Individualized prognostic prediction of the long-term functional trajectory in pediatric acquired brain injury

Erika Molteni, Marta Bianca Maria Ranzini, Elena Beretta, Marc Modat, Sandra Strazzer

Research output: Contribution to journalArticlepeer-review


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 stan-dardized 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.

Original languageEnglish
Article number675
Number of pages13
JournalJournal of Personalized Medicine
Issue number7
Publication statusPublished - Jul 2021


  • Acquired brain injury (ABI)
  • Functional Independence Measure for children (WeeFIM)
  • Latent class analysis
  • Mixed models
  • Single-subject recovery prediction
  • Structural equation modelling (SEM)
  • Trajectory prediction

ASJC Scopus subject areas

  • Medicine (miscellaneous)


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