Journal of clinical medicine
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Post-exertional malaise (PEM) is regarded as the hallmark symptom in chronic fatigue syndrome (CFS). The aim of the current study is to explore differences in CFS patients with and without PEM in indicators of aortic stiffness, autonomic nervous system function, and severity of fatigue. One-hundred and one patients met the Fukuda criteria. ⋯ For a one unit increase in sympathovagal balance, the risk of PEM increases by 330%. Higher mental fatigue and sympathetic activity in rest are related to an increased risk of PEM, while higher central systolic blood pressure is related to a reduced risk of PEM. However, none of the between group differences were significant after FDR correction, and therefore conclusions should be treated with caution and replicated in further studies.
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Trimethylamine N-oxide (TMAO), a novel cardiovascular (CV) disease and mortality risk marker, is a gut microbiota-derived metabolite as well. Recently, plasma concentrations of branched-chain amino acids (BCAA) have been reported to be affected by microbiota. The association of plasma TMAO with CV mortality in Type 2 Diabetes (T2D) and its determinants are still incompletely described. ⋯ The same was true for analyses with TMAO as continuous variable: adjHR 1.32 (95% CI 1.07; 1.63), p = 0.01 (per 1 SD increase). In contrast, BCAAs were not associated with increased CV mortality. In conclusion, higher plasma TMAO but not BCAA concentrations are associated with an increased risk of CV mortality in individuals with T2D, independent of clinical and biochemical risk markers.
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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing the coronavirus disease 2019 (COVID-19) led to an ongoing pandemic with a surge of critically ill patients. Very little is known about the occurrence and characteristic of cardiac arrest in critically ill patients with COVID-19 treated at the intensive care unit (ICU). The aim was to investigate the incidence and outcome of intensive care unit cardiac arrest (ICU-CA) in critically ill patients with COVID-19. ⋯ Multivariable logistic regression showed that the presence of ARDS (odds ratio (OR) 4.268, 95% confidence interval (CI) 1.211-15.036; p = 0.024) and high SAPS II (OR 1.031, 95% CI 0.997-1.065; p = 0.077) were independently associated with the occurrence of ICU-CA. A total of 18% of critically ill patients with COVID-19 suffered from a cardiac arrest within the intensive care unit. The occurrence of ICU-CA was associated with presence of ARDS and severity of illness.
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Previous scoring models, such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) score, do not adequately predict the mortality of patients receiving mechanical ventilation in the intensive care unit. Therefore, this study aimed to apply machine learning algorithms to improve the prediction accuracy for 30-day mortality of mechanically ventilated patients. The data of 16,940 mechanically ventilated patients were divided into the training-validation (83%, n = 13,988) and test (17%, n = 2952) sets. ⋯ The AUCs of these machine learning models as achieved by APACHE II and ProVent scores were higher than 0.67 (0.65-0.69), and 0.69 (0.67-0.71)), respectively. The most important variables in developing each machine learning model were APACHE II score, Charlson comorbidity index, and norepinephrine. The machine learning models have a higher AUC than conventional scoring systems, and can thus better predict the 30-day mortality of mechanically ventilated patients.