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!

Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction model

毛细支气管炎 医学 逻辑回归 儿科 心理干预 人口 呼吸系统 内科学 环境卫生 精神科
作者
Pekka Vartiainen,Sakari Jukarainen,Samuel Rhedin,Alexandra Prinz,Tuomo Hartonen,Andrius Vabalas,Essi Viippola,Rodosthenis S. Rodosthenous,Sara Koskelainen,Aoxing Liu,Cecilia Lundholm,Awad I. Smew,Emma Caffrey Osvald,Emmi Helle,Markus Perola,Catarina Almqvist,Santtu Heinonen,Andrea Ganna
出处
期刊:The Lancet Digital Health [Elsevier BV]
卷期号:5 (11): e821-e830 被引量:19
标识
DOI:10.1016/s2589-7500(23)00175-9
摘要

Novel immunisation methods against respiratory syncytial virus (RSV) are emerging, but knowledge of risk factors for severe RSV disease is insufficient for optimal targeting of interventions against them. Our aims were to identify predictors for RSV hospital admission from registry-based data and to develop and validate a clinical prediction model to guide RSV immunoprophylaxis for infants younger than 1 year.In this model development and validation study, we studied all infants born in Finland between June 1, 1997, and May 31, 2020, and in Sweden between June 1, 2006, and May 31, 2020, along with the data for their parents and siblings. Infants were excluded if they died or were admitted to hospital for RSV within the first 7 days of life. The outcome was hospital admission due to RSV bronchiolitis during the first year of life. The Finnish study population was divided into a development dataset (born between June 1, 1997, and May 31, 2017) and a temporal hold-out validation dataset (born between June 1, 2017, and May 31, 2020). The development dataset was used for predictor discovery and selection in which we screened 1511 candidate predictors from the infants', parents', and siblings' data, and developed a logistic regression model with the 16 most important predictors. This model was then validated using the Finnish hold-out validation dataset and the Swedish dataset.In total, there were 1 124 561 infants in the Finnish development dataset, 130 352 infants in the Finnish hold-out validation dataset, and 1 459 472 infants in the Swedish dataset. In addition to known predictors such as severe congenital heart defects (adjusted odds ratio 2·89, 95% CI 2·28-3·65), we confirmed some less established predictors for RSV hospital admission, most notably oesophageal malformations (3·11, 1·86-5·19) and lower complexity congenital heart defects (1·43, 1·25-1·63). The prediction model's C-statistic was 0·766 (95% CI 0·742-0·789) in Finnish data and 0·737 (0·710-0·762) in Swedish validation data. The infants in the highest decile of predicted RSV hospital admission probability had 4·5 times higher observed risk compared with others. Calibration varied according to epidemic intensity. The model's performance was similar to a machine learning (XGboost) model using all 1511 candidate predictors (C-statistic in Finland 0·771, 95% CI 0·754-0·788). The prediction model showed clinical utility in decision curve analysis and in hypothetical number needed to treat calculations for immunisation, and its C-statistic was similar across different strata of parental income.The identified predictors and the prediction model can be used in guiding RSV immunoprophylaxis in infants, or as a basis for further immunoprophylaxis targeting tools.Sigrid Jusélius Foundation, European Research Council, Pediatric Research Foundation, and Academy of Finland.
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
27秒前
30秒前
标致荔枝发布了新的文献求助10
30秒前
45秒前
量子星尘发布了新的文献求助150
45秒前
54秒前
紫色的土豆完成签到,获得积分10
56秒前
黄小渣发布了新的文献求助10
57秒前
黄小渣完成签到,获得积分10
1分钟前
zxx完成签到 ,获得积分10
1分钟前
汉堡包应助伯赏元彤采纳,获得10
1分钟前
机灵的衬衫完成签到 ,获得积分10
1分钟前
我是老大应助hky采纳,获得10
1分钟前
1分钟前
冰渊悬月完成签到,获得积分10
1分钟前
上官若男应助liang采纳,获得10
1分钟前
Ruri发布了新的文献求助10
1分钟前
GongSyi完成签到 ,获得积分10
1分钟前
2分钟前
2分钟前
StonesKing发布了新的文献求助10
2分钟前
liang发布了新的文献求助10
2分钟前
2分钟前
hky发布了新的文献求助10
2分钟前
liang完成签到,获得积分10
2分钟前
2分钟前
StonesKing完成签到,获得积分10
2分钟前
Orange应助lf采纳,获得10
2分钟前
hky完成签到,获得积分10
2分钟前
量子星尘发布了新的文献求助10
2分钟前
2分钟前
lf发布了新的文献求助10
2分钟前
2分钟前
2分钟前
文文课堂发布了新的文献求助10
2分钟前
秀丽松思完成签到 ,获得积分10
3分钟前
3分钟前
为神指路发布了新的文献求助10
3分钟前
3分钟前
葛力发布了新的文献求助10
3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 3976649
求助须知:如何正确求助?哪些是违规求助? 3520749
关于积分的说明 11204693
捐赠科研通 3257497
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 806629