{"doi":"10.1001/jamanetworkopen.2022.22249","title":"Analysis of Neonatal Neurobehavior and Developmental Outcomes Among Preterm Infants","abstract":"Importance: The ability to identify poor outcomes and treatable risk factors among very preterm infants remains challenging; improving early risk detection and intervention targets to potentially address developmental and behavioral delays is needed. Objective: To determine associations between neonatal neurobehavior using the Neonatal Intensive Care Unit (NICU) Network Neurobehavioral Scale (NNNS), neonatal medical risk, and 2-year outcomes. Design, Setting, and Participants: This multicenter cohort enrolled infants born at less than 30 weeks' gestation at 9 US university-affiliated NICUs. Enrollment was conducted from April 2014 to June 2016 with 2-year adjusted age follow-up assessment. Data were analyzed from December 2019 to January 2022. Exposures: Adverse medical and psychosocial conditions; neurobehavior. Main Outcomes and Measures: Bayley Scales of Infant and Toddler Development, third edition (Bayley-III), cognitive, language, and motor scores of less than 85 and Child Behavior Checklist (CBCL) T scores greater than 63. NNNS examinations were completed the week of NICU discharge, and 6 profiles of neurobehavior were identified by latent profile analysis. Generalized estimating equations tested associations among NNNS profiles, neonatal medical risk, and 2-year outcomes while adjusting for site, maternal socioeconomic and demographic factors, maternal psychopathology, and infant sex. Results: A total of 679 enrolled infants had medical and NNNS data; 2-year follow-up data were available for 479 mothers and 556 infants (mean [SD] postmenstrual age at birth, 27.0 [1.9] weeks; 255 [45.9%] female). Overall, 268 mothers (55.9%) were of minority race and ethnicity, and 127 (26.6%) lived in single-parent households. The most common neonatal medical morbidity was BPD (287 [51.7%]). Two NNNS behavior profiles, including 157 infants, were considered high behavioral risk. Infants with at least 2 medical morbidities (n = 123) were considered high medical risk. Infants with high behavioral and high medical risk were 4 times more likely to have Bayley-III motor scores less than 85 compared with those with low behavioral and low medical risk (adjusted relative risk [aRR], 4.1; 95% CI, 2.9-5.1). Infants with high behavioral and high medical risk also had increased risk for cognitive scores less than 85 (aRR, 2.7; 95% CI, 1.8-3.4). Only infants with high behavioral and low medical risk were in the clinical range for CBCL internalizing and total problem scores (internalizing: aRR, 2.3; 95% CI, 1.1-4.5; total: aRR, 2.5; 95% CI, 1.2-4.4). Conclusions and Relevance: In this study, high-risk neonatal neurobehavioral patterns at NICU discharge were associated with adverse cognitive, motor, and behavioral outcomes at 2 years. Used in conjunction with medical risk, neonatal neurobehavioral assessments could enhance identification of infants at highest risk for delay and offer opportunities to provide early, targeted therapies.","journal":"JAMA Network Open","year":2022,"id":236417,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":69,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9523,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":354352,"name":"Julie A. Hofheimer","orcid":"0000-0003-3233-1480","position":1,"is_corresponding":false},{"id":275849,"name":"T. Michael O’Shea","orcid":"0000-0001-6692-911X","position":2,"is_corresponding":false},{"id":501303,"name":"Howard W. Kilbride","orcid":"0000-0002-3433-1444","position":3,"is_corresponding":false},{"id":354351,"name":"Brian S. Carter","orcid":"0000-0003-0539-9164","position":4,"is_corresponding":false},{"id":695366,"name":"Jennifer Check","orcid":"0000-0002-6340-5334","position":5,"is_corresponding":false},{"id":355030,"name":"Jennifer Helderman","orcid":null,"position":6,"is_corresponding":false},{"id":355032,"name":"Charles R. Neal","orcid":null,"position":7,"is_corresponding":false},{"id":478245,"name":"Steve Pastyrnak","orcid":null,"position":8,"is_corresponding":false},{"id":354354,"name":"Lynne M. Smith","orcid":"0000-0002-3086-9167","position":9,"is_corresponding":false},{"id":309160,"name":"Marie Camerota","orcid":"0000-0001-8293-6467","position":10,"is_corresponding":false},{"id":355034,"name":"Lynne M. Dansereau","orcid":null,"position":11,"is_corresponding":false},{"id":478246,"name":"Sheri A. Della Grotta","orcid":null,"position":12,"is_corresponding":false},{"id":355035,"name":"Barry M. Lester","orcid":null,"position":13,"is_corresponding":false},{"id":355031,"name":"Elisabeth C. McGowan","orcid":null,"position":0,"is_corresponding":true}],"reference_count":59,"raw_metadata":null,"created_at":"2026-07-19T00:21:58.728756Z","pmid":"35849396","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}