Clinical therapeutic effects of probiotics in combination with antibiotics on periodontitis: A protocol for systematic review and meta-analysis

Background:Dental pain can have a detrimental effect on quality of life. Symptomatic apical periodontitis is the most common cause of dental pain and arise from an inflamed or necrotic dental pulp. There is growing evidence to support the effectiveness of probiotics in combination with antibiotics on periodontitis. We therefor will conduct this study to evaluate the clinical therapeutic effects of probiotics in combination with antibiotics on periodontitis.Methods:We will systematically search the following databases: PubMed, the Cochrane Library, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Database (CBM), and WanFang database. A grey literature search will be conducted using ZETOC Conference Proceedings and Open Grey. Only randomized controlled trials (RCTs) related to research on probiotics in combination with antibiotics to treatment patients with periodontitis will be included. All sources have to be searched from their inception to October 2020. Two authors will independently select studies, extract study data, and evaluate the quality of the included studies. We will use Review Manager Software (RevMan 5.3) to analyze data.Results:This study will systematically evaluate the clinical therapeutic effects of probiotics in combination with antibiotics on periodontitis.Conclusions:This study will generate evidence for a better clinical decision of patients with periodontitis.Registration number:DOI 10.17605/OSF.IO/QZ6SB (https://osf.io/qz6sb/).     

Radiation-Shielding Devices: The Best Combination for Spine Interventional Procedures

PurposeAlthough many studies have examined the efficiency of various protective devices for reducing the dose of radiation exposure to physicians during interventional pain procedures, no study has compared the protective effect of these devices when they are used in combination. The purpose of this prospective experimental study was to determine the best combination of radiation-shielding devices.Materials and MethodsUsing anthropomorphic phantoms of a physician and patient, we measured the radiation protection efficiency (RPE) of each of the following protection methods and in combination during C-arm–guided simulated lumbar epidural injection: (a) personal protective equipment (PPE), (b) bedside curtain shield (Curtain), (c) x-ray tube filter (Filter), and (d) fluoroscopic collimation method (Collimation). We measured exposure doses using personal electronic dosimeters at the eye, thyroid, and gonad levels for 1 minute. Each experiment was repeated 15 times.ResultsThe radiation exposure dose and RPE with the best single-, double-, and triple-protection methods were as follows: PPE for the single-protection method (11.82 μSv/min, 80.04%), PPE + Collimation for the double-combination method (4.68 μSv/min, 92.09%), and PPE + Collimation + Curtain for the triple-combination method (3.08 μSv/min, 93.39%). Additionally, PPE + Collimation + Curtain + Filter for the quadruple-combination method resulted in a radiation exposure and RPE of 2.91 μSv/min and 93.61%, respectively, compared with nonprotection.ConclusionsThe best single-, double-, and triple-protection method was PPE, PPE + Collimation, and PPE + Collimation + Curtain, respectively. While preparing protective equipment, we recommend prioritizing equipment in this order.     

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.     

Wireless body area network for health monitoring

A Wireless Sensor Networks (WSNs) consists basically of a group of nodes, that communicate with each other through a wireless transmission, and does not need any existing infrastructure. The recent developments in technology and wireless communication, to be used in various applications, foster the development of Wireless Body Area Networks (WBANs). They are emerging as important networks in order to reduce the need for patients, and to help the elderly and chronically ill people to live an independent life. In this paper, we propose a routing protocol for wireless body area networks, to transfer data in the network with minimum energy consumption, and longer network lifetime through multi-hop communication. The proposed protocol has been verified by performing simulations, and the obtained results show that our routing protocol ensures a robust optimisation of the energy consumption which helps to increase the lifetime of the network and its stability.     

基于超效率DEA的天津市基本公共卫生配置资源效率研究

评价天津市各辖区基本公共卫生服务的资源配置效率,寻求有效的资源配置措施和方法,为进一步优化卫生资源配置提供参考依据。方法利用数据包络分析,对天津市16辖区的基本公共卫生服务进行效率评价。结果天津市基本公共卫生服务的资源配置效率整体不高,仅有5辖区达到了规模最优,多数区非DEA有效,且投入过剩与产出不足并存。结论为了达到最优的基本公共卫生服务效率,政府及各级基本公共卫生服务机构必须有效地完善、落实相关政策,优化资源投入结构,统筹地区差异,加强资源供给管理,提高资源利用效率。     

Improving burn surgery education for medical students in China

IntroductionIn China, although burn treatment develops rapidly, and ranks in the forefront of the world, there is a relative shortage of burn specialists, which limits the development of burn education. In traditional curriculum of surgery education, burn surgery education accounts for few proportions, which results in the indifference to the burn surgery among medical students. To date, few research reported the application of Clinical pathway- Problem based Learning (CP-PBL) in burn surgery education. The objective of the study is to explore the teaching effect of this novel teaching method in burn surgery education.MethodsA pilot study was performed. One hundred and six students were randomly divided into a Lecture based Learning (LBL) only group (control group) and a LBL combined Clinical pathway- Problem based Learning group (observation group). A set of test was designed as evaluation criteria based on questions of burn surgery in National Medical Licensing Examination (NMLE) from 2011 to 2018.ResultsThe students with Clinical pathway- Problem based Learning had better academic performances in profession theory. Type A2 and Type A3/A4 scores in the observation group were higher than those in the control group (p < 0.05). The scores of the observation group were higher than those of control group in the domains of understanding and application (p < 0.05). They also have higher favorable impressions of learning experience.ConclusionsMore active approaches yield more learning and are viewed more favorable, which provides a vital message for the evolution of curriculum in Chinese medical schools.     

胃神经官能症予以中西医结合治疗

目的:观察胃神经官能症予以中西医结合治疗的效果。方法:选取我院2018年4月-2019年4月收治的134例胃神经官能症患者进行研究,依照治疗方法的不同,将其分为参照组和研究组两组,每组各67例,参照组实施穴位注射治疗,研究组在参照组的基础上采用中药剂柴胡桂枝汤治疗,对两组患者治疗前后的中医症状体征积分、焦虑评分、抑郁评分、治疗总有效率及复发情况进行观察和比较。结果:治疗前两组患者的食少纳差、胃脘胀痛、少寐多梦及神疲乏力等中医症状体征积分差异不明显(P>0.05),治疗后研究组患者的食少纳差、胃脘胀痛、少寐多梦及神疲乏力等中医症状体征积分明显比参照组优(P<0.05);治疗前两组患者的焦虑评分及抑郁评分差异不明显(P>0.05),治疗后研究组患者的焦虑评分、抑郁评分及复发率明显比参照组低(P<0.05);治疗总有效率明显比参照组高(P<0.05)。结论:穴位注射与中药剂柴胡桂枝汤联合治疗胃神经官能症,可使患者临床症状得到明显改善及治疗有效率得到提高,缓解患者产生的焦虑、抑郁情绪,并且还能使患者治疗后的复发率得到降低,值得进行临床应用和推广。     

Sleep disturbances and restless legs syndrome in postmenopausal women with early breast cancer given adjuvant aromatase inhibitor therapy

IntroductionWhether adjuvant therapy with aromatase inhibitors (AIs) causes sleep disturbances or not in postmenopausal women with early breast cancer (EBC) is still a controversial issue.MethodsBetween March 2014 and November 2017, validated questionnaires for assessing insomnia, anxiety, depression, quality of life (QoL) and restless legs syndrome (RLS) were administered to 160 EBC patients at baseline and after 3, 6, 12, and 24 months of AI therapy.ResultsAI therapy significantly decreased the patients’ QoL, but did not influence insomnia, anxiety or depression. However, it significantly increased the frequency and severity of RLS. Patients with RLS at baseline (19%) or who developed RLS during AI therapy (26.3%) reported statistically lower quality of sleep, higher anxiety and depression, and worse QoL compared to patients who never reported RLS (54.7%).ConclusionAlthough AI therapy does not affect sleep quality, it may increase RLS frequency. The presence of RLS could identify a group of EBC patients who may benefit from psychological support.