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。     

提高选题策划质量 提升行业期刊品牌影响力——以金属加工杂志社实践为例

【目的】 探讨行业期刊进行选题策划的方法,提升选题策划的质量。【方法】 利用互联网技术及新媒体资源,结合金属加工杂志社选题策划实例,归纳出几种选题策划的途径及方法。【结果】 结合行业热点进行选题策划,注重实效性和内容深度,提升期刊内容的可读性,可使期刊获得更多读者的关注和认可,提升期刊的行业影响力。【结论】 提高选题策划质量,可有效提升期刊内容的可读性,从而进一步提升期刊在行业的影响力。     

Racial matching and adolescent self-disclosure of substance use and mental health symptoms

Obtaining accurate assessment data from adolescents in treatment aids clinical decision making and facilitates more accurate outcome evaluations. However, findings could be biased due to underreported substance use and mental health symptoms. This article compares self-reports of youth in non-White matched client–assessor dyads and those in nonmatched dyads. There were no differences on self-reported substance use, but matched youth reported significantly fewer attention deficit/hyperactivity disorder symptoms versus the comparison group. One possible reason for these findings is the effect of in-group stereotype threat. Future studies should examine the potential effect that in-group stereotyping and perceived racism have on the therapeutic relationship.     

子宫腺肌症对患者的心理影响及心理护理效果观察

目的 分析子宫腺肌症可能对患者造成的心理影响,探讨子宫腺肌症患者的心理护理方法,观察护理效果。方法 将62例子宫腺肌症患者随机分配为常规护理干预组和心理护理干预组,每组31例。对常规护理干预组患者,实施常规护理干预措施。对心理护理干预组患者,在常规护理干预措施的基础上,进一步对其实施针对性的心理护理干预措施。结果 心理护理干预组患者的焦虑自评量表(SAS)评分、抑郁自评量表(SDS)评分,以及睡眠质量自评量表(SRSS)各维度评分,都明显低于常规护理干预组,差异具有统计学意义。心理护理干预组患者的生活质量综合评定量表(GQOLI-74)各维度评分,要显著的高于常规护理干预组,差异同样具有统计学意义。结论 应重视并切实做好对子宫腺肌症患者的心理护理工作,这能够有效缓解患者的焦虑、抑郁情绪,提高患者的心理健康水平,改善患者的水平及生活质量。     

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.     

人格特征对男性喉鳞状细胞癌患者术后近期心理状况的影响

目的 探讨人格特征对喉鳞状细胞癌（LSCC）患者术后近期心理健康状况的影响。方法 纳入2017年1月—2019年12月在湖北省肿瘤医院行手术治疗的119例男性LSCC患者，术后5~7 d采用SCL-90、SAS、SDS自评量表评估术后心理状态，采用EPQ问卷测评患者的人格特征。多元线性逐步回归方法分析LSCC患者术后近期SAS和SDS评分的影响因素。结果 男性LSCC患者术后SCL-90、SAS、SDS得分显著高于中国常模（P≤0.05），EPQ中精神质（P）量表和神经质（N）量表得分高于中国常模（P<0.01）。男性LSCC患者术后躯体化、强迫、焦虑、抑郁、敌对、恐怖、偏执、精神病性因子得分均显著高于中国常模（P<0.05）。家庭收入、手术方式、术后近期是否行放化疗、P和N人格特征是术后SAS评分的影响因素（均P<0.01）；家庭收入、手术方式、术后近期是否行放化疗和N人格特征是术后SDS评分的影响因素（P<0.01）。结论 LSCC患者术后近期存在抑郁、焦虑等心理障碍；具有P和N人格特征；家庭收入、手术方式、术后近期是否行放化疗以及P和N人格特征是影响术后SAS及SDS评分的独立危险因素。     

Midazolam exposure in the paediatric intensive care unit predicts acute post-traumatic stress symptoms in children

BackgroundClinically significant post-traumatic stress symptoms (PTSS) have been reported in up to a quarter of paediatric intensive care unit (PICU) survivors. Ongoing PTSS negatively impacts children's psychological development and physical recovery. However, few data regarding associations between potentially modifiable PICU treatment factors, such as analgosedatives and invasive procedures, and children's PTSS have been reported.ObjectivesWe sought to investigate the medical treatment factors associated with children's PTSS after PICU discharge.MethodsA prospective longitudinal cohort study was conducted in two Australian tertiary referral PICUs. Children aged 2-16 y admitted to the PICU between June 2008 and January 2011 for >8 h and <28 d were eligible for participation. Biometric and clinical data were obtained from medical records. Parents reported their child's PTSS using the Trauma Symptom Checklist for Young Children at 1, 3, 6, and 12 months after discharge. Logistic regression was used to assess potential associations between medical treatment and PTSS.ResultsA total of 265 children and their parents participated in the study. In the 12-month period following PICU discharge, 24% of children exhibited clinically elevated PTSS. Median risk of death (Paediatric Index of Mortality 2 [PIM2]) score was significantly higher in the PTSS group (0.31 [IQR 0.14–1.09] v 0.67 [IQR 0.20–1.18]; p = 0.014). Intubation and PICU and hospital length of stay were also significantly associated with PTSS at 1 month, as were midazolam, propofol, and morphine. After controlling for gender, reason for admission, and PIM2 score, only midazolam was significantly and independently associated with PTSS and only at 1 month (adjusted odds ration (aOR) 3.63, 95% CI 1.18, 11.12, p = 0.024). No significant relationship was observed between the use of medications and PTSS after 1 month.ConclusionsElevated PTSS were evident in one quarter (24%) of children during the 12 months after PICU discharge. One month after discharge, elevated PTSS were most likely to occur in children who had received midazolam therapy.