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

Underweight but not overweight is associated with excess mortality in septic ICU patients

Background Higher survival has been shown for overweight septic patients compared with normal or underweight patients in the past. This study aimed at investigating the management and outcome of septic ICU patients in different body mass index (BMI) categories in a large multicenter database. Methods In total, 16,612 patients of the eICU collaborative research database were included. Baseline characteristics and data on organ support were documented. Multilevel logistic regression analysis was performed to fit three sequential regression models for the binary primary outcome (ICU mortality) to evaluate the impact of the BMI categories: underweight (<18.5 kg/m2), normal weight (18.5 to < 25 kg/m2), overweight (25 to < 30 kg/m2) and obesity (≥ 30 kg/m2). Data were adjusted for patient level characteristics (model 2) as well as management strategies (model 3). Results Management strategies were similar across BMI categories. Underweight patients evidenced higher rates of ICU mortality. This finding persisted after adjusting in model 2 (aOR 1.54, 95% CI 1.15–2.06; p = 0.004) and model 3 (aOR 1.57, 95%CI 1.16–2.12; p = 0.003). No differences were found regarding ICU mortality between normal and overweight patients (aOR 0.93, 95%CI 0.81–1.06; p = 0.29). Obese patients evidenced a lower risk of ICU mortality compared to normal weight, a finding which persisted across all models (model 2: aOR 0.83, 95%CI 0.69–0.99; p = 0.04; model 3: aOR 0.82, 95%CI 0.68–0.98; p = 0.03). The protective effect of obesity and the negative effect of underweight were significant in individuals > 65 years only. Conclusion In this cohort, underweight was associated with a worse outcome, whereas obese patients evidenced lower mortality. Our analysis thus supports the thesis of the obesity paradox

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

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

Diabetes mellitus is associated with 90-day mortality in old critically ill COVID-19 patients: a multicenter prospective observational cohort study.

BACKGROUND: Several studies have found an association between diabetes mellitus, disease severity and outcome in COVID-19 patients. Old critically ill patients are particularly at risk. This study aimed to investigate the impact of diabetes mellitus on 90-day mortality in a high-risk cohort of critically ill patients over 70 years of age. METHODS: This multicentre international prospective cohort study was performed in 151 ICUs across 26 countries. We included patients ≥ 70 years of age with a confirmed SARS-CoV-2 infection admitted to the intensive care unit from 19th March 2020 through 15th July 2021. Patients were categorized into two groups according to the presence of diabetes mellitus. Primary outcome was 90-day mortality. Kaplan-Meier overall survival curves until day 90 were analysed and compared using the log-rank test. Mixed-effect Weibull regression models were computed to investigate the influence of diabetes mellitus on 90-day mortality. RESULTS: This study included 3420 patients with a median age of 76 years were included. Among these, 37.3% (n = 1277) had a history of diabetes mellitus. Patients with diabetes showed higher rates of frailty (32% vs. 18%) and several comorbidities including chronic heart failure (20% vs. 11%), hypertension (79% vs. 59%) and chronic kidney disease (25% vs. 11%), but not of pulmonary comorbidities (22% vs. 22%). The 90-day mortality was significantly higher in patients with diabetes than those without diabetes (64% vs. 56%, p < 0.001). The association of diabetes and 90-day mortality remained significant (HR 1.18 [1.06-1.31], p = 0.003) after adjustment for age, sex, SOFA-score and other comorbidities in a Weibull regression analysis. CONCLUSION: Diabetes mellitus was a relevant risk factor for 90-day mortality in old critically ill patients with COVID-19. STUDY REGISTRATION: NCT04321265, registered March 19th, 2020

Outcomes of patients aged ≥80 years with respiratory failure initially treated with non-invasive ventilation in European intensive care units before and during COVID-19 pandemic.

BACKGROUND: Non-invasive ventilation (NIV) has been commonly used to treat acute respiratory failure due to COVID-19. In this study we aimed to compare outcomes of older critically ill patients treated with NIV before and during the COVID-19 pandemic. METHODS: We analysed a merged cohort of older adults admitted to intensive care units (ICUs) due to respiratory failure. Patients were enrolled into one of two prospective observational studies: before COVID-19 (VIP2-2018 to 2019) and admitted due to COVID-19 (COVIP-March 2020 to January 2023). The outcomes included: 30-day mortality, intubation rate and NIV failure (death or intubation within 30 days). RESULTS: The final cohort included 1986 patients (1292 from VIP2, 694 from COVIP) with a median age of 83 years. NIV was used as a primary mode of respiratory support in 697 participants (35.1%). ICU admission due to COVID-19 was associated with an increased 30-day mortality (65.5% vs. 36.5%, HR 2.18, 95% CI 1.71 to 2.77), more frequent intubation (36.9% vs. 17.5%, OR 2.63, 95% CI 1.74 to 3.99) and NIV failure (76.2% vs. 45.3%, OR 4.21, 95% CI 2.84 to 6.34) compared to non-COVID causes of respiratory failure. Sensitivity analysis after exclusion of patients in whom life supporting treatment limitation was introduced during primary NIV confirmed higher 30-day mortality in patients with COVID-19 (52.5% vs. 23.4%, HR 2.64, 95% CI 1.83 to 3.80). CONCLUSION: The outcomes of patients aged ≥80 years treated with NIV during COVID-19 pandemic were worse compared then those treated with NIV in the pre-pandemic era

Provision of critical care for the elderly in Europe: a retrospective comparison of national healthcare frameworks in intensive care units.

OBJECTIVES: In Europe, there is a distinction between two different healthcare organisation systems, the tax-based healthcare system (THS) and the social health insurance system (SHI). Our aim was to investigate whether the characteristics, treatment and mortality of older, critically ill patients in the intensive care unit (ICU) differed between THS and SHI. SETTING: ICUs in 16 European countries. PARTICIPANTS: In total, 7817 critically ill older (≥80 years) patients were included in this study, 4941 in THS and 2876 in the SHI systems. PRIMARY AND SECONDARY OUTCOMES MEASURES: We chose generalised estimation equations with robust standard errors to produce population average adjusted OR (aOR). We adjusted for patient-specific variables, health economic data, including gross domestic product (GDP) and human development index (HDI), and treatment strategies. RESULTS: In SHI systems, there were higher rates of frail patients (Clinical Frailty Scale>4; 46% vs 41%; p<0.001), longer length of ICU stays (90±162 vs 72±134 hours; p<0.001) and increased levels of organ support. The ICU mortality (aOR 1.50, 95% CI 1.09 to 2.06; p=0.01) was consistently higher in the SHI; however, the 30-day mortality (aOR 0.89, 95% CI 0.66 to 1.21; p=0.47) was similar between THS and SHI. In a sensitivity analysis stratifying for the health economic data, the 30-day mortality was higher in SHI, in low GDP per capita (aOR 2.17, 95% CI 1.42 to 3.58) and low HDI (aOR 1.22, 95% CI 1.64 to 2.20) settings. CONCLUSIONS: The 30-day mortality was similar in both systems. Patients in SHI were older, sicker and frailer at baseline, which could be interpreted as a sign for a more liberal admission policy in SHI. We believe that the observed trend towards ICU excess mortality in SHI results mainly from a more liberal admission policy and an increase in treatment limitations. TRIAL REGISTRATION NUMBERS: NCT03134807 and NCT03370692