Objective:The models currently available for predicting the risk of seizure recurrence after antiepileptic drug (AED) withdrawal in adult epilepsy patients include the prediction model developed by Lamberink et al (Lamberink model, 2017) and the Medical Research Council prediction model (MRC model, 1993). However, there was no external validation for the two models. The purpose of this study was to perform an independent external validation and a comparison of the Lamberink model and the MRC model in adult patients. Methods: The study population was recruited from the Wenzhou Epilepsy Follow-up Registry Database (WEFURD). All the predictors of the Lamberink and MRC models and the occurrence of seizure recurrence in the participants were collected based on the WEFURD. Participants' predicted probabilities of seizure recurrence were obtained by a Web-based tool and the prognostic index formula. The external validation of the Lamberink model and the MRC model were quantified by discrimination, calibration, and decision curve analysis (DCA). Results: Of 212 patients, 126 (59.4%) had seizure recurrence after AED withdrawal. The Lamberink 2-year model, the Lamberink 5-year model, the MRC 1-year model, and the MRC 2-year model had areas under the curve of 0.71 (95% confidence interval [CI] = 0.64-0.78), 0.68 (95% CI = 0.60-0.76), 0.60 (95% CI = 0.50-0.69), and 0.58 (95% CI = 0.50-0.66), respectively. Additionally, the Lamberink 2-year model had a significantly better integrated discrimination improvement than the MRC 2-year model (P < .001). Regarding calibration, the Lamberink 2-year model (P = .121) and the MRC 1-year model (P = .264) were well calibrated, but the Lamberink 5-year model (P = .022) and the MRC 2-year model (P = .008) were not. In the DCA, the Lamberink 2-year model performed well at threshold probabilities of 30%-65%. Significance: This external validation shows that the Lamberink 2-year model might be more accurate and has greater clinical benefit than others for guiding drug withdrawal in adult epilepsy clinics. 116 | LIN et aL. K E Y W O R D S adult epilepsy, drug withdrawal, external validation, prediction model, seizure recurrence Key Points • The Lamberink 2-year model had the highest AUC (0.71) among the models in the external validation • The Lamberink 2-year model (P = .121) and the MRC 1-year model (P = .264) were well calibrated, but the other prediction models were not • In the DCA, the Lamberink 2-year model performed well at threshold probabilities of 30%-65%

The objective of this meta-analysis was to evaluate the effects of coenzyme Q10 (CoQ10) for the treatment of Parkinson's disease (PD) patients in order to arrive at qualitative and quantitative conclusions about the efficacy of CoQ10. Databases searched included PubMed, Google scholar, CNKI, Wan-Fang, and the Cochrane Library from inception to March 2016. We only included sham-controlled, randomized clinical trials of CoQ10 intervention for motor dysfunction in patients with PD. Relevant measures were extracted independently by two investigators. Weighted mean differences (WMD) were calculated with random-effects models. Eight studies with a total of 899 patients were included. Random-effects analysis revealed a pooled WMD of 1.02, indicating no significant difference when CoQ10 treatment compared with placebo in terms of UPDRS part 3 (p = 0.54). Meanwhile, the effect size of UPDRS part 1, UPDRS part 2, and total UPDRS scores were similar in CoQ10 group with in placebo group (p > 0.05). Moreover, we found CoQ10 was well tolerated compared with placebo group. Subgroup analysis showed that the effect size of CoQ10 in monocentric studies was larger than in multicenter studies. Using the GRADE criteria, we characterized the quality of evidence presented in this meta-analysis as moderate to high level. The current meta-analysis provided evidence that CoQ10 was safe and well tolerated in participants with PD and no superior to placebo in terms of motor symptoms. According to these results, we cannot recommend CoQ10 for the routine treatment of PD right now.

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Recognition of the spectrum of eight-and-a-half syndrome allows precise anatomic localization of the lesion to pontine tegmentum region.

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Objective: Explore Chinese patients' risk-benefit preferences and willingness-to-pay (WTP) for antiepileptic drugs (AEDs) treatment through the discrete choice experiment (DCE).Method: Six attributes including the efficacy of AEDs, adverse reactions (digestive system, neuropsychic systems, and the effects on the fetus), dosing frequency and drug costs (to estimate patient WTP) were included in the DCE questionnaire based on results collected from literature reviews, expert consultation, and patient survey. The alternative-specific conditional logit model was used to analyze patient preference and WTP for each attribute and its level and to assess the sociodemographic impact and clinical characteristics.Results: A total of 151 valid questionnaires were collected. The result shows that five out of the six attributes are significant, except the dosing frequency. Among the six attributes, the efficacy of AEDs (10.0; 95% CI 8.9–11.1) is mostly concerned by patients, followed by the effects of AEDs on the fetus (8.9; 95% CI 7.7–10.1), duration of side effects in the neuropsychic system (4.9; 95% CI 3.7–6.0) and adverse reactions of the digestive system (3.2; 95% CI 1.5–4.2). The patients surveyed are willing to spend ¥ 1,246 (95% CI, ¥ 632- ¥ 1,861) per month to ensure 100% seizure control, and ¥ 1,112 (95% CI, ¥ 586–¥ 1,658) to reduce the risk of the drug affecting the fetus to 3%. Besides, it was found that personal characteristics including the intention for conception and AEDs treatment regimens have statistical significance.Conclusion: Improving the drug's efficacy and reducing its side effects are predominant considerations for patients with epilepsy in China, especially for those who are concerned about the seizure control and the drug effect on the fetus. This finding is useful to physicians and can encourage shared decision-making between the patients and their doctors in the clinic.