Noninvasive assessment of left ventricular end-diastolic pressure using machine learning-derived phasic left atrial strain.

AIMS: While transthoracic echocardiography (TTE) assessment of left ventricular end-diastolic pressure (LVEDP) is critically important, the current paradigm is subject to error and indeterminate classification. Recently, peak left atrial strain (LAS) was found to be associated with LVEDP. We aimed to test the hypothesis that integration of the entire LAS time curve into a single parameter could improve the accuracy of peak LAS in the noninvasive assessment of LVEDP with TTE. METHODS AND RESULTS: We retrospectively identified 294 patients who underwent left heart catheterization and TTE within 24 h. LAS curves were trained using machine learning (100 patients) to detect LVEDP ≥ 15 mmHg, yielding the novel parameter LAS index (LASi). The accuracy of LASi was subsequently validated (194 patients), side by side with peak LAS and ASE/EACVI guidelines, against invasive filling pressures. Within the validation cohort, invasive LVEDP was elevated in 116 (59.8%) patients. The overall accuracy of LASi, peak LAS, and American Society of Echocardiography/European Association for Cardiovascular Imaging (ASE/EACVI) algorithm was 79, 75, and 76%, respectively (excluding 37 patients with indeterminate diastolic function by ASE/EACVI guidelines). When the number of LASi indeterminates (defined by near-zero LASi values) was matched to the ASE/EACVI guidelines (n = 37), the accuracy of LASi improved to 87%. Importantly, among the 37 patients with ASE/EACVI-indeterminate diastolic function, LASi had an accuracy of 81%, compared with 76% for peak LAS. CONCLUSION: LASi allows the detection of elevated LVEDP using invasive measurements as a reference, at least as accurately as peak LAS and current diastolic function guideline algorithm, with the advantage of no indeterminate classifications in patients with measurable LAS.

Assessment of right ventricular size and function from cardiovascular magnetic resonance images using artificial intelligence.

BACKGROUND: Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in our recent study, commercially available deep learning (DL) algorithms for RVEF quantification performed poorly in some patients. The current study was designed to test the hypothesis that quantification of RV function could be improved in these patients by using more diverse CMR datasets in addition to domain-specific quantitative performance evaluation metrics during the cross-validation phase of DL algorithm development. METHODS: We identified 100 patients from our prior study who had the largest differences between manually measured and automated RVEF values. Automated RVEF measurements were performed using the original version of the algorithm (DL1), an updated version (DL2) developed from a dataset that included a wider range of RV pathology and validated using multiple domain-specific quantitative performance evaluation metrics, and conventional methodology performed by a core laboratory (CORE). Each of the DL-RVEF approaches was compared against CORE-RVEF reference values using linear regression and Bland-Altman analyses. Additionally, RVEF values were classified into 3 categories: ≤ 35%, 35-50%, and ≥ 50%. Agreement between RVEF classifications made by the DL approaches and the CORE measurements was tested. RESULTS: CORE-RVEF and DL-RVEFs were obtained in all patients (feasibility of 100%). DL2-RVEF correlated with CORE-RVEF better than DL1-RVEF (r = 0.87 vs. r = 0.42), with narrower limits of agreement. As a result, DL2 algorithm also showed increasing accuracy from 0.53 to 0.80 for categorizing RV function. CONCLUSIONS: The use of a new DL algorithm cross-validated on a dataset with a wide range of RV pathology using multiple domain-specific metrics resulted in a considerable improvement in the accuracy of automated RVEF measurements. This improvement was demonstrated in patients whose images were the most challenging and resulted in the largest RVEF errors. These findings underscore the critical importance of this strategy in the development of DL approaches for automated CMR measurements.

An assessment of canine ectoparasiticide administration compliance in the USA.

BACKGROUND: This study evaluated the timing of dog owner ectoparasiticide purchases to estimate administration compliance and assess the consequent impact of dose purchase gaps on the proportion of time that dogs were protected over a 12-month period. METHODS: Ectoparasiticide purchase transactions over a 12-month period were evaluated for 626 US veterinary hospitals to determine dose purchase timing and identify consequent gaps between dose administration in dogs. Orally administered prescription ectoparasitic medications with active ingredients from the isoxazoline family (afoxolaner, fluralaner, lotilaner, or sarolaner) were included in the analysis. A period was calculated for each of the four isoxazoline-containing medications that represented the duration of protection provided by two doses of ectoparasiticide plus the average gap between these two doses. The maximum percentage of time possible for ectoparasiticide protection for this aggregate period was then calculated for each active ingredient. RESULTS: Ectoparasiticide transaction records of owners were analyzed for 506,637 dogs. These showed that 43% of dog owners purchased just one dose over the 12-month period considered. If a dog owner purchased more than one dose, then the timing of their transactions could create a time gap between the completion of ectoparasite protection from the first dose and onset of protection from the subsequent purchase and administration of the second dose. Such gaps were observed in purchases made by 31-65% of dog owners, depending on the selected active ingredient and number of doses. The average gap duration between dose purchases was calculated for all possible dose combinations over 12 months of ectoparasite protection. Time gaps between the first and second doses are as follows: for sarolaner, 20.3 weeks; for afoxolaner, 12.9 weeks; for fluralaner ,12.8 weeks; and for lotilaner, 8.9 weeks. The proportion of time when protection was provided during the aggregate period between administration of the first and second doses was as follows: for fluralaner, 65%; for lotilaner, 49%; for afoxolaner, 40%; and for sarolaner, 30%. CONCLUSIONS: Dog owner ectoparasiticide purchase transactions showed that there were time gaps between doses leading to reduced ectoparasite protection. The longer re-administration interval for fluralaner, a consequence of its extended duration of activity, resulted in dog owners gaining the greatest proportion of ectoparasite protection time with this medication compared with shorter-acting monthly re-treatment medications.

Developing Insights Regarding Tricuspid Valve Regurgitation: Morphology, Assessment of Severity, and the Need for a Novel Grading Scheme.

Current understanding that progressive tricuspid regurgitation (TR) is associated with worse outcomes has highlighted the clinical need for a more accurate assessment of TR morphology and severity. This need has been further emphasized owing to the development of a myriad of percutaneous right-sided interventions, which may offer successful treatment of TR in selected patients. Understanding the etiology and quantification of the severity of TR has important implications in the selection of novel therapeutic strategies, i.e., medical vs. percutaneous vs. surgical approaches. Newer grading schemas that better reflect the TR lesion severity have been recently proposed and may facilitate monitoring of the evolution of TR following percutaneous and/or surgical treatment. In this review, we summarize contemporary concepts regarding tricuspid valve morphology, TR etiology, and associated mechanisms and echocardiographic approaches to grade TR severity.

Can echocardiographic assessment of diastolic function be automated?

Echocardiographic evaluation of left ventricular diastolic function relies on a multi-pronged algorithm, which incorporates Doppler-based and volumetric parameters. Integration of clinical data in diastolic assessment is recommended, though not clearly outlined. We sought to develop an automated tool for diastolic function, compare its performance to human-generated diagnoses and identify the common sources of error. Our software tool is based on the 2016 diastolic guidelines algorithm, which uses 8 parameters as input, with 10 conditions as the logic and 5 possible outputs as final diagnoses. Initially, we prospectively studied 563 patients whose diastolic function was independently evaluated by an expert echocardiographer and by the automated tool. Incongruent cases were further analyzed, after which features of myocardial disease were integrated into a refined version of the software that was tested in an independent cohort of 1106 patients. In the initial analysis, 202/563 grades (36%) were incongruent between the automated and human reads, with the highest rate of discordance for mild and indeterminate categories. In 17% of cases, human diagnoses differed from that dictated by the algorithm due to integration of clinical factors. Follow-up analysis using the refined automated tool did not improve the discordance rate (440/1106; 40%). There was more discordance in cases of: age > 40 years, impaired mitral inflow patterns (E/A < 0.8) and reduced mitral e' values. Further analysis revealed differences in how readers interpreted the interaction between these factors and diastolic function, which could not be incorporated into the automated tool. In conclusion, although assessment of diastolic function relies on an algorithm that can be automated, this algorithm does not include clear guidance on how to incorporate age, or age-related changes in Doppler-based parameters, often resulting in discordant diagnoses. Standardized interpretation of these factors is needed to improve the reproducibility of diastolic function grading by human readers and the accuracy of the automated classification.

Mental health indicators in the later phase of lockdown due to COVID-19 pandemic in healthy youth combined elderly people: a web-based cross-sectional survey.

Lockdown was implemented throughout the world in March 2020 to control the spread of covid-19 infection. It affected the mental health of people in various ways. This web-based cross-sectional survey was conducted in the general population of India with an aim to evaluate the mental health of the healthy individuals in the later stage of the lockdown period. Data on socio-demographic factors, anxiety, depression (HADS scale), perceived stress (PSS scale), insomnia (insomnia severity index), subjective psychological feeling of well-being (WHO-5 well-being Index), and attitude towards covid-19 (7-point Likert scale) was collected. Univariate regression analysis and Karl Pearson's correlation were used to analyze the correlation of mental health abnormalities with socio-demographic factors. 119 subjects of mean age of 36.03 ± 18.04 years took part in the study. Their average number of days of stay at home during the lockdown and the average number of days of the lifestyle changes was 49.07 ± 31.92 and 61.39 ± 20.03 days, respectively. Depression, anxiety, stress, and clinical insomnia due to covid-19 were reported in 13.45%, 10.92%, 14.29%, and 11.76% subjects, respectively. There was a significant correlation of depression, anxiety, stress, and WHO-5 well-being score with age, socio-economic status, and the average number of days of the change in lifestyle due to the COVID-19 pandemic (P < 0.05). Therefore, the study concluded that the abnormalities of mental health were less prevalent in the older age group and lower socioeconomic status in the later phase of lockdown.

Analysis of gaps in feline ectoparasiticide purchases from veterinary clinics in the United States.

BACKGROUND: The study objective was to examine cat owner ectoparasiticide purchases in the United States and estimate the impact of purchase gaps on timely ectoparasite protection administration. These purchase gaps lead to periods of time when cats are unprotected from ectoparasites. METHODS: Ectoparasiticide purchase transactions for individual cats from 671 U.S. veterinary clinics from January 1, 2017 through June 30, 2019 were evaluated to determine time "gaps" between doses of ectoparasiticides purchased in a defined 12-month period. Ectoparasiticides examined were topically applied products that contained fluralaner, fipronil/(S)-methoprene/pyriproxyfen, imidacloprid/pyriproxyfen or selamectin as active ingredients. The duration of protection following administration of one dose was 8-12 weeks for the fluralaner-containing product and one month for the other products. RESULTS: Ectoparasiticide purchase records were obtained from 114,853 cat owners and analysis found that most owners bought ≤ 6 months of protection during the year, with 61-75% (depending on the product) purchasing just 1-3 months of protection. The size of the average purchase gap was determined for all dose combinations out to 12 months of protection (5-7 doses for fluralaner and 12 doses for the other three products dosed monthly. The largest gaps occurred between the first and second doses and the second and third doses. Average purchase gaps for the four different products between doses 1 and 2 ranged from 11.2 to 13.9 weeks and between doses 2 and 3 ranged from 7.7 to 12.2 weeks. The fraction of purchases separated by gaps and the average length of the gap tended to decrease with increasing number of doses purchased. Owners purchasing the 8 to 12-week duration product containing fluralaner provided ectoparasite protection ("doses plus gap period") for a larger proportion of each 2-dose period compared with owners purchasing products administered monthly. CONCLUSIONS: When cat owners purchase flea and tick medication, gaps between subsequent purchases reduces the proportion of time ectoparasite protection can be provided. The duration of the gap between doses has an impact on the effectiveness of flea/tick medication because it inserts a period without flea and tick protection between doses of flea and tick medication. The gaps between purchases were shorter and the period of ectoparasite protection was larger for owners purchasing a 12-week product than for owners purchasing a monthly product.

Peak left atrial strain as a single measure for the non-invasive assessment of left ventricular filling pressures.

Echocardiographic assessment of left ventricular (LV) filling pressures is performed using a multi-parametric algorithm. Left atrial (LA) strain was recently found to accurately classify the degree of diastolic dysfunction. We hypothesized that LA strain could be used as a stand-alone marker and sought to identify and test a cutoff, which would accurately detect elevated LV pressures. We studied 76 patients with a spectrum of LV function who underwent same-day echocardiogram and invasive left-heart catheterization. Speckle tracking was used to measure peak LA strain. The protocol involved a retrospective derivation group (N = 26) and an independent prospective validation cohort (N = 50) to derive and then test a peak LA strain cutoff which would identify pre-A-wave LV diastolic pressure > 15 mmHg. The guidelines-based assessment of filling pressures and peak LA strain were compared side-by-side against invasive hemodynamic data. In the derivation cohort, receiver-operating characteristic analysis showed area under curve of 0.76 and a peak LA strain cutoff < 20% was identified as optimal to detect elevated filling pressure. In the validation cohort, peak LA strain demonstrated better agreement with the invasive reference (81%) than the guidelines algorithm (72%). The improvement in classification using LA strain compared to the guidelines was more pronounced in subjects with normal LV function (91% versus 81%). In summary, the use of a peak LA strain to estimate elevated LV filling pressures is more accurate than the current guidelines. Incorporation of LA strain into the non-invasive assessment of LV diastolic function may improve the detection of elevated filling pressures.

Invasive Validation of the Echocardiographic Assessment of Left Ventricular Filling Pressures Using the 2016 Diastolic Guidelines: Head-to-Head Comparison with the 2009 Guidelines.

BACKGROUND: Recent American Society of Echocardiography (ASE)/European Association of Cardiovascular Imaging (EACVI) guidelines for echocardiographic evaluation of left ventricular (LV) diastolic function provide a practical, simplified diagnostic algorithm for estimating LV filling pressure. The aim of this study was to test the accuracy of this algorithm against invasively measured pressures and compare it with the accuracy of the previous 2009 guidelines in the same patient cohort. METHODS: Ninety patients underwent transthoracic echocardiography immediately before left heart catheterization. Mitral inflow E/A ratio, E/e', tricuspid regurgitation velocity, and left atrial volume index were used to estimate LV filling pressure as normal or elevated using the ASE/EACVI algorithm. Invasive LV pre-A pressure was used as a reference, with >12 mm Hg defined as elevated. RESULTS: Invasive LV pre-A pressure was elevated in 40 (44%) and normal in 50 (56%) patients. The 2016 algorithm resulted in classification of 9 of 90 patients (10%) as indeterminate but estimated LV filling pressures in agreement with the invasive reference in 61 of 81 patients (75%), with sensitivity of 0.69 and specificity of 0.81. The 2009 algorithm could not definitively classify 4 of 90 patients (4.4%), but estimated LV filling pressures in agreement with the invasive reference in 64 of 86 patients (74%), with sensitivity of 0.79 and specificity of 0.70. CONCLUSIONS: The 2016 ASE/EACVI guidelines for estimation of filling pressures are more user friendly and efficient than the 2009 guidelines and provide accurate estimates of LV filling pressure in the majority of patients when compared with invasive measurements. The simplicity of the new algorithm did not compromise its accuracy and is likely to encourage its incorporation into clinical decision making.

Appropriate Use Criteria for Echocardiography: Evolving Applications in the Era of Value-Based Healthcare.

The current climate in healthcare is increasingly emphasizing a value-based approach to diagnostic testing. Cardiac imaging, including echocardiography, has been a primary target of ongoing reforms in healthcare delivery and reimbursement. The Appropriate Use Criteria (AUC) for echocardiography is a physician-derived tool intended to guide utilization in optimal patient care. To date, the AUC have primarily been employed solely as justification for reimbursement, though evolving broader applications to guide clinical decision-making suggest a far more valuable role in the delivery of high-quality and high-value healthcare.