Dataset Information

Cardiac Index by Transthoracic Echocardiography (CITE) study.

ABSTRACT: AIMS:Left ventricular ejection fraction (LVEF) is the most frequently used parameter in the assessment of heart failure (HF). Cardiac index (CI) is considered a potential alternative to LVEF despite limited evidence. We aimed to assess and compare the predictive accuracy of LVEF and echocardiographically-assessed CI in HF patients. METHODS AND RESULTS:A single-centre, retrospective cohort study was conducted in patients hospitalized for acute HF from 2010-2016. Cox proportional hazard models including either LVEF or CI were created to predict all cause death, cardiovascular (CV) death, or first HF-readmission. Of 334 patients included in the analysis, 58.7% exhibited HF with reduced LVEF (HFrEF). Left ventricular ejection fraction did not show correlation with any endpoint, while CI was predictive of HF-readmission in the entire cohort. Both the LVEF-based and CI-based models demonstrated moderate discriminative accuracy when predicting all-cause death, CV death, or HF-readmission. Left ventricular ejection fraction proved to be an independent predictor of CV mortality in HFrEF-patients, while CI was predictive of HF-readmission in the non-HFrEF group. CONCLUSIONS:Left ventricular ejection fraction seemed to be associated more closely with disease severity in HFrEF, and CI in the non-HFrEF group, in this real-life cohort of elderly HF patients. The LVEF-based and CI-based predictive models have clinically similar predictive accuracy for mortality and HF-readmission, thus CI may be a potential alternative to LVEF in the assessment of left ventricular function. Cardiac index may be an important new tool in the assessment of HF patients with midrange or preserved LVEF.

SUBMITTER: Szabo B

PROVIDER: S-EPMC6291087 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Cardiac Index by Transthoracic Echocardiography (CITE) study.

Szabó Barna B Marosi Eszter Krisztina EK Vargová Katarina K Nyolczas Noémi N

PloS one 20181212 12

<h4>Aims</h4>Left ventricular ejection fraction (LVEF) is the most frequently used parameter in the assessment of heart failure (HF). Cardiac index (CI) is considered a potential alternative to LVEF despite limited evidence. We aimed to assess and compare the predictive accuracy of LVEF and echocardiographically-assessed CI in HF patients.<h4>Methods and results</h4>A single-centre, retrospective cohort study was conducted in patients hospitalized for acute HF from 2010-2016. Cox proportional ha ...[more]

PMID: 30540751

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Project description:BackgroundIn critically ill patients, changes in the velocity-time integral (VTI) of the left ventricular outflow tract, measured by transthoracic echocardiography (TTE), are often used to non-invasively assess the response to fluid administration or for performing tests assessing fluid responsiveness. However, the precision of TTE measurements has not yet been investigated in such patients. First, we aimed at assessing how many measurements should be averaged within one TTE examination to reach a sufficient precision for various variables. Second, we aimed at identifying the least significant change (LSC) of these variables between successive TTE examinations.MethodsWe prospectively included 100 haemodynamically stable patients in whom TTE examination was planned. Three TTE examinations were performed, the first and the third by one operator and the second by another one. We calculated the precision and LSC (1) within one examination depending on the number of averaged measurements and (2) between measurements performed in two successive examinations.ResultsIn patients in sinus rhythm, averaging three measurements within an examination was enough for obtaining an acceptable precision (interquartile range highest value < 10%) for VTI. In patients with atrial fibrillation, averaging five measurements was necessary. The precision of some other common TTE variables depending on the number of measurements is provided. Between two successive examinations performed by the same operator, the LSC was 11 [5-18]% for VTI. If two operators performed the examinations, the LSC for VTI significantly increased to 14 [8-26]%. The LSC between two examinations for other TTE variables is also provided.ConclusionsAveraging three measurements within one TTE examination is enough for obtaining precise measurements for VTI in patients in sinus rhythm but not in patients with atrial fibrillation. Between two TTE examinations performed by the same operator, the LSC of VTI is compatible with the assessment of the effects of a 500-mL fluid infusion but is not precise enough for assessing the effects of some tests predicting preload responsiveness.

Project description:Myocardial amyloidosis (CA) differs from other etiological pathologies of left ventricular hypertrophy in that transthoracic echocardiography is challenging to assess the texture features based on human visual observation. There are few studies on myocardial texture based on echocardiography. Therefore, this paper proposes an adaptive machine learning method based on ultrasonic image texture features to identify CA. In this retrospective study, a total of 289 participants (50 cases of myocardial amyloidosis; Hypertrophic cardiomyopathy: 70 cases; Uremic cardiomyopathy: 92 cases; Hypertensive heart disease: 77 cases). We extracted the myocardial ultrasonic imaging features of these patients and screened the features, and four models of random forest (RF), support vector machine (SVM), logistic regression (LR) and gradient decision-making lifting tree (GBDT) were established to distinguish myocardial amyloidosis from other diseases. Finally, the diagnostic efficiency of the model was evaluated and compared with the traditional ultrasonic diagnostic methods. In the overall population, the four machine learning models we established could effectively distinguish CA from nonCA diseases, AUC (RF 0.77, SVM 0.81, LR 0.81, GBDT 0.71). The LR model had the best diagnostic efficiency with recall, F1-score, sensitivity and specificity of 0.21, 0.34, 0.21 and 1.0, respectively. Slightly better than the traditional ultrasonic diagnosis model. In further subgroup analysis, the myocardial amyloidosis group was compared one-by-one with the patients with hypertrophic cardiomyopathy, uremic cardiomyopathy, and hypertensive heart disease groups, and the same method was used for feature extraction and data modeling. The diagnostic efficiency of the model was further improved. Notably, in identifying of the CA group and HHD group, AUC values reached more than 0.92, accuracy reached more than 0.87, sensitivity equal to or greater than 0.81, specificity 0.91, and F1 score higher than 0.84. This novel method based on echocardiography combined with machine learning may have the potential to be used in the diagnosis of CA.

Project description:BackgroundEchocardiography is the most frequently used non -invasive diagnostic tool to evaluate cardiac anatomy and function in domestic species but increasingly also in non -domestic species, especially since cardiac disease is being recognized as an important cause of death in captive primates. The purpose of this cross -sectional study was to investigate the feasibility of transthoracic echocardiography in healthy squirrel monkeys as well as to provide species specific normal values for standard echocardiographic measurements. A secondary aim was to determine plasma and serum levels of the cardiac biomarkers, N -terminal pro -brain natriuretic peptide (NT -proBNP) and cardiac troponin T (cTnT). Furthermore, a commercial, non -invasive, smartphone -based ECG (AliveCor Vet TM) monitoring device was used to evaluate the heart rate and rhythm and to diagnose possible arrhythmias.ResultsIn this study, transthoracic echocardiography of 14 squirrel monkeys was performed in right and left lateral recumbency. Similar standard right parasternal and left apical images were obtained as in dogs and cats and normal values for routine two -dimensional, time motion mode and Doppler mode measurements were generated. Thirteen animals were considered healthy and one squirrel monkey was identified with significant aortic dilation and regurgitation and consequently values obtained from this animal were not used when species specific normal values were calculated. NT -ProBNP and cTnT concentrations were available for 7 of the 13 healthy monkeys with NT -proBNP concentrations below detection limit in all animals and a mean cTnT concentration of 0.049 ng/mL. Electrocardiography was performed in all squirrel monkeys. The mean heart rate was 172 bpm. Frequent supraventricular premature beats were diagnosed in the squirrel monkey suffering from significant aortic dilation and regurgitation.ConclusionThis study presents echocardiographic normal values and additional cardiovascular data in anaesthetised Saimiri monkeys, fundamental from both the perspective of zoo animal health care as well as scientific research, since the squirrel monkey is often used as an animal model for human disease.

Dataset Information

Cardiac Index by Transthoracic Echocardiography (CITE) study.

Publications

Cardiac Index by Transthoracic Echocardiography (CITE) study.

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