LONG-HOSP评分：急性下消化道出血住院时间的新型预测评分 - 多中心全国性研究。
LONG-HOSP Score: A Novel Predictive Score for Length of Hospital Stay in Acute Lower Gastrointestinal Bleeding - A Multicenter Nationwide Study.
发表日期：2023 Aug 03
作者：
Minoru Fujita, Tomonori Aoki, Noriaki Manabe, Yoichiro Ito, Katsumasa Kobayashi, Atsushi Yamauchi, Atsuo Yamada, Jun Omori, Takashi Ikeya, Taiki Aoyama, Naoyuki Tominaga, Yoshinori Sato, Takaaki Kishino, Naoki Ishii, Tsunaki Sawada, Masaki Murata, Akinari Takao, Kazuhiro Mizukami, Ken Kinjo, Shunji Fujimori, Takahiro Uotani, Hiroki Sato, Sho Suzuki, Toshiaki Narasaka, Junnosuke Hayasaka, Tomohiro Funabiki, Yuzuru Kinjo, Akira Mizuki, Shu Kiyotoki, Tatsuya Mikami, Ryosuke Gushima, Hiroyuki Fujii, Yuta Fuyuno, Naohiko Gunji, Yosuke Toya, Kazuyuki Narimatsu, Koji Nagaike, Tetsu Kinjo, Yorinobu Sumida, Sadahiro Funakoshi, Kiyonori Kobayashi, Tamotsu Matsuhashi, Yuga Komaki, Kuniko Miki, Kazuhiro Watanabe, Maki Ayaki, Takahisa Murao, Mitsuhiko Suehiro, Akiko Shiotani, Jiro Hata, Ken Haruma, Mitsuru Kaise, Naoyoshi Nagata
来源：
Disease Models & Mechanisms
摘要：
住院时间（LOS）影响费用、患者生活质量和医院管理。然而，现有的适用于住院时期的胃肠道出血模型并未重点关注LOS。我们的目标是建立一种用于急性下消化道出血（ALGIB）的LOS预测模型。我们回顾性分析了49家医院（CODE BLUE-J研究）中8,547名急诊住院ALGIB患者的记录。通过使用7,107名患者的基线特征开发了一种预测住院时间延长的模型，并在1,440名患者中进行了外部验证。此外，多变量分析评估了住院期间附加变量对LOS的影响。我们以基线特征为重点，开发了一种预测住院时间延长的模型，即LONG-HOSP评分。该评分由低体质指数、实验室数据、高龄、不饮酒状态、非甾体抗炎药使用、医疗设施床位≥800张、心率、口服抗血栓药物使用、症状、收缩压、功能状态和既往病史组成。该评分在预测住院时间延长和高住院费用方面表现相对较好（曲线下面积：分别为派生0.70和0.73，外部验证0.66和0.71）。接下来，我们关注住院期间的管理。无论LONG-HOSP评分如何，结肠炎或结直肠癌的诊断、再出血以及需要输血、介入放射治疗和手术都会延长LOS。相反，早期结肠镜检查和内镜治疗会缩短LOS。在ALGIB的住院时期，我们的新型预测模型能够根据患者的住院时间延长风险对其进行分层。在住院期间，早期结肠镜检查和内镜治疗可以缩短住院时间。© 2023 The Author(s). Published by S. Karger AG, Basel.
Length of stay (LOS) in hospital affects cost, patient quality of life, and hospital management; however, existing gastrointestinal bleeding models applicable at hospital admission have not focused on LOS. We aimed to construct a predictive model for LOS in acute lower gastrointestinal bleeding (ALGIB).We retrospectively analyzed the records of 8,547 patients emergently hospitalized for ALGIB at 49 hospitals (the CODE BLUE-J Study). A predictive model for prolonged hospital stay was developed using the baseline characteristics of 7,107 patients and externally validated in 1,440 patients. Furthermore, a multivariate analysis assessed the impact of additional variables during hospitalization on LOS.Focusing on baseline characteristics, a predictive model for prolonged hospital stay was developed, the LONG-HOSP score, which consisted of low body mass index, laboratory data, old age, nondrinker status, nonsteroidal anti-inflammatory drug use, facility with ≥800 beds, heart rate, oral antithrombotic agent use, symptoms, systolic blood pressure, performance status, and past medical history. The score showed relatively high performance in predicting prolonged hospital stay and high hospitalization costs (area under the curve: 0.70 and 0.73 for derivation, respectively, and 0.66 and 0.71 for external validation, respectively). Next, we focused on in-hospital management. Diagnosis of colitis or colorectal cancer, rebleeding, and the need for blood transfusion, interventional radiology, and surgery prolonged LOS, regardless of the LONG-HOSP score. By contrast, early colonoscopy and endoscopic treatment shortened LOS.At hospital admission for ALGIB, our novel predictive model stratified patients by their risk of prolonged hospital stay. During hospitalization, early colonoscopy and endoscopic treatment shortened LOS.© 2023 The Author(s). Published by S. Karger AG, Basel.