Associations between depressive symptoms and disease progression in older patients with chronic kidney disease: results of the EQUAL study

Background Depressive symptoms are associated with adverse clinical outcomes in patients with end-stage kidney disease; however, few small studies have examined this association in patients with earlier phases of chronic kidney disease (CKD). We studied associations between baseline depressive symptoms and clinical outcomes in older patients with advanced CKD and examined whether these associations differed depending on sex. Methods CKD patients (>= 65 years; estimated glomerular filtration rate <= 20 mL/min/1.73 m(2)) were included from a European multicentre prospective cohort between 2012 and 2019. Depressive symptoms were measured by the five-item Mental Health Inventory (cut-off <= 70; 0-100 scale). Cox proportional hazard analysis was used to study associations between depressive symptoms and time to dialysis initiation, all-cause mortality and these outcomes combined. A joint model was used to study the association between depressive symptoms and kidney function over time. Analyses were adjusted for potential baseline confounders. Results Overall kidney function decline in 1326 patients was -0.12 mL/min/1.73 m(2)/month. A total of 515 patients showed depressive symptoms. No significant association was found between depressive symptoms and kidney function over time (P = 0.08). Unlike women, men with depressive symptoms had an increased mortality rate compared with those without symptoms [adjusted hazard ratio 1.41 (95% confidence interval 1.03-1.93)]. Depressive symptoms were not significantly associated with a higher hazard of dialysis initiation, or with the combined outcome (i.e. dialysis initiation and all-cause mortality). Conclusions There was no significant association between depressive symptoms at baseline and decline in kidney function over time in older patients with advanced CKD. Depressive symptoms at baseline were associated with a higher mortality rate in men

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary out- come the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs . 0.69, P < 0.01 [paired t -test with 95% confidence interval]). Conclusions: The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources

Documento di consenso ANMCO/SIC sulla gestione delle miocarditi

Myocarditis is an inflammatory heart disease that can occur acutely, as in acute myocarditis, or persistently, as in chronic myocarditis or chronic inflammatory cardiomyopathy. Different agents can induce myocarditis, with viruses being the most common triggers. Generally, acute myocarditis affects relatively young people and men more than women. Myocarditis has a broad spectrum of clinical presentations and evolution trajectories, although most cases resolve spontaneously. Patients with reduced left ventricular ejection fraction, heart failure symptoms, advanced atrioventricular block, sustained ventricular arrhythmias or cardiogenic shock (the latter known as fulminant myocarditis) are at increased risk for death and heart transplantation. The presentation of chronic inflammatory cardiomyopathy may be more subtle, with progressive symptoms of heart failure or appearance of rhythm disturbance, not rarely preceded by an infective episode. Autoimmune disorder or systemic inflammatory conditions can be another significant predisposing substrate of myocarditis, especially in women. Emerging causes of myocarditis are drug-related like the new anticancer therapies, the immune checkpoint inhibitors. In this Italian Association of Hospital Cardiologists (ANMCO) and Italian Society of Cardiology (SIC) expert consensus document on myocarditis, we propose diagnostic strategies for identifying possible causes of the disease and factors associated with increased risk. Finally, we propose potential treatments and when referring patients to tertiary centers, especially for high-risk patients. Even if endomyocardial biopsy is the invasive diagnostic tool for making definitive diagnosis and differentiation of histological subtypes (i.e., lymphocytic vs eosinophilic vs giant cell myocarditis), it is not always readily available in all centers. Thus, we propose when this exam is mandatory or when it can be postponed or substituted by cardiac magnetic resonance imaging. This document reflects the Italian perspective on managing patients with myocarditis and their follow-up, considering also current US and European scientific position statements

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

Background: Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is wide‑ spread. While the risks and benefts of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefts of diferent respiratory sup‑ port strategies, employed in intensive care units during the frst months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. Methods: Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclas‑ sifed into standard oxygen therapy ≥10 L/min (SOT), high-fow oxygen therapy (HFNC), noninvasive positive-pressureBackground: Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. Methods: Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. Results: Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). Conclusion: In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk

Kidney Failure Prediction Models: A Comprehensive External Validation Study in Patients with Advanced CKD

Background: Various prediction models have been developed to predict the risk of kidney failure in patients with CKD. However, guideline-recommended models have yet to be compared head to head, their validation in patients with advanced CKD is lacking, and most do not account for competing risks.Methods: To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration.Results: The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%-18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts.Conclusions: Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years)

Predicting Kidney Failure, Cardiovascular Disease and Death in Advanced CKD Patients

Introduction: Predicting the timing and occurrence of kidney replacement therapy (KRT), cardiovascular events, and death among patients with advanced chronic kidney disease (CKD) is clinically useful and relevant. We aimed to externally validate a recently developed CKD G4+ risk calculator for these outcomes and to assess its potential clinical impact in guiding vascular access placement. Methods: We included 1517 patients from the European Quality (EQUAL) study, a European multicentre prospective cohort study of nephrology-referred advanced CKD patients aged ≥65 years. Model performance was assessed based on discrimination and calibration. Potential clinical utility for timing of referral for vascular access placement was studied with diagnostic measures and decision curve analysis (DCA). Results: The model showed a good discrimination for KRT and “death after KRT,” with 2-year concordance (C) statistics of 0.74 and 0.76, respectively. Discrimination for cardiovascular events (2-year C-statistic: 0.70) and overall death (2-year C-statistic: 0.61) was poorer. Calibration was fairly accurate. Decision curves illustrated that using the model to guide vascular access referral would generally lead to less unused arteriovenous fistulas (AVFs) than following estimated glomerular filtration rate (eGFR) thresholds. Conclusion: This study shows moderate to good predictive performance of the model in an older cohort of nephrology-referred patients with advanced CKD. Using the model to guide referral for vascular access placement has potential in combating unnecessary vascular surgeries

The association between TMAO, CMPF and clinical outcomes in advanced CKD; results from the EQUAL study

Background Trimethylamine N-oxide (TMAO), a metabolite from red meat and fish consumption, plays a role in promoting cardiovascular events. However, data regarding TMAO and its impact on clinical outcomes are inconclusive, possibly due to its undetermined dietary source. Objectives We hypothesized that circulating TMAO derived from fish intake might cause less harm compared with red meat sources by examining the concomitant level of 3-carboxy-4-methyl-5-propyl-2-furanpropionate (CMPF), a known biomarker of fish intake, and investigated the association between TMAO, CMPF, and outcomes. Methods Patients were recruited from the European QUALity (EQUAL) Study on treatment in advanced chronic kidney disease among individuals aged &gt;= 65 y whose estimated glomerular filtration rate (eGFR) had dropped for the first time to &lt;= 20 mL/min per 1.73 m(2) during the last 6 mo. The association between TMAO, CMPF, and outcomes including all-cause mortality and kidney replacement therapy (KRT) was assessed among 737 patients. Patients were further stratified by median cutoffs of TMAO and CMPF, suggesting high/low red meat and fish intake. Results During a median of 39 mo of follow-up, 232 patients died. Higher TMAO was independently associated with an increased risk of all-cause mortality (multivariable HR: 1.46; 95% CI: 1.17, 1.83). Higher CMPF was associated with a reduced risk of both all-cause mortality (HR: 0.79; 95% CI: 0.71, 0.89) and KRT (HR: 0.80; 95% CI: 0.71, 0.90), independently of TMAO and other clinically relevant confounders. In comparison to patients with low TMAO and CMPF, patients with low TMAO and high CMPF had reduced risk of all-cause mortality (adjusted HR: 0.49; 95% CI: 0.31, 0.73), whereas those with high TMAO and high CMPF showed no association across adjusted models. Conclusions High CMPF conferred an independent role in health benefits and might even counteract the unfavorable association between TMAO and outcomes. Whether higher circulating CMPF concentrations are due to fish consumption, and/or if CMPF is a protective factor, remains to be verified

Symptom Burden before and after Dialysis Initiation in Older Patients

For older patients with kidney failure, lowering symptom burden may be more important than prolonging life. Dialysis initiation may affect individual kidney failure-related symptoms differently, but the change in symptoms before and after start of dialysis has not been studied. Therefore, we investigated the course of total and individual symptom number and burden before and after starting dialysis in older patients

Search for dark matter in association with an energetic photon in pp collisions at s = 13 TeV with the ATLAS detector

Abstract: A search for dark matter is conducted in final states containing a photon and missing transverse momentum in proton-proton collisions at s = 13 TeV. The data, collected during 2015–2018 by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 fb−1. No deviations from the predictions of the Standard Model are observed and 95% confidence-level upper limits between 2.45 fb and 0.5 fb are set on the visible cross section for contributions from physics beyond the Standard Model, in different ranges of the missing transverse momentum. The results are interpreted as 95% confidence-level limits in models where weakly interacting dark-matter candidates are pair-produced via an s-channel axial-vector or vector mediator. Dark-matter candidates with masses up to 415 (580) GeV are excluded for axial-vector (vector) mediators, while the maximum excluded mass of the mediator is 1460 (1470) GeV. In addition, the results are expressed in terms of 95% confidence-level limits on the parameters of a model with an axion-like particle produced in association with a photon, and are used to constrain the coupling gaZγ of an axion-like particle to the electroweak gauge bosons