Machine learning models predict liver steatosis but not liver fibrosis in a prospective cohort study

Introduction Screening for liver fibrosis continues to rely on laboratory panels and non-invasive tests such as FIB-4-score and transient elastography. In this study, we evaluated the potential of machine learning (ML) methods to predict liver steatosis on abdominal ultrasound and liver fibrosis, namely the intermediate-high risk of advanced fibrosis, in individuals participating in a screening program for colorectal cancer. Methods We performed ultrasound on 5834 patients admitted between 2006 and 2020, and transient elastography on a subset of 1240 patients. Steatosis on ultrasound was diagnosed if liver areas showed a significantly increased echogenicity compared to the renal parenchyma. Liver fibrosis was defined as a liver stiffness measurement ≥8 kPa in transient elastography. We evaluated the performance of three algorithms, namely Extreme Gradient Boosting, Feed-Forward neural network and Logistic Regression, deriving the models using data from patients admitted from January 2007 up to January 2016 and prospectively evaluating on the data of patients admitted from January 2016 up to March 2020. We also performed a performance comparison with the standard clinical test based on Fibrosis-4 Index (FIB-4). Results The mean age was 58±9 years with 3036 males (52%). Modelling laboratory parameters, clinical parameters, and data on eight food types/dietary patterns, we achieved high performance in predicting liver steatosis on ultrasound with AUC of 0.87 (95% CI [0.87–0.87]), and moderate performance in predicting liver fibrosis with AUC of 0.75 (95% CI [0.74–0.75]) using XGBoost machine learning algorithm. Patient-reported variables did not significantly improve predictive performance. Gender-specific analyses showed significantly higher performance in males with AUC of 0.74 (95% CI [0.73–0.74]) in comparison to female patients with AUC of 0.66 (95% CI [0.65–0.66]) in prediction of liver fibrosis. This difference was significantly smaller in prediction of steatosis with AUC of 0.85 (95% CI [0.83–0.87]) in female patients, in comparison to male patients with AUC of 0.82 (95% CI [0.80–0.84]). Conclusion ML based on point-prevalence laboratory and clinical information predicts liver steatosis with high accuracy and liver fibrosis with moderate accuracy. The observed gender differences suggest the need to develop gender-specific models

Frailty's influence on 30-day mortality in old critically ill ICU patients: a bayesian analysis evaluating the clinical frailty scale.

INTRODUCTION: Frailty is widely acknowledged as influencing health outcomes among critically ill old patients. Yet, the traditional understanding of its impact has predominantly been through frequentist statistics. We endeavored to explore this association using Bayesian statistics aiming to provide a more nuanced understanding of this multifaceted relationship. METHODS: Our analysis incorporated a cohort of 10,363 older (median age 82 years) patients from three international prospective studies, with 30-day all-cause mortality as the primary outcome. We defined frailty as Clinical Frailty Scale ≥ 5. A hierarchical Bayesian logistic regression model was employed, adjusting for covariables, using a range of priors. An international steering committee of registry members reached a consensus on a minimal clinically important difference (MCID). RESULTS: In our study, the 30-day mortality was 43%, with rates of 38% in non-frail and 51% in frail groups. Post-adjustment, the median odds ratio (OR) for frailty was 1.60 (95% CI 1.45-1.76). Frailty was invariably linked to adverse outcomes (OR > 1) with 100% probability and had a 90% chance of exceeding the minimal clinically important difference (MCID) (OR > 1.5). For the Clinical Frailty Scale (CFS) as a continuous variable, the median OR was 1.19 (1.16-1.22), with over 99% probability of the effect being more significant than 1.5 times the MCID. Frailty remained outside the region of practical equivalence (ROPE) in all analyses, underscoring its clinical importance regardless of how it is measured. CONCLUSIONS: This research demonstrates the significant impact of frailty on short-term mortality in critically ill elderly patients, particularly when the Clinical Frailty Scale (CFS) is used as a continuous measure. This approach, which views frailty as a spectrum, enables more effective, personalized care for this vulnerable group. Significantly, frailty was consistently outside the region of practical equivalence (ROPE) in our analysis, highlighting its clinical importance

Dynamic Changes of Heart Failure Biomarkers in Response to Parabolic Flight

Background: we aimed at investigating the influence of weightlessness and hypergravity by means of parabolic flight on the levels of the heart failure biomarkers H-FABP, sST2, IL-33, GDF-15, suPAR and Fetuin-A. Methods: 14 healthy volunteers (males: eight; mean age: 28.9) undergoing 31 short-term phases of weightlessness and hypergravity were included. At different time points (baseline, 1 h/24 h after parabolic flight), venous blood was drawn and analyzed by the use of ELISA. Results: sST2 evidenced a significant decrease 24 h after parabolic flight (baseline vs. 24, p = 0.009; 1 h vs. 24 h, p = 0.004). A similar finding was observed for GDF-15 (baseline vs. 24 h, p = 0.002; 1 h vs. 24 h, p = 0.025). The suPAR showed a significant decrease 24 h after parabolic flight (baseline vs. 24 h, p = 0.1726; 1 h vs. 24 h, p = 0.009). Fetuin-A showed a significant increase at 1 h and 24 h after parabolic flight (baseline vs. 24 h, p = 0.007; 1 h vs. 24 h, p = 0.04). H-FABP and IL-33 showed no significant differences at all time points. Conclusion: Our results suggest a reduction in cardiac stress induced by exposure to gravitational changes. Moreover, our findings indicate an influence of gravitational changes on proliferative processes and calcium homeostasis

Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation

Optimal performance is critical for decision-making tasks from medicine to autonomous driving, however common performance measures may be too general or too specific. For binary classifiers, diagnostic tests or prognosis at a timepoint, measures such as the area under the receiver operating characteristic curve, or the area under the precision recall curve, are too general because they include unrealistic decision thresholds. On the other hand, measures such as accuracy, sensitivity or the F1 score are measures at a single threshold that reflect an individual single probability or predicted risk, rather than a range of individuals or risk. We propose a method in between, deep ROC analysis, that examines groups of probabilities or predicted risks for more insightful analysis. We translate esoteric measures into familiar terms: AUC and the normalized concordant partial AUC are balanced average accuracy (a new finding); the normalized partial AUC is average sensitivity; and the normalized horizontal partial AUC is average specificity. Along with post-test measures, we provide a method that can improve model selection in some cases and provide interpretation and assurance for patients in each risk group. We demonstrate deep ROC analysis in two case studies and provide a toolkit in Python.Comment: 14 pages, 6 Figures, submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), currently under revie

Treatment of plutonium process residues by molten salt oxidation

Molten Salt Oxidation (MSO) is a thermal process that can remove more than 99.999% of the organic matrix from combustible {sup 238}Pu material. Plutonium processing residues are injected into a molten salt bed with an excess of air. The salt (sodium carbonate) functions as a catalyst for the conversion of the organic material to carbon dioxide and water. Reactive species such as fluorine, chlorine, bromine, iodine, sulfur, phosphorous and arsenic in the organic waste react with the molten salt to form the corresponding neutralized salts, NaF, NaCl, NaBr, NaI, Na{sub 2}SO{sub 4}, Na{sub 3}PO{sub 4} and NaAsO{sub 2} or Na{sub 3}AsO4. Plutonium and other metals react with the molten salt and air to form metal salts or oxides. Saturated salt will be recycled and aqueous chemical separation will be used to recover the {sup 238}Pu. The Los Alamos National Laboratory system, which is currently in the conceptual design stage, will be scaled down from current systems for use inside a glovebox

Hyperlactatemia and altered lactate kinetics are associated with excess mortality in sepsis

Severe hyperlactatemia (>10mmol/L) or impaired lactate metabolism are known to correlate with increased mortality. The maximum lactate concentration on day 1 of 10,724 septic patients from the eICU Collaborative Research Database was analyzed and patients were divided into three groups based on maximum lactate in the first 24 h (<5mmol/l; ≥5mmol/l & <10mmol/l; ≥10mmol/l). In addition, delta lactate was calculated using the following formula: (maximum lactate day 1 minus maximum lactate day 2) divided by maximum lactate day 1. A multilevel regression analysis was performed, with hospital mortality serving as the primary study end point. Significant differences in hospital mortality were found in patients with hyperlactatemia (lactate ≥10mmol/l: 79%, ≥5mmol/l & <10mmol/l: 43%, <5mmol/l, 13%; p<0.001). The sensitivity of severe hyperlactatemia (≥10mmol/l) for hospital mortality was 17%, the specificity was 99%. In patients with negative delta lactate in the first 24 h, hospital mortality was excessive (92%). In conclusion, mortality in patients with severe hyperlactatemia is very high, especially if it persists for more than 24 h. Severe hyperlactatemia, together with clinical parameters, could therefore provide a basis for setting treatment limits

Anti-CD3 antibody treatment reduces scar formation in a rat model of myocardial infarction

Introduction: Antibody treatment with anti-thymocyte globulin (ATG) has been shown to be cardioprotective. We aimed to evaluate which single anti-T-cell epitope antibody alters chemokine expression at a level similar to ATG and identified CD3, which is a T-cell co-receptor mediating T-cell activation. Based on these results, the effects of anti-CD3 antibody treatment on angiogenesis and cardioprotection were tested in vitro and in vivo. Methods: Concentrations of IL-8 and MCP-1 in supernatants of human peripheral blood mononuclear cell (PBMC) cultures following distinct antibody treatments were evaluated by Enzyme-linked Immunosorbent Assay (ELISA). In vivo, anti-CD3 antibodies or vehicle were injected intravenously in rats subjected to acute myocardial infarction (AMI). Chemotaxis and angiogenesis were evaluated using tube and migration assays. Intracellular pathways were assessed using Western blot. Extracellular vesicles (EVs) were quantitatively evaluated using fluorescence-activated cell scanning, exoELISA, and nanoparticle tracking analysis. Also, microRNA profiles were determined by next-generation sequencing. Results: Only PBMC stimulation with anti-CD3 antibody led to IL-8 and MCP-1 changes in secretion, similar to ATG. In a rat model of AMI, systemic treatment with an anti-CD3 antibody markedly reduced infarct scar size (27.8% (Inter-quartile range; IQR 16.2–34.9) vs. 12.6% (IQR 8.3–27.2); p < 0.01). The secretomes of anti-CD3 treated PBMC neither induced cardioprotective pathways in cardiomyocytes nor pro-angiogenic mechanisms in human umbilical vein endothelial cell (HUVECs) in vitro. While EVs quantities remained unchanged, PBMC incubation with an anti-CD3 antibody led to alterations in EVs miRNA expression. Conclusion: Treatment with an anti-CD3 antibody led to decreased scar size in a rat model of AMI. Whereas cardioprotective and pro-angiogenetic pathways were unaltered by anti-CD3 treatment, qualitative changes in the EVs miRNA expression could be observed, which might be causal for the observed cardioprotective phenotype. We provide evidence that EVs are a potential cardioprotective treatment target. Our findings will also provide the basis for a more detailed analysis of putatively relevant miRNA candidates

Failure of lactate clearance predicts the outcome of critically ill septic patients

Purpose: Early lactate clearance is an important parameter for prognosis assessment and therapy control in sepsis. Patients with a lactate clearance >0% might differ from patients with an inferior clearance in terms of intensive care management and outcomes. This study analyzes a large collective with regards to baseline risk distribution and outcomes. Methods: In total, 3299 patients were included in this analysis, consisting of 1528 (46%) ≤0% and 1771 (54%) >0% patients. The primary endpoint was intensive care unit (ICU) mortality. Multilevel logistic regression analyses were used to compare both groups: A baseline model (model 1) with lactate clearance as a fixed effect and ICU as a random effect was installed. For model 2, patient characteristics (model 2) were included. For model 3, intensive care treatment (mechanical ventilation and vasopressors) was added to the model. Models 1 and 2 were used to evaluate the primary and secondary outcomes, respectively. Model 3 was only used to evaluate the primary outcomes. Adjusted odds ratios (aORs) with respective 95% confidence intervals (CI) were calculated. Results: The cohorts had no relevant differences regarding the gender, BMI, age, heart rate, body temperature, and baseline lactate. Neither the primary infection focuses nor the ethnic background differed between both groups. In both groups, the most common infection sites were of pulmonary origin, the urinary tract, and the gastrointestinal tract. Patients with lactate clearance >0% evidenced lower sepsis-related organ failure assessment (SOFA) scores (7 ± 6 versus 9 ± 6; p < 0.001) and creatinine (1.53 ± 1.49 versus 1.80 ± 1.67; p < 0.001). The ICU mortality differed significantly (14% versus 32%), and remained this way after multivariable adjustment for patient characteristics and intensive care treatment (aOR 0.43 95% CI 0.36–0.53; p < 0.001). In the additional sensitivity analysis, the lack of lactate clearance was associated with a worse prognosis in each subgroup. Conclusion: In this large collective of septic patients, the 6 h lactate clearance is an independent method for outcome prediction

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years-a prospective multicentre cohort study.

BACKGROUND Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV. METHODS This is a substudy of COVIP study-an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality. RESULTS Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36-5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06-2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI - 2.27 to - 0.46 days) compared to primary IMV group (n = 1876). CONCLUSIONS Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial Registration NCT04321265 , registered 19 March 2020, https://clinicaltrials.gov

Long-QT syndrome-associated caveolin-3 mutations differentially regulate the hyperpolarization-activated cyclic nucleotide gated channel 4

Background. Caveolin-3 (cav-3) mutations are linked to the long-QT syndrome (LQTS) causing distinct clinical symptoms. Hyperpolarization-activated cyclic nucleotide channel 4 (HCN4) underlies the pacemaker current If. It associates with cav-3 and both form a macromolecular complex. Methods To examine the effects of human LQTS-associated cav-3 mutations on HCN4-channel function, HEK293-cells were cotransfected with HCN4 and wild-type (WT) cav-3 or a LQTS-associated cav-3 mutant (T78M, A85T, S141R, or F97C). HCN4 currents were recorded using the whole-cell patch-clamp technique. Results WT cav-3 significantly decreased HCN4 current density and shifted midpoint of activation into negative direction. HCN4 current properties were differentially modulated by LQTS-associated cav-3 mutations. When compared with WT cav-3, A85T, F97C, and T78M did not alter the specific effect of cav-3, but S141R significantly increased HCN4 current density. Compared with WT cav-3, no significant modifications of voltage dependence of steady-state activation curves were observed. However, while WT cav-3 alone had no significant effect on HCN4 current activation, all LQTS-associated cav-3 mutations significantly accelerated HCN4 activation kinetics. Conclusions Our results indicate that HCN4 channel function is modulated by cav-3. LQTS-associated mutations of cav-3 differentially influence pacemaker current properties indicating a pathophysiological role in clinical manifestations