Median nerve electrical stimulation is a common peripheral nerve electrical stimulation treatment technology in clinic. With simple operation, it has been widely used in clinical to promote coma after craniocerebral trauma, relieve pain, improve cognition, Parkinson’s disease and so on. However, its mechanism has always been a hot topic and difficult part. At present, there are a large number of clinical efficacy studies and animal experiments of median nerve electrical stimulation at home and abroad. This article reviews the clinical application and animal experiments of median nerve electrical stimulation in recent years, and summarizes its mechanism, hoping to contribute to relevant clinical applications and research.
The level of evidence in randomized controlled studies is high. However, it cannot be widely applied due to its high cost, external authenticity, ethics and other reasons. The traditional observational studies reduce the internal authenticity due to various confounding factors, and the level of evidence is low. Regression discontinuity design (RDD) is a design that observes and compares outcome of object around the threshold under practical clinical conditions. Its capability to adjust confounding factors is second only to that of randomized control studies. It can be used in cases where the intervention (or exposure) is directly related to the value of a continuous variable. For instance, whether an HIV patient needs antiretroviral treatment mainly depends on whether the CD4 cell count is lower than 200/μL. Because the measurement of continuous variables has random error, whether intervention is given near the threshold or is close to random, the baseline of patients in the intervention group and non-intervention group near the threshold should be balanced and comparable. Based on this assumption, the causal effect of intervention (or exposure) and outcome can be estimated by comparing the outcomes of populations near the threshold. RDD is mainly applicable to the study of classification outcomes in medicine, among which two-stage least square method, likelihood ratio based estimation method and Bayesian method are more commonly used model estimation methods. However, the application conditions of RDD and the requirement of sample size limit its extensive application in medicine. With the improvement of data accessibility and the development of real world research, RDD will be more widely used in clinical research.
Mixed methods research (MMR) is the third research paradigm that combines quantitative and qualitative research. MMR can overcome limitations of qualitative and quantitative methods by integrating the advantages of these two. The environment of real world research is complicated. When using real world data to assess the health status of patients, process of treatment, outcomes of prevention and treatment, prognosis and prediction, and support for medical policy development, MMR can be applied to tackle research questions more comprehensively for the quality of research.