Internal and emergency medicine
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Handgrip strength (HGS), a simple tool for the evaluation of muscular strength, is independently associated with negative prognosis in many diseases. It is unknown whether HGS is prognostically relevant in COVID-19. We evaluated the ability of HGS to predict clinical outcomes in people with COVID-19-related pneumonia. 118 patients (66% men, 63 ± 12 years), consecutively hospitalized to the "Santa Maria" Terni University Hospital for COVID-19-related pneumonia and respiratory failure, underwent HGS measurement (Jamar hand-dynamometer) at ward admission. ⋯ These two latter also showed independent association with the main end-point (HR 1.30, p = 0.03 and 3.89, p < 0.01, respectively). In conclusion, nHGS measured at hospital admission, independently and inversely predicts the risk of poor outcomes in people with COVID-19-related pneumonia. The evaluation of HGS may be useful in early stratifying the risk of adverse prognosis in COVID-19.
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The number of patients with opioid use disorder (OUD) has increased dramatically. Substance use disorders in general are thought to occur in one in five patients in primary care. However, despite this prevalence, there is a dearth of training in undergraduate and continuing medical education to manage OUDs, and internal medicine doctors need to have an understanding of the basic physiology and treatment options for this illness. ⋯ It will also allow clinicians to appropriately refer their patients for lifesaving specialized care and help them prevent dangerous medical complications often seen as a result of addiction. There are three FDA-approved medications to treat OUD disorder, known collectively as medication-assisted treatment (MAT). In this paper, the three medications-methadone, naltrexone, and buprenorphine-are presented, compared, contrasted, and clinically reviewed.
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Predictive models for key outcomes of coronavirus disease 2019 (COVID-19) can optimize resource utilization and patient outcome. We aimed to design and internally validate a web-based calculator predictive of hospitalization and length of stay (LOS) in a large cohort of COVID-19-positive patients presenting to the Emergency Department (ED) in a New York City health system. The study cohort consisted of consecutive adult (> 18 years) patients presenting to the ED of Mount Sinai Health System hospitals between March 2020 and April 2020, diagnosed with COVID-19. ⋯ A calculator was made available under the following URL: https://covid19-outcome-prediction.shinyapps.io/COVID19_Hospitalization_Calculator/. This study yielded internally validated models that predict hospitalization risk in COVID-19-positive patients, which can be used to optimize resource allocation. Predictors of hospitalization and extended LOS included older age, CKD, fever, oxygen desaturation, elevated C-reactive protein, creatinine, and ferritin.
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Previous studies that assessed risk factors for venous thromboembolism (VTE) in COVID-19 patients have shown inconsistent results. Our aim was to investigate VTE predictors by both logistic regression (LR) and machine learning (ML) approaches, due to their potential complementarity. This cohort study of a large Brazilian COVID-19 Registry included 4120 COVID-19 adult patients from 16 hospitals. ⋯ Atrial fibrillation, peripheral oxygen saturation/inspired oxygen fraction (SF) ratio and prophylactic use of anticoagulants were protective. Temperature at admission, SF ratio, neutrophil count, D-dimer, CRP and lactate levels were also identified as predictors by ML methods. By using ML and LR analyses, we showed that D-dimer, axillary temperature, neutrophil count, CRP and lactate levels are risk factors for VTE in COVID-19 patients.
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This study aims to evaluate the performance of CREWS (Chronic Respiratory Early Warning Score), S-NEWS (Salford-National Early Warning Score), qNEWS (Quick National Early Warning Score), NEWS (National Early Warning Score), and qSOFA (Quick Sequential Organ Failure Assessment) scores in predicting mortality, intensive care unit (ICU) admission and the need for mechanical ventilation (MV) of patients presented with acute exacerbations of chronic obstructive pulmonary disease (AECOPD). This retrospective cohort study was conducted in the emergency department of a tertiary hospital between January 1 and December 31, 2019. The patients with AECOPD and aged ≥ 18 were included. ⋯ ICU admission, age, and creatinine levels were associated with mortality (p < 0.05). All scores have better performance in predicting ICU admission and MV need than mortality. ICU admission, age, and creatinine levels may be the predictors of mortality among AECOPD patients.