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Record W2888674037 · doi:10.1080/09593985.2018.1510450

Personalized adapted locomotor training for an individual with sequelae of West Nile virus infection: a mixed-method case report

2018· article· en· W2888674037 on OpenAlexafffund
Janelle Unger, Hope Jervis-Rademeyer, Julio C. Furlan, Clara Pujol-Fuentes, Jaclyn Dawe, Kristin E. Musselman

Bibliographic record

VenuePhysiotherapy Theory and Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversity of SaskatchewanToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersOntario Neurotrauma Foundation
KeywordsParaplegiaRehabilitationMedicinePhysical medicine and rehabilitationPhysical therapyTetraplegiaTreadmillPsychologySpinal cord injurySpinal cordPsychiatry

Abstract

fetched live from OpenAlex

Background West Nile virus (WNV) can have severe consequences, including encephalitis and paralysis. Purpose: To describe the benefits of intensive locomotor training (LT) for an individual with a previous WNV infection resulting in chronic paraplegia. Case Description: The patient, who became a wheelchair user following standard rehabilitation, began LT 3 years post infection. Her goals included standing and walking with an assistive device and transferring independently. The intervention consisted of bodyweight-supported treadmill training and overground training, which involved walking, balancing, strengthening, and transferring activities. Outcomes: Following 5 months of LT, the patient ambulated independently with a walker at a speed = 0.34m/s. She walked 110.1 metres in 6 minutes and increased her Berg Balance Scale score by 17 points. These improvements were either maintained or further increased 3 months post LT. The patient’s perspectives on LT were collected through a semi-structured interview. A conventional content analysis, which uses data to drive themes, revealed three themes: (1) recalibrating goals, (2) outcomes (i.e. physical and psychological benefits, such as a sense of accomplishment), and (3) challenges of LT and effective coping strategies. Conclusions: The patient demonstrated improved balance and walking abilities. Intensive LT was feasible and effective for this individual with chronic paraplegia due to WNV infection.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.406
Teacher spread0.359 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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".

Quick stats

Citations2
Published2018
Admission routes2
Has abstractyes

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