亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Using a national surgical database to predict complications following posterior lumbar surgery and comparing the area under the curve and F1-score for the assessment of prognostic capability

医学 接收机工作特性 逻辑回归 外科 腰椎 曲线下面积 队列 回顾性队列研究 内科学
作者
Zachary DeVries,Eric Locke,Mohamad Hoda,Dita Moravek,Kim Phan,Alexandra Stratton,Stephen Kingwell,Eugene K. Wai,Philippe Phan
出处
期刊:The Spine Journal [Elsevier BV]
卷期号:21 (7): 1135-1142 被引量:67
标识
DOI:10.1016/j.spinee.2021.02.007
摘要

Abstract BACKGROUND With spinal surgery rates increasing in North America, models that are able to accurately predict which patients are at greater risk of developing complications are highly warranted. However, the previously published methods which have used large, multi-centre databases to develop their prediction models have relied on the receiver operator characteristics curve with the associated area under the curve (AUC) to assess their model's performance. Recently, it has been found that a precision-recall curve with the associated F1-score could provide a more realistic analysis for these models. PURPOSE To develop a logistic regression (LR) model for the prediction of complications following posterior lumbar spine surgery and to then assess for any difference in performance of the model when using the AUC versus the F1-score. STUDY DESIGN Retrospective review of a prospective cohort. PATIENT SAMPLE The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) registry was used. All patients that underwent posterior lumbar spine surgery between 2005 to 2016 with appropriate data were included. OUTCOME MEASURES Both the AUC and F1-score were utilized to assess the prognostic performance of the prediction model. METHODS In order to develop the LR model used to predict a complication during or following spine surgery, 19 variables were selected by three orthopedic spine surgeons from the NSQIP registry. Two datasets were developed for this analysis: (1) an imbalanced dataset, which was taken directly from the NSQIP registry, and (2) a down-sampled set. The purpose of the down-sampled set was to balance the data in order to evaluate whether balancing the data had an effect on model performance. The AUC and F1-score were applied to both of these datasets. RESULTS Within the NSQIP database, 52,787 spine surgery cases were identified of which only 10% of these cases had complications during surgery. Applying the LR model showed a large difference between the AUC (0.69) and the F1 score (0.075) on the imbalanced dataset. However, no major differences existed between the AUC and F1-score when the data was balanced and the LR model was reapplied (0.69 and 0.62, AUC and F1-score, respectively). CONCLUSIONS The F1-score detected a drastically lower performance for the prediction of complications when using the imbalanced data, but detected a performance similar to the AUC level when balancing techniques were utilized for the dataset. This difference is due to a low precision score when many false positive classifications are present, which is not identified when using the AUC value. This lowers the utility of the AUC score, as many of the datasets used in medicine are imbalanced. Therefore, we recommend using the F1-score on large, prospective databases when the data is imbalanced with a large amount of true negative classifications.
最长约 10秒,即可获得该文献文件

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
量子星尘发布了新的文献求助10
9秒前
12秒前
taiwenshuo完成签到,获得积分20
12秒前
优美若雁完成签到,获得积分10
17秒前
cossen完成签到,获得积分10
29秒前
堪归完成签到 ,获得积分10
29秒前
艾米发布了新的文献求助10
33秒前
科研通AI2S应助科研通管家采纳,获得10
39秒前
reeedirect应助科研通管家采纳,获得10
39秒前
酷波er应助科研通管家采纳,获得10
39秒前
42秒前
心若向阳发布了新的文献求助10
47秒前
CipherSage应助鲁丁丁采纳,获得10
51秒前
58秒前
handsomezzg完成签到,获得积分10
59秒前
艾米完成签到,获得积分10
1分钟前
Sunny完成签到 ,获得积分10
1分钟前
艾米发布了新的文献求助10
1分钟前
1分钟前
集典完成签到 ,获得积分10
1分钟前
Ultraman45发布了新的文献求助10
1分钟前
Ultraman45发布了新的文献求助10
1分钟前
1分钟前
量子星尘发布了新的文献求助10
1分钟前
1分钟前
Ultraman45完成签到,获得积分10
1分钟前
NexusExplorer应助江洋大盗采纳,获得10
1分钟前
meow完成签到 ,获得积分10
1分钟前
情怀应助lf采纳,获得10
1分钟前
1分钟前
1分钟前
hta_chen完成签到,获得积分10
1分钟前
lf发布了新的文献求助10
1分钟前
hta_chen发布了新的文献求助10
1分钟前
1分钟前
Zhy发布了新的文献求助10
2分钟前
李健的小迷弟应助He采纳,获得20
2分钟前
繁荣的青旋完成签到,获得积分10
2分钟前
2分钟前
2分钟前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 700
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
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 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3976619
求助须知:如何正确求助?哪些是违规求助? 3520720
关于积分的说明 11204567
捐赠科研通 3257359
什么是DOI,文献DOI怎么找? 1798716
邀请新用户注册赠送积分活动 877897
科研通“疑难数据库(出版商)”最低求助积分说明 806613