Internal and emergency medicine
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Letter Historical Article
Vincenzo Tiberio (1869-1915) and the dawn of the antibiotic age.
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The human respiratory tract, usually considered sterile, is currently being investigated for human-associated microbial communities. According to Dickson's conceptual model, the lung microbiota (LMt) is a dynamic ecosystem, whose composition, in healthy lungs, is likely to reflect microbial migration, reproduction, and elimination. However, which microbial genera constitutes a "healthy microbiome" per se remains hotly debated. ⋯ Some authors hypothesize that the use of specific bacterial strains, termed "probiotics," with positive effects on the host immunity and/or against pathogens, could have beneficial effects in the treatment of intestinal disorders and pulmonary diseases. In this manuscript, we have reviewed the literature available on the LMt to delineate and discuss the potential relationship between composition alterations of LMt and lung diseases. Finally, we have reported some meaningful clinical studies that used integrated probiotics' treatments to contrast some lung-correlated disorders.
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Observational Study
Renal effects of Sacubitril/Valsartan in heart failure with reduced ejection fraction: a real life 1-year follow-up study.
Real-life data confirming the favourable renal outcome in patients with heart failure (HF) treated with Sacubitril/Valsartan, previously found in several trials (RCTs), are still scant. We evaluated the renal effects of Sacubitril/Valsartan in a real-life sample of HF patients. Observational analysis of 54 consecutive outpatients affected by HF with reduced ejection fraction (HFrEF) and clinical indication for Sacubitril/Valsartan. ⋯ A statistically (p = 0.009), but not clinically significant increase in serum potassium was also found, regardless of age and CKD. This is the first study focused on the renal effects of Sacubitril/Valsartan in HFrEF patients followed for 12 months in a real-life clinical context. The improved eGFR, despite lower BP, represents an important confirmation outside the peculiar world of RCTs.
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The primary study objective is to compare the outcomes of patients taking oral anticoagulant medications in two distinct populations treated according to different management models (comprehensive vs. usual care). (Design: regional prospective cohort study; setting: hospital admission data from two regions). Eligible partecipants were patients taking oral anticoagulant drugs (vitamin K antagonist or direct oral anticoagulants), residents in the Vicenza and Cremona districts from February 1st, 2016 to June 30th, 2017. Patients were identified by accessing the administrative databases of patient drug prescriptions. ⋯ Across the two cohorts, the risk of bleeding was lower in patients being treated with DOACs rather than warfarin (10/4574 vs. 42/8161 event/person-years, respectively, IRR 0.42 95% CI 0.19-0.86). We conclude that a comprehensive management model providing centralized dose prescription and follow-up may significantly reduce the rate of thromboembolic complications, without substantially increasing the number of bleeding complications. Patients treated with direct oral anticoagulants appear to have a rate of thromboembolic complications comparable to VKA patients under the best management model, with a reduction of major bleeding.
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The purpose of the present study is to develop and validate a prediction tool to identify patients who refuse to receive percutaneous coronary intervention (PCI) rapidly. We developed a risk stratification model using the derivation cohort of 288 patients with ST segment elevation myocardial infarction (STEMI) in our hospital and validated it in a prospective cohort of 115 patients. There were 52 (18.1%) patients and 18 (15.7%) patients who refused PCI among derivation and validation cohort, respectively. ⋯ And similar results were obtained when this prediction tool was applied prospectively to the validation cohort. Patients at low and high risk can be easily identified for refusal of PCI by the prediction tool using common clinical data. This practical model might provide useful information for rapid recognition and early response for this kind of crowd.