Internal and emergency medicine
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Pain is a multidimensional experience, potentially rendering unidimensional pain scales inappropriate for assessment. Prior research highlighted their inadequacy as reliable indicators of analgesic requirement. This systematic review aimed to compare multidimensional with unidimensional pain scales in assessing analgesic requirements in the emergency department (ED). ⋯ Limited heterogenous literature suggests that in the ED, a multidimensional pain scale (DVPRS), may better discriminate moderate and severe pain compared to a unidimensional pain scale (NRS). This potentially impacts analgesia, particularly when analgesic interventions rely on pain scores. Patients might prefer multidimensional pain scales (BPI-SF, MPQ-SF) over NRS or VAS for assessing their pain experience.
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Autophagy is an evolutionarily conserved process that plays a pivotal role in the maintenance of cellular homeostasis and its impairment has been implicated in the pathogenesis of various metabolic diseases including obesity, type 2 diabetes (T2D), and metabolic dysfunction-associated steatotic liver disease (MASLD). This review synthesizes the current evidence from human studies on autophagy alterations under these metabolic conditions. In obesity, most data point to autophagy upregulation during the initiation phase of autophagosome formation, potentially in response to proinflammatory conditions in the adipose tissue. ⋯ Owing to these constraints, determining whether the observed shifts in autophagic activity precede or result from metabolic diseases remains challenging. Additionally, autophagy-modulating strategies are shortly discussed. To conclude, more studies investigating autophagy impairment are required to gain a more comprehensive understanding of its role in the pathogenesis of obesity, T2D, and MASLD and to unveil novel therapeutic strategies for these conditions.
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Multicenter Study
Heart failure, recurrent vascular events and death in patients with ischemic stroke-results of the MonDAFIS study.
Heart failure (HF) is associated with poor outcome after stroke, but data from large prospective trials are sparse. We assessed the impact of HF on clinical endpoints in patients hospitalized with acute ischemic stroke or transient ischemic attack (TIA) enrolled in the prospective, multicenter Systematic Monitoring for Detection of Atrial Fibrillation in Patients with Acute Ischemic Stroke (MonDAFIS) trial. HF was defined as left ventricular ejection fraction (LVEF) < 55% or a history of HF on admission. ⋯ The data were adjusted for age, stroke severity, cardiovascular risk factors, and randomization. Patients with ischemic stroke or TIA and comorbid HF have a higher risk of myocardial infarction and death compared with non-HF patients whereas the risk of recurrent stroke or major hemorrhage was similar. Trial registration number Clinicaltrials.gov NCT02204267.
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Multicenter Study
A COVID-19 specific multiparametric and ECG-based score for the prediction of in-hospital mortality: ELCOVID score.
We aimed to develop and validate a COVID-19 specific scoring system, also including some ECG features, to predict all-cause in-hospital mortality at admission. Patients were retrieved from the ELCOVID study (ClinicalTrials.gov identifier: NCT04367129), a prospective, multicenter Italian study enrolling COVID-19 patients between May to September 2020. For the model validation, we randomly selected two-thirds of participants to create a derivation dataset and we used the remaining one-third of participants as the validation set. ⋯ The derived risk-scoring system, namely EL COVID score, showed a moderate discriminatory capacity and good calibration. A cut-off score of ≥ 4 had a sensitivity of 78.4% and 65.2% specificity in predicting all-cause in-hospital mortality. ELCOVID score represents a valid, reliable, sensitive, and inexpensive scoring system that can be used for the prognostication of COVID-19 patients at admission and may allow the earlier identification of patients having a higher mortality risk who may be benefit from more aggressive treatments and closer monitoring.
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To develop a more accurate prognostic model that incorporates indicators of multi-organ involvement for immunoglobulin light-chain (AL) Amyloidosis patients. Biopsy-proven AL amyloidosis patients between January 1, 2012, and February 28, 2023, were enrolled and randomly divided into a training set and a test set at a ratio of 7:3. Prognostic indicators that comprehensively cover cardiac, renal, and hepatic involvement were identified in the training set by random survival forest (RSF). ⋯ The RSF model based on the above indicators achieved C-index and IBS values of 0.834 (95% CI 0.725-0.915) and 0.151 (95% CI 0.1402-0.181), respectively. At last, the NRI and IDI of the RSF model were 0.301 (95% CI 0.048-0.546, P = 0.012) and 0.157 (95% CI 0.041-0.269, P < 0.001) at 5-year by comparing the RSF model with the Cox model which is based on the Mayo 2012 staging system. The RSF model that incorporates indicators of multi-organ involvement had a great performance, which may be helpful for physicians' decision-making and more accurate overall survival prediction.