Anàlisi de l’expressió inflamatòria i la supervivència dels pacients cirròtics

Treballs Finals de Grau en Estadística UB-UPC, Facultat d'Economia i Empresa (UB) i Facultat de Matemàtiques i Estadística (UPC), Curs: 2017-2018, Tutors: Àlex Amorós; Guadalupe Gómez; Àlex Sànchez(cat) La cirrosi hepàtica es pot presentar de forma compensada o descompensada, caracteritzant-se aquesta última per l’aparició d’alguna complicació com ascites, encefalopatia hepàtica, hemorràgia gastrointestinal i/o infecció bacteriana. En cirrosi descompensada, és freqüent el desenvolupament de la síndrome Acute-on-Chronic Liver Failure (ACLF), definida per la presència d’insuficiències i disfuncions orgàniques i una elevada taxa de mortalitat a curt termini. Recentment, s’ha trobat que el desenvolupament del mecanisme d’inflamació sistèmica té un rol rellevant en els pacients que pateixen ACLF. L’objectiu de la present investigació, és estudiar el patró d’expressió inflamatòria dels pacients cirròtics en funció de la presència de possibles complicacions orgàniques, així com la mortalitat, considerant la mort com a esdeveniment principal i el trasplantament de fetge com a esdeveniment competitiu.(eng) Liver cirrhosis is a degenerative disease caused by the deterioration of healthy liver tissue and may be either compensated or decompensated, characterized the latter by the development of large ascites, hepatic encephalopathy, gastrointestinal hemorrhage, bacterial infection, or any combination of them. In the context of decompensated cirrhosis, the development of the syndrome known as Acute-on-Chronic Liver Failure (ACLF) is common. The syndrome is defined by the presence of organ dysfunctions and organ failures and high short-term mortality. Patients with decompensated cirrhosis without ACLF may have a single liver failure, while ACLF is defined by the occurrence of a single renal failure, single non-renal failure (liver, coagulation, circulation, respiration) associated with organ dysfunction (renal/cerebral) or patients with more than one failure. Recently, it has been found that the development of the systemic inflammation mechanism has a relevant role in ACLF patients. The first aim of the present investigation is to study the inflammatory expression pattern in a sample of 582 healthy, compensated, decompensated and ACLF patients, depending on the presence of possible organ complications. Commonly, cirrhotic patients need to receive a liver transplant which modifies their probability of dying. Because of this, the second objective of this project is to assess their mortality considering death as a primary event and liver transplant as a competitive event and quantify the risk of death of decompensated and ACLF patients according to the development of organ dysfunctions and organ failures. The results show a clear association between worsening hepatic cirrhosis, along with the manifestation of organic complications, and accentuation of inflammation. Moreover, there is evidence that ACLF patients have a higher risk of dying than the decompensated individuals without ACLF, being the probability of dying from the two groups of 37% and 16%, respectively. In addition, there is no certainty that the development of organ dysfunction or organ failure in decompensated cirrhotic patients leads to an increase in the risk of death

AI-based glioma grading for a trustworthy diagnosis: an analytical pipeline for improved reliability

Glioma is the most common type of tumor in humans originating in the brain. According to the World Health Organization, gliomas can be graded on a four-stage scale, ranging from the most benign to the most malignant. The grading of these tumors from image information is a far from trivial task for radiologists and one in which they could be assisted by machine-learning-based decision support. However, the machine learning analytical pipeline is also fraught with perils stemming from different sources, such as inadvertent data leakage, adequacy of 2D image sampling, or classifier assessment biases. In this paper, we analyze a glioma database sourced from multiple datasets using a simple classifier, aiming to obtain a reliable tumor grading and, on the way, we provide a few guidelines to ensure such reliability. Our results reveal that by focusing on the tumor region of interest and using data augmentation techniques we significantly enhanced the accuracy and confidence in tumor classifications. Evaluation on an independent test set resulted in an AUC-ROC of 0.932 in the discrimination of low-grade gliomas from high-grade gliomas, and an AUC-ROC of 0.893 in the classification of grades 2, 3, and 4. The study also highlights the importance of providing, beyond generic classification performance, measures of how reliable and trustworthy the model’s output is, thus assessing the model’s certainty and robustness.Carla Pitarch is a fellow of Eurecat’s “Vicente López” PhD grant program.Peer ReviewedPostprint (published version

HDL-related biomarkers are robust predictors of survival in patients with chronic liver failure

Background & Aims: High-density lipoprotein cholesterol (HDL-C) levels are reduced in patients with chronic liver disease and inversely correlate with disease severity. During acute conditions such as sepsis, HDL-C levels decrease rapidly and HDL particles undergo profound changes in their composition and function. We aimed to determine whether indices of HDL quantity and quality associate with progression and survival in patients with advanced liver disease. Methods: HDL-related biomarkers were studied in 508 patients with compensated or decompensated cirrhosis (including acute-on-chronic liver failure [ACLF]) and 40 age- and gender-matched controls. Specifically, we studied levels of HDL-C, its subclasses HDL2-C and HDL3-C, and apolipoprotein A1 (apoA-I), as well as HDL cholesterol efflux capacity as a metric of HDL functionality. Results: Baseline levels of HDL-C and apoA-I were significantly lower in patients with stable cirrhosis compared to controls and were further decreased in patients with acute decompensation (AD) and ACLF. In stable cirrhosis (n = 228), both HDL-C and apoA-I predicted the development of liver-related complications independently of model for end-stage liver disease (MELD) score. In patients with AD, with or without ACLF (n = 280), both HDL-C and apoA-I were MELD-independent predictors of 90-day mortality. On ROC analysis, both HDL-C and apoA-I had high diagnostic accuracy for 90-day mortality in patients with AD (AUROCs of 0.79 and 0.80, respectively, similar to that of MELD 0.81). On Kaplan-Meier analysis, HDL-C <17 mg/dl and apoA-I <50 mg/dl indicated poor short-term survival. The prognostic accuracy of HDL-C was validated in a large external validation cohort of 985 patients with portal hypertension due to advanced chronic liver disease (AUROCs HDL-C: 0.81 vs. MELD: 0.77). Conclusion: HDL-related biomarkers are robust predictors of disease progression and survival in chronic liver failure

Machine learning approaches for the prediction of polygenic obesity using genome-wide genotyping data

In the last decade, Polygenic Risk Scores (PRSs) have been widely used to identify individuals at high risk of being obese. In the present study, we propose to consider a variety of Machine Learning (ML) algorithms to estimate the prediction of obesity. We benchmarked PRS, Random Forest (RF), Gradient Boosting (GB) and Support Vector Machine (SVM) on a database of thousands of patients and millions of Single Nucleotide Polymorphisms (SNPs). To deal with the high-dimensional data we needed to deploy a HDP (Hortonworks Data Platform) cluster composed of multiple machines in order to distribute our data and processes. We used the most popular tools for processing Big Data, Apache Hadoop and Apache Spark, which allow for the parallelization across the cluster

Addressing profiles of systemic inflammation across the different clinical phenotypes of acutely decompensated cirrhosis

Background: Patients with acutely decompensated cirrhosis (AD) may or may not develop acute-on-chronic liver failure (ACLF). ACLF is characterized by high-grade systemic inflammation, organ failures (OF) and high short-term mortality. Although patients with AD cirrhosis exhibit distinct clinical phenotypes at baseline, they have low short-term mortality, unless ACLF develops during follow-up. Because little is known about the association of profile of systemic inflammation with clinical phenotypes of patients with AD cirrhosis, we aimed to investigate a battery of markers of systemic inflammation in these patients. Methods: Upon hospital admission baseline plasma levels of 15 markers (cytokines, chemokines, and oxidized albumin) were measured in 40 healthy controls, 39 compensated cirrhosis, 342 AD cirrhosis, and 161 ACLF. According to EASL-CLIF criteria, AD cirrhosis was divided into three distinct clinical phenotypes (AD-1: Creatinine<1.5, no HE, no OF; AD-2: creatinine 1.5-2, and or HE grade I/II, no OF; AD-3: Creatinine<1.5, no HE, non-renal OF). Results: Most markers were slightly abnormal in compensated cirrhosis, but markedly increased in AD. Patients with ACLF exhibited the largest number of abnormal markers, indicating "full-blown" systemic inflammation (all markers). AD-patients exhibited distinct systemic inflammation profiles across three different clinical phenotypes. In each phenotype, activation of systemic inflammation was only partial (30% of the markers). Mortality related to each clinical AD-phenotype was significantly lower than mortality associated with ACLF (p < 0.0001 by gray test). Among AD-patients baseline systemic inflammation (especially IL-8, IL-6, IL-1ra, HNA2 independently associated) was more intense in those who had poor 28-day outcomes (ACLF, death) than those who did not experience these outcomes. Conclusions: Although AD-patients exhibit distinct profiles of systemic inflammation depending on their clinical phenotypes, all these patients have only partial activation of systemic inflammation. However, those with the most extended baseline systemic inflammation had the highest the risk of ACLF development and death