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OBJECTIVES Although stroke incidence is inversely associated with socioeconomic status, whether similar disparities exist with moyamoya disease (MMD) is unknown. Determining the socioeconomic and demographic factors involved in MMD will provide better direction in elucidating the etiology or addressing healthcare inequalities. https://www.selleckchem.com/products/envonalkib.html PATIENTS AND METHODS To investigate MMD incidence with respect to sex, age, income, residence, and race/ethnicity, we examined the largest American administrative dataset, the National (Nationwide) Inpatient Sample (NIS), which surveys 20 % of United States discharges irrespective of payor. We then determined median annual incidence per 100,000 people and trends between 2008-2015. RESULTS Overall MMD incidence (with 25th and 75th quartiles) was 0.293 (0.283, 0.324) and annually increasing (τ = 0.857, p = 0.004). Females had an incidence of 0.398 (0.371, 0.464), larger (p = 0.008) than the male incidence of 0.185 (0.165, 0.195). Amongst age groups incidence varied (χ2 = 8.857, p = 0.012)e significantly varied between all groups. Annually incidence was significantly increasing for females (τ = 0.929, p = 0.002), ages 18-44 (τ = 0.786, p = 0.009), ages 45-64 (τ = 0.714, p = 0.019), middle/high income (τ = 0.786, p = 0.009), and urban (τ = 0.714, p = 0.019) or suburban (τ = 0.714, p = 0.035) dwelling patients. CONCLUSION MMD diagnoses between 2008-2015 have been significantly increasing in the United States, with disparities growing between socioeconomic and demographic strata. Disproportionately, incidence was greatest for patients who were low income, urban living, female, aged 18-44, and Asian/Pacific Islanders. This data highlights a growing healthcare inequality amongst MMD and provides direction in etiology elucidation. OBJECTIVES No established approaches exist for the pharmacological management of cardiovascular diseases (CVDs) in residents of long-term care facilities (LTCFs). This study aimed to evaluate the use of drugs for CVD prevention and treatment (CVD-related drugs) in a major type of LTCF in Japan. METHODS This study included 1318 randomly selected residents at 349 intermediate care facilities for older adults (called Roken). Prescriptions were investigated at admission and two months after admission according to therapeutic categories. Logistic regression was used to identify residents' characteristics that were associated with prescriptions of CVD-related drugs. RESULTS Prescriptions of all types of drugs and CVD-related drugs decreased in 36 % and 16 % of residents, respectively. Half of the residents received antihypertensives, a quarter received antiplatelets and diuretics, whereas one-tenth received antidiabetics, oral anticoagulants, and lipid-modifying drugs. The prevalence of most of individual drug categories were similar among residents with different physical or cognitive function, except for fewer antihypertensive and lipid-modifying drugs in those with severe cognitive disability. Adjusted analyses for prescriptions at two months after admission revealed that bedridden residents were more likely to be prescribed diuretics but less likely to be prescribed antihypertensives, antiplatelets, or lipid-modifying drugs. Residents with severe cognitive disability were less likely to be prescribed antihypertensives or lipid-modifying drugs. A known history of cardiovascular events was associated with greater use of CVD-related drugs. CONCLUSION CVD-related drugs were commonly prescribed for Roken residents, including those with low physical and cognitive functions. Deprescribing may contribute to the optimization of pharmacotherapy in LTCF residents. BACKGROUND Degenerative cervical myelopathy (DCM) is the most common cause of spinal cord dysfunction worldwide. Current guidelines recommend management based on the severity of myelopathy, measured by the modified Japanese Orthopedic Association (mJOA) score. Patients with moderate to severe myelopathy, defined by an mJOA below 15, are recommended to undergo surgery. However, the management for mild myelopathy (mJOA between 15 and 17) is controversial since the response to surgery is more heterogeneous. PURPOSE To develop machine learning algorithms predicting phenotypes of mild myelopathy patients that would benefit most from surgery. STUDY DESIGN Retrospective subgroup analysis of prospectively collected data. PATIENT SAMPLES Data were obtained from 193 mild DCM patients who underwent surgical decompression and were enrolled in the multicenter AOSpine CSM clinical trials. OUTCOME MEASURES The mJOA score, an assessment of functional status, was used to isolate patients with mild DCM. The primary outcome mea in which the GBM and earth models showed AUCs of 0.77 and 0.78, respectively, as well as fair to good calibration across the predicted range of probabilities. Female patients with a low initial MCS were less likely to experience significant improvement in MCS than males. The presence of certain signs and symptoms (eg, lower limb spasticity, clumsy hands) were also predictive of worse outcome. CONCLUSIONS Machine learning models showed good predictive power and provided information about the phenotypes of mild DCM patients most likely to benefit from surgical intervention. Overall, machine learning may be a useful tool for management of mild DCM, though external validation and prospective analysis should be performed to better solidify its role. BACKGROUND CONTEXT Psychological characteristics are important in the development and progression of low back pain (LBP); however, their role in persistent, severe LBP is unclear. PURPOSE To investigate the relationship between catastrophization, depression, fear of movement, and anxiety and persistent, severe LBP, and disability. STUDY DESIGN/ SETTING One-year prospective cohort study. PATIENT SAMPLE Participants were selected from the SpineData registry (Denmark), which enrolls individuals with LBP of 2 to 12 months duration without radiculopathy and without satisfactory response to primary intervention. OUTCOME MEASURES Psychological characteristics, including catastrophization, depression, fear of movement, and anxiety, were examined at baseline using a validated screening questionnaire. Current, typical, and worst pain in the past 2 weeks were assessed by 11-point numeric rating scales and an average pain score was calculated. Disability was measured using the 23-item Roland-Morris Disability Questionnaire.
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