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Objective: The aim of the present study was to systematically evaluate and quantify the effectiveness of dual-task training on gait parameters, motor symptoms and balance in individuals diagnosed with Parkinson’s disease. Data resources: A systematic review of published literature was conducted until May 2020, using PubMed, EMBASE, Cochrane Library, Web of Science, EBSCO and CNKI databases. Methods: We included randomized controlled trials (RCTs) and non-RCTs to evaluate the effects of dual-task training compared with those of non-intervention or other forms of training. The measurements included gait parameters, motor symptoms and balance parameters. Methodological quality was assessed using the PEDro scale. Outcomes were pooled by calculating between-group mean differences using fixed- or random-effects models based on study heterogeneity. Results: A total of 11 RCTs comprising 322 subjects were included in the present meta-analysis. Results showed that dual-task training significantly improved gait speed (standardized mean difference [SMD], −0.23; 95% confidence interval [CI], −0.38 to −0.08; P = 0.002), cadence (SMD, −0.25; 95% CI, −0.48 to −0.02; P = 0.03), motor symptoms (SMD, 0.56; 95% CI, 0.18 to 0.94; P = 0.004) and balance (SMD, −0.44; 95% CI, −0.84 to −0.05; P = 0.03). However, no significant changes were detected in step length or stride length. Conclusion: Dual-task training was effective in improving gait performance, motor symptoms and balance in patients with Parkinson’s disease relative to other forms of training or non-intervention.

Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. Methods Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal–Wallis tests were used in our statistical analysis. Results A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19. Graphic abstract

Aim The aim of this study was to assess the caregiver burden over time of patients with haemorrhagic stroke and the determinants of this. Background Identification of the predictors for caregiver burden can be used to improve the outcomes of stroke survivors and caregivers. Few studies focus on the caregiver burden of patients with haemorrhagic stroke and how this changes over time. Design This was a prospective longitudinal study. Methods A convenience sample of 202 stroke survivor/caregiver pairs were recruited in the neurosurgery unit from March 2015 to March 2016. The participants were assessed at three different times by face to face or telephone interview. Caregiver burden was assessed using the Bakas Caregiver Outcomes Scale. Sociodemographic data and other characteristics of the pairs were also collected. Multiple linear regression was performed to identify the determinants. Results Caregiver burden decreased from T1 to T3 significantly. The physical function, depression of stroke survivors, and self‐rated burden of caregivers were the most important determinants for overall caregiver burden. The factors identified explained 41.6% to 67.4% of overall burden. Conclusion Caregiver burden decreased over time, affected by factors from patients and caregivers. More professional caregivers are needed to support informal carers.

Background The United States has the highest numbers of confirmed cases of COVID-19, where they took up nearly half in the hot spot states of New York, New Jersey, Connecticut, and California. The workforce in these states was required to work from home except for essential services. It is necessary to evaluate an appropriate date for resumption of business since premature reopening of economy will lead to broader spread of COVID-19, while the opposite situation would cause greater loss of economy. Methods To consider pre-symptomatic and asymptomatic transmission of COIVD-19, it is crucial to evaluate the unobserved numbers of unidentified infectious individuals but not the observed number of confirmed cases, which reflect the real-time risks of different stage of infectious disease. We proposed an epidemic model in considering the pre-symptomatic transmission and asymptomatic transmission of COVID-19 to evaluate the real-time risk of epidemic for the states of New York, New Jersey and Connecticut, and compared with California state (where it effectively phased reopened on May 8) for assessments of the appropriate Monday for resumption of business. Results The predicted numbers of unidentified infectious individuals per 100,000 for states of New York, New Jersey and Connecticut which are close to those in California state are 12.23 with 95% CI (10.68, 13.57) on June 1, 25.65 with 95% CI (20.04, 30.43) on June 15, 28.49 with 95% CI (19.10, 38.65) on June 22, respectively, which may cause 11.23%, 15.64% and 17.32% higher than the estimated number of cumulative confirmed cases on July 11, if the second wave of the infection would happen after people return to work. Conclusions It may be feasible for states of New York, New Jersey and Connecticut to reopen business on June 1 (or even May 18), June 15 and June 22. For the period after resumption of work, if the number of unidentified infectious individuals is still non-zero, the risks for the second wave of the infection would never vanish.

Identifying the determinants of health-related quality of life (HRQOL) improved assessment and decision-making in clinical practice. A few studies have focused on the determinants of HRQOL and their interrelationships in patients with hemorrhagic stroke. The aim of this study was to identify the factors contributing to HRQOL and exam their interrelationships. A total of 202 patients with hemorrhagic stroke who were discharged from the neurological unit participated in this study. Stroke-specific quality of life was used to assess HRQOL. The Hamilton Rating Scale for Anxiety, the Hamilton Rating Scale for Depression, the Scandinavian Stroke Scale and the Barthel Index were collected as potential predictors as well as social-demographic data. A path analysis was used to explore the potential interrelationships between various factors based on the International Classification of Functioning model. The final model reasonably fitted the data. The activities of daily living, neurological function and anxiety had direct effects on quality of life. Age, comorbidities, hemorrhage type, financial status, anxiety, and neurological function also had indirect influences on quality of life. All these factors explained 82.0% of all variance in quality of life. HRQOL in patients with stroke can be predicted by anxiety, neurological function, activities of daily living and other personal and environmental factors. These identified predictors and their interrelationships may assist clinical professions focusing their assessments and developing strategies for modifiable factors to improve HRQOL.

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Objective Our study aimed to verify the validity of the Chinese version of Alzheimer's Disease Assessment Scale‐Cognitive Subscale (ADAS‐Cog) for the community‐dwelling older people in China. Methods A total of 1276 individuals composed by 628 normal controls (NCs), 572 people living with mild cognitive impairment (MCI), and 76 people living with Alzheimer's disease (AD) were recruited for the current study. All of the participants underwent ADAS‐Cog, clinical interview and examination, Quick Cognitive Screening Scale for the Elderly, and Activities of Daily Living Scale. The sensitivity and specificity of ADAS‐Cog were calculated, and a receiver operating characteristic curve (ROC curve) was drawn to decide the optimal cutoff points of ADAS‐Cog for screening MCI and AD. Results Statistically significant differences were observed among the three groups (P <. 001, NC < MCI