Acute kidney injury (AKI) is a frequent complication after cardiac surgery and is associated with increased mortality. The aim was to design a nondialytic AKI score in patients with previously normal renal function undergoing cardiac surgery. Data were collected on 909 patients who underwent cardiac surgery with cardiopulmonary bypass between 2012 and 2014. A total of 810 patients fulfilled the inclusion criteria. Patients were classified as having AKI based on the RIFLE criteria. Postoperative AKI occurred in 137 patients (16.9%). Several parameters were recorded preoperatively, intraoperatively, and at intensive care unit admission, looking for a univariate and multivariate association with AKI risk. A second data set of 741 patients, from 2 different hospitals, was recorded as a validation cohort. Four independent risk factors were included in the CRATE score: creatinine (odds ratio [OR], 9.66; 95% confidence interval [CI], 4.77-19.56; P < .001), EuroSCORE (OR, 1.40; CI, 1.29-1.52; P < .001), lactate (OR, 1.03; CI, 1.01-1.04; P < .001), and cardiopulmonary bypass time (OR, 1.01; CI, 1.01-1.02; P < .001). The accuracy of the model was good, with an area under the curve of 0.89 (CI, 0.85-0.92). The CRATE score retained good discrimination in validation cohort, with an area under the curve of 0.81 (95% CI, 0.78-0.85). CRATE score is an accurate and easy to calculate risk score that uses affordable and widely available variables in the routine care surgical patients.

Acute kidney injury (AKI) and Chronic Kidney Disease (CKD) are global health problems. The pathophysiology of acute-on-chronic kidney disease (AoCKD) is not well understood. We aimed to study clinical outcomes in patients with previous normal (pure acute kidney injury; P-AKI) or impaired kidney function (AoCKD) across the 2012 Kidney Disease Improving Global Outcomes (KDIGO) AKI classification. We performed a retrospective study of patients with AKI, divided into P-AKI and AoCKD groups, evaluating clinical and epidemiological features, distribution across KDIGO-2012 criteria, in-hospital mortality and need for dialysis. One thousand, two hundred and sixty-nine subjects were included. AoCKD individuals were older and had higher comorbidity. P-AKI individuals fulfilled more often the serum creatinine (SCr) ≥ 3.0× criterion in AKI-Stage3, AoCKD subjects reached SCr ≥ 4.0 mg/dL criterion more frequently. AKI severity was associated with in-hospital mortality independently of baseline renal function. AoCKD subjects presented higher mortality when fulfilling AKI-Stage1 criteria or SCr ≥ 3.0× criterion within AKI-Stage3. The relationship between mortality and associated risk factors, such as the net increase of SCr or AoCKD status, fluctuated depending on AKI stage and stage criteria sub-strata. AoCKD patients that fulfil SCr increment rate criteria may be exposed to more severe insults, possibly explaining the higher mortality. AoCKD may constitute a unique clinical syndrome. Adequate staging criteria may help prompt diagnosis and administration of appropriate therapy.

Goal-directed therapy based on brain-oxygen saturation (bSo₂) is controversial and hotly debated. While meta-analyses of aggregated data have shown no clinical benefit for brain near-infrared spectroscopy (NIRS)-based interventions after cardiac surgery, no network meta-analyses involving both major cardiac and noncardiac procedures have yet been undertaken. Randomized controlled trials involving NIRS monitoring in both major cardiac and noncardiac surgery were included. Aggregate-level data summary estimates of critical outcomes (postoperative cognitive decline (POCD)/postoperative delirium (POD), acute kidney injury, cardiovascular events, bleeding/need for transfusion, and postoperative mortality) were obtained. NIRS was only associated with protection against POCD/POD in cardiac surgery patients (pooled odds ratio (OR)/95% confidence interval (CI)/I²/number of studies (n): 0.34/0.14–0.85/75%/7), although a favorable effect was observed in the analysis, including both cardiac and noncardiac procedures. However, the benefit of the use of NIRS monitoring was undetectable in Bayesian network meta-analysis, although maintaining bSo₂ > 80% of the baseline appeared to have the most pronounced impact. Evidence was imprecise regarding acute kidney injury, cardiovascular events, bleeding/need for transfusion, and postoperative mortality. There is evidence that brain NIRS-based algorithms are effective in preventing POCD/POD in cardiac surgery, but not in major noncardiac surgery. However, the specific target bSo₂ threshold has yet to be determined.

Major changes have occurred in the epidemiology and etiology of infective endocarditis (IE). Nevertheless, the differences between nosocomial infective endocarditis (NIE) and community-acquired infective endocarditis (CIE) have not been addressed in a population-based study. We conducted a retrospective, nationwide, temporal trend study from 1997 to 2014 analyzing the epidemiology, clinical, geographical, meteorological characteristics of patients diagnosed with IE in Spain, to distinguish NIE from CIE. Among 25,952 patients with IE (62.2 ± 18·6 years; 65.9% men), 45.9% had NIE. The incidence of IE increased from 2.83 to 3.73 due to the NIE incidence increment with a decline in CIE. Patients with NIE were older (63.8 years vs. 60.8 years, p < 0·001), presented a higher Charlson index (1.22 vs. 1.03, p < 0.001), a greater history of implanted cardiac devices (8.7% vs. 4.6%, p < 0.001), and higher mortality (31.5% vs. 21.7%, p < 0.001). The most frequent microorganism for both NIE and CIE was Staphylococcus (p < 0.001), and the North reported a higher incidence (p < 0.001). Risk factors of mortality for NIE were age, Charlson index, hemodialysis, shock, heart failure, and stroke. Risk factors for CIE included female sex, renal disease, and cardiac-device carriers. The etiology of IE shifted from community origins to mostly nosocomial-associated infections. Higher morbidity, mortality, and poorer outcomes are associated with NIE.

Background: Anti‐SARS‐CoV‐2 S antibodies prevent viral replication. Critically ill COVID‐19 patients show viral material in plasma, associated with a dysregulated host response. If these antibodies influence survival and viral dissemination in ICU‐COVID patients is unknown.Patients/Methods: We studied the impact of anti‐SARS‐CoV‐2 S antibodies levels on survival, viral RNA‐load in plasma, and N‐antigenaemia in 92 COVID‐19 patients over ICU admission.Results: Frequency of N‐antigenaemia was >2.5‐fold higher in absence of antibodies. Antibodies correlated inversely with viral RNA‐load in plasma, representing a protective factor against mortality (adjusted HR [CI 95%], p): (S IgM [AUC ≥ 60]: 0.44 [0.22; 0.88], 0.020); (S IgG [AUC ≥ 237]: 0.31 [0.16; 0.61], <0.001). Viral RNA‐load in plasma and N‐antigenaemia predicted increased mortality: (N1‐viral load [≥2.156 copies/ml]: 2.25 [1.16; 4.36], 0.016); (N‐antigenaemia: 2.45 [1.27; 4.69], 0.007).Conclusions: Low anti‐SARS‐CoV‐2 S antibody levels predict mortality in critical COVID‐19. Our findings support that these antibodies contribute to prevent systemic dissemination of SARS‐CoV‐2.