PREDICT identifies precipitating events associated with the clinical course of acutely decompensated cirrhosis

Background & Aims: Acute decompensation (AD) of cirrhosis may present without acute-on-chronic liver failure (ACLF) (ADNo ACLF), or with ACLF (AD-ACLF), defined by organ failure(s). Herein, we aimed to analyze and characterize the precipitants leading to both of these AD phenotypes. Methods: The multicenter, prospective, observational PREDICT study (NCT03056612) included 1,273 non-electively hospitalized patients with AD (No ACLF = 1,071; ACLF = 202). Medical history, clinical data and laboratory data were collected at enrolment and during 90-day follow-up, with particular attention given to the following characteristics of precipitants: induction of organ dysfunction or failure, systemic inflammation, chronology, intensity, and relationship to outcome. Results: Among various clinical events, 4 distinct events were precipitants consistently related to AD: proven bacterial infections, severe alcoholic hepatitis, gastrointestinal bleeding with shock and toxic encephalopathy. Among patients with precipitants in the AD-No ACLF cohort and the AD-ACLF cohort (38% and 71%, respectively), almost all (96% and 97%, respectively) showed proven bacterial infection and severe alcoholic hepatitis, either alone or in combination with other events. Survival was similar in patients with proven bacterial infections or severe alcoholic hepatitis in both AD phenotypes. The number of precipitants was associated with significantly increased 90day mortality and was paralleled by increasing levels of surrogates for systemic inflammation. Importantly, adequate first-line antibiotic treatment of proven bacterial infections was associated with a lower ACLF development rate and lower 90-day mortality. Conclusions: This study identified precipitants that are significantly associated with a distinct clinical course and prognosis in patients with AD. Specific preventive and therapeutic strategies targeting these events may improve outcomes in patients with decompensated cirrhosis. Lay summary: Acute decompensation (AD) of cirrhosis is characterized by a rapid deterioration in patient health. Herein, we aimed to analyze the precipitating events that cause AD in patients with cirrhosis. Proven bacterial infections and severe alcoholic hepatitis, either alone or in combination, accounted for almost all (96-97%) cases of AD and acute-on-chronic liver failure. Whilst the type of precipitant was not associated with mortality, the number of precipitant(s) was. This study identified precipitants that are significantly associated with a distinct clinical course and prognosis of patients with AD. Specific preventive and therapeutic strategies targeting these events may improve patient outcomes. (c) 2020 European Association for the Study of the Liver. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Intubation difficile en chirurgie thyroïdienne (mythe ou réalité ? )

Le rôle de la chirurgie thyroïdienne comme facteur de risque d'intubation difficile (ID) est actuellement controversé. Nous avons inclus 324 patients afin d'évaluer l'incidence de l'ID avec un score d'ID et recherché des facteurs de risques prédictifs d'ID. L'incidence globale de l'ID pour cette cohorte de patient était de 11,1%. Trois groupes ont été prédéfinis : groupe sans augmentation échographique du volume de la thyroïde, groupe avec goitre palpable et groupe avec goitre non palpable. L'incidence de l'ID était respectivement de 9,9%, 12,5% et 10,7% sans différence significative. Les critères prédictifs spécifiques recherchés (palpation, goitre endothoracique, déformation des voies aériennes, signes de compression ou thyroïde maligne) n'étaient pas associés à une ID. Les critères prédictifs classiques (Limitation d'ouverture de bouche, Mallampati 3 ou 4, cou court, mobilité du cou réduite, petite distance thyromentonnière et rétrognatisme) étaient associés avec une ID.TOULOUSE3-BU Santé-Centrale (315552105) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Application of LC-MS-based metabolomics method in differentiating septic survivors from non-survivors

Septic shock is the most severe form of sepsis, which is still one of the leading causes of death in the intensive care unit (ICU). Even though early prognosis and diagnosis are known to be indispensable for reaching an optimistic outcome, pathogenic complexities and the lack of specific treatment make it difficult to predict the outcome individually. In the present study, serum samples from surviving and non-surviving septic shock patients were drawn before clinical intervention at admission. Metabolic profiles of all the samples were analyzed by liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. One thousand four hundred nineteen peaks in positive mode and 1878 peaks in negative mode were retained with their relative standard deviation (RSD) below 30 %, in which 187 metabolites were initially identified by retention time and database in the light of the exact molecular mass. Differences between samples from the survivors and the non-survivors were investigated using multivariate and univariate analysis. Finally, 43 significantly varied metabolites were found in the comparison between survivors and non-survivors. Concretely, metabolites in the tricarboxylic acid (TCA) cycle, amino acids, and several energy metabolism-related metabolites were up-regulated in the non-survivors, whereas those in the urea cycle and fatty acids were generally down-regulated. Metabolites such as lysine, alanine, and methionine did not present significant changes in the comparison. Six metabolites were further defined as primary discriminators differentiating the survivors from the non-survivors at the early stage of septic shock. Our findings reveal that LC-MS-based metabolomics is a useful tool for studying septic shock

Case Report Difficult Airway Management Algorithm in Emergency Medicine: Do Not Struggle against the Patient, Just Skip to Next Step

We report a case of prehospital "cannot intubate" and "cannot ventilate" scenarios successfully managed by strictly following a difficult airway management algorithm. Five airway devices were used: the Macintosh laryngoscope, the gum elastic Eschmann bougie, the LMA Fastrach, the Melker cricothyrotomy cannula, and the flexible fiberscope. Although several airway devices were used, overall airway management duration was relatively short, at 20 min, because for each scenario, failed primary and secondary backup devices were quickly abandoned after 2 failed attempts, each attempt of no more than 2 min in duration, in favor of the tertiary rescue device. Equally, all three of these rescue devices failed, an uncuffed cricothyroidotomy cannula was inserted to restore optimal arterial oxygenation until a definitive airway was secured in the ICU using a flexible fiberscope. Our case reinforces the need to strictly follow a difficult airway management algorithm that employs a limited number of effective devices and techniques, and highlights the imperative for early activation of successive preplanned steps of the algorithm

Nuclear magnetic resonance based metabolomics and liver diseases Recent advances and future clinical applications

International audienceMetabolomics is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. It is an "omics" technique that is situated downstream of genomics, transcriptomics and proteomics. Metabolomics is recognized as a promising technique in the field of systems biology for the evaluation of global metabolic changes. During the last decade, metabolomics approaches have become widely used in the study of liver diseases for the detection of early biomarkers and altered metabolic pathways. It is a powerful technique to improve our pathophysiological knowledge of various liver diseases. It can be a useful tool to help clinicians in the diagnostic process especially to distinguish malignant and non-malignant liver disease as well as to determine the etiology or severity of the liver disease. It can also assess therapeutic response or predict drug induced liver injury. Nevertheless, the usefulness of metabolomics is often not understood by clinicians, especially the concept of metabolomics profiling or fingerprinting. In the present work, after a concise description of the different techniques and processes used in metabolomics, we will review the main research on this subject by focusing specifically on in vitro proton nuclear magnetic resonance spectroscopy based metabolomics approaches in human studies. We will first consider the clinical point of view enlighten physicians on this new approach and emphasis its future use in clinical "routine"

PLS/OPLS models in metabolomics: the impact of permutation of dataset rows on the K-fold cross-validation quality parameters

Among all the software packages available for discriminant analyses based on projection to latent structures (PLS-DA) or orthogonal projection to latent structures (OPLS-DA), SIMCA (Umetrics, Umea Sweden) is the more widely used in the metabolomics field. SIMCA proposes many parameters or tests to assess the quality of the computed model (the number of significant components, R-2, Q(2), PCV-ANOVA, and the permutation test). Significance thresholds for these parameters are strongly application-dependent. Concerning the Q(2) parameter, a significance threshold of 0.5 is generally admitted. However, during the last few years, many PLS-DA/OPLS-DA models built using SIMCA have been published with Q(2) values lower than 0.5. The purpose of this opinion note is to point out that, in some circumstances frequently encountered in metabolomics, the values of these parameters strongly depend on the individuals that constitute the validation subsets. As a result of the way in which the software selects members of the calibration and validation subsets, a simple permutation of dataset rows can, in several cases, lead to contradictory conclusions about the significance of the models when a K-fold cross-validation is used. We believe that, when Q(2) values lower than 0.5 are obtained, SIMCA users should at least verify that the quality parameters are stable towards permutation of the rows in their dataset

Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate