Revista espanola de cardiologia最新文献

Most of the signs and symptoms of heart failure can be explained by fluid overload, which is also related to disease progression. Fluid overload is a complex phenomenon that extends beyond increased intravascular pressures and poses challenges for accurate diagnosis and effective treatment. Current recommendations advise a multiparametric approach, including clinical data (symptoms/signs), imaging tests, and biomarkers. This article proposes a practical therapeutic approach to managing hydrosaline overload in heart failure in both inpatient and outpatient settings. This document is an initiative of the Spanish Society of Internal Medicine (SEMI) in collaboration with the Spanish Society of Cardiology (SEC) and the Spanish Society of Nephrology (S.E.N.).

Introduction and objectives

The PEACE study (Performance of a sirolimus-eluting balloon strategy in acute and chronic coronary syndromes) investigated for the first time whether a sirolimus-coated balloon (SCB) (Magic Touch, Concept Medical, India) is associated with different outcomes depending on whether it is used in acute coronary syndromes (ACS) or chronic coronary syndromes (CCS).

Methods

This was a post-hoc analysis from the all-comers EASTBOURNE Registry (NCT03085823). Out of 2083 patients enrolled, an SCB was used to treat 968 (46.5%) ACS and 1115 (53.5%) CCS patients. The primary endpoint was target lesion revascularization at 12 months, while secondary endpoints were angiographic success and major adverse cardiovascular events.

Results

Baseline demographics, mean reference vessel diameter and mean lesion length were comparable between ACS and CCS. Predilatation was more commonly performed in ACS (P = .007). SCB was inflated at a standard pressure in both groups with a slight trend toward longer inflation time in ACS. Angiographic success was high in both groups (ACS 97.4% vs CCS 97.7%, P = .820) with limited bailout stenting. Similarly, at 12 months the cumulative incidence of target lesion revascularization (ACS 6.6% vs CCS 5.2%, P = .258) was comparable between ACS and CCS. Conversely, a higher rate of major adverse cardiovascular events in acute presenters was mainly driven by myocardial infarction recurrencies (ACS 10.4% vs CCS 8.3%, P = .009). In-stent restenosis showed a higher proportion of target lesion revascularization and major adverse cardiovascular events than de novo lesions, independently of the type of presentation at the index procedure.

Conclusions

This SCB shows good performance in terms of acute and 1-year outcomes independently of the clinical presentation.

Introduction and objectives

Hypercoagulability and thromboembolism are processes that arise from severe acute respiratory syndrome coronavirus 2 infection and are responsible for a high degree of coronavirus disease 2019 (COVID-19)-related morbidity and mortality. This study sought to assess the effect of antiplatelet drugs on COVID-19 severity (risk of hospitalization and mortality), susceptibility to severe acute respiratory syndrome coronavirus 2 infection, and progression to severe COVID-19.

Methods

We conducted a population-based case-control study in a northwestern region of Spain in 2020. The study involved 3060 participants with a positive polymerase chain reaction test who were hospitalized, 26 757 participants with a positive polymerase chain reaction test who were not hospitalized, and 56 785 healthy controls.

Results

Triflusal seemed to be associated with a significant increase in risk of hospitalization (aOR, 1.97; 95%CI, 1.27-3.04) and susceptibility to infection (OR, 1.45; 95%CI, 1.07-1.96). It also appeared to lead to a nonsignificant increase in the risk of mortality (OR, 2.23; 95%CI, 0.89-5.55) and/or progression to more severe disease stages (OR, 1.42; 95%CI, 0.8-2.51). Aspirin seemed to be associated with a statistically significant decrease in susceptibility to severe acute respiratory syndrome coronavirus 2 infection (OR, 0.92; 95%CI, 0.86-0.98).

Conclusions

Triflusal use appears to increase the risk of susceptibility to COVID-19 infection and an even higher risk of hospitalization, whereas the other antiplatelets could be associated with a reduction in the risk of the various outcomes or have no effect on risk. These findings could support reconsideration of triflusal prescription in COVID-19 pandemic situations.

Introduction and objectives

The present study sought to establish the diagnostic yield of cardiovascular magnetic resonance (CMR) in a large cohort of patients admitted with myocardial infarction (MI) with nonobstructive coronary artery disease (MINOCA) based on the timing of referral to CMR.

Methods

Consecutive patients referred to CMR from January 2009 to February 2022 with a working diagnosis of MINOCA were retrospectively evaluated. Cine, T₂-weighted, early, and late gadolinium-enhanced images were acquired and analyzed. The frequency of the underlying diagnosis and the association between timing of CMR and relative frequency of each diagnosis were assessed.

Results

We included 207 patients (median age 50 years, 60% men). Final diagnosis after CMR was achieved in 91% of the patients (myocarditis in 45%, MI in 20%, tako-tsubo cardiomyopathy in 19%, and other cardiomyopathies in 7%). The performance of CMR within 7 days of admission with MINOCA (median, 5 days; 117 patients) allowed a higher diagnostic yield compared with CMR performed later (median, 10 days; 88 patients) (96% vs 86%, P = .02). Although myocarditis was the most frequent diagnosis in both groups according to time to CMR, its frequency was higher among patients with a CMR performed within the first 7 days (53% vs 35%, P = .02). The frequency of other underlying diagnoses was not influenced by CMR timing.

Conclusions

CMR led to an underlying diagnosis of MINOCA in 91% of patients and its diagnostic yield increased to 96% when CMR was performed within 7 days of admission. The most frequent diagnosis was myocarditis.

Introduction and objectives

Delirium, recognized as a crucial prognostic factor in the cardiac intensive care unit (CICU), has evolved in response to the changing demographics among critically ill cardiac patients. This study aimed to create a predictive model for delirium for patients in the CICU.

Methods

This study included consecutive patients admitted to the CICU of the Samsung Medical Center. To assess the candidate variables for the model: we applied the following machine learning methods: random forest, extreme gradient boosting, partial least squares, and Plmnet-elastic.net. After selecting relevant variables, we performed a logistic regression analysis to derive the model formula. Internal validation was conducted using 100-repeated hold-out validation.

Results

We analyzed 2774 patients, 677 (24.4%) of whom developed delirium in the CICU. Machine learning-based models showed good predictive performance. Clinically significant and frequently important predictors were selected to construct a delirium prediction scoring model for CICU patients. The model included albumin level, international normalized ratio, blood urea nitrogen, white blood cell count, C-reactive protein level, age, heart rate, and mechanical ventilation. The model had an area under the receiver operating characteristics curve (AUROC) of 0.861 (95%CI, 0.843-0.879). Similar results were obtained in internal validation with 100-repeated cross-validation (AUROC, 0.854; 95%CI, 0.826-0.883).

Conclusions

Using variables frequently ranked as highly important in four machine learning methods, we created a novel delirium prediction model. This model could serve as a useful and simple tool for risk stratification for the occurrence of delirium at the patient's bedside in the CICU.