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Ventricular Function

Ventricular Function: The pumping ability and performance of the ventricles of the heart.
It includes the (ventricular) muscle contractions that circulate blood through the lungs and throughout the body.
Accurate assessment of ventricular function is crucial for diagnosing and managing cardiovascular conditions.

Most cited protocols related to «Ventricular Function»

Investigating Air Pollution's Cardiac Impacts

For this report, we used the data collected for the Air Pollution and Cardiac Risk and its Time Course (APACR) study, which we designed to investigate the mechanisms and the time course of the adverse effects of PM_2.5 on cardiac electrophysiology, blood coagulation, and systemic inflammation. The APACR study has maintained approval by Penn State University College of Medicine institutional review board. All participants gave written informed consent prior to their participation in the study. All study participants were recruited from communities in central Pennsylvania, mostly from the Harrisburg metropolitan area. The inclusion criteria for the study included nonsmoking adults > 45 years old who had not been diagnosed with severe cardiac problems (defined as diagnosed valvular heart disease, congenital heart disease, acute myocardial infarction or stroke within 6 months, or congestive heart failure). Community recruitment specialists from the General Clinical Research Center (GCRC), which is funded by the National Institutes of Health, at the Penn State College of Medicine, and the GCRC-organized community outreach activities, supported the recruitment of the participants. The GCRC maintains a list of individuals who live in central Pennsylvania communities for various health-related studies. The APACR study participants were numerated from the GCRC’s list of potential participants; approximately 75% of the individuals who were contacted and who met our inclusion criteria were enrolled in the study. Our targeted sample size was 100 individuals, and we enrolled and examined 106 individuals. The examination of two participants per week was conducted from November 2007 to June 2009 for the entire examination period except for major holidays.
Study participants were examined in the GCRC in the morning between 0800 and 1000 hours. All participants fasted for at least 8 hr before the clinical examination. After completing a health history questionnaire, a trained research nurse measured seated blood pressure (BP) three times, height, and weight, and drew 50 mL blood for biomarker assays according to the blood sample preparation protocols. A trained investigator connected the PM_2.5 and Holter ECG recorders. Participants were given an hourly activity log to record special events that occurred in the next 24 hr, including outdoor activities, exposure to traffic on the street, travel in an automobile, and any physical activities. The entire examination session lasted for about 1 hr. Participants were then released to proceed with their usual daily routines. The next morning, they returned to the GCRC to remove the PM and Holter monitors, to deliver the completed activity log, and to have their seated BP measured three times and another 50 mL of blood drawn. An exercise echocardiogram was then performed to measure the ventricular function and structure for each participant. The entire second day session lasted for about 1 hr and 45 min. A description of the participants’ characteristics are presented in Table 1.
The study protocol was approved by Penn State University College of Medicine institutional review board. Each participant received $50 and two certificates for breakfast in the hospital cafeteria, and they were reimbursed for their transportation costs.

Liao D., Shaffer M.L., Rodriguez-Colon S., He F., Li X., Wolbrette D.L., Yanosky J, & Cascio W.E. (2010). Acute Adverse Effects of Fine Particulate Air Pollution on Ventricular Repolarization. Environmental Health Perspectives, 118(7), 1010-1015.

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Publication 2010

Adult Air Pollution Biological Assay Biological Markers BLOOD Blood Pressure Cardiac Electrophysiology Cerebrovascular Accident Coagulation, Blood Congenital Heart Defects Congestive Heart Failure Echocardiography Ethics Committees, Research Heart Holter Electrocardiography Inflammation Myocardial Infarction Nurses Physical Examination Specialists Valve Disease, Heart Ventricular Function

Framingham Offspring Study: sST2 Biomarker

The study design of the Framingham Offspring Study has been described (20 (link)(. Participants who attended Examination 6 and had sST2 concentrations checked from banked serum were eligible for the current investigation (1996–1998; n = 3450).
We excluded the following participants in hierarchical fashion: prevalent LV dysfunction (n = 302), prevalent heart failure (n = 39), missing sST2 concentration (n = 4), missing high-sensitivity troponin (n = 35), and no blood sample available (offsite examination; n = 43). The general sample contained 3109 individuals.
A healthy reference sample was also selected, from which participants with the following characteristics were excluded: missing biomarker information (n = 4), high-sensitivity troponin concentration extreme outlier (n = 1), age <35 or ≥75 years (because of too few individuals in these age groups to determine a reliable reference limit; n = 23), renal dysfunction [defined by estimated glomerular filtration rate (GFR) < 60 mL/min/1.73m² (21 (link)); n = 85], pulmonary dysfunction [forced expiratory volume in 1 s (FEV₁) < lower limit of normal for the population as calculated by Hankinson et al. (22 (link)); n = 114], LV dysfunction (echocardiographically determined by fractional shortening <0.30, ventricular function coded as borderline or mild to severe dysfunction; n = 86), valve disease (systolic murmur graded 3/6 or worse or any diastolic murmur; n = 19), obesity [body mass index (BMI) ≥30 kg/m²; n = 367], hypertension (systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or use of an antihypertensive medication; n = 1019), diabetes [fasting blood glucose >125 mg/dL (>6.94 mmol/L); n = 312], atrial fibrillation (n = 61), heart failure (n = 13), or coronary heart disease (myocardial infarction, angina pectoris, or coronary insufficiency; n = 292). After applying these exclusions, the resulting reference sample included 1136 individuals. Of note, we excluded individuals with renal disease (on the basis of GFR) to maintain the similarity between our reference population and reference populations used in other biomarker studies. There was no significant correlation between log(ST2) and log(GFR) in our analysis (data not shown). This is consistent with the work from Dieplinger et al. (19 (link)), who did not find any difference in sST2 concentrations between healthy controls and individuals with renal disease.
Given previous links to asthma, a secondary analysis was performed on the entire Examination 6 population to investigate the relationship between sST2 concentrations, asthma, and measures of pulmonary function by pulmonary function testing. For this analysis, participants were excluded for prevalent heart failure (n = 56), coronary heart disease (n = 159), or chronic kidney disease stage IV (n = 27). Additionally, participants with missing covariates including BMI, height, weight, pack-years smoked, smoking status, and diabetes (n = 421) and missing pulmonary function testing (n = 518) were excluded. After applying these exclusions, the sample for the secondary analysis included 2374 individuals.
All participants in the Framingham Heart Study provided written informed consent, and the study protocol was approved by the Institutional Review Board of the Boston University Medical Center.

Coglianese E.E., Larson M.G., Vasan R.S., Ho J.E., Ghorbani A., McCabe E.L., Cheng S., Fradley M.G., Kretschman D., Gao W., O’Connor G., Wang T.J, & Januzzi J.J. (2012). Distribution and Clinical Correlates of the Interleukin Receptor Family Member Soluble ST2 in the Framingham Heart Study. Clinical chemistry, 58(12), 1673-1681.

Publication 2012

Age Groups Angina Pectoris Antihypertensive Agents Asthma Atrial Fibrillation BAD protein, human Biological Markers BLOOD Blood Glucose Chronic Kidney Diseases Congestive Heart Failure Diabetes Mellitus Ethics Committees, Research Glomerular Filtration Rate Heart Heart Disease, Coronary High Blood Pressures Hypersensitivity Index, Body Mass Kidney Diseases Kidney Failure Lung Myocardial Infarction Obesity Pressure, Diastolic Serum Systolic Pressure Troponin Ventricular Dysfunction, Left Ventricular Function Volumes, Forced Expiratory

Quantifying Myocardial Blood Flow with Rubidium

A two-compartment model was used for ⁸²Rb to allow for accurate estimation of myocardial extraction fraction because the latter is only partially extracted by the myocardium (16 ). The two compartments of the model are the “free rubidium space” (blood perfusing the myocardium plus interstitial space) and the “trapped rubidium space” (muscle of the myocardium). The main parameters of the model are the kinetic transport constants K₁ (mL/min/g) and k₂ (min^-1), which denote the extraction (forward) and egress (backward) rates of transport between the metabolically trapped space (myocardium) and the freely diffusible space (blood pool), respectively. In order to estimate myocardial blood flow (MBF) from measures of K₁, we used the extraction fraction (E) reported previously by Yoshida et al. (17 (link)) in open-chest dogs as:
Equation 1 was solved for MBF using the fixed point iteration approach (18 ). Since the equation is not solvable for high values of MBF, we used the following linear extrapolation for K₁ > 0.92 ml/g/min:
The tissue time activity curve in each voxel, C_T(t), was modeled as a combination of 3 contributions: the contribution from myocardial tissue, modeled using a two-compartment model, and contributions from left and right ventricular cavities, modeled as fractions of measured left (LV) and right (RV) ventricle functions:
where C_{T_i} (t) is the value of the polar map sector i (1 ≤ i ≤ 17) at time t, C_{T_i} is the time activity curve of sector i, C_a (t) is the measured left ventricle input function, and C_r (t) is the measured right ventricle input function, k₂ⁱ, f_yⁱ, and r_vⁱ are the kinetic parameters for sector i, where K₁ⁱ [mL/min/g] characterizes myocardial tissue extraction (inflow), k₂ⁱ [min^-1] characterizes myocardial tissue egress (outflow), f_vⁱ [dimensionless] represents the contribution to the total activity from the blood input function C_a (t), and r_vⁱ [dimensionless] represents the contribution from the activity in the right ventricle, C_r (t), which in general differs from the input function C_a (t). Both C_a (t) and C_r (t) were determined by GFADS.

, & Fakhri G.E. (2009). Reproducibility and Accuracy of Quantitative Myocardial Blood Flow Using 82Rb-PET: Comparison with 13N-Ammonia. Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 50(7), 1062-1071.

Publication 2009

BLOOD Blood Circulation Blood Physiological Phenomena Canis familiaris Chest Dental Caries Kinetics Left Ventricular Function Muscle Tissue Myocardium Rubidium Tissues Ventricles, Right Ventricular Function Ventricular Function, Right

Extracting Echocardiography Metrics from EMR

Echocardiography reports in the VUMC EMR are in the portable document format (PDF) and have undergone three formatting iterations since 1997. Reports prior to 1997 are not in digital format and not included in the EMRs. Each report contains structured, semi-structured, and unstructured data. Structured data are generally quantitative measures such as wall thicknesses, chamber dimensions, or flow velocities. Semi-structured data fields contain subjective interpretations of parameters with a limited number of potential values. These fields frequently contain ordinal data. For example, valvular lesions and abnormalities of ventricular function are often subjectively quantified as “mild”, “moderate”, or “severe”. Unstructured fields contain unrestricted prose descriptions of clinically relevant findings as interpreted by the reader.
Fields containing structured, semi-structured, and unstructured data were identified within echocardiography reports in the EMRs. Numeric values for left ventricular septal thickness, left ventricular posterior wall thicknesses, left ventricular end systolic diameter, left ventricular end diastolic diameter, left atrial diameter, and aortic root diameter were subsequently parsed from reports using natural language processing.

Wells Q.S., Farber-Eger E, & Crawford D.C. (2014). Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function. Journal of Clinical Bioinformatics, 4, 12.

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Publication 2014

Aortic Root Atrium, Left Congenital Abnormality Diastole Echocardiography Left Ventricles Systole Ventricular Function

Multiparametric Cardiac MRI Protocol

Imaging was performed on a 1.5T Siemens Avanto (Siemens Healthcare Sector, Erlangen, Germany) with an 8 channel cardiac coil. The CMR protocol consisted of 3 components: 1) ventricular function, 2) post-contrast T1 mapping, and 3) LGE. Ventricular function was assessed using breath-hold, retrospective electrocardiogram-gated, TrueFISP cine imaging sequences in 10–16 contiguous short axis images using conventional techniques.[15 (link)] Intravenous Gd-DTPA contrast (gadopentate dimeglumine, Magnevist®, Bayer Healthcare Pharmaceuticals, Wayne, NJ, USA) at a dose of 0.2mmol/kg was administered through a peripheral IV. The Look-Locker was obtained in the short axis plane at the level of the papillary muscles 10 minutes after contrast administration with imaging parameters of: field of view 275–400mm × 340–400mm, matrix 66–96 × 192, slice thickness 8mm, flip angle 30 degrees, no parallel imaging. Standard Look-Locker imaging included 17–35 images acquired every other R-R interval with phase intervals of approximately 30ms. The images were ECG-gated and were acquired using segmented k-space during breath-holds. Late gadolinium enhancement was obtained in a stack of short axis slices using: 1) single shot inversion recovery TrueFISP with an optimized inversion time to null normal myocardium and 2) phase sensitive inversion recovery TrueFISP with an inversion time of 300ms.

Soslow J.H., Damon B.M., Saville B.R., Lu Z., Burnette W.B., Lawson M.A., Parra D.A., Sawyer D.B, & Markham L.W. (2014). Evaluation of Post-Contrast Myocardial T1 in Duchenne Muscular Dystrophy Using Cardiac Magnetic Resonance Imaging. Pediatric cardiology, 36(1), 49-56.

Publication 2014

Aftercare Epistropheus Gadolinium Gadolinium DTPA Heart Inversion, Chromosome Magnevist Myocardium Papillary Muscles Pharmaceutical Preparations Ventricular Function

Most recents protocols related to «Ventricular Function»

Adjudication of Cardiovascular Outcomes in WHI

The ascertainment and adjudication of primary and secondary outcomes for WHI have been described in detail previously (21 (link)). In brief, OS study participants were contacted by mail annually to collect self-reported outcomes, as well as updated exposure data (15 (link)). The adjudication of outcomes for all OS participants continued through August 2009, allowing for an average duration of follow-up for OS participants of 12 years (17 (link)). The initial adjudication of outcomes was performed by a physician adjudicator at a local clinical center and consisted of a physician review of hospital discharge summaries, relevant diagnostic tests, and death certificates. Primary and safety outcomes were subsequently confirmed by central adjudication; a review of primary cardiovascular outcomes was performed by the WHI Cardiovascular Central Adjudication Committee (21 (link)).
Outcomes for the current analysis were adjudicated total CVD (fatal and non-fatal) and three major types of CVD: CHD, heart failure, and stroke, occurring within 5 years of baseline. These comprised primary (CHD) or secondary (CVD, heart failure, and stroke) cardiovascular outcomes in the WHI CT and were also ascertained among OS participants; (21 (link)) methods for ascertainment of these outcomes were therefore well documented and consistent across local clinical centers.
Cardiovascular outcomes were defined as in the WHI OS. Non-fatal CVD outcomes were defined as CHD, stroke, heart failure, peripheral vascular disease, angina, coronary artery bypass graft (CABG), coronary revascularization, and pulmonary embolism (21 (link)). Fatal CVD outcomes were defined as death due to cerebrovascular, definite CHD, possible CHD, pulmonary embolism, other cardiovascular, or unknown cardiovascular causes.
The outcome of CHD in WHI OS participants was defined as hospitalized myocardial infarction (MI) (definite or probable) or coronary death (21 (link)). Definite and probable MI events were identified by an algorithm comprising medical history data, electrocardiogram readings, and cardiac enzyme/troponin levels, as available (22 (link)). Silent MI events were not ascertained in OS participants; therefore, silent MI was not considered as an outcome in this analysis. Fatal coronary outcomes comprised out-of-hospital as well as hospitalized deaths: coronary death was identified based on a physician review of medical records and death certificate data and was defined as death consistent with an underlying cause of death of CHD (21 (link)).
Outcome of heart failure was defined as signs and symptoms of heart failure together with one of the following: pulmonary edema on X-ray; ventricular dilation/poor ventricular function; or physician diagnosis and treatment for heart failure. Stroke was defined as rupture or obstruction of the brain arterial system, resulting in rapid neurological deficit persisting for 24 h or more. Stroke outcome comprised stroke, hemorrhagic stroke, or cause of death reported as stroke. Heart failure and stroke not resulting in hospitalization were not considered as WHI outcomes (21 (link)).

Wright C.E., Enquobahrie D.A., Prager S., Painter I., Kooperberg C., Wild R.A., Park K., Sealy-Jefferson S, & Kernic M.A. (2023). Pregnancy loss and risk of incident CVD within 5 years: Findings from the Women's Health Initiative. Frontiers in Cardiovascular Medicine, 10, 1108286.

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Publication 2023

Angina Pectoris Arterial Occlusion Brain Cardiac Death Cardiovascular System Cerebrovascular Accident Congestive Heart Failure Coronary Artery Bypass Surgery Diagnosis Dilatation Electrocardiography Fatal Outcome Heart Hemorrhagic Stroke Hospitalization Myocardial Infarction Patient Discharge Peripheral Vascular Diseases Physicians Pulmonary Edema Pulmonary Embolism Radiography Safety Test, Clinical Enzyme Tests, Diagnostic Troponin Ventricular Function

Heart Model Elastance and Timing Parameters

The heart model includes elastance and timing parameters. Noting that compliance is the inverse of elastance and that the compliance in the heart is minimal during end-systole (computed at the maximum pressure and minimal volume) [17 (link)], we calculate the maximum and minimum elastances (mmHg ml⁻¹) as

E_{M, i} = \frac{p_{M, i}}{V_{m, i} - V_{u n, i}} and E_{m, i} = \frac{p_{m, i}}{V_{M, i} - V_{u n, i}},

where i = la, ra, lv, rv.
Nominal timing parameters for the right atrial and ventricular elastance functions are extracted from the time-series data. Maximum and minimum right ventricular elastance occur at peak systole and the beginning of diastole, corresponding to T_c,v and T_v,r, respectively. Right atrium data are used to determine the end of atrial systole, the start of atrial contraction and peak atrial contraction, i.e. T_r,a, τ_c,a and T_c,a. Since dynamic data are unavailable for the left atrium and ventricle, we set left-heart chamber timing parameters equal to the right-heart timing parameters.

Colunga A.L., Colebank M.J, & Olufsen M.S. (2023). Parameter inference in a computational model of haemodynamics in pulmonary hypertension. Journal of the Royal Society Interface, 20(200), 20220735.

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Publication 2023

Atrium, Left Atrium, Right Cerebral Ventricles Diastole Heart Heart Atrium Pressure Systole Ventricles, Right Ventricular Function

Cardiovascular Function Prediction Protocol

Clinically, PH diagnosis requires invasive measurements of pulmonary blood pressure by RHC. These measurements are typically combined with systolic and diastolic systemic arterial pressure and cardiac output measurements. These measurements describe arterial dynamics but lack detailed information related to ventricular function. Our model predicts pressure, flow and volume in each compartment, augmenting information obtained from measurements. By combining these predictions, we can gain additional insight into the state of the cardiovascular system. Specifically, we compute:

(i)

Stroke work refers to the integral of the pressure–volume loop∫Vp(t) dV′,for each heart chamber. This is a clinical measure of ventricular function [9 (link),23 (link),24 (link)]. We convert stroke work to Joules (J) using the conversion that 1 J = 7.5 × 10³ mmHg ml.

(ii)

Resistance ratio: the pulmonary and systemic resistance ratio is defined as R_p/R_s (non-dimensional) [23 (link)].

(iii)

Compliance ratio of pulmonary and systemic arterial compliance, C_pa/C_sa (non-dimensional).

(iv)

Pulsatility index (PI) refers to to the ratio of pulmonary arterial pulse pressure to average right atrial pressure, (pM,pa−pm,pa)/p¯ra [25 (link)].

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Publication 2023

Arteries Cardiac Output Cardiovascular System Cerebrovascular Accident Determination, Blood Pressure Diagnosis Heart Lung Pressure Pressure, Diastolic Pulmonary Artery Pulse Pressure RA 25 Systole Ventricular Function

Intraoperative Cardiac Hemodynamics in Cardiac Surgery

We performed a prospective, observational, single-centre study in a closed format, 20-bed mixed ICU in a tertiary teaching hospital in the Netherlands. By protocol in our hospital, all valve surgery patients and coronary artery bypass grafting (CABG) patients with a poor left ventricular (LV) function are monitored perioperative with a continuous cardiac output pulmonary artery catheter (PAC; 7.5F CCO catheter, model 774F75; Edwards Lifesciences, Edwards, Irvine, CA, USA). This PAC is interfaced with a computerised monitoring system (Vigilance; Edwards Lifesciences; Irvine, California). The PAC enables near-continuous data on cardiac index (CI), mixed venous oxygen saturation (SvO₂), RV end-diastolic volume and RV ejection fraction (RVEF).
Over a 2-year period (2015–2016), we included all cardiac surgery patients ≥18 years of age with available preoperative and postoperative invasive haemodynamic measurements. There were no exclusion criteria. Two dedicated cardiothoracic anaesthesiologists recorded baseline PAC-derived RVEF after induction but before sternotomy, in addition to the routinely recorded RVEF in the postoperative ICU phase.

Bethlehem C., Bootsma I.T., De Lange F, & Boerma E.C. (2023). Identifying risk factors for perioperative decline in right ventricular performance in cardiac surgery patients: a prospective observational study in a tertiary care hospital. BMJ Open, 13(2), e068598.

Publication 2023

Anesthesiologist Cardiac Output Catheters Diastole Heart Hemodynamics Operative Surgical Procedures Oxygen Saturation Patients Pulmonary Artery Sternotomy Surgical Procedure, Cardiac Veins Ventricular Function Wakefulness

Chagas Disease Serum Characterization

The study was approved by the Human Research Ethics Committee of UFMG, with protocol numbers: CAAE–32343114.9.0000.5149/CAAE-48354315.8.0000.5149. CD-positive serum samples (n = 58) were classified according to the clinical form of the disease as described by Rocha et al. (2003) [34 (link)]: indeterminate form (IND, n = 30) for asymptomatic individuals who have sinus rhythm, without significant changes in the electrocardiogram, chest radiograph, and echocardiogram; and cardiac form 5 (CARD, n = 28) for individuals with echocardiographic signs of dilated left ventricle with systolic function impaired ventricular function, with or without manifestations of heart failure. Healthy individuals (n = 30) from a nonendemic area for the CD with negative characterization tests and individuals infected with leishmaniasis, visceral (n = 30), and cutaneous (n = 30), for cross-reactivity assessment, were included as the control group (NI). All sera were collected and characterized using two or more tests (indirect immune fluorescence, ELISA, or indirect hemagglutination).

Machado J.M., Pereira I.A., Maia A.C., Francisco M.F., Nogueira L.M., Gandra I.B., Ribeiro A.J., Silva K.A., Resende C.A., da Silva J.O., dos Santos M., Gonçalves A.A., Tavares G.D., Chávez-Fumagalli M.A., Campos-da-Paz M., Giunchetti R.C., Rocha M.O., Chaves A.T., Coelho E.A, & Galdino A.S. (2023). Proof of Concept of a Novel Multiepitope Recombinant Protein for the Serodiagnosis of Patients with Chagas Disease. Pathogens, 12(2), 312.

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Publication 2023

Cross Reactions Echocardiography Electrocardiography Enzyme-Linked Immunosorbent Assay Ethics Committees, Research Fluorescence Heart Heart Failure Homo sapiens Left Ventricles Leishmaniasis Radiography, Thoracic Serum Sinuses, Nasal Skin Systole Test, Hemagglutination Ventricular Function

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Echopac software by GE Healthcare

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More about "Ventricular Function"

Ventricular function is a crucial aspect of cardiovascular health, describing the pumping ability and performance of the heart's ventricles.
This physiological process involves the contractions of the ventricular muscles, which circulate blood through the lungs and throughout the body.
Accurate assessment of ventricular function is vital for diagnosing and managing various cardiovascular conditions.
The evaluation of ventricular function can be performed using a variety of medical imaging techniques, such as echocardiography, cardiac MRI, and cardiac CT.
Echocardiography, using systems like the Vevo 2100, Tim Trio, Sonos 5500, and GE Vivid 7, provides real-time, non-invasive assessment of ventricular function, including parameters like ejection fraction, stroke volume, and cardiac output.
The EchoPAC software is often used in conjunction with these systems to analyze and interpret the echocardiographic data.
For cardiac MRI, the Magnetom Avanto system and Dotarem contrast agent can be used to visualize and quantify ventricular function, offering high-resolution images and detailed information about ventricular contractility and blood flow.
Similarly, cardiac CT with the Brilliance iCT system can provide comprehensive evaluation of ventricular anatomy and function.
In addition to these imaging modalities, various other tools and techniques are available for assessing ventricular function, such as the Capto SP844 MLT844 pressure transducer for invasive hemodynamic measurements.
Researchers and clinicians can leverage the power of AI-driven platforms like PubCompare.ai to streamline their research process, identify the most effective solutions, and enhance the reproducibility and accuracy of their work in the field of ventricular function optimization.