Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis

Background & Aims: In individuals with compensated advanced chronic liver disease (cACLD), the severity of portal hypertension (PH) determines the risk of decompensation. Invasive measurement of the hepatic venous pressure gradient (HVPG) is the diagnostic gold standard for PH. We evaluated the utility of machine learning models (MLMs) based on standard laboratory parameters to predict the severity of PH in individuals with cACLD. Methods: A detailed laboratory workup of individuals with cACLD recruited from the Vienna cohort (NCT03267615) was utilised to predict clinically significant portal hypertension (CSPH, i.e., HVPG ≥10 mmHg) and severe PH (i.e., HVPG ≥16 mmHg). The MLMs were then evaluated in individual external datasets and optimised in the merged cohort. Results: Among 1,232 participants with cACLD, the prevalence of CSPH/severe PH was similar in the Vienna (n = 163, 67.4%/35.0%) and validation (n = 1,069, 70.3%/34.7%) cohorts. The MLMs were based on 3 (3P: platelet count, bilirubin, international normalised ratio) or 5 (5P: +cholinesterase, +gamma-glutamyl transferase, +activated partial thromboplastin time replacing international normalised ratio) laboratory parameters. The MLMs performed robustly in the Vienna cohort. 5P-MLM had the best AUCs for CSPH (0.813) and severe PH (0.887) and compared favourably to liver stiffness measurement (AUC: 0.808). Their performance in external validation datasets was heterogeneous (AUCs: 0.589-0.887). Training on the merged cohort optimised model performance for CSPH (AUCs for 3P and 5P: 0.775 and 0.789, respectively) and severe PH (0.737 and 0.828, respectively). Conclusions: Internally trained MLMs reliably predicted PH severity in the Vienna cACLD cohort but exhibited heterogeneous results on external validation. The proposed 3P/5P online tool can reliably identify individuals with CSPH or severe PH, who are thus at risk of hepatic decompensation. Impact and implications: We used machine learning models based on widely available laboratory parameters to develop a non-invasive model to predict the severity of portal hypertension in individuals with compensated cirrhosis, who currently require invasive measurement of hepatic venous pressure gradient. We validated our findings in a large multicentre cohort of individuals with advanced chronic liver disease (cACLD) of any cause. Finally, we provide a readily available online calculator, based on 3 (platelet count, bilirubin, international normalised ratio) or 5 (platelet count, bilirubin, activated partial thromboplastin time, gamma-glutamyltransferase, choline-esterase) widely available laboratory parameters, that clinicians can use to predict the likelihood of their patients with cACLD having clinically significant or severe portal hypertension

Typical displacement behaviours of slope movements

Understanding and quantifying the evolution of landslides are research topics that have always engaged researchers. Indeed, scientific literature provides a large number of contributions introducing and/or applying procedures, which are based on mechanical or phenomenological methods. The first ones are usually implemented to analyse the mechanical behaviour of a single complex phenomenon for which a consistent dataset is available. Phenomenological models are aimed at identifying common characteristics of landslides to be used for different purposes, such as forecasting the time of failure. This paper presents the implementation of a phenomenological model that allows the identification and quantification of well-defined dimensionless displacement trends for a large number of phenomena that are well documented in the literature. The analysed landslides involve different materials and are characterized by different stages of activity induced by seasonal and/or occasional triggering factors. The case studies include the well-known Vajont landslide, for which the obtained results show that the displacement trend was different from those usually characterizing occasionally reactivated landslides, since the beginning of the paroxysmal phase

INVESTIGATING THE EVOLUTION OF LANDSLIDES VIA DIMENSIONLESS DISPLACEMENT TRENDS

Understanding and quantifying the time evolution of landslides has always engaged researchers because of the consequences of such phenomena on the stability of buildings and infrastructure, and the loss of life. Consider, e.g., the catastrophic Vajont landslide in northern Italy in 1963 which caused great damage and the death of 1,917 people. The scientific literature reports both mechanical and phenomenological approaches to analyzing landslide evolution. This paper aims to fill the gap between such approaches by introducing a geometric stability analysis of experimentally measured displacements trends. The proposed analysis organizes the experimental data of a given event into a dimensionless chart. The overall set of displacement data is partitioned into a sequence of activity stages associated with different triggering factors. This preliminary, but fundamental step, allows recognition of the common growth properties of different landslide displacements, independently of the volume of the main moving body, the material composition, and so on. The second step consists of a powerlaw regularization of the experimental data that allows the computing of time derivatives of the dimensionless cumulative displacements up to the third order (velocity, acceleration and second acceleration, or jerk). The approximating functions are used to understand and quantify the behavior of an experimentally monitored landslide event, by tracking its activity stages into a stability chart that accounts for five different regimes. The robustness of the proposed procedure is demonstrated through application to many well-documented case studies

Evidence-based criteria for the choice and the clinical use of the most appropriate lock solutions for central venous catheters (excluding dialysis catheters): a GAVeCeLT consensus

BACKGROUND:The most appropriate lock solution for central venous access devices is still to be defined. GAVeCeLT - the Italian group for venous access devices - has developed a consensus on the evidence-based criteria for the choice and the clinical use of the most appropriate lock solution for central venous catheters (excluding dialysis catheters). METHOD:After the constitution of a panel of experts, a systematic collection and review of the literature has been performed, focusing on clinical studies dealing with lock solutions used for prevention of occlusion (heparin, citrate, urokinase, recombinant tissue plasminogen activator [r-TPA], normal saline) or for prevention of infection (citrate, ethanol, taurolidine, ethylene-diamine-tetra-acetic acid [EDTA], vancomycin, linezolid and other antibiotics), in both adults and in pediatric patients. Studies on central lines used for dialysis or pheresis, on peripheral venous lines and on arterial lines were excluded from this analysis. Studies on lock solutions used for treatment of obstruction or infection were not considered. The consensus has been carried out according to the Delphi method. RESULTS:The panel has concluded that: (a) there is no evidence supporting the heparin lock; (b) the prevention of occlusion is based on the proper flushing and locking technique with normal saline; (c) the most appropriate lock solution for infection prevention should include citrate and/or taurolidine, which have both anti-bacterial and anti-biofilm activity, with negligible undesired effects if compared to antibiotics; (d) the patient populations most likely to benefit from citrate/taurolidine lock are yet to be defined. CONCLUSIONS:The actual value of heparinization for non-dialysis catheters should be reconsidered. Also, the use of lock with substances with anti-bacterial and anti-biofilm activity (such as citrate or taurolidine) should be taken into consideration in selected populations of patients