A protocol of Chinese expert consensuses for the management of health risk in the general public.

Introduction: Non-communicable diseases (NCDs) represent the leading cause of mortality and disability worldwide. Robust evidence has demonstrated that modifiable lifestyle factors such as unhealthy diet, smoking, alcohol consumption and physical inactivity are the primary causes of NCDs. Although a series of guidelines for the management of NCDs have been published in China, these guidelines mainly focus on clinical practice targeting clinicians rather than the general population, and the evidence for NCD prevention based on modifiable lifestyle factors has been disorganized. Therefore, comprehensive and evidence-based guidance for the risk management of major NCDs for the general Chinese population is urgently needed. To achieve this overarching aim, we plan to develop a series of expert consensuses covering 15 major NCDs on health risk management for the general Chinese population. The objectives of these consensuses are (1) to identify and recommend suitable risk assessment methods for the Chinese population; and (2) to make recommendations for the prevention of major NCDs by integrating the current best evidence and experts' opinions. Methods and analysis: For each expert consensus, we will establish a consensus working group comprising 40-50 members. Consensus questions will be formulated by integrating literature reviews, expert opinions, and an online survey. Systematic reviews will be considered as the primary evidence sources. We will conduct new systematic reviews if there are no eligible systematic reviews, the methodological quality is low, or the existing systematic reviews have been published for more than 3 years. We will evaluate the quality of evidence and make recommendations according to the GRADE approach. The consensuses will be reported according to the Reporting Items for Practice Guidelines in Healthcare (RIGHT).

Age and Sex Affect Essential Tremor (ET) Plus: Clinical Heterogeneity in ET Based on the National Survey in China.

The new term essential tremor (ET) plus was proposed in the 2018 tremor consensus criteria. The National Survey of Essential Tremor Plus in China, a large multicenter registry study, aimed to evaluate the clinical features of pure ET and ET plus and explore possible factors related to ET plus. All patients with ET underwent neurological examination and neuropsychological assessment at 17 clinical sites. The diagnosis was made according to the 2018 consensus criteria. Clinicodemographic characteristics were analyzed. A total of 1160 patients were included, including 546 patients with pure ET and 614 patients with ET plus. The proportion of females was significantly higher in the ET plus than that in the pure ET (P = 0.001). The age at onset (AAO) of pure ET showed a bimodal distribution, with peaks in the 2nd and 5th decades. However, the AAO of the ET plus group demonstrated a skewed distribution, with a single peak in the 6th decade. Female sex (OR=1.645, P<0.001), older age (OR=1.023, P<0.001), lower educational level (OR=0.934, P<0.001), head tremor (OR=1.457, P<0.001), and higher the Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS)-II scores (OR=1.134, P<0.001) were significantly associated with ET plus. Old age and female sex may contribute to ET plus development. Pure ET showed a bimodal distribution for AAO, whereas ET plus showed a unimodal distribution. It remains unclear whether pure ET and ET plus are merely different stages of a single disease or represent distinct disease entities.

Characteristics of fatigue in Parkinson's disease: A longitudinal cohort study.

Objective: To assess the prevalence, evolution, clinical characteristics, correlates and predictors of fatigue as well as to investigate the influence of comorbid fatigue on the longitudinal changes in motor and non-motor symptoms over a 2-year longitudinal follow-up period in a large cohort of patients with Parkinson's disease (PD). Materials and methods: A total of 2,100 PD patients were enrolled from the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC), and their motor and non-motor symptoms were assessed biennially using comprehensive scales, including the 16-item Parkinson Fatigue Scale (PFS-16). Each PD patient was categorized as PD with or without fatigue on the basis of a cut-off mean PFS-16 score of 3.3. Results: The prevalence of fatigue in our cohort was 36.8%. Compared to PD patients without fatigue, PD patients with fatigue were more likely to be older, have a longer disease duration, and higher baseline levodopa equivalent daily dose (all p < 0.05). Moreover, PD patients with fatigue showed more severe motor and non-motor phenotypes than those without fatigue. Overall, high total Unified Parkinson's Disease Rating Scale (UPDRS) score (odds ratio [OR] = 1.016, 95% confidence interval [CI]: 1.009-1.024), Non-Motor Symptoms Scale score (OR = 1.022, 95% CI: 1.015-1.029), postural instability and gait difficulty (PIGD) subtype (OR = 1.586, 95% CI: 1.211-2.079), presence of excessive daytime sleepiness (EDS; OR = 1.343, 95% CI: 1.083-1.666), and wearing-off (OR = 1.282, 95% CI: 1.023-1.607) were significantly associated with fatigue in PD patients (all p < 0.05). High total UPDRS score at baseline (OR = 1.014, 95% CI: 1.002-1.027, p = 0.028) increased the risk of developing fatigue during follow-up. Although significant, the odds ratios were low and confidence intervals were narrow. Analysis of disease progression showed significant group differences in motor and non-motor symptoms. In comparison with the never-fatigue group, the persistent-fatigue group showed significantly greater progression in motor, autonomic dysfunction, sleep, depression and cognitive symptoms (all p < 0.05). Conclusion: Increased disease severity, presence of the PIGD subtype, EDS, and wearing-off were associated with fatigue in PD patients. Significant subgroup-level differences were observed in the progression of motor and non-motor symptoms across different fatigue subgroups of PD patients.

Genome-wide association study using whole-genome sequencing identifies risk loci for Parkinson's disease in Chinese population.

Genome-wide association studies (GWASs) have identified numerous susceptibility loci for Parkinson's disease (PD), but its genetic architecture remains underexplored in populations of non-European ancestry. To identify genetic variants associated with PD in the Chinese population, we performed a GWAS using whole-genome sequencing (WGS) in 1,972 cases and 2,478 controls, and a replication study in a total of 8209 cases and 9454 controls. We identified one new risk variant rs61204179 (Pcombined = 1.47 × 10-9) with low allele frequency, four previously reported risk variants (NUCKS1/RAB29-rs11557080, SNCA-rs356182, FYN-rs997368, and VPS13C-rs2251086), as well as three risk variants in LRRK2 coding region (A419V, R1628P, and G2385R) with genome-wide significance (P < 5 × 10-8) for PD in Chinese population. Moreover, of the reported genome-wide significant risk variants found mostly in European ancestry populations, the correlation coefficient (rb) of effect size accounting for sampling errors was 0.91 between datasets and 63.6% attained P < 0.05 in Chinese population. Accordingly, we estimated a heritability of 0.14-0.18 for PD, and a moderate genetic correlation between European ancestry and Chinese populations (rg = 0.47, se = 0.21). Polygenic risk score (PRS) analysis revealed that individuals with PRS values in the highest quartile had a 3.9-fold higher risk of developing PD than the lowest quartile. In conclusion, the present GWAS identified PD-associated variants in Chinese population, as well as genetic factors shared among distant populations. Our findings shed light on the genetic homogeneity and heterogeneity of PD in different ethnic groups and suggested WGS might continue to improve our understanding of the genetic architecture of PD.

Subtyping of early-onset Parkinson's disease using cluster analysis: A large cohort study.

Background: Increasing evidence suggests that early-onset Parkinson's disease (EOPD) is heterogeneous in its clinical presentation and progression. Defining subtypes of EOPD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies. Objective: To identify clinical subtypes of EOPD, assess the clinical characteristics of each EOPD subtype, and compare the progression between EOPD subtypes. Materials and methods: A total of 1,217 patients were enrolled from a large EOPD cohort of the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) between January 2017 and September 2021. A comprehensive spectrum of motor and non-motor features were assessed at baseline. Cluster analysis was performed using data on demographics, motor symptoms and signs, and other non-motor manifestations. In 454 out of total patients were reassessed after a mean follow-up time of 1.5 years to compare progression between different subtypes. Results: Three subtypes were defined: mild motor and non-motor dysfunction/slow progression, intermediate and severe motor and non-motor dysfunction/malignant. Compared to patients with mild subtype, patients with the severe subtype were more likely to have rapid eye movement sleep behavior disorder, wearing-off, and dyskinesia, after adjusting for age and disease duration at baseline, and showed a more rapid progression in Unified Parkinson's Disease Rating Scale (UPDRS) total score (P = 0.002), UPDRS part II (P = 0.014), and III (P = 0.001) scores, Hoehn and Yahr stage (P = 0.001), and Parkinson's disease questionnaire-39 item version score (P = 0.012) at prospective follow-up. Conclusion: We identified three different clinical subtypes (mild, intermediate, and severe) using cluster analysis in a large EOPD cohort for the first time, which is important for tailoring therapy to individuals with EOPD.

Constructing prediction models for excessive daytime sleepiness by nomogram and machine learning: A large Chinese multicenter cohort study.

Objective: Although risk factors for excessive daytime sleepiness (EDS) have been reported, there are still few cohort-based predictive models for EDS in Parkinson's disease (PD). This 1-year longitudinal study aimed to develop a predictive model of EDS in patients with PD using a nomogram and machine learning (ML). Materials and methods: A total of 995 patients with PD without EDS were included, and clinical data during the baseline period were recorded, which included basic information as well as motor and non-motor symptoms. One year later, the presence of EDS in this population was re-evaluated. First, the baseline characteristics of patients with PD with or without EDS were analyzed. Furthermore, a Cox proportional risk regression model and XGBoost ML were used to construct a prediction model of EDS in PD. Results: At the 1-year follow-up, EDS occurred in 260 of 995 patients with PD (26.13%). Baseline features analysis showed that EDS correlated significantly with age, age of onset (AOO), hypertension, freezing of gait (FOG). In the Cox proportional risk regression model, we included high body mass index (BMI), late AOO, low motor score on the 39-item Parkinson's Disease Questionnaire (PDQ-39), low orientation score on the Mini-Mental State Examination (MMSE), and absence of FOG. Kaplan-Meier survival curves showed that the survival prognosis of patients with PD in the high-risk group was significantly worse than that in the low-risk group. XGBoost demonstrated that BMI, AOO, PDQ-39 motor score, MMSE orientation score, and FOG contributed to the model to different degrees, in decreasing order of importance, and the overall accuracy of the model was 71.86% after testing. Conclusion: In this study, we showed that risk factors for EDS in patients with PD include high BMI, late AOO, a low motor score of PDQ-39, low orientation score of MMSE, and lack of FOG, and their importance decreased in turn. Our model can predict EDS in PD with relative effectivity and accuracy.

The Chinese Parkinson's Disease Registry (CPDR): Study Design and Baseline Patient Characteristics.

BACKGROUND: There is a lack of large multicenter Parkinson's disease (PD) cohort studies and limited data on the natural history of PD in China. OBJECTIVES: The objective of this study was to launch the Chinese Parkinson's Disease Registry (CPDR) and to report its protocol, cross-sectional baseline data, and prospects for a comprehensive observational, longitudinal, multicenter study. METHODS: The CPDR recruited PD patients from 19 clinical sites across China between January 2018 and December 2020. Clinical data were collected prospectively using at least 17 core assessment scales. Patients were followed up for clinical outcomes through face-to-face interviews biennially. RESULTS: We launched the CPDR in China based on the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network (PD-MDCNC). A total of 3148 PD patients were enrolled comprising 1623 men (51.6%) and 1525 women (48.4%). The proportions of early-onset PD (EOPD, age at onset ≤50 years) and late-onset PD (LOPD) were 897 (28.5%) and 2251 (71.5%), respectively. Stratification by age at onset showed that EOPD manifested milder motor and nonmotor phenotypes and was related to increased probability of dyskinesia. Comparison across genders suggested a slightly older average age at PD onset, milder motor symptoms, and a higher rate of developing levodopa-induced dyskinesias in women. CONCLUSIONS: The CPDR is one of the largest multicenter, observational, longitudinal, and natural history studies of PD in China. It offers an opportunity to expand the understanding of clinical features, genetic, imaging, and biological markers of PD progression. © 2022 International Parkinson and Movement Disorder Society.

Dose-response relationship in non-pharmacological interventions for individuals with mild cognitive impairment: A systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: Non-pharmacological interventions (NPIs) are important in cognitive decline prevention in individuals with mild cognitive impairment (MCI). However, the dose-response relationship remains unclear. DESIGN: Systematic review and meta-analysis of randomised controlled trials. METHODS: Seven databases were searched until April 2020. RCTs of NPIs in individuals with MCI were eligible for inclusion. Hedge's g was used to calculate the effect size. A random-effect meta-analysis was used to explore the impact of NPIs on cognition. Subgroup analysis was used to investigate the moderates. The dose was measured by prescription (frequency, intensity, type, time and volume) and intervention characteristics (period, energy expenditure, delivery mode and setting) in NPIs. RESULTS: Forty-two studies with 4401 participants were included. In the NPIs, cognitive intervention (g = 0.167), physical exercise (g = 0.536) and multicomponent intervention (g = 0.386) had significant effect on cognition in individuals with MCI. Dose-response results showed cognition could be significantly improved in 1-2 times/week (p < .05), 60-120 min/session (p < .05), ≥12 weeks (p < .05), supervised (p < .05), clinical setting (p < .05) in cognitive intervention. In physical exercise, cognition could be improved in ≥3 times/week (p < .05), vigorous-intensity (p < .05), muscle-strengthening activity (p < .05), 30-60 min/session (p < .05), 6-12 weeks (p < .05), unsupervised (p < .05), community setting (p < .05). In the multicomponent intervention, cognition could be improved in 1-2 times/week (p < .05), 30-60 min/session (p < .05), 8-16 weeks (p < .05), clinical (p < .05). In nutrition intervention, cognition could be better improved DHA (p < .05), >1000 mg/day (p < .05). CONCLUSIONS: The effectiveness of cognitive intervention is significantly influenced by frequency, time, period, delivery mode and setting. The effectiveness of physical exercise is significantly influenced by frequency, intensity, type, time, period, delivery mode and setting. The effectiveness of multicomponent intervention is significantly influenced by frequency, time, period and setting. The effectiveness of nutrition intervention is significantly influenced by dose and type. RELEVANCE TO CLINICAL PRACTICE: The research summarised the evidence to guide the best prescription of NPIs and helped clinicians design more effective interventions in individuals with MCI.

Characteristics of Autonomic Dysfunction in Parkinson's Disease: A Large Chinese Multicenter Cohort Study.

Autonomic dysfunction (AutD) is one of the non-motor symptoms (NMSs) in Parkinson's disease (PD). To investigate the prevalence and clinical features of AutD in Chinese patients with PD, a large multicenter cohort of 2,556 individuals with PD were consecutively involved in the Parkinson's Disease and Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) between January 1, 2017, and December 31, 2019. The assessment of AutD was performed using the Scale for Outcomes in Parkinson's Disease for Autonomic Symptoms (SCOPA-AUT). The evaluation of motor symptoms and other NMSs were performed using well-established scales recommended by the Movement Disorder Society. We found that out of 2,556 patients with PD, 2,333 patients with PD (91.28%) had AutD. Compared with the group of patients with PD without AutD, the group of patients with PD with AutD had older age, older age of onset, longer disease duration, more severe motor symptoms, motor complications, and more frequent NMSs. As for partial correlation analysis, the total SCOPA-AUT score was significantly and positively associated with motor severity scales [Unified Parkinson's Disease Rating Scale (UPDRS) total score] and some of the NMSs [Rapid Eye Movement Sleep Behavior Disorder Questionnaire (RBD), Epworth Sleepiness Scale, Hamilton Depression Scale], Fatigue Severity Scale, and Parkinson's disease questionnaire. PD Sleep Scale was significantly and negatively correlated with AutD. With logistic regression analysis for potentially related factors, age, UPDRS total score, RBD, hyposmia, depression, and fatigue may be associated with PD with AutD. In conclusion, our multicenter cohort study reported the high prevalence of AutD in Chinese PD and revealed the associated factors of PD with AutD.

Assessment of Carotid Plaque Stability Using Contrast-Enhanced Ultrasound and Its Correlation With the Expression of CD147 and MMP-9 in the Plaque.

This study aims to investigate the correlation between the enhancement degree of contrast-enhanced ultrasound (CEUS) and the expression of CD147 and MMP-9 in carotid atherosclerotic plaques in patients with carotid endarterectomy and evaluate the diagnostic efficacy of CEUS using pathological results as the gold standard. Thirty-eight patients who underwent carotid endarterectomy (CEA) for carotid stenosis in the Department of Neurovascular Surgery of the Second People's Hospital of Shenzhen from July 2019 to June 2020 were selected. Preoperatively, two-dimensional (2D) ultrasound scan was performed on all patients to assess the characteristics of the plaque and degree of stenosis, and CEUS was used to evaluate the surface morphology of the plaque and the distribution of neovascularization. Postoperatively, pathological sections and immunohistochemical analysis of CD147 and MMP-9 levels in the plaque were performed on the stripped plaque tissue, and the results were analyzed against the CEUS grading and pathological results. Among the 38 patients, pathological results showed that 10 and 28 were in the stable and vulnerable plaque groups, respectively. There were more smokers in the vulnerable plaque group than in the stable plaque group, with higher intraplaques CD147 and MMP-9. The difference in ultrasound plaque surface morphology grading and CEUS grading between the two groups was statistically significant. There was no significant difference in age, sex, incidence of complications such as hypertension, diabetes, and coronary heart disease between the two groups. CD147 was higher in the CEUS grade IV group than in the grades I (P = 0.040) and II (P = 0.010) groups. MMP-9 was higher in the CEUS grade IV group than in the grade II group (P = 0.017); MMP-9 was higher in the grade III group than in the grade II group (P = 0.015). Intraplaque contrast enhancement intensity was positively correlated with CD147 (r = 0.462, P = 0.003) and MMP-9 (r = 0.382, P = 0.018) levels. There was moderate consistency between the assessment of plaque vulnerability by 2D-ultrasound and by histopathological hematoxylin-eosin (HE) (kappa = 0.457, P > 0.05). 2D diagnosis of vulnerable plaque had a sensitivity of 85.7%, a specificity of 60.0%, a positive predictive value of 85.7%, a negative predictive value of 60.0%, and an accuracy of 78.0%. There was a strong consistency between the assessment of plaque vulnerability by CEUS and histopathological HE (kappa = 0.671, P < 0.01). CEUS had a sensitivity of 89.2%, a specificity of 80.0%, a positive predictive value of 92.6%, a negative predictive value of 72.7%, and an accuracy of 86.8% for the diagnosis of vulnerable plaques; CEUS is a reliable, non-invasive test that can show the distribution of neovascularization within vulnerable plaques, evaluate the vulnerability and risk of intraplaque hemorrhage, with a high consistency with pathological findings. The degree of intraplaque enhancement and the levels of CD147 and MMP-9 in the tissue were positively correlated.

Constructing Prediction Models for Freezing of Gait by Nomogram and Machine Learning: A Longitudinal Study.

Objectives: Although risk factors for freezing of gait (FOG) have been reported, there are still few prediction models based on cohorts that predict FOG. This 1-year longitudinal study was aimed to identify the clinical measurements closely linked with FOG in Chinese patients with Parkinson's disease (PD) and construct prediction models based on those clinical measurements using Cox regression and machine learning. Methods: The study enrolled 967 PD patients without FOG in the Hoehn and Yahr (H&Y) stage 1-3 at baseline. The development of FOG during follow-up was the end-point. Neurologists trained in movement disorders collected information from the patients on a PD medication regimen and their clinical characteristics. The cohort was assessed on the same clinical scales, and the baseline characteristics were recorded and compared. After the patients were divided into the training set and test set by the stratified random sampling method, prediction models were constructed using Cox regression and random forests (RF). Results: At the end of the study, 26.4% (255/967) of the patients suffered from FOG. Patients with FOG had significantly longer disease duration, greater age at baseline and H&Y stage, lower proportion in Tremor Dominant (TD) subtype, a higher proportion in wearing-off, levodopa equivalent daily dosage (LEDD), usage of L-Dopa and catechol-O-methyltransferase (COMT) inhibitors, a higher score in scales of Unified Parkinson's Disease Rate Scale (UPDRS), 39-item Parkinson's Disease Questionnaire (PDQ-39), Non-Motor Symptoms Scale (NMSS), Hamilton Depression Rating Scale (HDRS)-17, Parkinson's Fatigue Scale (PFS), rapid eye movement sleep behavior disorder questionnaire-Hong Kong (RBDQ-HK), Epworth Sleepiness Scale (ESS), and a lower score in scales of Parkinson's Disease Sleep Scale (PDSS) (P < 0.05). The risk factors associated with FOG included PD onset not being under the age of 50 years, a lower degree of tremor symptom, impaired activities of daily living (ADL), UPDRS item 30 posture instability, unexplained weight loss, and a higher degree of fatigue. The concordance index (C-index) was 0.68 for the training set (for internal validation) and 0.71 for the test set (for external validation) of the nomogram prediction model, which showed a good predictive ability for patients in different survival times. The RF model also performed well, the C-index was 0.74 for the test set, and the AUC was 0.74. Conclusions: The study found some new risk factors associated with the FOG including a lower degree of tremor symptom, unexplained weight loss, and a higher degree of fatigue through a longitudinal study, and constructed relatively acceptable prediction models.

Extent, reasons and consequences of off-labeled and unlicensed drug prescription in hospitalized children: a narrative review.

BACKGROUND: Off-label and unlicensed prescriptions pose a severe safety concern among the pediatric population. We aimed to summarize the up-to-date evidence on the extent, reasons, and consequences of off-label and unlicensed drugs in hospitalized pediatric patients. METHODS: We systematically searched PubMed, EMBASE, SCOPUS, Web of Science and Google Scholar between 1990 and 2020 in which the last search was conducted on 12 February 2021. We included studies with the following inclusion criteria: (1) observational studies in design; (2) target population was hospitalized pediatric patients whether admitted in the intensive care unit or in the general ward; (3) study reporting the prevalence of off-label, unlicensed prescriptions or both; and (4) published in English. RESULTS: A total of 47 studies were eligible for inclusion. The proportion of off-label and unlicensed prescriptions ranged from 7.4% to 99.5% and 0.1% to 74.4%, respectively. The most frequent category of off-label prescriptions was prescription outside the age range, with the most commonly reported reason for off-label prescriptions being the lack of information specifically for pediatrics on the drug information leaflets. The consequences of off-label and unlicensed prescriptions ranged from minor and bearable skin reactions to debilitating renal failure, risking deaths. CONCLUSIONS: Off-label and unlicensed prescriptions are extensive and require progressively meditative interventions. However, the pediatric population is currently a "therapeutic orphan". Unless adequate pediatric clinical trials and licensed drugs become available, off-label and unlicensed drug prescription should not entirely be banned but rather promoted in an organized manner.

Poor guideline adherence in type 1 diabetes education in real-world clinical practice: Evidence from a multicentre, national survey.

OBJECTIVE: To examine how physicians implement guidelines to deliver insulin dosing education for type 1 diabetes patients in real-world settings. METHODS: A nationally representative sample of endocrinologists from top tertiary hospitals in China was obtained by a multistage random sampling method (n = 385). Knowledge, perceptions and practices of insulin dosing were assessed by validated questionnaires. Multivariable logistic regression was used to identify independent determinants of clinical practice and knowledge. RESULTS: Only 20.5% of endocrinologists correctly answered> 75% of the items regarding insulin dosing knowledge. Only 37.7% of endocrinologists reported often teaching insulin-to-carbohydrate ratio and insulin sensitivity factor. Practice behaviours were independently associated with guideline familiarity (OR: 5.92, 95% CI: 3.36-10.41), receiving standardized training (OR: 2.00, 95% CI:1.23-3.25), self-reported lack of time (OR: 0.58, 95% CI:0.34-0.99) and insufficient teaching approaches (OR: 0.57, 95% CI:0.33-0.97) CONCLUSIONS: There was a large gap between guidelines and clinical practice in insulin dosing education. Modifiable factors, including self-reported lack of time, unfamiliarity with guidelines, the shortage of medical training and educational tools hinder insulin dosing education. PRACTICE IMPLICATIONS: Sufficient medical training and educational tools are important to optimize insulin dosing education. The current care paradigm should also be modified to relieve the burden of physicians.

Development and application of a new framework for infectious disease management at the early stage of new epidemics: Taking COVID-19 outbreak in China as an example.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) rapidly spread across worldwide, posing a significant challenge to public health. Several shortcomings in the existing infectious disease management system were exposed during the pandemic, which hindered the control of the disease globally. To cope with this issue, we propose a window-period framework to reveal the general rule of the progression of management of infectious diseases and to help with decision making at the early stage of epidemics with a focus on healthcare provisions. METHODS: The framework has two significant periods (dark-window period and bright-window period). Outbreak of COVID-19 in China was used as an example for the application of the framework. RESULTS: The framework could reflect the progression of the epidemic objectively. The spread increased slowly in the dark-window period, but rocketed up in the bright-window period. The beginning of the bright-window period was the time when healthcare personnel were exposed to a substantially high risk of nosocomial infection. Additionally, proper and prompt preventive actions during the dark-window and bright-window periods were substantially important to reduce the future spreading of the disease. CONCLUSIONS: It was recommended that when possible healthcare provisions should upgrade to the highest level of alert for the control of an unknown epidemic in the dark-window period, while countermeasures in the bright-window period could be accordingly adjusted with full exploration and considerations. The framework may provide some insights into how to accelerate the control of future epidemics promptly and effectively.

Impact of MASP2 gene polymorphism and gene-tea drinking interaction on susceptibility to tuberculosis.

Mannan-binding lectin-associated serine protease-2 (MASP-2) has been reported to play an important role as a key enzyme in the lectin pathway of the complement system. The objectives of our study were to determine whether the single-nucleotide polymorphism (SNPs) of MASP2 and the gene-tea drinking interaction were associated with the susceptibility to TB. In total, 503 patients and 494 healthy controls were contained. Three SNPs (rs12142107, rs12711521, and rs7548659) were genotyped. The association between the SNPs and susceptibility to TB were investigated by conducting multivariate unconditional logistic regression analysis. The gene-tea drinking interactions were analyzed by the additive model of marginal structural linear odds models. Both genotype AC + AA at rs12711521 of MASP2 genes and genotype GT + GG at rs7548659 of MASP2 genes were more prevalent in the TB patient group than the healthy control group (OR: 1.423 and 1.439, respectively, P < 0.05). In addition, The relative excess risk of interaction (RERI) between tea drinking and rs12142107, rs12711521, and rs7548659 of MASP2 genes was found to suggest negative interactions, which reached - 0.2311 (95% confidence interval (CI): - 0.4736, - 0.0113), - 0.7080 (95% CI - 1.3998, - 0.0163), and - 0.5140 (95% CI - 0.8988, - 0.1291), respectively (P < 0.05). Our finding indicated that the SNPs (rs12711521 and rs7548659) of MASP2 were associated with the susceptibility to TB. Furthermore, there were negative interactions between tea drinking and rs12142107, rs12711521, and rs75548659 of MASP2 gene, respectively. Our research provides a basis for studying the pathogenesis and prevention of tuberculosis.

A Risk Prediction Model Based on Machine Learning for Cognitive Impairment Among Chinese Community-Dwelling Elderly People With Normal Cognition: Development and Validation Study.

BACKGROUND: Identifying cognitive impairment early enough could support timely intervention that may hinder or delay the trajectory of cognitive impairment, thus increasing the chances for successful cognitive aging. OBJECTIVE: We aimed to build a prediction model based on machine learning for cognitive impairment among Chinese community-dwelling elderly people with normal cognition. METHODS: A prospective cohort of 6718 older people from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) register, followed between 2008 and 2011, was used to develop and validate the prediction model. Participants were included if they were aged 60 years or above, were community-dwelling elderly people, and had a cognitive Mini-Mental State Examination (MMSE) score ≥18. They were excluded if they were diagnosed with a severe disease (eg, cancer and dementia) or were living in institutions. Cognitive impairment was identified using the Chinese version of the MMSE. Several machine learning algorithms (random forest, XGBoost, naïve Bayes, and logistic regression) were used to assess the 3-year risk of developing cognitive impairment. Optimal cutoffs and adjusted parameters were explored in validation data, and the model was further evaluated in test data. A nomogram was established to vividly present the prediction model. RESULTS: The mean age of the participants was 80.4 years (SD 10.3 years), and 50.85% (3416/6718) were female. During a 3-year follow-up, 991 (14.8%) participants were identified with cognitive impairment. Among 45 features, the following four features were finally selected to develop the model: age, instrumental activities of daily living, marital status, and baseline cognitive function. The concordance index of the model constructed by logistic regression was 0.814 (95% CI 0.781-0.846). Older people with normal cognitive functioning having a nomogram score of less than 170 were considered to have a low 3-year risk of cognitive impairment, and those with a score of 170 or greater were considered to have a high 3-year risk of cognitive impairment. CONCLUSIONS: This simple and feasible cognitive impairment prediction model could identify community-dwelling elderly people at the greatest 3-year risk for cognitive impairment, which could help community nurses in the early identification of dementia.

Impact of marital status on the prognosis of liver cancer patients without surgery and the critical window.

BACKGROUND: Liver cancer (LC) is the second leading cause of cancer-associated mortality. However, the critical time window during the marital status may influence the prognosis of LC is still unknown. METHODS: Information on a total of 4,933 patients diagnosed with primary LC who had not undergone surgery was collected from the Surveillance, Epidemiology, and End Results (SEER) database to analyze the impact of marital status on the risk of cancer-specific mortality (CSM). All confirmed patients were monitored from January 1, 2010 until December 31, 2015 for the occurrence of death. We performed 1:1 propensity score matching among the married and non-married groups to eliminate dissimilarities in age, sex, race and clinical characteristics. Cox proportional hazards regression model was adopted to investigate the associations between marital status and the risk of CSM. RESULTS: Married patients were significantly negatively associated with the risk of CSM among patients compared to non-married status, with a hazard ratio (HR) [95% confidence interval (CI)] of 1.15 (1.07-1.23). The strongest associations were observed for patients with Grade II, American Joint Committee on Cancer (AJCC) I and III. Furthermore, the protective effect of marriage on the prognosis of LC was independent of sex, age, race, grade, AJCC and SEER stage. Unmarried or separated patients may have a worse prognosis. CONCLUSIONS: Marriage was strongly associated with a positive prognosis among patients with LC, especially in the critical window of Grade II, AJCC I and III. This study highlights the important impact of marriage on cancer prognosis.

Impact of PD-1 gene polymorphism and its interaction with tea drinking on susceptibility to tuberculosis.

The aim of this study was to explore the impact of polymorphism of PD-1 gene and its interaction with tea drinking on susceptibility to tuberculosis (TB). A total of 503 patients with TB and 494 controls were enrolled in this case-control study. Three single-nucleotide polymorphisms of PD-1 (rs7568402, rs2227982 and rs36084323) were genotyped and unconditional logistic regression analysis was used to identify the association between PD-1 polymorphism and TB, while marginal structural linear odds models were used to estimate the interactions. Genotypes GA (OR 1.434), AA (OR 1.891) and GA + AA (OR 1.493) at rs7568402 were more prevalent in the TB patients than in the controls (P < 0.05). The relative excess risk of interaction (RERI) between rs7568402 of PD-1 genes and tea drinking was -0.3856 (95% confidence interval -0.7920 to -0.0209, P < 0.05), which showed a negative interaction. However, the RERIs between tea drinking and both rs2227982 and rs36084323 of PD-1 genes were not statistically significant. Our data demonstrate that rs7568402 of PD-1 genes was associated with susceptibility to TB, and there was a significant negative interaction between rs7568402 and tea drinking. Therefore, preventive measures through promoting the consumption of tea should be emphasised in the high-risk populations.

Effects of computerised cognitive training on cognitive impairment: a meta-analysis.

INTRODUCTION: Computerised cognitive training (CCT) has been shown to enhance cognitive function in elderly individuals with cognitive deterioration, but evidence is controversial. Additionally, whether specific CCT is most effective and which stages of cognitive impairment benefit most is unclear. METHODS: We systematically searched nine medical and technological databases to collect randomized controlled trials related to CCT primarily conducted in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). RESULTS: We identified 12 studies in patients with SCD and MCI. Pooled analysis showed that CCT could significantly improve cognitive function (g = 0.518, p = 0.000), especially related to memory. In terms of different types of cognitive training, specific CCT was more efficacious than non-specific CCT (g = 0.381, p = 0.007) or placebo (g = 0.734, p = 0.000) but not traditional CT (p = 0.628). In terms of stages of cognitive deterioration, the effect of CCT on SCD (g = 0.926, p = 0.002) was almost double that of its effect on MCI (g = 0.502, p = 0.000). CONCLUSION: CCT was most effective in cognitive rehabilitation, particularly in the subdomain of memory. Early intervention in SCD is better.