Echocardiography is crucial for evaluating patients at risk of clinical deterioration. Left ventricular ejection fraction (LVEF) and velocity time integral (VTI) aid in diagnosing shock, but bedside calculations can be time-consuming and prone to variability. Artificial intelligence technology shows promise in providing assistance to clinicians performing point-of-care echocardiography. We conducted a systematic review, utilizing a comprehensive literature search on PubMed, to evaluate the interchangeability of LVEF and/or VTI measurements obtained through automated mode as compared to the echocardiographic reference methods in non-cardiology settings, e.g., Simpson´s method (LVEF) or manual trace (VTI). Eight studies were included, four studying automated-LVEF, three automated-VTI, and one both. When reported, the feasibility of automated measurements ranged from 78.4 to 93.3%. The automated-LVEF had a mean bias ranging from 0 to 2.9% for experienced operators and from 0% to -10.2% for non-experienced ones, but in both cases, with wide limits of agreement (LoA). For the automated-VTI, the mean bias ranged between − 1.7 cm and − 1.9 cm. The correlation between automated and reference methods for automated-LVEF ranged between 0.63 and 0.86 for experienced and between 0.56 and 0.81 for non-experienced operators. Only one study reported a correlation between automated-VTI and manual VTI (0.86 for experienced and 0.79 for non-experienced operators). We found limited studies reporting the interchangeability of automated LVEF or VTI measurements versus a reference approach. The accuracy and precision of these automated methods should be considered within the clinical context and decision-making. Such variability could be acceptable, especially in the hands of trained operators. PROSPERO number CRD42024564868.

Automated and reference methods for the calculation of left ventricular outflow tract velocity time integral or ejection fraction by non-cardiologists: a systematic review on the agreement of the two methods

Santonocito C.;Sanfilippo F.
2025-01-01

Abstract

Echocardiography is crucial for evaluating patients at risk of clinical deterioration. Left ventricular ejection fraction (LVEF) and velocity time integral (VTI) aid in diagnosing shock, but bedside calculations can be time-consuming and prone to variability. Artificial intelligence technology shows promise in providing assistance to clinicians performing point-of-care echocardiography. We conducted a systematic review, utilizing a comprehensive literature search on PubMed, to evaluate the interchangeability of LVEF and/or VTI measurements obtained through automated mode as compared to the echocardiographic reference methods in non-cardiology settings, e.g., Simpson´s method (LVEF) or manual trace (VTI). Eight studies were included, four studying automated-LVEF, three automated-VTI, and one both. When reported, the feasibility of automated measurements ranged from 78.4 to 93.3%. The automated-LVEF had a mean bias ranging from 0 to 2.9% for experienced operators and from 0% to -10.2% for non-experienced ones, but in both cases, with wide limits of agreement (LoA). For the automated-VTI, the mean bias ranged between − 1.7 cm and − 1.9 cm. The correlation between automated and reference methods for automated-LVEF ranged between 0.63 and 0.86 for experienced and between 0.56 and 0.81 for non-experienced operators. Only one study reported a correlation between automated-VTI and manual VTI (0.86 for experienced and 0.79 for non-experienced operators). We found limited studies reporting the interchangeability of automated LVEF or VTI measurements versus a reference approach. The accuracy and precision of these automated methods should be considered within the clinical context and decision-making. Such variability could be acceptable, especially in the hands of trained operators. PROSPERO number CRD42024564868.
2025
Artificial intelligence
Critical care
Echocardiography
Left ventricle ejection fraction
Velocity time integral
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/720611
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