Plos One
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Observational Study
Risk factors for severe illness in hospitalized Covid-19 patients at a regional hospital.
The Covid-19 pandemic threatens to overwhelm scarce clinical resources. Risk factors for severe illness must be identified to make efficient resource allocations. ⋯ At our regional medical center, patients with Covid-19 had an average length of stay just under 12 days, required ICU care in 31% of cases, and had a 25% mortality rate. Patients with increased sputum production and higher supplemental oxygen requirements at admission, and insulin dependent diabetes or chronic kidney disease may be at increased risk for severe illness. A model for predicting intensive care unit admission or death with excellent discrimination was created that may aid in treatment decisions and resource allocation. Early identification of patients at increased risk for severe illness may lead to improved outcomes in patients hospitalized with Covid-19.
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Meta Analysis Comparative Study
Yoga compared to non-exercise or physical therapy exercise on pain, disability, and quality of life for patients with chronic low back pain: A systematic review and meta-analysis of randomized controlled trials.
Chronic low back pain (CLBP) is a common and often disabling musculoskeletal condition. Yoga has been proven to be an effective therapy for chronic low back pain. However, there are still controversies about the effects of yoga at different follow-up periods and compared with other physical therapy exercises. ⋯ This meta-analysis provided evidence from very low to moderate investigating the effectiveness of yoga for chronic low back pain patients at different time points. Yoga might decrease pain from short term to intermediate term and improve functional disability status from short term to long term compared with non-exercise (e.g. usual care, education). Yoga had the same effect on pain and disability as any other exercise or physical therapy. Yoga might not improve the physical and mental quality of life based on the result of a merging.
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Non-Invasive Venous waveform Analysis (NIVA) is novel technology that captures and analyzes changes in venous waveforms from a piezoelectric sensor on the wrist for hemodynamic volume assessment. Complex cranial vault reconstruction is performed in children with craniosynostosis and is associated with extensive blood loss, potential life-threatening risks, and significant morbidity. In this preliminary study, we hypothesized that NIVA will provide a reliable, non-invasive, quantitative assessment of intravascular volume changes in children undergoing complex cranial vault reconstruction. ⋯ NIVA values correlate more closely to intravascular volume changes in pediatric craniofacial patients than MAP. This initial study suggests that NIVA is a potential safe, reliable, non-invasive quantitative method of measuring intravascular volume changes for children undergoing surgery.
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Estimating the risk of pre-existing comorbidities on coronavirus disease 2019 (COVID-19) mortality may promote the importance of targeting populations at risk to improve survival. This systematic review and meta-analysis aimed to estimate the association of pre-existing comorbidities with COVID-19 mortality. ⋯ Patients with COVID-19 with cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer have a greater risk of mortality compared to patients with COVID-19 without these comorbidities. Tailored infection prevention and treatment strategies targeting this high-risk population might improve survival.
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Multicenter Study
Development and validation a nomogram for predicting the risk of severe COVID-19: A multi-center study in Sichuan, China.
Since December 2019, coronavirus disease 2019 (COVID-19) emerged in Wuhan and spread across the globe. The objective of this study is to build and validate a practical nomogram for estimating the risk of severe COVID-19. ⋯ We established an early warning model incorporating clinical characteristics that could be quickly obtained on admission. This model can be used to help predict severe COVID-19 and identify patients at risk of developing severe disease.