Internal and emergency medicine
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There is limited information on predicting incident cardiovascular outcomes among high- to very high-risk populations such as the elderly (≥ 65 years) in the absence of prior cardiovascular disease and the presence of non-cardiovascular multi-morbidity. We hypothesized that statistical/machine learning modeling can improve risk prediction, thus helping inform care management strategies. We defined a population from the Medicare health plan, a US government-funded program mostly for the elderly and varied levels of non-cardiovascular multi-morbidity. ⋯ Complex models based on machine learning algorithms yielded incrementally better discriminatory power and much improved goodness-of-fitness tests from those based on main effect statistical modeling. This Medicare population represents a highly vulnerable group for incident CVD events. This population would benefit from an integrated approach to their care and management, including attention to their comorbidities and lifestyle factors, as well as medication adherence.
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As a prolonged surge scenario, the COVID-19 pandemic has offered an unparalleled opportunity to improve hospital surge capacity (SC) understanding and the ability to manage it. In this study, the authors report the experience of a large hospital network and evaluate potential relationships between Intensive Care Units SC (ICU-SC) and some hospital-related variables: bed occupancy, emergency department admissions, ward admission from ED, and elective surgery procedures. Pearson's partial correlation coefficient (r) has been used to define the relationship between SC and the daily values of the above variables, collected through a dedicated digital platform that also ensured a regular quality check of the data. ⋯ This study identified a positive correlation between SC and three variables monitored: ICU bed occupancy, non-ICU bed occupancy, and ward admissions from ED. On the contrary, the correlation was negative for ED admission and the number of elective surgery procedures. The results have been confirmed across all levels of analysis adopted.
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Observational Study
Prehospital stratification and prioritisation of non-ST-segment elevation acute coronary syndrome patients (NSTEACS): the MARIACHI scale.
The objective of this study was to develop and validate a risk scale (MARIACHI) for patients classified as non-ST-segment elevation acute coronary syndrome (NSTEACS) in a prehospital setting with the ability to identify patients at an increased risk of mortality at an early stage. ⋯ The MARIACHI scale showed correct discrimination and calibration to predict high-risk NSTEACS. Identification of high-risk patients may help with treatment and low referral decisions at the prehospital level.
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Chronic anaemia in advanced liver disease is a frequent finding. The aim was to explore the clinical impact of spur cell anaemia, a rare entity typically associated with end-stage of the disease. One-hundred and nineteen patients (73.9% males) with liver cirrhosis of any etiology were included. ⋯ ACLF and liver-related mortality were significantly and independently associated with the presence of > 5% spur cells but not with baseline severe anaemia. Cirrhotic patients have a fairly high prevalence of spur cells, not always associated with severe haemolytic anaemia. The presence of spur red cells is per se associated with a worse prognosis and, therefore, should be always evaluated to prioritize patients for intensive management and eventually liver transplantation.
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Unmet needs challenge clinical management of sepsis especially concerning patient profiling, enhancing recovery, and long-term sequelae. Here, we preliminarily focused on sclerostin (SOST) as a candidate biomarker to encompass such a broad range of clinical needs related to sepsis. Seventy-three septic patients were enrolled at internal medicine wards between January 2017 and December 2019 in this pilot study. ⋯ SOST levels generally decreased over 7 to 14 days after enrollment (p for trend < 0.001). The degree of this variation further predicted long-term mortality (HR for Δ SOST T0-day 14: 1.006 with 95% CI 1.001-1.011). Our results suggest a role for SOST in both short- and long-time prediction of worse outcome in septic elderly admitted to internal medicine wards.