Landa Rebecca J, Reetzke Rachel, Holingue Calliope B, Herman Dana, Hess Christine Reiner
Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, United States.
Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Front Psychiatry. 2022 Mar 15;13:805686. doi: 10.3389/fpsyt.2022.805686. eCollection 2022.
Given the importance of early detection, it is critical to understand the non-linearity in manifestation of ASD before age 24 months, when ASD symptoms are beginning to consolidate, through the age of 36 months when stability of ASD diagnosis is reportedly high into school-age when increased demands may challenge previously successful compensatory processes and permit first ASD detection. We employed a prospective, longitudinal design focused on children with an older sibling with ASD ( = 210) who received diagnostic evaluations at mean ages of 15.4 months (Time 1), 36.6 months (Time 2), and 5.7 years (Time 3) to examine: (1) diagnostic stability, (2) developmental trajectories associated with different patterns of ASD vs. non-ASD classifications, and (3) predictors of classification group over time. Clinical best estimate (CBE) diagnosis of ASD or non-ASD was made at each time point. Linear mixed-effects models were implemented to examine differences in developmental trajectories of stable and dynamic diagnostic groups. Multinomial logistic regression analyses were used to examine predictors of the likelihood of belonging to each CBE diagnostic classification group. Results revealed that sensitivity and stability of an ASD diagnosis significantly increased from Time 1 (sensitivity: 52%; stability: 63%) to Time 2 (sensitivity: 86%; stability: 68%). Different developmental trajectories of autism symptom severity and non-verbal and verbal IQ were observed across groups, with differences first observed at Time 1 and becoming more pronounced through Time 3. Presence of restricted and repetitive behaviors as well as limitations in initiation of joint attention and expressive language skills differentially predicted the likelihood of belonging to the different CBE diagnostic classification groups. Results suggest that ASD symptoms may emerge or attenuate over time, with some children meeting diagnosis at follow-up, and other children no longer meeting diagnostic criteria. From a systems perspective, diagnostic non-linearity may be viewed as a dynamic developmental process, where emergent properties arising from various biological, genetic, and experiential factors interact, culminating in phenotypic phenomena that change over time. Clinical implications include extending universal ASD and social communication screening into school-age, supporting families' understanding of diagnostic shifts, and ensuring unbiased diagnostic decision-making when following children with ASD.
鉴于早期发现的重要性,关键在于了解24个月前(此时自闭症谱系障碍(ASD)症状开始巩固)至36个月(据报道此时ASD诊断的稳定性较高)直至学龄期(此时增加的需求可能会挑战先前成功的代偿过程并首次实现ASD检测)ASD表现中的非线性情况。我们采用了前瞻性纵向设计,聚焦于有一个患ASD哥哥或姐姐的儿童(n = 210),他们在平均年龄15.4个月(时间1)、36.6个月(时间2)和5.7岁(时间3)接受了诊断评估,以研究:(1)诊断稳定性;(2)与ASD和非ASD不同分类模式相关的发育轨迹;(3)随时间变化的分类组预测因素。在每个时间点进行ASD或非ASD的临床最佳估计(CBE)诊断。采用线性混合效应模型来检验稳定和动态诊断组发育轨迹的差异。使用多项逻辑回归分析来检验属于每个CBE诊断分类组可能性的预测因素。结果显示,ASD诊断的敏感性和稳定性从时间1(敏感性:52%;稳定性:63%)到时间2(敏感性:86%;稳定性:68%)显著增加。各群体间观察到自闭症症状严重程度、非言语和言语智商的不同发育轨迹,差异首先在时间1观察到,并在时间3变得更加明显。存在受限和重复行为以及联合注意发起和表达语言技能的局限分别预测了属于不同CBE诊断分类组的可能性。结果表明,ASD症状可能随时间出现或减轻,一些儿童在随访时符合诊断,而其他儿童不再符合诊断标准。从系统角度来看,诊断非线性可被视为一个动态发育过程,其中各种生物、遗传和经验因素产生的新兴特性相互作用,最终导致随时间变化的表型现象。临床意义包括将普遍的ASD和社会沟通筛查扩展到学龄期,支持家庭对诊断变化的理解,并确保在跟踪ASD儿童时进行无偏倚的诊断决策。