Obesity, which is a worldwide epidemic, confers increased risk for multiple serious conditions including type 2 diabetes, nonalcoholic fatty liver disease, and cardiovascular diseases. Adipose tissue ...is considered one of the largest endocrine organs in the body as well as an active tissue for cellular reactions and metabolic homeostasis rather than an inert tissue only for energy storage. The functional pleiotropism of adipose tissue relies on its ability to synthesize and release a large number of hormones, cytokines, extracellular matrix proteins, and growth and vasoactive factors, which are collectively called adipokines known to influence a variety of physiological and pathophysiological processes. In the obese state, excessive visceral fat accumulation causes adipose tissue dysfunctionality that strongly contributes to the onset of obesity-related comorbidities. The mechanisms underlying adipose tissue dysfunction include adipocyte hypertrophy and hyperplasia, increased inflammation, impaired extracellular matrix remodeling, and fibrosis together with an altered secretion of adipokines. This review describes the relevance of specific adipokines in the obesity-associated cardiovascular disease.
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•Health care professionals are not familiar with machine learning.•It is simple to apply machine learning supervised algorithms to clinical data.•Machine learning adds value to ...traditional regression techniques.•Both R (script) and RapidMiner (graphic) are user-friendly tools for it.•Readers can easily replicate this analysis and apply it to their own data.
The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical software platforms, were also compared.
The data used in this research come from the open database of the Framingham Heart Study, which originated in 1948 in Framingham, Massachusetts as a prospective study of risk factors for cardiovascular disease. Through data mining processes, three data models were elaborated and a comparative methodological study between the different ML algorithms – decision tree, random forest, support vector machines, neural networks, and logistic regression – was carried out. The global selection criterium for choosing the right set of hyperparameters and the type of data manipulation was the area under a curve (AUC). The software tools used to analyze the data were R-Studio® and RapidMiner®.
The Framingham study open database contains 4240 observations. The algorithm that yielded the greatest AUC when analyzing the data in R-Studio was neural network applied to a model that excluded all observations in which there was at least one missing value (AUC = 0.71); when analyzing the data in RapidMiner and applying the same model, the best algorithm was support vector machines (AUC = 0.75).
ML algorithms can reinforce the diagnostic and prognostic capacity of traditional regression techniques. Differences between the applicability of those algorithms and the results obtained with them were a function of the software platforms used in the data analysis.
Since the description of ghrelin in 1999, several studies have dug into the effects of this hormone and its relationship with bariatric surgery. While some aspects are still unresolved, a clear ...connection between ghrelin and the changes after metabolic surgery have been established. Besides weight loss, a significant amelioration in obesity-related comorbidities following surgery has also been reported. These changes in patients occur in the early postoperative period, before the weight loss appears, so that amelioration may be mainly due to hormonal changes. The purpose of this review is to go through the current body of knowledge of ghrelin’s physiology, as well as to update and clarify the changes that take place in ghrelin concentrations following bariatric/metabolic surgery together with their potential consolidation to outcomes.
Cardiovascular Prevention in Obese Patients Landecho, Manuel F; Moncada, Rafael; Valentí, Víctor ...
Current pharmaceutical design,
01/2016, Letnik:
22, Številka:
37
Journal Article
Recenzirano
The World Health Organization has emphasized that an increased body mass index (BMI) is a major risk factor for non-communicable diseases (NCDs) such as cardiovascular disease (CVD) together with ...diabetes, musculoskeletal disorders and some cancers. The American Heart Association had already identified obesity as an independent risk factor in 1995. There is a significantly increased risk of CVD independently of other traditional risk factors (age, sex, physical activity, smoking, blood pressure and cholesterol levels) for patients fulfilling BMI criteria of moderate overweight, which increases with the diagnosis of obesity. Thus, both overweight and obesity are major risk factors for type 2 diabetes (T2D), hypertension, and atherogenic dyslipidemia, among others. These diseases, when clustered, form the metabolic syndrome, a condition with exponential risk for CVD as compared with its isolated components. In this scenario, obesity emerges as a major public health challenge due to its huge clinical implications, taxing not only individuals but also health-care systems and society at large.
The present review focuses on: i) the link between dysfunctional fat excess and CVD; ii) the apparent controversies surrounding the obesity paradox as well as the concept of metabolically healthy obesity; iii) the known beneficial effects following weight loss; and iv) available strategies to treat obesity in order to ameliorate cardiovascular risk, which include lifestyle interventions, drug therapy, endoscopic and surgical procedures.
Obesity is a highly heterogeneous disease that requires customized recommendations. Weight loss in different degrees is attainable via diverse procedures reducing morbidity and mortality while improving psychological well-being and social function. Therapeutic strategies should be tailored to the patient's characteristics and need a long-term personal commitment to change.
The purpose of this study was to evaluate the presence of retinal and microvascular alterations in COVID-19 patients with bilateral pneumonia due to SARS-COV-2 that required hospital admission and ...compare this with a cohort of age- and sex-matched controls. COVID-19 bilateral pneumonia patients underwent retinal imaging 14 days after hospital discharge with structural optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) measurements. Vessel density (VD) and foveal avascular zone (FAZ) area were evaluated in the superficial, deep capillary plexus (SCP, DCP), and choriocapillaris (CC). After exclusion criteria, only one eye per patient was selected, and 50 eyes (25 patients and 25 controls) were included in the analysis. COVID-19 patients presented significantly thinner ganglion cell layer (GCL) (
= 0.003) and thicker retinal nerve fiber layer (RNFL) compared to controls (
= 0.048), and this RNFL thickening was greater in COVID-19 cases with cotton wool spots (CWS), when compared with patients without CWS (
= 0.032). In both SCP and DCP, COVID-19 patients presented lower VD in the foveal region (
< 0.001) and a greater FAZ area than controls (
= 0.007). These findings suggest that thrombotic and inflammatory phenomena could be happening in the retina of COVID-19 patients. Further research is warranted to analyze the longitudinal evolution of these changes over time as well as their correlation with disease severity.
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).
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.
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: (X(2)=12.9, p=0.113) for SAPS II and (X(2)=4.07, p=0.851) for SAPS 3.
Although both scores overpredicted mortality, SAPS II showed better discrimination for patients admitted to ImCU in terms of SMR.
Intermediate care units (ImCUs) have been shown as appropriate units for the management of selected septic patients. Developing specific protocols for residents in training may be useful for their ...medical performance. The objective of this study was to analyze whether a simulation-based learning bundle is useful for residents while acquiring competencies in the management of sepsis during their internship in an ImCU.A prospective study, set in a tertiary-care academic medical center was performed enrolling residents who performed their internship in an ImCU from 2014 to 2017. The pillars of the simulation-based learning bundle were sepsis scenario in the simulation center, instructional material, and sepsis lecture, and management of septic patients admitted in the ImCU. Each resident was evaluated in the beginning and at the end of their internship displaying a sepsis-case scenario in the simulation center. The authors developed a sepsis-checklist that residents must fulfill during their performance which included 5 areas: hemodynamics (0-10), oxygenation (0-5), antibiotic therapy (0-9), organic injury (0-5), and miscellaneous (0-4).Thirty-four residents from different years of residency and specialties were evaluated. The total median score (interquartile range) increased significantly after training: 12 (25) vs 23 (16), P = .001. First-year residents scored significantly lower than older residents at baseline: 10 (14) vs 14.5 (19), P = .024. However, the performance at the end of the training period was similar in both groups: 21.5 (11) vs 23 (16), P = 1.000. Internal Medicine residents scored significantly higher than residents from other specialties: 18 (17) vs 10.5 (21), P = .007. Nonetheless, the performance at the end of the training period was similar in both groups: 24.5 (9) vs 22 (13), P = 1.000.Combining medical simulation with didactic lectures and a rotation in an ImCU staffed by hospitalists seems to be useful in acquiring competencies to manage critically ill patients with sepsis. We designed a checklist to assure an objective evaluation of the performance of the residents and to identify those aspects that could be potentially improved.
Abstract
Background
One of the most important challenges in medical education is the preparation of multiple-choice questions able to discriminate between students with different academic level. ...Average questions may be very easy for students with good performance, reducing their discriminant power in this group of students. The aim of this study was to analyze if the discriminative power of multiple-choice questions is different according to the students’ academic performance.
Methods
We retrospectively analyzed the difficulty and discrimination indices of 257 multiple-choice questions used for the end of course examination of pathophysiology and analyzed whether the discrimination indices were lower in students with good academic performance (group 1) than in students with moderate/poor academic performance (group 2). We also evaluated whether case-based questions maintained their discriminant power better than factual questions in both groups of students or not. Comparison of the difficulty and discrimination indices between both groups was based on the Wilcoxon test.
Results
Difficulty index was significantly higher in group 1 (median: 0.78 versus 0.56;
P
< 0.001) and discrimination index was significantly higher in group 2 (median: 0.21 versus 0.28;
P
< 0.001). Factual questions had higher discriminative indices in group 2 than in group 1 (median: 0.28 versus 0.20;
P
< 0.001), but discriminative indices of case-based questions did not differ significantly between groups (median: 0.30 versus 0.24;
P
= 0.296).
Conclusions
Multiple-choice question exams have lower discriminative power in the group of students with high scores. The use of clinical vignettes may allow to maintain the discriminative power of multiple-choice questions.
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