Evidence-based medicine is the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients. The practice of evidence-based medicine means to integrate individual clinical expertise with the best available external clinical evidence from systematic research. So evidence and its quality is the key issue of evidence-based medicine. The purpose of this article is to introduce to the healthcare professionals the sources of evidence and how to search for evidence for them.
Evidence has been retrieved through MEDLINE and Cochrane Libray about the treatment for patients with advanced Parkinson’s disease who suffered from on-off, dyskinesia and depression after chronic use of L-dopa. All of the evidence has been evaluated. Methods of evidence-based treatment were drawn up according to the evidence, clinciams’ experiences and patients’ preferences. All symptoms of the patient have been improved obviously.
ObjectiveTo systematically review the efficacy of antidepressants in the prevention of poststroke depression (PSD). MethodsWe searched The Cochrane Library (Issue 2, 2015), PubMed, MEDLINE, EMbase, CNKI and VIP databases to collect randomized controlled trials (RCTs) about antidepressants in preventing PSD from inception to April 2015. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then, meta-analysis was performed using RevMan 5.3 software. ResultsA total of 26 RCTs involving 2 190 patients were included. The results of meta-analysis showed that:compared with the control group, the antidepressants group could significantly reduce the incidence of PSD (OR=0.24, 95%CI 0.17 to 0.36, P<0.000 01). Subgroup analysis based on types of drugs showed that:the selective serotonin reuptake Inhibitor (SSRI) could significantly reduce the incidence of PSD (OR=0.23, 95%CI 0.15 to 0.37, P<0.000 01). Subgroup analysis based on length of time showed that antidepressants could decrease the incidence of PSD in short term (OR=0.11, 95%CI 0.06 to 0.19, P<0.000 01), middle term (OR=0.31, 95%CI 0.21 to 0.46, P<0.000 01) and long term (OR=0.30, 95%CI 0.19 to 0.49, P<0.000 01). In addition, there was no statistical difference in the incidence of adverse effect between the antidepressants group and the control group (P>0.05). ConclusionAntidepressants is effective in the prevention of PSD, and may not affect patient's life quality. Due to the limited quantity and quality of included studies, more high quality studies are needed to verify the above conclusion.
The extraction of neuroimaging features of migraine patients and the design of identification models are of great significance for the auxiliary diagnosis of related diseases. Compared with the commonly used image features, this study directly uses time-series signals to characterize the functional state of the brain in migraine patients and healthy controls, which can effectively utilize the temporal information and reduce the computational effort of classification model training. Firstly, Group Independent Component Analysis and Dictionary Learning were used to segment different brain areas for small-sample groups and then the regional average time-series signals were extracted. Next, the extracted time series were divided equally into multiple subseries to expand the model input sample. Finally, the time series were modeled using a bi-directional long-short term memory network to learn the pre-and-post temporal information within each time series to characterize the periodic brain state changes to improve the diagnostic accuracy of migraine. The results showed that the classification accuracy of migraine patients and healthy controls was 96.94%, the area under the curve was 0.98, and the computation time was relatively shorter. The experiments indicate that the method in this paper has strong applicability, and the combination of time-series feature extraction and bi-directional long-short term memory network model can be better used for the classification and diagnosis of migraine. This work provides a new idea for the lightweight diagnostic model based on small-sample neuroimaging data, and contributes to the exploration of the neural discrimination mechanism of related diseases.
【摘要】 目的 分析无面部血管瘤的Sturge-Weber综合征（SWS）的临床特点。 方法 2008年10月收治1例女性患儿，8岁，因发作性四肢强直入院，患儿无面部血管瘤及眼部异常，仅表现为癫痫。患儿接受丙戊酸钠抗癫痫治疗。 结果 患儿经头部CT、MRI确诊为无面部血管瘤的SWS。抗癫痫治疗后随访12个月，未再发癫痫，智力发育无减退，未出现瘫痪、蛛网膜下腔出血、脑出血、脑卒中样发作等。 结论 无面部血管瘤的SWS确诊依靠头部CT及MRI，治疗方法为药物抗癫痫治疗。复习文献得出无面部血管瘤的SWS患者临床表现不同于有面部血管瘤者，多仅表现出癫痫发作，且药物治疗有效，无需手术切除病灶，预后较好。【Abstract】 Objective To analyze the clinical features of Sturge-Weber syndrome without facial hemangioma. Methods One eight-year-old girl was admitted to the hospital for tonic seizure in October 2008. The physical examination results were normal with neither facial hemangioma nor ocular abnormalities. The only manifestation of the patient was epilepsy. The patient was treated with sodium valproate. Results According to cranial CT and MRI results, the patient was considered to have Sturge-Weber syndrome without facial hemangioma. The patient was treated with anticonvulsant drugs and experienced no recurrence of the seizures or any manifestations of mental retardation, hemiplegia, subarachnoid hemorrhage, cerebral hemorrhage, stroke-like episodes or migraine during the following 12 months of follow-up. Conclusion In the absence of facial hemangioma, the diagnosis can be based on cranial CT and MRI. Sturge-Weber syndrome patients without facial hemangioma are helped by anticonvulsant drugs. According to this case and the reports of literature, most patients without facial hemangioma only manifest epilepsy which can be treated effectively with antiepileptic drugs and such patients have a good prognosis without operation, which is different from those with facial hemangioma.