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Published on: January 30, 2018
Individualized Prognostic Prediction of the Long-Term Functional Trajectory in Pediatric Acquired Brain Injury
Erika Molteni1, Marta Bianca Maria Ranzini1, Elena Beretta2
1School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Insights
This study identified four distinct recovery trajectories in pediatric acquired brain injury patients undergoing rehabilitation. Early prediction of these trajectories at first discharge can guide treatment decisions and improve long-term outcome prediction.
Area of Science:
- Neuroscience
- Rehabilitation Medicine
- Pediatric Neurology
Background:
- Heterogeneity in functional recovery after pediatric acquired brain injury (ABI) complicates medical decision-making and outcome prediction.
- Standardized rehabilitation programs are crucial, but individual responses vary significantly.
- Early identification of recovery patterns is needed to optimize patient management.
Purpose of the Study:
- To identify distinct patient subgroups with similar functional recovery trajectories following pediatric ABI.
- To develop a method for early prediction of long-term recovery courses based on initial clinical status post-discharge.
Main Methods:
- Latent class modeling was used to classify functional trajectories of 600 pediatric ABI patients over 7 years.
- Functional Independent Measure (FIM) scores were collected annually.
- A predictive model was developed to forecast trajectory membership using data from first discharge.
Main Results:
- Four distinct recovery trajectories were identified: high-start fast (N=92), low-start fast (N=168), slow (N=130), and non-responders (N=210).
- Fast responders were older and had shorter coma durations than non-responders.
- Early prediction of trajectory membership at first discharge achieved high accuracy (0.80).
Conclusions:
- Patient stratification based on recovery evolution following a specific rehabilitation program is feasible.
- Early prediction of long-term recovery trajectories is possible using data available at first discharge.
- This approach aids in identifying slow responders who, despite initial poor gains, achieve comparable long-term recovery to fast responders.
Abstract:
In pediatric acquired brain injury, heterogeneity of functional response to specific rehabilitation treatments is a key confound to medical decisions and outcome prediction. We aimed to identify patient subgroups sharing comparable trajectories, and to implement a method for the early prediction of the long-term recovery course from clinical condition at first discharge. 600 consecutive patients with acquired brain injury (7.4 years ± 5.2; 367 males; median GCS = 6) entered a standardized rehabilitation program. Functional Independent Measure scores were measured yearly, until year 7. We classified the functional trajectories in clusters, through a latent class model. We performed single-subject prediction of trajectory membership in cases unseen during model fitting. Four trajectory types were identified (post.prob. > 0.95): high-start fast (N = 92), low-start fast (N = 168), slow (N = 130) and non-responders (N = 210). Fast responders were older (chigh = 1.8; clow = 1.1) than non-responders and suffered shorter coma (chigh = -14.7; clow = -4.3). High-start fast-responders had shorter length of stay (c = -1.6), and slow responders had lower incidence of epilepsy (c = -1.4), than non-responders (p < 0.001). Single-subject trajectory could be predicted with high accuracy at first discharge (accuracy = 0.80). In conclusion, we stratified patients based on the evolution of their response to a specific treatment program. Data at first discharge predicted the response over 7 years. This method enables early detection of the slow responders, who show poor post-acute functional gains, but achieve recovery comparable to fast responders by year 7. Further external validation in other rehabilitation programs is warranted.
