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Introduction: Central poststroke pain (CPSP) develops commonly after stroke, which impairs the quality of life, mood, and social functioning. Current pharmacological approaches for the treatment of CPSP are not satisfactory. Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive technique which has been recommended for the treatment of chronic CPSP. However, few studies have evaluated the analgesic effects of rTMS in patients with acute neuropathic pain after stroke. Methods: We evaluated the analgesic effects of rTMS applied over the upper extremity area of the motor cortex (M1) in patients with acute CPSP. Forty patients were randomized to receive either rTMS (10 Hz, 2000 stimuli) (n = 20) or a sham intervention (n = 20) for 3 weeks. The Numeric Rating Scale (NRS), Short-form McGill Pain Questionnaire-2 (SF-MPQ-2, Chinese version), Hamilton Anxiety Scale (HAM-A), Hamilton Depression Scale (HAM-D), brain-derived neurotrophic factor (BDNF) levels, and motor-evoked potentials (MEP) were analyzed at baseline, 3 days, 1 week, 2 weeks, and 3 weeks. Results: Significant treatment–time interactions were found for pain intensity. Compared with the sham group, the NRS and SF-MPQ-2 scores were significantly lower on the seventh day of treatment in the rTMS group (P < 0.001, Cohen's d = 1.302) (P = 0.003, Cohen's d = 0.771), and this effect lasted until the third week (P = 0.001, Cohen's d = 0.860) (P = 0.027, Cohen's d = 0.550). The HAM-A and HAM-D scores did not change in the rTMS group when compared with the sham group (P = 0.341, Cohen's d = 0.224) (P = 0.356, Cohen's d = 0.217). The serum BDNF levels were significantly higher in the treated group (P = 0.048, Cohen's d = −0.487), and the resting motor threshold (RMT) decreased by 163.65%. Conclusion: Our findings indicate that rTMS applied over the upper extremity area of the motor cortex can effectively alleviate acute CPSP, possibly by influencing cortical excitability and serum BDNF secretion. Trial Registration: This trial is registered with Clinical Trial Registry of China: Reg. No. ChiCTR-INR-17012880. [ABSTRACT FROM AUTHOR]

Background: Prediction of the functional outcome for patients with convulsive status epilepticus (CSE) has been a challenge. The aim of this study was to characterize the prognostic factors and functional outcomes of patients after CSE in order to develop a practicable scoring system for outcome prediction.Methods: We performed a retrospective explorative analysis on consecutive patients diagnosed with CSE between March, 2008 and November, 2014 in a tertiary academic medical center in northwest China. The modified Rankin Scale (mRS) was used to measure the functional outcome at three months post discharge.Results: A total of 132 CSE patients was included, with a median age of 25.5 years and 60.6% were male. Three months post discharge, an unfavorable outcome with mRS of 3-6 was seen in 62 (47.0%) patients, 25 (18.9%) of whom died. Logistic regression analysis revealed that encephalitis (p = 0.029), nonconvulsive SE (p = 0.018), diazepam resistance (p = 0.005), image abnormalities (unilateral lesions, p = 0.027; bilateral lesions or diffuse cerebral edema, p < 0.001) and tracheal intubation (p = 0.032) were significant independent predictors for unfavorable outcomes. Based on the coefficients in the model, these predictors were assigned a value of 1 point each, with the exception of the image, creating a 6-point scoring system, which we refer to as END-IT, for the outcome prediction of CSE. The area under the receiver operating characteristic curve for the END-IT score was 0.833 and using a cut-off point of 3 produced the highest sum sensitivity (83.9%) and specificity (68.6%). Compared with status epilepticus severity score (STESS) and Epidemiology-based Mortality score in SE (EMSE), END-IT score showed better discriminative power and predictive accuracy for the outcome prediction.Conclusions: We developed an END-IT score with a strong discriminative power for predicting the functional outcome of CSE patients. External prospective validation in different cohorts is needed for END-IT score. [ABSTRACT FROM AUTHOR]

Background: Prediction of the functional outcome for patients with convulsive status epilepticus (CSE) has been a challenge. The aim of this study was to characterize the prognostic factors and functional outcomes of patients after CSE in order to develop a practicable scoring system for outcome prediction., Methods: We performed a retrospective explorative analysis on consecutive patients diagnosed with CSE between March, 2008 and November, 2014 in a tertiary academic medical center in northwest China. The modified Rankin Scale (mRS) was used to measure the functional outcome at three months post discharge., Results: A total of 132 CSE patients was included, with a median age of 25.5 years and 60.6% were male. Three months post discharge, an unfavorable outcome with mRS of 3-6 was seen in 62 (47.0%) patients, 25 (18.9%) of whom died. Logistic regression analysis revealed that encephalitis (p = 0.029), nonconvulsive SE (p = 0.018), diazepam resistance (p = 0.005), image abnormalities (unilateral lesions, p = 0.027; bilateral lesions or diffuse cerebral edema, p < 0.001) and tracheal intubation (p = 0.032) were significant independent predictors for unfavorable outcomes. Based on the coefficients in the model, these predictors were assigned a value of 1 point each, with the exception of the image, creating a 6-point scoring system, which we refer to as END-IT, for the outcome prediction of CSE. The area under the receiver operating characteristic curve for the END-IT score was 0.833 and using a cut-off point of 3 produced the highest sum sensitivity (83.9%) and specificity (68.6%). Compared with status epilepticus severity score (STESS) and Epidemiology-based Mortality score in SE (EMSE), END-IT score showed better discriminative power and predictive accuracy for the outcome prediction., Conclusions: We developed an END-IT score with a strong discriminative power for predicting the functional outcome of CSE patients. External prospective validation in different cohorts is needed for END-IT score.