The Elevated High-Sensitivity Cardiac Troponin T Pilot: Diagnoses and Outcomes

Potential Biomarker of Acute Anthracycline-induced Cardiotoxicity Among Children With Acute Lymphoblastic Leukemia: Cardiac Adriamycin-responsive Protein

ABSTRACT

This study aimed to investigate whether serum cardiac adriamycin-responsive protein (CARP) can serve as a sensitive and specific biomarker of anthracyclines (ANT)-induced cardiotoxicity. Fifty-five children with acute lymphoblastic leukemia were recruited. Before and after the administration of ANT, serum levels of CARP, high-sensitivity troponin T, creatine kinase-MB, and electrocardiogram were measured. Postchemotherapeutic clinical manifestations of cardiotoxicity were also investigated. Adverse cardiac events (ACEs) were graded according to the Common Terminology Criteria for Adverse Events 4.0. Then, the CARP expression was statistically analyzed among different groups. The receiver operating characteristic curve was used to evaluate the efficacy of CARP in predicting acute ANT-induced cardiotoxicity. After ANT chemotherapy, the serum CARP concentration increased in the non-ACEs group but decreased in the ACEs group ( P < 0.05). In addition, not only the serum CARP levels (△CARP) was negatively correlated with the grade of ACEs (R=-0.754, P < 0.0001) but also the extent of QT interval corrected (QTc) prolongation (△QTc; R=-0.5592, P < 0.01). The area under the receiver operating characteristic curve of CARP was 90.94% ( P < 0.0001), and the sensitivity and specificity were 88.64% and 91.67%, respectively, all of which are superior to △high-sensitivity troponin T, △creatine kinase-MB, and △QTc. In conclusion, serum CARP could serve as a novel sensitive and specific biomarker of acute ANT-induced cardiotoxicity, which is negatively associated with ACE grade.

Higher troponin T serum concentrations in hospital patients without diagnosed cardiac diseases compared to a population-based cohort

OBJECTIVES

Upper reference limits of high-sensitivity cardiac troponin T (hs-cTnT) are derived from healthy, population-based cohorts, and are frequently exceeded in hospitalized patients. In this study we aim to systematically examine the differences between in-hospital patients with no diagnosed cardiac diseases and a population-based cohort.

METHODS

Retrospective analyses were performed in two independent cohorts. We included 5,652 participants of the prospective population-based LIFE cohort as well as 9,300 patients having been treated at our hospital between 2014 and 2021. In both cohorts, subjects with diagnosed or suspected cardiac diseases were excluded. We used Spearman's rank correlation for correlation analyses of hs-cTnT serum concentrations and age. Sex- and age-adjusted 99th percentiles for hs-cTnT in subjects with preserved renal function were obtained in both cohorts.

RESULTS

In both cohorts, hs-cTnT serum concentrations positively correlated with age. Male sex was associated with higher hs-cTnT serum concentrations. Persons treated in hospital showed significantly higher hs-cTnT concentrations in females and males aged above 50. While in the population-based cohort only 99th percentile hs-cTnT results of females aged above 70 and males aged above 60 years exceeded the assay's upper reference limit, the 99th percentiles of in-hospital females over 40 years and males of all age groups exceeded this threshold.

CONCLUSIONS

Besides age and sex, hospitalization per se is correlated with higher serum concentrations of hs-cTnT in most age groups. Our results indicate, that unconditionally applying current hs-cTnT cut-offs to inpatients might overestimate myocardial infarction and potentially lead to overdiagnosis.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways

Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10 -14 ), Alzheimer's disease (FDR ≤ 5.46×10 -10 ) and coronary artery disease (FDR ≤ 4.64×10 -2 ). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Changes of Electrocardiogram and Myocardial Enzymes in Patients with Intracerebral Hemorrhage

Purpose

Cardiac complications are common in patients with spontaneous intracerebral hemorrhage (ICH). The present study is aimed at observing the incidence of cardiac complications after ICH, so as at improving the understanding of the relationship between cardiac complications and ICH.

Methods

This is a retrospective study on analyzing electrocardiogram (ECG) and serum myocardial enzyme of 208 patients with ICH admitted to a tertiary hospital from 2018 to 2019. For each patient, demographics, medical history, clinical presentation, ECG, serum myocardial enzyme, and head CT on admission were reviewed. Mortality was noted.

Results

Among the 208 patients, 145 (69.71%) had one or more ECG abnormalities. The top three abnormalities were corrected QT interval (QTc) prolongation 52 (25%), ST depression 48 (23.08%), and T wave inversion 38 (18.27%). One hundred and thirty-nine patients (66.83%) had increased serum levels of at least one kind of myocardial enzyme, which were high-sensitive cardiac troponin T (hs-cTnT) 79 (37.98%), lactic dehydrogenase (LDH) 80 (38.46%), creatine kinase (CK) 57 (27.40%), and creatine kinase-myocardial subfraction (CKMB) 57 (27.40%). The logistic regression analysis showed the following: secondary intraventricular hemorrhage (SIVH) (odds ratio (OR) 5.32; 95% confidence interval (CI) 2.55–11.08; p < 0.001) and hematoma volume > 30 ml (OR 3.81; 95% CI 1.86–7.81; p < 0.001) were independent predictive factors of QTc prolongation; thalamus location (OR 5.79; 95% CI 1.94–17.28; p < 0.05), hematoma volume > 30 ml (OR 24.187; 95% CI 3.14-186.33; p < 0.05), insular involvement (OR 19.08; 95% CI 5.77-63.07; p < 0.001), and SIVH (OR 2.62; 95% CI 1.69-5.86; p < 0.05) were independent predictive factors of ST depression; insular involvement (OR 2.90; 95% CI 1.12–7.50; p < 0.05) and hematoma volume > 30 ml (OR 1.98; 95% CI 1.06–3.70; p < 0.05) were independent predictive factors of increase of CK; Glasgow Coma Scale (GCS) (OR 0.86; 95% CI 0.78–0.98; p < 0.05) and insular involvement (OR 5.56; 95% CI 1.98–15.62; p < 0.05) were independent predictive factors of increase of CKMB; SIVH (OR 2.05; 95% CI 1.07–3.92; p < 0.05) was independent predictive factor of increase of LDH; age (OR 1.03; 95% CI 1.01–1.06; p < 0.05), blood glucose on admission (OR 1.10; 95% CI 1.01–1.20; p < 0.05), and history of antiplatelet drug use (OR 3.50; 95% CI 1.01–12.12; p < 0.05) were independent predictive factors of hs-cTnT. All the injury indexes were not related to in-hospital mortality.

Conclusion

The study suggests that insular involvement, hematoma volume > 30 ml, and SIVH are the strongest risk factors for ECG abnormalities and elevated myocardial enzymes after ICH followed which are the risk factors such as GCS, age, admission blood glucose, and ICH location in the thalamus.