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  • MDPI AG  (3)
  • Kusunose, Kenya  (3)
  • 1
    In: Biomolecules, MDPI AG, Vol. 10, No. 5 ( 2020-04-25), p. 665-
    Abstract: A proper echocardiographic study requires several video clips recorded from different acquisition angles for observation of the complex cardiac anatomy. However, these video clips are not necessarily labeled in a database. Identification of the acquired view becomes the first step of analyzing an echocardiogram. Currently, there is no consensus whether the mislabeled samples can be used to create a feasible clinical prediction model of ejection fraction (EF). The aim of this study was to test two types of input methods for the classification of images, and to test the accuracy of the prediction model for EF in a learning database containing mislabeled images that were not checked by observers. We enrolled 340 patients with five standard views (long axis, short axis, 3-chamber view, 4-chamber view and 2-chamber view) and 10 images in a cycle, used for training a convolutional neural network to classify views (total 17,000 labeled images). All DICOM images were rigidly registered and rescaled into a reference image to fit the size of echocardiographic images. We employed 5-fold cross validation to examine model performance. We tested models trained by two types of data, averaged images and 10 selected images. Our best model (from 10 selected images) classified video views with 98.1% overall test accuracy in the independent cohort. In our view classification model, 1.9% of the images were mislabeled. To determine if this 98.1% accuracy was acceptable for creating the clinical prediction model using echocardiographic data, we tested the prediction model for EF using learning data with a 1.9% error rate. The accuracy of the prediction model for EF was warranted, even with training data containing 1.9% mislabeled images. The CNN algorithm can classify images into five standard views in a clinical setting. Our results suggest that this approach may provide a clinically feasible accuracy level of view classification for the analysis of echocardiographic data.
    Type of Medium: Online Resource
    ISSN: 2218-273X
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2701262-1
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  • 2
    In: Nutrients, MDPI AG, Vol. 13, No. 2 ( 2021-01-23), p. 335-
    Abstract: A broad range of chronic conditions, including heart failure (HF), have been associated with vitamin D deficiency. Existing clinical trials involving vitamin D supplementation in chronic HF patients have been inconclusive. We sought to evaluate the outcomes of patients with vitamin D supplementation, compared with a matched cohort using real-world big data of HF hospitalization. This study was based on the Diagnosis Procedure Combination database in the Japanese Registry of All Cardiac and Vascular Datasets (JROAD-DPC). After exclusion criteria, we identified 93,692 patients who were first hospitalized with HF between April 2012 and March 2017 (mean age was 79 ± 12 years, and 52.2% were male). Propensity score (PS) was estimated with logistic regression model, with vitamin D supplementation as the dependent variable and clinically relevant covariates. On PS-matched analysis with 10,974 patients, patients with vitamin D supplementation had lower total in-hospital mortality (6.5 vs. 9.4%, odds ratio: 0.67, p 〈 0.001) and in-hospital mortality within 7 days and 30 days (0.9 vs. 2.5%, OR, 0.34, and 3.8 vs. 6.5%, OR: 0.56, both p 〈 0.001). In the sub-group analysis, mortalities in patients with age 〈 75, diabetes, dyslipidemia, atrial arrhythmia, cancer, renin-angiotensin system blocker, and β-blocker were not affected by vitamin D supplementation. Patients with vitamin D supplementation had a lower in-hospital mortality for HF than patients without vitamin D supplementation in the propensity matched cohort. The identification of specific clinical characteristics in patients benefitting from vitamin D may be useful for determining targets of future randomized control trials.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518386-2
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  • 3
    In: Journal of Cardiovascular Development and Disease, MDPI AG, Vol. 8, No. 10 ( 2021-09-30), p. 124-
    Abstract: Background: Echocardiography requires a high degree of skill on the part of the examiner, and the skill may be more improved in larger volume centers. This study investigated trends and outcomes associated with the use and volume of echocardiographic exams from a real-world registry database of heart failure (HF) hospitalizations. Methods: This study was based on the Diagnosis Procedure Combination database in the Japanese Registry of All Cardiac and Vascular Datasets (JROAD-DPC). A first analysis was performed to assess the trend of echocardiographic examinations between 2012 and 2016. A secondary analysis was performed to assess whether echocardiographic use was associated with in-hospital mortality in 2015. Results: During this period, the use of echocardiography grew at an average annual rate of 6%. Patients with echocardiography had declining rates of hospital mortality, and these trends were associated with high hospitalization costs. In the 2015 sample, a total of 52,832 echocardiograms were examined, corresponding to 65.6% of all HF hospital admissions for that year. We found that the use and volume of echocardiography exams were associated with significantly lower odds of all-cause hospital mortality in heart failure (adjusted odds ratio (OR): 0.48 for use of echocardiography and 0.78 for the third tertile; both p 〈 0.001). Conclusions: The use of echocardiography was associated with decreased odds of hospital mortality in HF. The volumes of echocardiographic examinations were also associated with hospital mortality.
    Type of Medium: Online Resource
    ISSN: 2308-3425
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2777082-5
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