Accuracy of conventional and novel scoring systems in predicting severity and outcomes of acute pancreatitis: a retrospective study

急性胰腺炎 医学 接收机工作特性 逻辑回归 计分系统 内科学 疾病严重程度 胰腺炎 急性呼吸窘迫 回顾性队列研究 重症监护医学
作者
Qing Wu,Jie Wang,Mengbin Qin,Huiying Yang,Zhihai Liang,Guodu Tang
出处
期刊:Lipids in Health and Disease [Springer Nature]
卷期号:20 (1): 41-41 被引量:23
标识
DOI:10.1186/s12944-021-01470-4
摘要

Abstract Background Recently, several novel scoring systems have been developed to evaluate the severity and outcomes of acute pancreatitis. This study aimed to compare the effectiveness of novel and conventional scoring systems in predicting the severity and outcomes of acute pancreatitis. Methods Patients treated between January 2003 and August 2020 were reviewed. The Ranson score (RS), Glasgow score (GS), bedside index of severity in acute pancreatitis (BISAP), pancreatic activity scoring system (PASS), and Chinese simple scoring system (CSSS) were determined within 48 h after admission. Multivariate logistic regression was used for severity, mortality, and organ failure prediction. Optimum cutoffs were identified using receiver operating characteristic curve analysis. Results A total of 1848 patients were included. The areas under the curve (AUCs) of RS, GS, BISAP, PASS, and CSSS for severity prediction were 0.861, 0.865, 0.829, 0.778, and 0.816, respectively. The corresponding AUCs for mortality prediction were 0.693, 0.736, 0.789, 0.858, and 0.759. The corresponding AUCs for acute respiratory distress syndrome prediction were 0.745, 0.784, 0.834, 0.936, and 0.820. Finally, the corresponding AUCs for acute renal failure prediction were 0.707, 0.734, 0.781, 0.868, and 0.816. Conclusions RS and GS predicted severity better than they predicted mortality and organ failure, while PASS predicted mortality and organ failure better. BISAP and CSSS performed equally well in severity and outcome predictions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ding应助YSH采纳,获得10
1秒前
英姑应助老登采纳,获得10
1秒前
Lico发布了新的文献求助20
1秒前
SciGPT应助bnuhbniuniu采纳,获得10
2秒前
2秒前
汪澳完成签到,获得积分10
2秒前
科研通AI6应助嘻嘻采纳,获得30
3秒前
Titter发布了新的文献求助10
3秒前
小佳同学完成签到 ,获得积分10
3秒前
淡定成风应助典雅的俊驰采纳,获得10
4秒前
4秒前
慈祥的博发布了新的文献求助10
5秒前
5秒前
5秒前
7秒前
7秒前
597发布了新的文献求助30
7秒前
8秒前
在水一方应助葳蕤采纳,获得10
9秒前
9秒前
9秒前
在水一方应助piaopiao采纳,获得10
9秒前
科研通AI2S应助hanyy采纳,获得10
9秒前
9秒前
dubo666发布了新的文献求助30
9秒前
边走边听发布了新的文献求助10
9秒前
bnuhbniuniu完成签到,获得积分10
9秒前
Jennifer发布了新的文献求助10
10秒前
DuFlank发布了新的文献求助30
11秒前
11秒前
hzt发布了新的文献求助10
11秒前
星辰大海应助沉醉采纳,获得10
11秒前
Hands完成签到,获得积分10
11秒前
12秒前
zlx0920完成签到 ,获得积分20
12秒前
小白发布了新的文献求助10
12秒前
椛柚完成签到 ,获得积分10
12秒前
Duan发布了新的文献求助10
13秒前
13秒前
笑点低的哈密瓜完成签到,获得积分10
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
《机器学习——数据表示学习及应用》 600
Holistic Discourse Analysis 600
Vertébrés continentaux du Crétacé supérieur de Provence (Sud-Est de la France) 600
Fiction e non fiction: storia, teorie e forme 500
Routledge Handbook on Spaces of Mental Health and Wellbeing 500
Elle ou lui ? Histoire des transsexuels en France 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5321673
求助须知:如何正确求助?哪些是违规求助? 4463315
关于积分的说明 13889726
捐赠科研通 4354469
什么是DOI,文献DOI怎么找? 2391781
邀请新用户注册赠送积分活动 1385392
关于科研通互助平台的介绍 1355144