Hand-held cardiac ultrasound examinations performed in primary care patients by nonexperts to identify reduced ejection fraction

Artificial intelligence-assisted evaluation of cardiac function by oncology staff in chemotherapy patients

Aims

Left ventricular ejection fraction (LVEF) calculation by echocardiography is pivotal in evaluating cancer patients' cardiac function. Artificial intelligence (AI) can facilitate the acquisition of optimal images and automated LVEF (autoEF) calculation. We sought to evaluate the feasibility and accuracy of LVEF calculation by oncology staff using an AI-enabled handheld ultrasound device (HUD).

Methods and results

We studied 115 patients referred for echocardiographic LVEF estimation. All patients were scanned by a cardiologist using standard echocardiography (SE), and biplane Simpson's LVEF was the reference standard. Hands-on training using the Kosmos HUD was provided to the oncology staff before the study. Each patient was scanned by a cardiologist, a senior oncologist, an oncology resident, and a nurse using the TRIO AI and KOSMOS EF deep learning algorithms to obtain autoEF. The correlation between autoEF and SE-ejection fraction (EF) was excellent for the cardiologist (r = 0.90), the junior oncologist (r = 0.82), and the nurse (r = 0.84), and good for the senior oncologist (r = 0.79). The Bland-Altman analysis showed a small underestimation by autoEF compared with SE-EF. Detection of impaired LVEF < 50% was feasible with a sensitivity of 95% and specificity of 94% for the cardiologist; sensitivity of 86% and specificity of 93% for the senior oncologist; sensitivity of 95% and specificity of 91% for the junior oncologist; and sensitivity of 94% and specificity of 87% for the nurse.

Conclusion

Automated LVEF calculation by oncology staff was feasible using AI-enabled HUD in a selected patient population. Detection of LVEF < 50% was possible with good accuracy. These findings show the potential to expedite the clinical workflow of cancer patients and speed up a referral when necessary.

Usefulness of Heart Failure Categories Based on Left Ventricular Ejection Fraction

BACKGROUND

Heart failure guidelines have recently introduced a narrow category with mildly reduced left ventricular ejection fraction (LVEF) (heart failure with mildly reduced ejection fraction; LVEF 41%-49%) between the previous categories of reduced (heart failure with reduced ejection fraction; LVEF ≤40%) and preserved (heart failure with preserved ejection fraction; LVEF ≥50%) ejection fraction. Grouping of continuous measurements into narrow categories can be questioned if their variability is high.

METHODS AND RESULTS

We constructed a cohort of all 9716 new cases of chronic heart failure with an available LVEF in Stockholm, Sweden, from January 1, 2015, until December 31, 2020. All values of LVEF were collected over time, and patients were followed up until death, moving out of Stockholm, or end of study. Mixed models were used to quantify within-person variance in LVEF, and multistate Markov models, with death as an absorbing state, to quantify the stability of LVEF categories. LVEF values followed a normal distribution. The SD of the within-person variance in LVEF over time was 7.4%. The mean time spent in any LVEF category before transition to another category was on average <1 year for heart failure with mildly reduced ejection fraction. Probabilities of transitioning between categories during the first year were substantial; patients with heart failure with mildly reduced ejection fraction had a probability of <25% of remaining in that category 1 year later.

CONCLUSIONS

LVEF follows a normal distribution and has considerable variability over time, which may impose a risk for underuse of efficient treatment. The heart failure with mildly reduced ejection fraction category is especially inconstant. Assumptions of a patient's current LVEF should take this variability and the normal distribution of LVEF into account.

Combination of Tele-Cardiology Tools for Cardiovascular Risk Stratification in Primary Care: Data from the PROVAR+ Study

BACKGROUND

Tele-cardiology tools are valuable strategies to improve risk stratification.

OBJECTIVE

We aimed to evaluate the accuracy of tele-electrocardiography (ECG) to predict abnormalities in screening echocardiography (echo) in primary care (PC).

METHODS

In 17 months, 6 health providers at 16 PC units were trained on simplified handheld echo protocols. Tele-ECGs were recorded for final diagnosis by a cardiologist. Consented patients with major ECG abnormalities by the Minnesota code, and a 1:5 sample of normal individuals underwent clinical questionnaire and screening echo interpreted remotely. Major heart disease was defined as moderate/severe valve disease, ventricular dysfunction/hypertrophy, pericardial effusion, or wall-motion abnormalities. Association between major ECG and echo abnormalities was assessed by logistic regression as follows: 1) unadjusted model; 2) model 1 adjusted for age/sex; 3) model 2 plus risk factors (hypertension/diabetes); 4) model 3 plus history of cardiovascular disease (Chagas/rheumatic heart disease/ischemic heart disease/stroke/heart failure). P-values < 0.05 were considered significant.

RESULTS

A total 1,411 patients underwent echo; 1,149 (81%) had major ECG abnormalities. Median age was 67 (IQR 60 to 74) years, and 51.4% were male. Major ECG abnormalities were associated with a 2.4-fold chance of major heart disease on echo in bivariate analysis (OR = 2.42 [95% CI 1.76 to 3.39]), and remained significant after adjustments in models (p < 0.001) 2 (OR = 2.57 [95% CI 1.84 to 3.65]), model 3 (OR = 2.52 [95% CI 1.80 to3.58]), and model 4 (OR = 2.23 [95%CI 1.59 to 3.19]). Age, male sex, heart failure, and ischemic heart disease were also independent predictors of major heart disease on echo.

CONCLUSIONS

Tele-ECG abnormalities increased the likelihood of major heart disease on screening echo, even after adjustments for demographic and clinical variables.

Artificial Intelligence-Based Left Ventricular Ejection Fraction by Medical Students for Mortality and Readmission Prediction

INTRODUCTION

Point-of-care ultrasound has become a universal practice, employed by physicians across various disciplines, contributing to diagnostic processes and decision-making.

AIM

To assess the association of reduced (<50%) left-ventricular ejection fraction (LVEF) based on prospective point-of-care ultrasound operated by medical students using an artificial intelligence (AI) tool and 1-year primary composite outcome, including mortality and readmission for cardiovascular-related causes.

METHODS

Eight trained medical students used a hand-held ultrasound device (HUD) equipped with an AI-based tool for automatic evaluation of the LVEF of non-selected patients hospitalized in a cardiology department from March 2019 through March 2020.

RESULTS

The study included 82 patients (72 males aged 58.5 ± 16.8 years), of whom 34 (41.5%) were diagnosed with AI-based reduced LVEF. The rates of the composite outcome were higher among patients with reduced systolic function compared to those with preserved LVEF (41.2% vs. 16.7%, p = 0.014). Adjusting for pertinent variables, reduced LVEF independently predicted the composite outcome (HR 2.717, 95% CI 1.083-6.817, p = 0.033). As compared to those with LVEF ≥ 50%, patients with reduced LVEF had a longer length of stay and higher rates of the secondary composite outcome, including in-hospital death, advanced ventilatory support, shock, and acute decompensated heart failure.

CONCLUSION

AI-based assessment of reduced systolic function in the hands of medical students, independently predicted 1-year mortality and cardiovascular-related readmission and was associated with unfavorable in-hospital outcomes. AI utilization by novice users may be an important tool for risk stratification for hospitalized patients.

Clinical comparison of a handheld cardiac ultrasound device for the assessment of left ventricular function

PURPOSE

Recently developed handheld ultrasound devices (HHUD) represent a promising method to evaluate the cardiovascular abnormalities at the point of care. However, this technology has not been rigorously evaluated. The aim of this study was to explore the correlation and the agreement between the LVEF (Left Ventricular Ejection Fraction) visually assessed by a moderately experienced sonographer using an HHUD compared to the routine LVEF assessment performed at the Echocardiography Laboratory.

METHODS

This was a prospective single center study which enrolled 120 adult inpatients and outpatients referred for a comprehensive Echocardiography (EC).

RESULTS

The mean age of the patients was 69.9 ± 12.5 years. There were 47 females (39.2%). The R-squared was r 0.94 (p < 0.0001) and the ICC was 0.93 (IC 95% 0.91-0.95, p ≤ 0.0001). The Bland-Altman plot showed limits of agreement (LOA): Upper LOA 10.61 and Lower LOA - 8.95. The overall agreement on the LVEF assessment when it was stratified as "normal" or "reduced" was 89.1%, with a kappa of 0.77 (p < 0.0001). When the LVEF was classified as "normal", "mildly reduced", "moderately reduced", or "severely reduced," the kappa was 0.77 (p < 0.0001). The kappa between the HHUD EC and the comprehensive EC for the detection of RWMAs in the territories supplied by the LAD, LCX and RCA was 0.85, 0.73 and 0.85, respectively.

CONCLUSION

With current HHUD, an averagely experienced operator can accurately bedside visual estimate the LVEF. This may facilitate the incorporation of this technology in daily clinical practice improving the management of patients.

The measurement of the left ventricle ejection fraction by a bedside FoCUS examination

The use of point-of-care ultrasound is rapidly increasing in medical practice. This study aims to evaluate the left ventricle systolic function by the bedside focus cardiac ultrasound (FoCUS). We consecutively enrolled n.59 patients of the Emergency Medicine Unit of S. Andrea Hospital. Every patient received a bedside FoCUS examination to estimate the left ventricle (LV) ejection fraction (EF); the LV EF measurements were compared with those obtained by standard echocardiography (as gold standard). The LV EF obtained by the bedside FoCUS examination and the standard echocardiography, resulted, respectively: 50.2 ± 15.1% (by the Quinones equation), 39.5 + 12.0% (by the Lvivo app) and 53.7 + 11.1% (by the standard echocardiography). The correlations between the bedside FoCUS EF measurements versus standard echocardiography were statistically significant: r =  + 0.694 p < 1.9 × 10-6 (Quinones equation, Bland-Altman analysis mean = - 2.3%) and r =  + 0.571 p < 0.01 (Lvivo app, Bland-Altman analysis mean = - 13.3%). In conclusion, the present study showed a high accuracy of the bedside FoCUS EF evaluations, which may support the diagnosis of the heart failure in an emergency setting without delaying. The EF measurements by the operational method are more precise than those obtained by the unselected images of the software application.

Reasons for disagreement between screening and standard echocardiography in primary care: data from the PROVAR + study : Disagreement between screening and standard echo

We aimed to evaluate the reasons for disagreement between screening echocardiography (echo), acquired by nonexperts, and standard echo in the Brazilian primary care (PC). Over 20 months, 22 PC workers were trained on simplified handheld (GE VSCAN) echo protocols. Screening groups, consisting of patients aged 17-20, 35-40 and 60-65 years, and patients referred for clinical indications underwent focused echo. Studies were remotelyinterpreted in US and Brazil, and those diagnosed with major or severe HD were referred for standard echoperformed by an expert. Major HD was defined as moderate to severe valve disease, ventriculardysfunction/hypertrophy, pericardial effusion or wall-motion abnormalities. A random sample of exams wasselected for evaluation of variables accounting for disagreement. A sample of 768 patients was analyzed, 651(85%) in the referred group. Quality issues were reported in 5.8%, and the random Kappa for major HD between screening and standard echo was 0.51. The most frequent reasons for disagreement were: overestimation of mitral regurgitation (MR) (17.9%, N=138), left ventricular (LV) dysfunction (15.7%, N=121), aortic regurgitation (AR) (15.2%, N=117), LV hypertrophy (13.5%, N=104) and tricuspid regurgitation (12.7%, N=98). Misdiagnosis of mitral and aortic morphological abnormalities was observed in 12.4% and 3.0%, and underestimation of AR and MR occurred in 4.6% and 11.1%. Among 257 patients with suspected mild/moderate MR, 129 were reclassified to normal. In conclusion, although screening echo with task-shifting in PC is a promising tool in low-income areas, estimation of valve regurgitation and LV function and size account for considerable disagreement with standard exams.

Learning strategies of general practitioners striving to achieve point-of-care ultrasound competence: a qualitative study

BACKGROUND

Point-of-care ultrasonography (POCUS) is increasingly used in general practice despite the lack of official educational programmes or guidelines for general practitioners (GPs).

AIM

To explore how GPs have learnt to use POCUS and which barriers they have encountered in their learning process.

DESIGN AND SETTING

Qualitative study conducted in office-based general practice in Denmark.

METHODS

Semi-structured interviews were conducted with 13 GPs who had implemented POCUS without supporting guidelines or regulations. Analysis was carried out using systematic text condensation. The interview data for this study were collected along with data used in a previous study.

RESULTS

The participating GPs described having composed their own ultrasound education following a continuous learning process. Basic POCUS competences were achieved through formalized training sessions at hospital departments or courses. The GPs further developed and expanded their scanning skills through additional courses and continuous self-study practice on patients often while consulting internet sources, textbooks or colleagues. Lack of available ultrasound courses, supervision, and clinical guidelines together with time constraints and financial aspects were mentioned as barriers to their ultrasound training.

CONCLUSION

This study showed how GPs had composed their own ultrasound education individually and differently, guided by their own experiences and beliefs about good clinical practice. Formalized ultrasound training was considered a prerequisite for achieving basic ultrasound competences while continuous practice was considered paramount to develop and maintain scanning skills. There were several obstacles to overcome in the learning process including lack of supervision, guidance, and opportunity for practicing skills.Key pointsLittle is known about the educational needs of general practitioners striving to achieve ultrasound competences.General practitioners described using formalized training to achieve basic scanning competences and continuous self-study and practice to further develop their skills.Lack of time, supervision, clinical guidelines and ultrasound courses were considered barriers in the learning process together with financial aspects.

Diagnostic accuracy of handheld cardiac ultrasound device for assessment of left ventricular structure and function: systematic review and meta-analysis

Objective

Handheld ultrasound devices (HUD) has diagnostic value in the assessment of patients with suspected left ventricular (LV) dysfunction. This meta-analysis evaluates the diagnostic ability of HUD compared with transthoracic echocardiography (TTE) and assesses the importance of operator experience.

Methods

MEDLINE and EMBASE databases were searched in October 2020. Diagnostic studies using HUD and TTE imaging to determine LV dysfunction were included. Pooled sensitivities and specificities, and summary receiver operating characteristic curves were used to determine the diagnostic ability of HUD and evaluate the impact of operator experience on test accuracy.

Results

Thirty-three studies with 6062 participants were included in the meta-analysis. Experienced operators could predict reduced LV ejection fraction (LVEF), wall motion abnormality (WMA), LV dilatation and LV hypertrophy with pooled sensitivities of 88%, 85%, 89% and 85%, respectively, and pooled specificities of 96%, 95%, 98% and 91%, respectively. Non-experienced operators are able to detect cardiac abnormalities with reasonable sensitivity and specificity. There was a significant difference in the diagnostic accuracy between experienced and inexperienced users in LV dilatation, LVEF (moderate/severe) and WMA. The diagnostic OR for LVEF (moderate/severe), LV dilatation and WMA in an experienced hand was 276 (95% CI 58 to 1320), 225 (95% CI 87 to 578) and 90 (95% CI 31 to 265), respectively, compared with 41 (95% CI 18 to 94), 45 (95% CI 16 to 123) and 28 (95% CI 20 to 41), respectively, for inexperienced users.

Conclusion

This meta-analysis is the first to establish HUD as a powerful modality for predicting LV size and function. Experienced operators are able to accurately diagnose cardiac disease using HUD. A cautious, supervised approach should be implemented when imaging is performed by inexperienced users. This study provides a strong rationale for considering HUD as an auxiliary tool to physical examination in secondary care, to aid clinical decision making when considering referral for TTE.

Trial registration number

CRD42020182429.

Cardiovascular examination using hand-held cardiac ultrasound

Echocardiography is the first-line imaging modality for assessing cardiac function and morphology. The miniaturisation of ultrasound technology has led to the development of hand-held cardiac ultrasound (HCU) devices. The increasing sophistication of available HCU devices enables clinicians to more comprehensively examine patients at the bedside. HCU can augment clinical exam findings by offering a rapid screening assessment of cardiac dysfunction in both the Emergency Department and in cardiology clinics. Possible implications of implementing HCU into clinical practice are discussed in this review paper.

Education of general practitioners in the use of point-of-care ultrasonography: a systematic review

OBJECTIVE

To systematically review and synthesize the published literature regarding the education of general practitioners (GPs) and GPs in training (GPTs) in the use of ultrasonography.

DESIGN

This systematic review was prospectively registered in PROSPERO, conducted according to the Cochrane recommendations. We combined studies identified in a previous systematic review with studies from an updated literature search using the same search string. We searched the following databases: MEDLINE via Pubmed, EMBASE via OVID, Cinahl via Ebsco, Web of Science and Cochrane Register of Controlled Trials using the words 'ultrasonography' and 'general practice'. Two reviewers independently screened articles, extracted data and assessed the quality of included papers according to the Down and Black quality assessment tool. Disagreements were resolved by involving a third reviewer.

RESULTS

Thirty-three papers were included. Ultrasound training was described to include both theoretical and practical training sessions. Theoretical training was achieved through introductory e-learning and/or didactic lectures. Practical training included focussed hands-on training sessions, while some papers described additional longitudinal practical training through proctored scans during clinical work or through self-study practice with continuous feedback on recorded scans.

CONCLUSION

There was a large variation in ultrasound training programs for GPs and GPTs, with an overall emphasis on focussed practical training. Few studies included a longitudinal learning process in the training program. However, diagnostic accuracy seemed to improve with hours of practical training, and studies including continuous feedback on scans conducted during clinical patient encounters showed superior results.