1 Projecting outcomes in respiratory technology-dependent children after serious illness (Project ORCAS)

Objectives/Goals: Children with chronic respiratory technology needs (CRTN) are becoming a dominant patient group in pediatric intensive care units (ICUs). However, little is known about patient-level, long-term outcomes in this population. The lack of such knowledge may lead to inadequate ICU therapies, interventions, or follow-up care. Methods/Study Population: This project will deploy a set of ecological momentary assessment (EMA) modules measuring real-time functioning as well as standardized instruments to measure child and family outcomes including health care utilization, physical functioning, and health-related quality of life following pediatric critical illness in children with CRTN. EMA has particular strength in assessing conditions where individual-level characteristics vary over time, as after critical illness. EMA’s recurrent measurements allow for evaluation of the variables’ temporal course and limit the potential for bias associated with recall surveys. Pulmonary function in children with CRTN in this study will be monitored over time using standardized pulmonary metrics and information from home respiratory machines. Results/Anticipated Results: This work tests the central hypothesis that long-term functional outcomes in children with CRTN are predicted by multimodal data obtained during and shortly after critical illness. To date, 17 families (of a planned 70) have been enrolled. Adherence to EMA modules is high, with 80% completion. Following serial data collection at 3, 6, and 9 months after hospital discharge, phenotypes of recovery (including improvement, stability, or deterioration) will be described. This will include 1) describing the patient demographic and clinical features associated with each long-term outcome trajectory and 2) identifying subgroups with similar outcome trajectories using patient demographics, features of the clinical illness, and EMA data using both traditional biostatistical and causal analysis techniques. Discussion/Significance of Impact: This project will provide important insights into the long-term outcomes following critical illness of children with CRTN while utilizing an innovative methodology. This proposal will provide the necessary information to drive future clinical trials assessing potential interventions at a number of different points to improve outcomes.

Authors

Institutions

Publication Details

Journal
Journal of Clinical and Translational Science
Published
2025-03-25
DOI
https://doi.org/10.1017/cts.2024.695
Primary Topic
Respiratory Support and Mechanisms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

1 Projecting outcomes in respiratory technology-dependent children after serious illness (Project ORCAS)

Samuel Goldfarb, Scott J. Crow, Julia A. Heneghan, Sisi Ma et al.
Journal of Clinical and Translational Science
Respiratory Support and Mechanisms
article

1 Projecting outcomes in respiratory technology-dependent children after serious illness (Project ORCAS)

Samuel Goldfarb, Scott J. Crow, Julia A. Heneghan, Sisi Ma, Elizabeth K. Marsh, Marie E. Steiner
article en

Abstract

Objectives/Goals: Children with chronic respiratory technology needs (CRTN) are becoming a dominant patient group in pediatric intensive care units (ICUs). However, little is known about patient-level, long-term outcomes in this population. The lack of such knowledge may lead to inadequate ICU therapies, interventions, or follow-up care. Methods/Study Population: This project will deploy a set of ecological momentary assessment (EMA) modules measuring real-time functioning as well as standardized instruments to measure child and family outcomes including health care utilization, physical functioning, and health-related quality of life following pediatric critical illness in children with CRTN. EMA has particular strength in assessing conditions where individual-level characteristics vary over time, as after critical illness. EMA’s recurrent measurements allow for evaluation of the variables’ temporal course and limit the potential for bias associated with recall surveys. Pulmonary function in children with CRTN in this study will be monitored over time using standardized pulmonary metrics and information from home respiratory machines. Results/Anticipated Results: This work tests the central hypothesis that long-term functional outcomes in children with CRTN are predicted by multimodal data obtained during and shortly after critical illness. To date, 17 families (of a planned 70) have been enrolled. Adherence to EMA modules is high, with 80% completion. Following serial data collection at 3, 6, and 9 months after hospital discharge, phenotypes of recovery (including improvement, stability, or deterioration) will be described. This will include 1) describing the patient demographic and clinical features associated with each long-term outcome trajectory and 2) identifying subgroups with similar outcome trajectories using patient demographics, features of the clinical illness, and EMA data using both traditional biostatistical and causal analysis techniques. Discussion/Significance of Impact: This project will provide important insights into the long-term outcomes following critical illness of children with CRTN while utilizing an innovative methodology. This proposal will provide the necessary information to drive future clinical trials assessing potential interventions at a number of different points to improve outcomes.

Journal of Clinical and Translational ScienceVol. 9(s1)
University of Minnesota (US), University of Minnesota System (US), Hospices Civils de Lyon (FR)
Openalex Percentile: Top 91%
Respiratory Support and Mechanisms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.