BackgroundEvidence suggests that schizophrenia may be associated with an increased risk of dementia, but results from prior studies have been inconsistent. This study aimed to estimate the relationship between schizophrenia and incident dementia using a quantitative meta-analysis.MethodsSeveral databases were used to gather relevant information, including PubMed, Embase, and Web of Science, with the publication date of articles limited up to December 23, 2017. All studies reported a multivariate-adjusted estimate, represented as relative risk (RR) with 95% confidence intervals (CIs), for the association between schizophrenia and risk of dementia incidence. Pooled RRs were calculated using a random-effects model.ResultsSix studies met our inclusion criteria for this meta-analysis, which included 206,694 cases of dementia and 5,063,316 participants. All individuals were without dementia at baseline. Overall, the quantitative meta-analysis suggested that subjects with schizophrenia were associated with a significantly greater risk of dementia incidence (RR 2.29; 95% CI 1.35–3.88) than those without.ConclusionThe results of this meta-analysis indicate that individuals with schizophrenia may have an increased risk for the development of dementia. Future studies should explore whether schizophrenia is a modifiable risk factor for dementia.

PurposeThere is a need for biomarkers in multiple sclerosis (MS) to make an early diagnosis and monitor its progression. This study was designed to evaluate the value of neurofilament light (NFL) chain levels as cerebrospinal fluid (CSF) or blood biomarker in patients with MS by using a quantitative meta-analysis.MethodsThe PubMed, Embase, and Web of Science databases were systematically searched for relevant studies. Articles in English that evaluated the utility of NFL in CSF and blood in the diagnosis of MS were included. Data were extracted by two independent researchers. Mean (± SD) NFL concentration for MS patients and control subjects were extracted. Review Manager version 5.3 software with a continuous-variable random-effects model was used to summarize the diagnostic indexes from eligible studies. The Newcastle–Ottawa Scale was used for assessing the quality and risk of bias of included studies. In addition, subgroup analysis and meta-regression were performed to assess potential heterogeneity sources.ResultsThe meta-analysis included 13 articles containing results from 15 studies. A total of 10 studies measured NFL levels in CSF and five studies measured NFL levels in blood. Data were available on 795 participants in CSF and 1,856 participants in blood. Moreover, CSF NFL in MS patients was higher than that in healthy control groups (pooled standard mean difference [Std.MD]=0.88, 95% CI [0.50, 1.26], P<0.00001) and serum NFL in MS patients was higher than that in control subjects (pooled Std.MD=0.47, 95% CI [0.24, 0.71], P<0.0001).ConclusionNFL chain has significantly increased in MS patients, which substantially strengthens the clinical evidence of the NFL in MS. The NFL may be used as a prognostic biomarker to monitor disease progression, disease activity, and treatment efficacy in the future.

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Background: To determine the influence of gender on the different pain subtypes experienced by patients with Parkinson's disease (PD). Methods: Two hundred patients with PD were recruited for this research. Demographic features for all patients were recorded, as well as clinical data on age, disease duration, levodopa equivalent daily dose (LEDD), and scores for Unified Parkinson's Disease Rating Scale-III (UPDRS III), Hoehn-Yahr Scale (H&Y), King's Parkinson's disease Pain Scale (KPPS), Pittsburgh Sleep Quality Index (PSQI), Mini-mental State Examination (MMSE), activities of daily living scale (ADL), Hamilton Depression Rating Scale (HAMD), and Hamilton Anxiety Rating Scale (HAMA) scales. Results: Male and female patients showed no significant differences in terms of age, disease duration, LEDD, H&Y stage, and UPDRS III, HAMD, HAMA, PSQI and ADL scores. Women showed significantly lower MMSE than men, but their KPPS scores were higher (both p < 0.05). Female also showed significantly higher scores for chronic, fluctuation-related pain and oro-facial pain and more discoloration;edema/swelling than males (p < 0.05). Conclusions: Female gender was associated with pain in PD patients, with stronger associations for certain subtypes of PD-related pain.

Purpose To assess Parkinson’s disease (PD)-related pain using the Chinese translation of King’s Parkinson’s disease Pain Scale (KPPS). Patients and Methods A cohort of 200 patients with primary PD was recruited for this study. Their demographic and clinical features, including age, disease duration, levodopa equivalent daily dose (LEDD), and scores on the Unified Parkinson’s Disease Rating Scale-III (UPDRS III), Hoehn-Yahr Scale (H&Y), Mini-Mental State Examination (MMSE), Activities of Daily Living Scale (ADL), Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), Pittsburgh Sleep Quality Index (PSQI), Visual Analogue Scale (VAS) and KPPS, were recorded. Results The prevalence of PD-related pain was 44.5%. Among the patients with PD-related pain, the average KPPS score was 41.2 ± 26.8. Pain was most commonly located in the lower limbs (60.7%), upper limbs (22.5%) and waist (21.3%). The most common pain type was musculoskeletal pain (68.5%). Compared with the PD group without pain, the PD group with pain had a longer disease duration ( p = 0.022), higher LEDD ( p = 0.008), higher UPDRSIII score ( p = 0.018), higher H&Y stage ( p = 0.003), higher HAMD score ( p < 0.001), higher HAMA score ( p < 0.001), lower ADL score ( p = 0.046) and higher PSQI score ( p < 0.001). PD-related pain was correlated with the H&Y stage and the PSQI score ( p < 0.05). Cut-off points of 0, 34, and 70 were obtained to discriminate pain severity levels between no pain, mild, moderate, and severe pain, respectively. Conclusion Chinese version of KPPS is not only an easy tool for characterization and scoring of pain in PD patients but also has the ability to distinguish between different levels of pain severity.