The prevalence of abnormal right ventricle speckle strain in the setting of acute myocarditis and preserved left ventricle function.

BACKGROUND: Acute myocarditis has a wide spectrum of clinical presentation, from subclinical disease to acute heart failure, and sudden cardiac death. Two-dimensional speckle tracking echocardiography (2D-STE) has been proven effective in early diagnosis of subclinical cardiac injury, however, there is a limited data regarding the right ventricle (RV) involvement among patients with acute myocarditis. PURPOSE: We evaluated the prevalence of early subclinical RV injury assessed by 2D-STE, among patients with acute myocarditis and preserved left ventricle (LV) function. METHODS: We performed a retrospective single-center study at Tel-Aviv Sourasky Medical Center, including all adult patients hospitalized with acute myocarditis, who presented with preserved LV function. 2D-STE analysis of the RV was performed offline, assessing both the RV four-chamber longitudinal strain peak systolic (RV4CLS PK) and the free wall longitudinal strain peak systolic (RVFWLS PK). The myocarditis group was compared to a healthy control group. RESULTS: From 2011 to 2020, a total of 90 patients included in the study and were compared to 70 healthy subjects. RV 2D-STE emerged as significantly lower for both the RV4CLS PK (-21.8 ± 4.2 vs. -24.9 ± 4.8, P < 0.001) and RVFWLS PK (-24.7 ± 4.9 vs. -28.4 ± 5, P < 0.001), and remained significant in a multivariate analysis. CONCLUSION: We presented for the first time the presence of subclinical RV dysfunction, assessed by 2D-STE, in patients diagnosed with acute myocarditis, in the presence of preserved LV function. Further studies are needed to evaluate its' role in the development of LV dysfunction, heart failure and mortality.

Assessing data gathering of chatbot based symptom checkers - a clinical vignettes study.

BACKGROUND: The burden on healthcare systems is mounting continuously owing to population growth and aging, overuse of medical services, and the recent COVID-19 pandemic. This overload is also causing reduced healthcare quality and outcomes. One solution gaining momentum is the integration of intelligent self-assessment tools, known as symptom-checkers, into healthcare-providers' systems. To the best of our knowledge, no study so far has investigated the data-gathering capabilities of these tools, which represent a crucial resource for simulating doctors' skills in medical-interviews. OBJECTIVES: The goal of this study was to evaluate the data-gathering function of currently available chatbot symptom-checkers. METHODS: We evaluated 8 symptom-checkers using 28 clinical vignettes from the repository of MSD-Manual case studies. The mean number of predefined pertinent findings for each case was 31.8 ± 6.8. The vignettes were entered into the platforms by 3 medical students who simulated the role of the patient. For each conversation, we obtained the number of pertinent findings retrieved and the number of questions asked. We then calculated the recall-rates (pertinent-findings retrieved out of all predefined pertinent-findings), and efficiency-rates (pertinent-findings retrieved out of the number of questions asked) of data-gathering, and compared them between the platforms. RESULTS: The overall recall rate for all symptom-checkers was 0.32(2,280/7,112;95 %CI 0.31-0.33) for all pertinent findings, 0.37(1,110/2,992;95 %CI 0.35-0.39) for present findings, and 0.28(1140/4120;95 %CI 0.26-0.29) for absent findings. Among the symptom-checkers, Kahun platform had the highest recall rate with 0.51(450/889;95 %CI 0.47-0.54). Out of 4,877 questions asked overall, 2,280 findings were gathered, yielding an efficiency rate of 0.46(95 %CI 0.45-0.48) across all platforms. Kahun was the most efficient tool 0.74 (95 %CI 0.70-0.77) without a statistically significant difference from Your.MD 0.69(95 %CI 0.65-0.73). CONCLUSION: The data-gathering performance of currently available symptom checkers is questionable. From among the tools available, Kahun demonstrated the best overall performance.