、足少阳胆经。配伍穴位相关性分析中,相关性频度前三位组合依次为太冲穴-太溪穴、太冲穴-肾俞穴、太冲穴-三阴交。电针波形中以连续波与疏密波常见,均具有较高的临床应用价值。结论电针治疗乳腺增生病处方以足阳明胃经为最多,其次为任脉;电针波型以连续波为主。     

Optimal parameter selection problem with application to the synchronization of delivery cycles in a supply chain with Wiener process

In this paper, we use optimal parameter selection technique to develop two models involving single‐vendor–multiple‐buyer supply chain, which are called the dynamic independent optimization (DIO) model and the dynamic synchronized cycles (DSC) model, respectively. These models are, respectively, similar to the traditional static independent policy model and the traditional static synchronized cycle model, except that the deterministic demands of the buyers in the above two static models are now being replaced by the stochastic demands satisfying a Wiener process, which have more real‐life applications. Similar to the above static synchronized cycles model, the synchronization of the supply chain in our DSC model is also achieved by scheduling the delivery days of the buyers and coordinating them with the vendor's production cycle. Finding the optimal expected system costs of the DIO model and the DSC model involves solving optimal parameter selection problems governed by ordinary differential equations, whose final times are continuous decision variables and discrete decision variables, respectively. Computational methods have been developed for solving these problems. Numerical results show that the coordinated policy is better than the independent optimization policy, in terms of minimizing the expected system cost of the entire supply chain. Sensitivity analysis is performed to test the effect of changing the cost coefficients and the value on the performances of these models, where is the ratio of the total mean demand rate of all the buyers over the vendor's production rate.     

On the origin of schizophrenia: Testing evolutionary theories in the post‐genomic era

Considering the relatively high heritability of schizophrenia and the fact that it significantly reduces the reproductive fitness of affected individuals, it is not clear how the disorder is still maintained in human populations at a disproportionally high prevalence. Many theories propose that the disorder is a result of a trade‐off between costs and benefits of the evolution of exclusively human adaptations. There have also been suggestions that schizophrenia risk alleles are accompanied with increase in fitness of affected persons or their relatives in both past and current social contexts. The discoveries of novel schizophrenia‐related genes and the advancements in comparative genomics (especially comparisons of the human genome and the genomes of related species, such as chimpanzees and extinct hominids) have finally made certain evolutionary theories testable. In this paper, we review the current understanding of the genetics of schizophrenia, the basic principles of evolution that complement our understanding of the subject, and the latest genetic studies that examine long‐standing evolutionary theories of schizophrenia using novel methodologies and data. We find that the origin of schizophrenia is complex and likely governed by different evolutionary mechanisms that are not mutually exclusive. Furthermore, the most recent evidence implies that schizophrenia cannot be comprehended as a trait that has elevated fitness in human evolutionary lineage, but has been a mildly deleterious by‐product of specific patterns of the evolution of the human brain. In other words, novel findings do not support previous hypotheses stating that schizophrenia risk genes have an evolutionary advantage.