直近一年間の累計
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ダウンロード数 : ?
ID 118966
著者
Hirata, Yukina Tokushima University
Tsuji, Takumasa Teikyo University
Kotoku, Jun’ichi Teikyo University
キーワード
Pulmonary hypertension
left heart disease
classification
echocardiography
artificial intelligence
machine learning
資料タイプ
学術雑誌論文
抄録
Objective: The classification of pulmonary hypertension (PH) is crucial for determining the appropriate therapeutic strategy. We investigated whether machine learning (ML) algorithms may assist in echocardiographic PH prediction, where current guidelines recommend integrating several different parameters.
Methods: We obtained physical and echocardiographic data from 885 patients who underwent right heart catheterization (RHC). Patients were classified into three groups: non-PH, pre-capillary PH, and post-capillary PH, based on values obtained from RHC. Utilizing 24 parameters, we created predictive models employing four different classifiers and selected the one with the highest area under the curve (AUC). We then calculated the macro-average classification accuracy for PH on the derivation cohort (n=720) and prospective validation dataset (n=165), comparing the results with guideline-based echocardiographic assessment obtained from each cohort.
Results: Logistic regression with elastic net regularization had the highest classification accuracy, with AUCs of 0.789, 0.766, and 0.742 for normal, pre-capillary PH, and post-capillary PH, respectively. The ML model demonstrated significantly better predictive accuracy than the guideline-based echocardiographic assessment in the derivation cohort (59.4% vs. 51.6%, p<0.01). In the independent validation dataset, the ML model's accuracy was comparable to the guideline-based PH classification (59.4% vs. 57.8%, p=0.638).
Conclusions: This preliminary study suggests promising potential for our ML model in predicting echocardiographic PH. Further research and validation are needed to fully assess its clinical utility in PH diagnosis and treatment decision-making.
掲載誌名
Heart
ISSN
1468201X
13556037
cat書誌ID
AA12780139
AA11059124
出版者
BMJ Publishing Group|British Cardiovascular Society
110
開始ページ
586
終了ページ
593
発行日
2024-01-30
権利情報
This article has been accepted for publication in Heart, 2024 following peer review, and the Version of Record can be accessed online at https://doi.org/10.1136/heartjnl-2023-323320
EDB ID
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
著者版
部局
医学系
病院