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Record W3109856917 · doi:10.3389/fneur.2020.596526

Early Supported Discharge for Neurorehabilitation Following Acquired Brain Injury

2020· article· en· W3109856917 on OpenAlexaffabout
Regan King, Trevor Seeger, Meng Wang, Rodney Li Pi Shan, Christine McGovern, Jason Knox, Lisa Vinodbhai Patel, Tak Fung, Tolulope T. Sajobi, Chantel T. Debert

Bibliographic record

VenueFrontiers in Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsRehabilitationNeurorehabilitationPhysical therapyMedicineRating scaleMontreal Cognitive AssessmentPhysical medicine and rehabilitationPsychologyCognitionCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Early Supported Discharge (ESD) is a clinical flow management service offering interdisciplinary rehabilitation, wherein patients are provided supported in-home rehabilitation treatment; in comparison to conventional hospital-based rehabilitation model of service delivery. There has been little research into the functional outcomes for other types of acquired brain injury (ABI). Methods: In this prospective cohort study, ABI patients presenting at a level I trauma center in Calgary, Canada were placed in either an ESD program or conventional inpatient rehabilitation (IPR) program based on their medical history and presentation. A small number of patients completed both programs (ESD+IPR group). ESD therapies were designed to emulate IPR. Participants completed professionally-rated Mayo-Portland Adaptability Index-4 (MPAI), Quality of Life after Brain Injury (QOLIBRI), Generalized Anxiety Questionnaire-7 (GAD7), Montreal Cognitive Assessment (MoCA), and Patient Health Questionnaire-9 (PHQ9) surveys at 1, 3, and 6 months following initial assessment pre-rehabilitation. Caregivers completed the Zarit Burden Interview (ZBI) at the same time points. The Supervision Rating Scale (SRS) and Disability Rating Scale (DRS) were completed at admission to rehabilitation and all follow-ups. Generalized estimate equations models were used to describe the three groups over time, including age as a covariate. Results: Significant effects of time were reported in the MPAI participant sub-score in the ESD and IPR groups ( χ(2)2 = 42.429, p < 0.000; χ(2)2 = 9.773, p = 0.008), showing significantly higher scores between 1 and 3 month timepoints for both groups. ZBI scores were significantly lower in the ESD group at 1 month compared to 3 and 6 months ( χ(2)2 = 31.252, p < 0.001). The proportion of patients with medical complications during rehabilitation was 25.3% in ESD compared to 74.7% patients in IPR. Conclusions: Improvements in functional outcomes were evident in patients participating in ESD and IPR, with more medical complications reported in the IPR group. Caregiver burden lessened over time in the ESD group but not in the IPR group. Both ESD and ESD+IPR groups can be considered viable alternatives to traditional inpatient rehabilitation. A randomized control trial would be required to properly compare rehabilitation streams. Further investigation into affective and lifestyle elements of ABI recovery would also improve our understanding of targeted neurorehabilitation in this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.325
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations9
Published2020
Admission routes2
Has abstractyes

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