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Abstract Background Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest (RF)) in predicting walking independence at discharge in stroke patients, as well as to explore the variables that predict prognosis. Methods 778 (80% for the training set and 20% for the test set) stroke patients admitted to China Rehabilitation Research Center between February 2020 and January 2023 were retrospectively included. The training set was used for training models. The test set was used to validate and compare the performance of the four models in terms of area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score. Results Among the three ML models, the AUC of the XGBoost model is significantly higher than that of the SVM and RF models (P

BackgroundPost-stroke aphasia (PSA) is one of the most devastating symptoms after stroke, yet limited treatment options are available. Prolonged intermittent theta burst stimulation (piTBS) is a promising therapy for PSA. However, its efficacy remains unclear. Therefore, we aim to investigate the efficacy of piTBS over the left supplementary motor area (SMA) in improving language function for PSA patients and further explore the mechanism of language recovery.MethodsThis is a randomized, double-blinded, sham-controlled trial. A total of 30 PSA patients will be randomly allocated to receive either piTBS stimulation or sham stimulation for 15 sessions over a period of 3 weeks. The primary outcome is the Western Aphasia Battery Revised (WAB-R) changes after treatment. The secondary outcomes include The Stroke and Aphasia Quality of Life Scale (SAQOL-39 g), resting-state electroencephalogram (resting-state EEG), Event-related potentials (ERP), brain derived neurotrophic factor (BDNF). These outcome measures are assessed before treatment, after treatment, and at 4-weeks follow up. This study was registered in Chinese Clinical Trial Registry (No. ChiCTR23000203238).DiscussionThis study protocol is promising for improving language in PSA patients. Resting-state EEG, ERP, and blood examination can be used to explore the neural mechanisms of PSA treatment with piTBS.Clinical trial registrationhttps://www.chictr.org.cn/index.html, ChiCTR2300074533.

The hippocampus is one of the brain areas affected by autism spectrum disorder (ASD). Individuals with ASD typically have impairments in hippocampus-dependent learning, memory, language ability, emotional regulation, and cognitive map creation. However, the pathological changes in the hippocampus that result in these cognitive deficits in ASD are not yet fully understood. In the present review, we will first summarize the hippocampal involvement in individuals with ASD. We will then provide an overview of hippocampal structural and functional abnormalities in genetic, environment-induced, and idiopathic animal models of ASD. Finally, we will discuss some pharmacological and non-pharmacological interventions that show positive impacts on the structure and function of the hippocampus in animal models of ASD. A further comprehension of hippocampal aberrations in ASD might elucidate their influence on the manifestation of this developmental disorder and provide clues for forthcoming diagnostic and therapeutic innovation.

In terms of both economy and sustainability, rural areas can greatly benefit from adopting E-commerce. The Chinese government is currently devoting significant efforts to developing agricultural E-commerce. However, one of the most significant problems is the lack of effective tools for evaluating regional potentials in this regard, possibly leading to inappropriate policymaking, investment allocation, and regional planning. To address this issue, this study proposes a novel and effective method for evaluating regional potentials for agricultural E-commerce development, integrating the method based on the removal effects of criteria (MEREC), Heronian mean operator, and combined compromise solution (CoCoSo) method. The method’s effectiveness is then tested and confirmed in the Chinese city of Yibin through an evaluation of its ten regions. The results suggest that such a method is robust, objective, and able to consider indicator interactions effectively. By applying this method, regional agricultural E-commerce development potentials can be thoroughly evaluated and ranked. This study contributes to the literature by providing new analytical techniques for agricultural studies, as well as by supporting political and investment decision-making for governments and E-commerce practitioners in the agriculture sector.

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) system over Nakagami-m channels. The single-antenna base station serves two single-antenna NOMA users based on statistical channel state information (CSI). We derive the closed-form expression of the exact outage probability under a given decoding order, and we also deduce the asymptotic outage probability and diversity order in a high-SNR regime. Then, we analyze all the possible power allocation ranges and theoretically prove the optimal power allocation range under the corresponding decoding order. The demarcation points of the optimal power allocation ranges are affected by target data rates and total power, without an effect from the CSI. In particular, the values of the demarcation points are proportional to the total power. Furthermore, we formulate a joint decoding order and power allocation optimization problem to maximize the sum throughput, which is solved by efficiently searching in our obtained optimal power allocation ranges. Finally, Monte Carlo simulations are conducted to confirm the accuracy of our derived exact outage probability. Numerical results show the accuracy of our deduced demarcation points of the optimal power allocation ranges. And the optimal decoding order is not constant at different total transmit power levels.

BackgroundUpper limb motor recovery is one of the important goals of stroke rehabilitation. Intermittent theta burst stimulation (iTBS), a new type of repetitive transcranial magnetic stimulation (rTMS), is considered a potential therapy. However, there is still no consensus on the efficacy of iTBS for upper limb motor dysfunction after stroke. Stimulus dose may be an important factor affecting the efficacy of iTBS. Therefore, we aim to investigate and compare the effects and neural mechanisms of three doses of iTBS on upper limb motor recovery in stroke patients, and our hypothesis is that the higher the dose of iTBS, the greater the improvement in upper limb motor function.MethodsThis prospective, randomized, controlled trial will recruit 56 stroke patients with upper limb motor dysfunction. All participants will be randomized in a 1:1:1:1 ratio to receive 21 sessions of 600 pulses active iTBS, 1,200 pulses active iTBS, 1,800 pulses active iTBS, or 1,800 pulses sham iTBS in addition to conventional rehabilitation training. The primary outcome is the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) score from baseline to end of intervention, and the secondary outcomes are the Wolf Motor Function Test (WMFT), Grip Strength (GS), Modified Barthel Index (MBI), and Stroke Impact Scale (SIS). The FMA-UE, MBI, and SIS are assessed pre-treatment, post-treatment, and at the 3-weeks follow-up. The WMFT, GS, and resting-state functional magnetic resonance imaging (rs-fMRI) data will be obtained pre- and post-treatment.DiscussionThe iTBS intervention in this study protocol is expected to be a potential method to promote upper limb motor recovery after stroke, and the results may provide supportive evidence for the optimal dose of iTBS intervention.

BackgroundPost-stroke cognitive impairment (PSCI) is a significant health concern. Transcranial magnetic stimulation (TMS) is considered a promising rehabilitation therapy for improving cognition, and the effects of excitatory TMS on PSCI have received much attention in recent years. However, the effects of different cerebral hemispheres on excitatory TMS treatment of cognitive impairment have not been studied. This review aimed to study the effects of excitatory TMS over the dorsolateral prefrontal cortex (DLPFC) of different cerebral hemispheres on the cognitive function of patients with PSCI.MethodsLiterature published in PubMed, Web of Science, Embase, Cochrane Library, Scopus, and Wiley from inception to September 30, 2022, were searched. Two researchers independently performed literature screening, data extraction, and quality assessment. Furthermore, we conducted a meta-analysis using RevMan software (version 5.4) and rated the strength of evidence using GRADEpro.ResultsA total of 19 studies were included in this meta-analysis. The results showed that excitatory TMS over the left hemisphere DLPFC was significantly better in improving global cognition (SMD = 2.26, 95% CI 1.67–2.86, P < 0.00001; vs. SMD = 2.53, 95% CI 1.86–3.20, P < 0.00001), memory (SMD = 1.29, 95% CI 0.72–1.87, P < 0.0001), attention (SMD = 2.32, 95% CI 1.64–3.01, P < 0.00001), executive (SMD = 0.64, 95% CI 0.21–1.07, P = 0.004), P300 latency (SMD = 2.69, 95% CI 2.13–3.25, P < 0.00001), and depression (SMD = 0.95, 95% CI 0.26–1.63, P = 0.007) than that of the control group, but the effect on improving activities of daily living (ADL) was unclear (P = 0.03 vs. P = 0.17). Subgroup analysis further showed that excitatory TMS over the right hemisphere DLPFC was effective in improving the global cognition of PSCI patients (P < 0.00001), but the stimulation effect over the ipsilateral hemisphere DLPFC was unclear (P = 0.11 vs. P = 0.003). Additionally, excitatory TMS over the ipsilateral hemisphere DLPFC showed no statistical difference in improving ADL between the two groups (P = 0.25).ConclusionsCompared to other hemispheric sides, excitatory TMS over the left hemisphere DLPFC was a more effective stimulation area, which can significantly improved the global cognitive function, memory, attention, executive, P300 latency, and depression in patients with PSCI. There was no apparent therapeutic effect on improving activities of daily living (ADL). In the future, more randomized controlled trials with large-sample, high quality, and follow-up are necessary to explore a usable protocol further.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022369096.

ObjectiveTraumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. In this study, the characteristics of the patients, who were admitted to the China Rehabilitation Research Center, were elucidated in the TBI database, and a prediction model based on the Fugl-Meyer assessment scale (FMA) was established using this database.MethodsA retrospective analysis of 463 TBI patients, who were hospitalized from June 2016 to June 2020, was performed. The data of the patients used for this study included the age and gender of the patients, course of TBI, complications, and concurrent dysfunctions, which were assessed using FMA and other measures. The information was collected at the time of admission to the hospital and 1 month after hospitalization. After 1 month, a prediction model, based on the correlation analyses and a 1-layer genetic algorithms modified back propagation (GA-BP) neural network with 175 patients, was established to predict the FMA. The correlations between the predicted and actual values of 58 patients (prediction set) were described.ResultsMost of the TBI patients, included in this study, had severe conditions (70%). The main causes of the TBI were car accidents (56.59%), while the most common complication and dysfunctions were hydrocephalus (46.44%) and cognitive and motor dysfunction (65.23 and 63.50%), respectively. A total of 233 patients were used in the prediction model, studying the 11 prognostic factors, such as gender, course of the disease, epilepsy, and hydrocephalus. The correlation between the predicted and the actual value of 58 patients was R2 = 0.95.ConclusionThe genetic algorithms modified back propagation neural network can predict motor function in patients with traumatic brain injury, which can be used as a reference for risk and prognosis assessment and guide clinical decision-making.

BackgroundCombined cognitive and physical intervention is commonly used as a non-pharmacological therapy to improve cognitive function in older adults, but it is uncertain whether combined intervention can produce stronger cognitive gains than either single cognitive or sham intervention. To address this uncertainty, we performed a systematic review and meta-analysis to evaluate the effects of combined intervention on cognition in older adults with and without mild cognitive impairment (MCI).MethodsWe systematically searched eight databases for relevant articles published from inception to November 1, 2021. Randomized controlled trials (RCTs) and non-randomized controlled trials (NRCTs) were used to compare the effects of the combined intervention with a single cognitive or sham intervention on cognition in older adults with and without MCI aged ≥ 50 years. We also searched Google Scholar, references of the included articles, and relevant reviews. Two independent reviewers performed the article screening, data extraction, and bias assessment. GRADEpro was used to rate the strength of evidence, and RevMan software was used to perform the meta-analysis.ResultsSeventeen studies were included in the analysis, comprising eight studies of cognitively healthy older adults and nine studies of older adults with MCI. The meta-analysis showed that the combined intervention significantly improved most cognitive functions and depression (SMD = 0.99, 95% CI 0.54–1.43, p < 0.0001) in older adults compared to the control groups, but the intervention effects varied by cognition domains. However, there was no statistically significant difference in the maintenance between the combined and sham interventions (SMD = 1.34, 95% CI −0.58–3.27, p = 0.17). The subgroup analysis also showed that there was no statistical difference in the combined intervention to improve global cognition, memory, attention, and executive function between cognitive healthy older adults and older adults with MCI.ConclusionsCombined intervention improves cognitive functions in older adults with and without MCI, especially in global cognition, memory, and executive function. However, there was no statistical difference in the efficacy of the combined intervention to improve cognition between cognitive healthy older adults and older adults with MCI. Moreover, the maintenance of the combined intervention remains unclear due to the limited follow-up data and high heterogeneity. In the future, more stringent study designs with more follow-ups are needed further to explore the effects of combined intervention in older adults.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier: CRD42021292490.

BackgroundRepetitive transcranial magnetic stimulation (rTMS) is a promising therapy to promote recovery of the upper limb after stroke. According to the regulation of cortical excitability, rTMS can be divided into excitatory rTMS and inhibitory rTMS, and excitatory rTMS includes high-frequency rTMS (HF-rTMS) or intermittent theta-burst stimulation (iTBS). We aimed to evaluate the effects of excitatory rTMS over the ipsilesional hemisphere on upper limb motor recovery after stroke.MethodsDatabases of PubMed, Embase, ISI Web of Science, and the Cochrane Library were searched for randomized controlled trials published before 31 December 2021. RCTs on the effects of HF-rTMS or iTBS on upper limb function in patients diagnosed with stroke were included. Two researchers independently screened the literature, extracted the data, and assessed quality. The meta-analysis was performed by using Review Manager Version 5.4 software.ResultsFifteen studies with 449 participants were included in this meta-analysis. This meta-analysis found that excitatory rTMS had significant efficacy on upper limb motor function (MD = 5.88, 95% CI, 3.32–8.43, P < 0.001), hand strength (SMD = 0.53, 95% CI, 0.04–1.01, P = 0.03), and hand dexterity (SMD = 0.76, 95% CI, 0.39–1.14, P < 0.001). Subgroup analyses based on different types of rTMS showed that both iTBS and HF-rTMS significantly promoted upper limb motor function (iTBS, P < 0.001; HF-rTMS, P < 0.001) and hand dexterity (iTBS, P = 0.01; HF-rTMS, P < 0.001) but not hand strength (iTBS, P = 0.07; HF-rTMS, P = 0.12). Further subgroup analysis based on the duration of illness demonstrated that applying excitatory rTMS during the first 3 months (