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  • Frontiers Media SA  (3)
  • Keller, Till  (3)
  • 1
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    Table_1.DOCX
    Frontiers Media SA ; 2022
    In:  Frontiers in Cardiovascular Medicine Vol. 9 ( 2022-3-31)
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    In: Frontiers in Cardiovascular Medicine, Frontiers Media SA, Vol. 9 ( 2022-3-31)
    Abstract: Pulmonary hypertension (PH) is an established risk factor in patients with heart failure (HF). However, right heart catheterisation (RHC) and vasoreactivity testing (VRT) are not routinely recommended in these patients. Methods The primary objective of the present study was to explore the impact of VRT using sublingual glyceryl trinitrate (GTN) on transplant/ventricular assist device-free survival in HF patients with post-capillary PH. RHC parameters were correlated retrospectively with the primary outcome. Results The cohort comprised 154 HF patients with post-capillary PH undergoing RHC with GTN-VRT at a tertiary heart failure centre. Multiple parameters were associated with survival. After adjustment for established prognosis-relevant clinical variables from the MAGGIC Score, variables with the most relevant odds ratios (OR) obtained after GTN-VRT were: calculated effective pulmonary arterial (PA) elastance (adjusted OR 2.26, 95%CI 1.30–3.92; p = 0.004), PA compliance (PAC-GTN; adjusted OR 0.45, 95%CI 0.25–0.80; p = 0.006), and total pulmonary resistance (adjusted OR 2.29, 95%CI 1.34–3.93; p = 0.003). Forest plot analysis including these three variables as well as PAC at baseline, delta PAC, and the presence of combined post- and pre-capillary PH revealed prognostic superiority of PAC-GTN, which was confirmed by Kaplan-Meier analysis. Conclusions In our cohort of symptomatic HF patients with post-capillary PH, improved PAC after administration of GTN was associated with survival independent of established hemodynamic and clinical risk factors. VRT using GTN may be better described as unloading test due to GTN's complex effects on the circulation. This could be used for advanced prognostication and should be investigated in further studies.
    Type of Medium: Online Resource
    ISSN: 2297-055X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fcvm.2022.838898
    DOI: 10.3389/fcvm.2022.838898.s001
    DOI: 10.3389/fcvm.2022.838898.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2781496-8
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  • 2
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    Data_Sheet_1.PDF
    Frontiers Media SA ; 2021
    In:  Frontiers in Cardiovascular Medicine Vol. 8 ( 2021-11-2)
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    In: Frontiers in Cardiovascular Medicine, Frontiers Media SA, Vol. 8 ( 2021-11-2)
    Abstract: Inflammation is a hallmark of the period after a myocardial infarction (MI) that is either promoted or resolved by distinct subtypes of circulating inflammatory cells. The three main monocyte subpopulations play different roles inflammation. This study examined whether the type of MI (type 1 or type 2) or the extent of myocardial injury is associated with differences in monocyte subpopulations. For this purpose, peripheral whole blood from patients with a suspected MI was used for flow cytometric measurements of the monocyte subpopulations, and myocardial injury was classified by cardiac troponin levels in serum. In patients with acute coronary syndrome ( n = 82, 62.2% male) similar proportions of the monocyte subsets were associated with the two types of MI, whereas total monocyte counts were increased in patients with substantial myocardial injury vs. those with minor injury ( p = 0.045). This was accompanied by a higher proportion of intermediate ( p = 0.045) and classical monocytes ( p = 0.059); no difference was found for non-classical monocytes ( p = 0.772). In patients with chronic coronary syndrome ( n = 144, 66.5% male), an independent association with myocardial injury was also observed for classical monocytes ( p = 0.01) and intermediate monocytes ( p = 0.08). In conclusion, changes in monocyte subpopulation counts, particularly for classical and intermediate monocytes, were related to the extent of myocardial injury in acute and stable coronary artery disease but not to the type of MI.
    Type of Medium: Online Resource
    ISSN: 2297-055X
    URL: Article
    URL: Article
    DOI: 10.3389/fcvm.2021.741890
    DOI: 10.3389/fcvm.2021.741890.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2781496-8
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  • 3
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    Identifying Heart Failure in ECG Data With Artificial Intelligence—A Meta-Analysis
    Frontiers Media SA ; 2021
    In:  Frontiers in Digital Health Vol. 2 ( 2021-2-25)
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    In: Frontiers in Digital Health, Frontiers Media SA, Vol. 2 ( 2021-2-25)
    Abstract: Introduction: Electrocardiography (ECG) is a quick and easily accessible method for diagnosis and screening of cardiovascular diseases including heart failure (HF). Artificial intelligence (AI) can be used for semi-automated ECG analysis. The aim of this evaluation was to provide an overview of AI use in HF detection from ECG signals and to perform a meta-analysis of available studies. Methods and Results: An independent comprehensive search of the PubMed and Google Scholar database was conducted for articles dealing with the ability of AI to predict HF based on ECG signals. Only original articles published in peer-reviewed journals were considered. A total of five reports including 57,027 patients and 579,134 ECG datasets were identified including two sets of patient-level data and three with ECG-based datasets. The AI-processed ECG data yielded areas under the receiver operator characteristics curves between 0.92 and 0.99 to identify HF with higher values in ECG-based datasets. Applying a random-effects model, an sROC of 0.987 was calculated. Using the contingency tables led to diagnostic odds ratios ranging from 3.44 [95% confidence interval (CI) = 3.12–3.76] to 13.61 (95% CI = 13.14–14.08) also with lower values in patient-level datasets. The meta-analysis diagnostic odds ratio was 7.59 (95% CI = 5.85–9.34). Conclusions: The present meta-analysis confirms the ability of AI to predict HF from standard 12-lead ECG signals underlining the potential of such an approach. The observed overestimation of the diagnostic ability in artificial ECG databases compared to patient-level data stipulate the need for robust prospective studies.
    Type of Medium: Online Resource
    ISSN: 2673-253X
    URL: Article
    DOI: 10.3389/fdgth.2020.584555
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 3017798-4
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