Journal of personalized medicine
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Sarcopenia is a geriatric syndrome characterized by losses of quantity and quality of skeletal muscle, which is associated with negative outcomes in older adults and in cancer patients. Different definitions of sarcopenia have been used, with quantitative data more frequently used in oncology, while functional measures have been advocated in the geriatric literature. Little is known about the correlation between frailty status as assessed by comprehensive geriatric assessment (CGA) and sarcopenia in cancer patients. ⋯ Only 13 patients satisfied both the requirements for being defined as sarcopenic and frail. Grade 3-4 treatment-related toxicities (according to Common Terminology Criteria for Adverse Events) were more common in sarcopenic and frail sarcopenic patients. Our data support the use of a definition of sarcopenia that includes both quantitative and functional data in order to identify frail patients who need tailored treatment.
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Early warning scores (EWSs) help prevent and recognize and thereby act as the first signs of clinical and physiological deterioration. The objective of this study is to evaluate different EWSs (National Early Warning Score 2 (NEWS2), quick sequential organ failure assessment score (qSOFA), Modified Rapid Emergency Medicine Score (MREMS) and Rapid Acute Physiology Score (RAPS)) to predict mortality within the first 48 h in patients suspected to have Coronavirus disease 2019 (COVID-19). We conducted a retrospective observational study in patients over 18 years of age who were treated by the advanced life support units and transferred to the emergency departments between March and July of 2020. ⋯ The scale with the best capacity to predict early mortality was the National Early Warning Score 2 (NEWS2), with an area under the curve of 0.825 (95% CI: 0.75-0.89). The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients presented an area under the curve (AUC) of 0.804 (95% CI: 0.71-0.89), and the negative ones with an AUC of 0.863 (95% CI: 0.76-0.95). Among the EWSs, NEWS2 presented the best predictive power, even when it was separately applied to patients who tested positive and negative for SARS-CoV-2.