Classification of Children and Adolescents With Avoidant/Restrictive Food Intake Disorder

医学 潜在类模型 食物摄入量 儿科 人口学 统计 内科学 数学 社会学
作者
Debra K. Katzman,Tim Guimond,Wendy Spettigue,Holly Agostino,Jennifer Couturier,Mark L. Norris
出处
期刊:Pediatrics [American Academy of Pediatrics]
卷期号:150 (3) 被引量:25
标识
DOI:10.1542/peds.2022-057494
摘要

BACKGROUND AND OBJECTIVES Evidence suggests that children and adolescents with avoidant/restrictive food intake disorder (ARFID) have heterogeneous clinical presentations. To use latent class analysis (LCA) and determine the frequency of various classes in pediatric patients with ARFID drawn from a 2-year surveillance study. METHODS Cases were ascertained using the Canadian Pediatric Surveillance Program methodology from January 1, 2016, to December 31, 2017. An exploratory LCA was undertaken with latent class models ranging from 1 to 5 classes. RESULTS Based on fit statistics and class interpretability, a 3-class model had the best fit: Acute Medical (AM), Lack of Appetite (LOA), and Sensory (S). The probability of being classified as AM, LOA, and S was 52%, 40.7%, and 6.9%, respectively. The AM class was distinct for increased likelihood of weight loss (92%), a shorter length of illness (<12 months) (66%), medical hospitalization (56%), and heart rate <60 beats per minute (31%). The LOA class was distinct for failure to gain weight (97%) and faltering growth (68%). The S class was distinct for avoiding certain foods (100%) and refusing to eat because of sensory characteristics of the food (100%). Using posterior probability assignments, a mixed group AM/LOA (n = 30; 14.5%) had characteristics of both AM and LOA classes. CONCLUSIONS This LCA suggests that ARFID is a heterogeneous diagnosis with 3 distinct classes corresponding to the 3 subtypes described in the literature: AM, LOA, and S. The AM/LOA group had a mixed clinical presentation. Clinicians need to be aware of these different ARFID presentations because clinical and treatment needs will vary.

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
1秒前
科研通AI6.1应助开花采纳,获得10
1秒前
linhappy发布了新的文献求助10
1秒前
量子星尘发布了新的文献求助10
2秒前
哼哼哒发布了新的文献求助10
2秒前
连lian发布了新的文献求助10
2秒前
4秒前
steelorange发布了新的文献求助10
4秒前
量子星尘发布了新的文献求助10
4秒前
JamesPei应助wzzf采纳,获得10
4秒前
5秒前
paul发布了新的文献求助10
6秒前
李健发布了新的文献求助10
6秒前
6秒前
咸鱼好翻身完成签到,获得积分20
6秒前
6秒前
7秒前
7秒前
研友_GZbjPZ完成签到,获得积分10
8秒前
collins发布了新的文献求助10
9秒前
9秒前
Zz发布了新的文献求助10
10秒前
10秒前
BJ_whc发布了新的文献求助30
10秒前
11秒前
科研通AI6.1应助冷酷雨泽采纳,获得30
12秒前
steelorange完成签到,获得积分10
12秒前
13秒前
哼哼哒完成签到,获得积分10
13秒前
13秒前
漾漾发布了新的文献求助10
14秒前
Lucas应助wangjun采纳,获得10
15秒前
77nic发布了新的文献求助30
16秒前
17秒前
Akim应助优秀醉易采纳,获得10
17秒前
17秒前
17秒前
lome发布了新的文献求助10
17秒前
wzzf发布了新的文献求助10
17秒前
18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
Encyclopedia of Forensic and Legal Medicine Third Edition 5000
Introduction to strong mixing conditions volume 1-3 5000
the Oxford Guide to the Bantu Languages 3000
Agyptische Geschichte der 21.30. Dynastie 3000
„Semitische Wissenschaften“? 1510
从k到英国情人 1500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5761878
求助须知:如何正确求助?哪些是违规求助? 5532710
关于积分的说明 15401214
捐赠科研通 4898111
什么是DOI,文献DOI怎么找? 2634724
邀请新用户注册赠送积分活动 1582875
关于科研通互助平台的介绍 1538103