Development and validation of a prognostic model for death 30 days after adult emergency laparotomy

医学 剖腹手术 一致性 急诊医学 死亡率 队列 布里氏评分 急诊科 外科 普通外科 内科学 计算机科学 精神科 人工智能
作者
N Eugene,Angela Kuryba,Peter Martin,Charles M. Oliver,Michael Berry,Iain Moppett,John P. Greenwood,Sarah Hare,Sonia Lockwood,Dave Murray,Kate Walker,David Cromwell
出处
期刊:Anaesthesia [Wiley]
卷期号:78 (10): 1262-1271 被引量:6
标识
DOI:10.1111/anae.16096
摘要

The probability of death after emergency laparotomy varies greatly between patients. Accurate pre-operative risk prediction is fundamental to planning care and improving outcomes. We aimed to develop a model limited to a few pre-operative factors that performed well irrespective of surgical indication: obstruction; sepsis; ischaemia; bleeding; and other. We derived a model with data from the National Emergency Laparotomy Audit for patients who had emergency laparotomy between December 2016 and November 2018. We tested the model on patients who underwent emergency laparotomy between December 2018 and November 2019. There were 4077/40,816 (10%) deaths 30 days after surgery in the derivation cohort. The final model had 13 pre-operative variables: surgical indication; age; blood pressure; heart rate; respiratory history; urgency; biochemical markers; anticipated malignancy; anticipated peritoneal soiling; and ASA physical status. The predicted mortality probability deciles ranged from 0.1% to 47%. There were 1888/11,187 deaths in the test cohort. The scaled Brier score, integrated calibration index and concordance for the model were 20%, 0.006 and 0.86, respectively. Model metrics were similar for the five surgical indications. In conclusion, we think that this prognostic model is suitable to support decision-making before emergency laparotomy as well as for risk adjustment for comparing organisations.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
王子睿发布了新的文献求助10
2秒前
ZRZR发布了新的文献求助10
2秒前
小汤完成签到 ,获得积分10
2秒前
张睿发布了新的文献求助10
3秒前
茯苓发布了新的文献求助10
4秒前
long完成签到,获得积分10
5秒前
shinn完成签到,获得积分10
5秒前
铁甲小宝完成签到,获得积分10
5秒前
想人陪的飞薇完成签到 ,获得积分10
7秒前
呆萌斩完成签到,获得积分20
8秒前
许诺完成签到,获得积分20
10秒前
去你丫的随机昵称完成签到 ,获得积分10
11秒前
科研通AI6.1应助阿坤采纳,获得10
12秒前
www完成签到,获得积分10
15秒前
英俊的铭应助wjq采纳,获得10
17秒前
李健的小迷弟应助王子睿采纳,获得30
18秒前
19秒前
zhuboujs完成签到,获得积分10
21秒前
科研通AI6.3应助阿坤采纳,获得10
23秒前
隐形曼青应助ccxr采纳,获得10
23秒前
yangya完成签到,获得积分10
24秒前
WZH发布了新的文献求助10
26秒前
26秒前
26秒前
熙原完成签到,获得积分10
27秒前
28秒前
科研通AI6.2应助张睿采纳,获得10
30秒前
禹宛白发布了新的文献求助10
31秒前
哈哈完成签到 ,获得积分10
31秒前
wjq发布了新的文献求助10
32秒前
WZH完成签到,获得积分10
32秒前
崔松岩完成签到,获得积分10
36秒前
dingdingdingding完成签到,获得积分10
36秒前
烟花应助dxk采纳,获得10
37秒前
打打应助阿坤采纳,获得10
38秒前
39秒前
hhh发布了新的文献求助20
39秒前
戴泽完成签到,获得积分10
39秒前
Akim应助斯文翠采纳,获得10
40秒前
41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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6353802
求助须知:如何正确求助?哪些是违规求助? 8168918
关于积分的说明 17194868
捐赠科研通 5410005
什么是DOI,文献DOI怎么找? 2863885
邀请新用户注册赠送积分活动 1841285
关于科研通互助平台的介绍 1689925