Search

Producción Científica, Background: procalcitonin is a valuable marker in the diagnosis of bacterial infections; however, the impairment of renal function can influence its diagnostic precision. The objective of this study is to evaluate the differential behaviour of procalcitonin, as well as its usefulness in the diagnosis of postoperative pulmonary infection after cardiac surgery, depending on the presence or absence of impaired renal function. Materials and methods: A total of 805 adult patients undergoing cardiac surgery with extracorporeal circulation (CBP) were prospectively recruited, comparing the behaviour of biomarkers between the groups with and without postoperative pneumonia and according to the presence or absence of renal dysfunction. Results: Pulmonary infection was diagnosed in 42 patients (5.21%). In total, 228 patients (28.32%) presented postoperative renal dysfunction. Procalcitonin was significantly higher in infected patients, even in the presence of renal dysfunction. The optimal procalcitonin threshold differed markedly in patients with renal dysfunction compared to patients without renal dysfunction (1 vs. 0.78 ng/mL p < 0.05). The diagnostic accuracy of procalcitonin increased significantly when the procalcitonin threshold was adapted to renal function. Conclusions: Procalcitonin is an accurate marker of postoperative infection in cardiac surgery, even in the presence of renal dysfunction. Renal function is an important determinant of procalcitonin levels and, therefore, its diagnostic thresholds must be adapted in the presence of renal dysfunction., Instituto de Salud Carlos III - (grant COV20/00491, PI18/01238, CIBERINFEC CB21/13/00051), Junta de Castilla y León - (grant VA321P18, GRS 1922/A/19, GRS 2057/A/19), Junta de Castilla y León, Consejería de Educación - (grant VA256P20), Fundación Ramón Areces - (grant CIVP19A5953), Instituto de Salud Carlos III y Fondo Europeo de Desarrollo Regional (FEDER)/Fondo Social Europeo - (grant CM20/00138)

Diagnosis of cardiac surgery-associated acute kidney injury (CSA-AKI), a syndrome of sudden renal dysfunction occurring in the immediate post-operative period, is still sub-optimal. Standard CSA-AKI diagnosis is performed according to the international criteria for AKI diagnosis, afflicted with insufficient sensitivity, specificity, and prognostic capacity. In this article, we describe the limitations of current diagnostic procedures and of the so-called injury biomarkers and analyze new strategies under development for a conceptually enhanced diagnosis of CSA-AKI. Specifically, early pathophysiological diagnosis and patient stratification based on the underlying mechanisms of disease are presented as ongoing developments. This new approach should be underpinned by process-specific biomarkers including, but not limited to, glomerular filtration rate (GFR) to other functions of renal excretion causing GFR-independent hydro-electrolytic and acid-based disorders. In addition, biomarker-based strategies for the assessment of AKI evolution and prognosis are also discussed. Finally, special focus is devoted to the novel concept of pre-emptive diagnosis of acquired risk of AKI, a premorbid condition of renal frailty providing interesting prophylactic opportunities to prevent disease through diagnosis-guided personalized patient handling. Indeed, a new strategy of risk assessment complementing the traditional scores based on the computing of risk factors is advanced. The new strategy pinpoints the assessment of the status of the primary mechanisms of renal function regulation on which the impact of risk factors converges, namely renal hemodynamics and tubular competence, to generate a composite and personalized estimation of individual risk.

Pneumonia is the leading cause of hospital admission and mortality in coronavirus disease 2019 (COVID-19). We aimed to identify the cytokines responsible for lung damage and mortality. We prospectively recruited 108 COVID-19 patients between March and April 2020 and divided them into four groups according to the severity of respiratory symptoms. Twenty-eight healthy volunteers were used for normalization of the results. Multiple cytokines showed statistically significant differences between mild and critical patients. High HGF levels were associated with the critical group (OR = 3.51, p &lt, 0.001, 95%CI = 1.95–6.33). Moreover, high IL-1α (OR = 1.36, p = 0.01, 95%CI = 1.07–1.73) and low IL-27 (OR = 0.58, 0.005, 95%CI = 0.39–0.85) greatly increased the risk of ending up in the severe group. This model was especially sensitive in order to predict critical status (AUC = 0.794, specificity = 69.74%, sensitivity = 81.25%). Furthermore, high levels of HGF and IL-1α showed significant results in the survival analysis (p = 0.033 and p = 0.011, respectively). HGF, IL-1α, and IL 27 at hospital admission were strongly associated with severe/critical COVID-19 patients and therefore are excellent predictors of bad prognosis. HGF and IL-1α were also mortality biomarkers.

Cardiac surgery-associated acute kidney injury (CSA-AKI) is a recognized and serious complication and one of the stronger risk factors for mortality in patients undergoing cardiac surgery [...]

Producción Científica, Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores., Instituto de Salud Carlos III (grant PI15/01451), Junta de Castilla y León (grant 1255/A/16), Universidad de Valladolid - Fondo Europeo de Desarrollo Regional (grant VA321P18)

Producción Científica, Acute kidney injury (AKI) is a widely held concern related to a substantial burden of morbidity, mortality and expenditure in the healthcare system. AKI is not a simple illness but a complex conglomeration of syndromes that often occurs as part of other syndromes in its wide clinical spectrum of the disease. Genetic factors have been suggested as potentially responsible for its susceptibility and severity. As there is no current cure nor an effective treatment other than generally accepted supportive measures and renal replacement therapy, updated knowledge of the genetic implications may serve as a strategic tactic to counteract its dire consequences. Further understanding of the genetics that predispose AKI may shed light on novel approaches for the prevention and treatment of this condition. This review attempts to address the role of key genes in the appearance and development of AKI, providing not only a comprehensive update of the intertwined process involved but also identifying specific markers that could serve as precise targets for further AKI therapies.

Lymphopenia has been related to increased mortality in septic patients. Nonetheless, the impact of lymphocyte count on candidemia mortality and prognosis has not been addressed. We conducted a retrospective study, including all admitted patients with candidemia from 2007 to 2016. We examined lymphocyte counts during the first 5 days following the diagnosis of candidemia. Multivariable logistic regression analysis was performed to determine the relationship between lymphocyte count and mortality. Classification and Regression Tree analysis was used to identify the best cut-off of lymphocyte count for mortality associated with candidemia. From 296 cases of candidemia, 115 died, (39.8% 30-day mortality). Low lymphocyte count was related to mortality and poor outcome (p &lt, 0.001). Lymphocyte counts &lt, 0.703 &times, 109 cells/L at diagnosis (area under the curve (AUC)-ROC, 0.783 &plusmn, 0.042, 95% confidence interval (CI), 0.700&ndash, 0.867, p &lt, 0.001), and lymphocyte count &lt, 1.272 &times, 109 cells/L five days later (AUC-ROC, 0.791 &plusmn, 0.038, 95%CI, 0.716&ndash, 0.866, p &lt, 0.001) increased the odds of mortality five-fold (odds ratio (OR), 5.01, 95%CI, 2.39&ndash, 10.93) at time of diagnosis, and three-fold (OR, 3.27, 95%CI, 1.24&ndash, 8.62) by day 5, respectively. Low lymphocyte count is an independent predictor of mortality in patients with candidemia and might serve as a biomarker for predicting candidemia-associated mortality and poor outcome.