Circulating Cardiac Troponin T Exhibits a Diurnal Rhythm

ObjectivesThe goal of this study was to test the unverified assumption that chronically elevated cardiac troponin T (cTnT) levels fluctuate randomly around a homeostatic set point.BackgroundThe introduction of high-sensitivity cardiac troponin (cTn) assays has improved sensitivity for acute myocardial infarction (AMI). However, many patients with a single positive cTn test result do not have AMI. Therefore, the diagnosis of AMI relies strongly on serial testing and interpretation of cTn kinetics. Essential in this regard is a profound understanding of the biological variation of cTn.MethodsTwo studies were conducted to assess biological cTnT variation and to investigate the presence of a diurnal rhythm of cTnT. Study 1 comprised 23 male subjects with type 2 diabetes, with no acute cardiovascular disease. Serial venous blood samples were drawn over an 11-h period (8:30 am to 7:30 pm). In study 2, the presence of a diurnal cTnT rhythm was investigated by hourly sampling of 7 subjects from study 1 over 25 h.ResultsIn study 1, we observed a gradual decrease in cTnT concentrations during the day (24 ± 2%). This decrease was present in all participants and was most prominent in subjects with the highest baseline cTnT values (Pearson’s R 0.93). Diurnal variation of cTnT, as assessed in study 2, was characterized by peak concentrations during morning hours (8:30 am, 17.1 ± 2.9 ng/l), gradually decreasing values during daytime (8:30 pm, 11.9 ± 1.6 ng/l), and rising concentrations during nighttime (8:30 am the next day, 16.9 ± 2.8 ng/l).ConclusionsA diurnal cTnT rhythm substantiates the recommendation that all dynamic changes in cTnT should be interpreted in relation to the clinical presentation. Epidemiological studies and risk-stratification protocols with the use of cTnT may benefit from standardized sampling times. (Exercise and Glycemic Control in Type 2 Diabetes; NCT00945165

Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department

Abstract Background Many prediction models have been developed to help identify emergency department (ED) patients at high risk of poor outcome. However, these models often underperform in clinical practice and their actual clinical impact has hardly ever been evaluated. We aim to perform a clinical trial to investigate the clinical impact of a prediction model based on machine learning (ML) technology. Methods The study is a prospective, randomized, open-label, non-inferiority pilot clinical trial. We will investigate the clinical impact of a prediction model based on ML technology, the RISKINDEX, which has been developed to predict the risk of 31-day mortality based on the results of laboratory tests and demographic characteristics. In previous studies, the RISKINDEX was shown to outperform internal medicine specialists and to have high discriminatory performance. Adults patients (18 years or older) will be recruited in the ED. All participants will be randomly assigned to the control group or the intervention group in a 1:1 ratio. Participants in the control group will receive care as usual in which the study team asks the attending physicians questions about their clinical intuition. Participants in the intervention group will also receive care as usual, but in addition to asking the clinical impression questions, the study team presents the RISKINDEX to the attending physician in order to assess the extent to which clinical treatment is influenced by the results. Discussion This pilot clinical trial investigates the clinical impact and implementation of an ML based prediction model in the ED. By assessing the clinical impact and prognostic accuracy of the RISKINDEX, this study aims to contribute valuable insights to optimize patient care and inform future research in the field of ML based clinical prediction models. Trial registration ClinicalTrials.gov NCT05497830. Machine Learning for Risk Stratification in the Emergency Department (MARS-ED). Registered on August 11, 2022. URL: https://clinicaltrials.gov/study/NCT05497830

Additional file 1 of Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department

Supplementary Material

Effect of Antioxidant Supplementation on Exercise-Induced Cardiac Troponin Release in Cyclists: A Randomized Trial

<div><p>Background</p><p>Cardiac troponin is the biochemical gold standard to diagnose acute myocardial infarction. Interestingly however, elevated cardiac troponin concentrations are also frequently observed during and after endurance-type exercise. Oxidative stress associated with prolonged exercise has been proposed to contribute to cardiac troponin release. Therefore, the aim of this study was to assess the effect of 4 week astaxanthin supplementation (a potent cartenoid antioxidant) on antioxidant capacity and exercise-induced cardiac troponin release in cyclists.</p><p>Methods</p><p>Thirty-two well-trained male cyclists (age 25±5, weight 73±7 kg, maximum O₂ uptake 60±5 mL·kg⁻¹·min⁻¹, W_max 5.4±0.5 W·kg⁻¹; mean ± SD) were repeatedly subjected to a laboratory based standardized exercise protocol before and after 4 weeks of astaxanthin (20 mg/day), or placebo supplementation in a double-blind randomized manner. Blood samples were obtained at baseline, at 60 min of cycling and immediately post-exercise (≈ 120 min).</p><p>Results</p><p>The pre-supplementation cycling trial induced a significant rise of median cardiac troponin T concentrations from 3.2 (IQR 3.0–4.2) to 4.7 ng/L (IQR 3.7–6.7), immediately post-exercise (p<0.001). Four weeks of astaxanthin supplementation significantly increased mean basal plasma astaxanthin concentrations from non-detectable values to 175±86 µg·kg⁻¹. However, daily astaxanthin supplementation had no effect on exercise-induced cardiac troponin T release (p = 0.24), as measured by the incremental area under the curve. Furthermore, the elevation in basal plasma astaxanthin concentrations was not reflected in changes in antioxidant capacity markers (trolox equivalent antioxidant capacity, uric acid, and malondialdehyde). Markers of inflammation (high-sensitivity C-reactive protein) and exercise-induced skeletal muscle damage (creatine kinase) were equally unaffected by astaxanthin supplementation.</p><p>Conclusion</p><p>Despite substantial increases in plasma astaxanthin concentrations, astaxanthin supplementation did not improve antioxidant capacity in well-trained cyclists. Accordingly, exercise-induced cardiac troponin T concentrations were not affected by astaxanthin supplementation.</p><p>Trial registration</p><p>ClinicalTrials.gov <a href="http://clinicaltrials.gov/ct2/show/NCT01241877?term=NCT01241877&rank=1" target="_blank">NCT01241877</a></p></div

Huh-7 or HepG2 cells: which is the better model for studying human apolipoprotein-B100 assembly and secretion?[S]

Apolipoprotein-B100 (apoB100) is the essential protein for the assembly and secretion of very low density lipoproteins (VLDL) from liver. The hepatoma HepG2 cell line has been the cell line of choice for the study of synthesis and secretion of human apoB-100. Despite the general use of HepG2 cells to study apoB100 metabolism, they secrete relatively dense, lipid-poor particles compared with VLDL secreted in vivo. Recently, Huh-7 cells were adopted as an alternative model to HepG2 cells, with the implicit assumption that Huh-7 cells were superior in some respects of lipoprotein metabolism, including VLDL secretion. In this study we addressed the hypothesis that the spectrum of apoB100 lipoprotein particles secreted by Huh-7 cells more closely resembles the native state in human liver. We find that Huh-7 cells resemble HepG2 cells in the effects of exogenous lipids, microsomal triglyceride transfer protein (MTP)-inhibition, and proteasome inhibitors of apoB100 secretion, recovery, and degradation. In contrast to HepG2 cells, however, MEK-ERK inhibition does not correct the defect in VLDL secretion. Huh-7 cells do not appear to offer any advantages over HepG2 cells as a general model of human apoB100-lipoprotein metabolism

Participants characteristics.

<p>Data are presented as mean ± SD.</p

Flow chart of the trial.

<p>Flow chart of the trial.</p

cTnT, CK and hsCRP concentrations during the pre- and post-supplementation exercise trials.

<p>A, D, G. Whole group cTnT, CK and hsCRP concentrations during the pre-supplementation exercise trials. B, E, H. cTnT, CK and hsCRP concentrations in the placebo group measured during the pre- and post-supplementation cycling trials. C, F, I. cTnT, CK and hsCRP concentrations in the astaxanthin group during the pre- and post-supplementation trials. ***denotes a significant increase from baseline (P<0.001). Values are median and interquartile range.</p