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  1. Alsharqi M, Lapidaire W, Iturria-Medina Y, Xiong Z, Williamson W, Mohamed A, et al.
    Eur Heart J Imaging Methods Pract, 2023 Sep;1(2):qyad029.
    PMID: 37818310 DOI: 10.1093/ehjimp/qyad029
    AIMS: Accurate staging of hypertension-related cardiac changes, before the development of significant left ventricular hypertrophy, could help guide early prevention advice. We evaluated whether a novel semi-supervised machine learning approach could generate a clinically meaningful summary score of cardiac remodelling in hypertension.

    METHODS AND RESULTS: A contrastive trajectories inference approach was applied to data collected from three UK studies of young adults. Low-dimensional variance was identified in 66 echocardiography variables from participants with hypertension (systolic ≥160 mmHg) relative to a normotensive group (systolic < 120 mmHg) using a contrasted principal component analysis. A minimum spanning tree was constructed to derive a normalized score for each individual reflecting extent of cardiac remodelling between zero (health) and one (disease). Model stability and clinical interpretability were evaluated as well as modifiability in response to a 16-week exercise intervention. A total of 411 young adults (29 ± 6 years) were included in the analysis, and, after contrastive dimensionality reduction, 21 variables characterized >80% of data variance. Repeated scores for an individual in cross-validation were stable (root mean squared deviation = 0.1 ± 0.002) with good differentiation of normotensive and hypertensive individuals (area under the receiver operating characteristics 0.98). The derived score followed expected hypertension-related patterns in individual cardiac parameters at baseline and reduced after exercise, proportional to intervention compliance (P = 0.04) and improvement in ventilatory threshold (P = 0.01).

    CONCLUSION: A quantitative score that summarizes hypertension-related cardiac remodelling in young adults can be generated from a computational model. This score might allow more personalized early prevention advice, but further evaluation of clinical applicability is required.

  2. Dorobantu DM, Wadey CA, Berryman B, Amir NH, Forsythe L, Stuart AG, et al.
    Eur Heart J Imaging Methods Pract, 2024 Jan;2(1):qyae021.
    PMID: 39045209 DOI: 10.1093/ehjimp/qyae021
    AIMS: The value of cardiopulmonary exercise testing (CPET) and exercise stress echocardiography (ESE) in managing cardiac disease is well known, but no standard CPET-ESE protocol is currently recommended. This pilot study aims to compare feasibility and cardiac function responses between a new high-intensity single-stage combined test (CPET-hiESE) and a standard maximal ESE (smESE).

    METHODS AND RESULTS: After screening and maximal CPET, all volunteers (n = 21) underwent three ESE modalities: (i) based on the gas exchange threshold (hiESE-GET, 40% of peak-GET, 6 min), (ii) based on heart rate (HR) (hiESE-HR, 80% of peak HR, 6 min), and (iii) smESE (85% of predicted peak HR for age, 3 min). Speckle tracking echocardiography (STE) and tissue Doppler imaging (TDI) were measured at each step. There was superior image quality and data completeness for the right ventricle strain for both hiESE modalities compared with smESE (71.4 and 76.2 vs. 42.9%, P = 0.07). Left ventricular STE data completeness was similar for all three conditions. Despite systematically higher HR, work rate and levels of exertion in the smESE compared with hiESE, STE and TDI parameters were not systematically different. Concordance correlation coefficients ranged from 0.56 to 0.88, lowest for strain rate parameters and mean difference from -0.34 to 1.53, highest for TDI measurements.

    CONCLUSION: The novel CPET-hiESE protocol allowed for better data completeness, at lower levels of exertion compared with smESE, without systematically different cardiac reserve measurements in healthy participants. This single-stage protocol can be individualized to clinical populations, which would provide practical advantages to standard testing.

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