Obesity as an adipose tissue dysfunction disease and a risk factor for infections – Covid-19 as a case study

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV2) disease (COVID-19) is a novel threat that hampers life expectancy especially in obese individuals. Though this association is clinically relevant, the underlying mechanisms are not fully elucidated. SARS CoV2 enters host cells via the Angiotensin Converting Enzyme 2 receptor, that is also expressed in adipose tissue. Moreover, adipose tissue is also a source of many proinflammatory mediators and adipokines that might enhance the characteristic COVID-19 cytokine storm due to a chronic low-grade inflammatory preconditioning. Further obesity-dependent thoracic mechanical constraints may also incise negatively into the prognosis of obese subjects with COVID-19. This review summarizes the current body of knowledge on the obesity-dependent circumstances triggering an increased risk for COVID-19 severity, and their clinical relevanc

Relación entre las fases precoces de la enfermedad renal y el síndrome metabólico

Advanced kidney disease is a major health problem due to its association with high cardiovascular morbidity and mortality. Early recognition of advanced kidney disease is the mainstay to avoid its progression. Since metabolic syndrome and insulin resistance are risk factors for both cardiovascular and advanced kidney disease, we investigated the relationship of early kidney disease (EKD) with metabolic syndrome and insulin resistance, and their association with surrogate markers of arteriosclerosis. METHODS: We studied 1498 subjects. Insulin resistance was defined as HOMA >/=3.7 mmol (muU)/L(2) and EKD as stages 1 and 2 of the NKF-KDOQI. Carotid intima-media thickness was used as a surrogate marker of arteriosclerosis. RESULTS: The presence of one trait of metabolic syndrome was associated with an odds ratio (OR) for EKD of 2.3 (95% confidence interval [CI], 1.18-4.48) that increased to 6.72 (95% CI, 3.56-13.69) in subjects with the syndrome. All the traits of the syndrome except low level of high-density lipoproteins showed an increased OR for EKD. Increasing HOMA was also directly correlated with higher OR for EKD, being as high as 3.89 (95% CI, 1.99-7.59) for subjects in the fourth quartile. Subjects with the syndrome plus EKD showed an increased intima-media thickness compared with those without kidney disease. CONCLUSIONS: Insulin resistance and all metabolic syndrome traits except low level of high-density lipoproteins were significantly associated with an increased OR for EKD. Both metabolic syndrome and EKD were independently and additively related to the presence of surrogate markers of arteriosclerosis

Predictors of mortality and poor outcome in cancer patients with E. faecium bloodstream infection

Background. To analyze predictors of mortality and poor outcome in cancer patients diagnosed with E. faecium bloodstream infection. Methods. Demographic, clinical and microbiological data were collected (January 1998-June 2011). Results. After multivariate analysis, presence of a urinary catheter was associated with a worse 7-day prognosis, and higher mortality at discharge. A high Charlson index was also associated with higher 7-day mortality. Conclusion. Presence of a urinary catheter was associated with poor 7-day prognosis and higher mortality at discharge in the present series.Fundamento. Analizar los predictores de mortalidad y mal pronóstico en el paciente oncológico diagnosticado de bacteriemia por E. faecium. Métodos. Se analizaron datos demográficos, clínicos y microbiológicos (Enero 1998-Junio 2011). Resultados. El análisis multivariable demostró que la presencia de una sonda urinaria se asoció a mal pronóstico a los 7 días y alta mortalidad del paciente al final del estudio. Un índice de Charlson elevado se asoció a un aumento en la mortalidad a los 7 días. Conclusión. En nuestro estudio, la presencia de sonda urinaria se asoció con mal pronóstico del paciente a los 7 días y aumento de la mortalidad

Association of phagocytic NADPH oxidase activity with hypertensive heart disease: a role for cardiotrophin-1?

Left ventricular hypertrophy (LVH) is an independent marker of mortality in hypertension. Although the mechanisms contributing to LVH are complex, inflammation and oxidative stress may favor its development. We analyzed the association of the phagocytic NADPH oxidase–mediated superoxide anion release and LVH in patients with essential hypertension and the role of cardiotrophin-1 (CT-1) and interleukin-6 (IL-6), cytokines implicated in cardiac growth. Blood pressure, echocardiography data, and serum CT-1 and IL-6 levels were obtained in 140 subjects: 18 normotensives without LVH, 42 hypertensives without LVH, and 80 hypertensives with LVH. The NADPH oxidase–dependent superoxide production was assessed by chemiluminescence in peripheral blood mononuclear cells. Peripheral blood mononuclear cells were stimulated with CT-1 in vitro. Superoxide anion production by peripheral blood mononuclear cells associated with LVH and correlated with the left ventricular mass index. Serum CT-1 and IL-6 levels, which associated with the left ventricular mass index, correlated with superoxide production. Serum CT-1 and IL-6 levels were correlated. CT-1 stimulated NADPH oxidase superoxide production in peripheral blood mononuclear cells, which resulted in an increased release of IL-6. Our results show that superoxide anion production by the phagocytic NADPH oxidase associates with hypertensive heart disease, being significantly enhanced in hypertensive patients with LVH. This may be attributable to the activation of the NADPH oxidase by CT-1 and the subsequent release of IL-6. The phagocytic NADPH oxidase may be a therapeutic target in hypertensive heart diseas

Performance of SAPS II and SAPS 3 in Intermediate Care

Objective: The efficacy and reliability of prognostic scores has been described extensively for intensive care, but their role for predicting mortality in intermediate care patients is uncertain. To provide more information in this field, we have analyzed the performance of the Simplified Acute Physiology Score (SAPS) II and SAPS 3 in a single center intermediate care unit (ImCU). Materials and Methods: Cohort study with prospectively collected data from all patients admitted to a single center ImCU in Pamplona, Spain, from April 2006 to April 2012. The SAPS II and SAPS 3 scores with respective predicted mortality rates were calculated according to standard coefficients. Discrimination was evaluated by calculating the area under receiver operating characteristic curve (AUROC) and calibration with the Hosmer-Lemeshow goodness of fit test. Standardized mortality ratios (SMR) with 95% confidence interval (95% CI) were calculated for each model. Results: The study included 607 patients. The observed in-hospital mortality was 20.1% resulting in a SMR of 0.87 (95% CI 0.73-1.04) for SAPS II and 0.56 (95% CI 0.47-0.67) for SAPS 3. Both scores showed acceptable discrimination, with an AUROC of 0.76 (95% CI 0.71-0.80) for SAPS II and 0.75 (95% CI 0.71- 0.80) for SAPS 3. Calibration curves showed similar performance based on Hosmer-Lemeshow goodness of fit C-test: (X2=12.9, p=0.113) for SAPS II and (X2=4.07, p=0.851) for SAPS 3. Conclusions: Although both scores overpredicted mortality, SAPS II showed better discrimination for patients admitted to ImCU in terms of SMR

Long-term outcome of critically III advanced cancer patients managed in an intermediate care unit

Background: To analyze the long-term outcomes for advanced cancer patients admitted to an intermediate care unit (ImCU), an analysis of a do not resuscitate orders (DNR) subgroup was made. Methods: A retrospective observational study was conducted from 2006 to January 2019 in a single academic medical center of cancer patients with stage IV disease who suffered acute severe complications. The Simplified Acute Physiology Score 3 (SAPS 3) was used as a prognostic and severity score. In-hospital mortality, 30-day mortality and survival after hospital discharge were calculated. Results: Two hundred and forty patients with stage IV cancer who attended at an ImCU were included. In total, 47.5% of the cohort had DNR orders. The two most frequent reasons for admission were sepsis (32.1%) and acute respiratory failure (excluding sepsis) (38.7%). Mortality in the ImCU was 10.8%. The mean predicted in-hospital mortality according to SAPS 3 was 51.9%. The observed in-hospital mortality was 37.5% (standard mortality ratio of 0.72). Patients discharged from hospital had a median survival of 81 (30.75-391.25) days (patients with DNR orders 46 days (19.5-92.25), patients without DNR orders 162 days (39.5-632)). The observed mortality was higher in patients with DNR orders: 52.6% vs. 23.8%, p 0 < 0.001. By multivariate logistic regression, a worse ECOG performance status (3-4 vs. 0-2), a higher SAPS 3 Score and DNR orders were associated with a higher in-hospital mortality. By multivariate analysis, non-invasive mechanical ventilation, higher bilirubin levels and DNR orders were significantly associated with 30-day mortality. Conclusion: For patients with advanced cancer disease, even those with DNR orders, who suffer from acute complications or require continuous monitoring, an ImCU-centered multidisciplinary management shows encouraging results in terms of observed-to-expected mortality ratios

Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies