入院時に臓器不全のない患者の重症急性炎への進行を予測するモデル
Jianhua Wan1, Yaoyu Zou1, Maobin Kuang1
1Department of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
まとめ
新しいACRスコアは,初期急性炎 (AP) が有るが,臓器不全 (OF) がない患者の重症急性炎 (SAP) の進行を予測する. このシンプルなツールは,よりよい管理のために,高リスクの個人を特定するのに役立ちます.
科学分野:
- 胃腸内科 胃腸内科
- クリニカル・メディシン 臨床医学
- 予測型アナリティクス (Predictive Analytics) とは,予測型アナリティクス (Predictive Analytics) を意味する.
背景:
- 急性炎 (AP) は,初期臓器不全 (OF) がなくても重症急性炎 (SAP) に進行することがあります.
- この進行を予測することは,適時な介入に不可欠です.
研究 の 目的:
- SAPの進歩を予測するためのシンプルなスコアリングシステムを開発し,検証する.
- SAPを発症するリスクのある初期OFのないAP患者さんを特定する.
主な方法:
- 将来的に維持されるAPデータベースを利用した.
- 変数選択のために多変数ロジスティック回帰,Boruta,LASSOを使用しました.
- ノモグラムを開発し,簡素化されたACRスコアを導き出した.
主要な成果:
- 最初のOFのない3,813人のAP患者の12.0%がSAPに進行した.
- ACRスコアは強力な予測性能 (AUC 0.827) を示し,APACHE II,SIRS,BISAPを上回った.
- 低リスク,中リスク,高リスクのグループに分けると,SAPの発生率が著しく増加した (2.9%,16.5%,52.1%).
結論:
- ACRスコアは,初期OFのないAP患者のSAP進行リスクを効果的に分層化します.
- 簡単にアクセスできる6つの臨床パラメータを含む.
- 高リスク患者の早期発見を容易にする.
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