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Enregistrement W3215753736 · doi:10.1101/2021.11.30.21265051

Segmental analysis in cervical spinal cord injury reveals the recovery potential of hand muscles with preserved corticospinal tract: Insights beyond impairment scales

2021· preprint· en· W3215753736 sur OpenAlexaff
Gustavo Balbinot, Guijin Li, Sukhvinder Kalsi‐Ryan, Rainer Abel, Doris Maier, Yorck-Bernhard Kalke, Norbert Weidner, Rüdiger Rupp, Martin Schubert, Armin Curt, José Zariffa

Notice bibliographique

RevuemedRxiv · 2021
Typepreprint
Langueen
DomaineMedicine
ThématiqueSpinal Cord Injury Research
Établissements canadiensUniversity of TorontoToronto Rehabilitation InstituteUniversity Health Network
Organismes subventionnairesWings for Life
Mots-clésCorticospinal tractPhysical medicine and rehabilitationSpinal cord injuryPyramidal tractsUpper motor neuronSpinal cordSomatosensory systemNeuroplasticityPsychologyNeuroscienceSomatosensory evoked potentialMedicineDiffusion MRIMagnetic resonance imagingAmyotrophic lateral sclerosis

Résumé

récupéré en direct d'OpenAlex

Abstract Cervical spinal cord injury (SCI) severely impacts widespread bodily functions with extensive impairments for individuals, who prioritize regaining hand function. Although prior work has focused on the recovery at the person- level, the factors determining the recovery potential of individual muscles are poorly understood. There is a need for changing this paradigm in the field by moving beyond person-level classification of residual strength and sacral sparing to a muscle-specific analysis with a focus on the role of corticospinal tract (CST) sparing. The most striking part of human evolution involved the development of dextrous hand use with a respective expansion of the sensorimotor cortex controlling hand movements, which, because of the extensive CST projections, may constitute a drawback after SCI. Here, we investigated the muscle-specific natural recovery after cervical SCI in 748 patients from the European Multicenter Study about SCI (EMSCI), one of the largest datasets analysed to date. All participants were assessed within the first 4 weeks after SCI and re-assessed at 12, 24, and 48 weeks. Subsets of individuals underwent electrophysiological multimodal evaluations to discern CST and lower motor neuron (LMN) integrity [motor evoked potentials (MEP): N = 203; somatosensory evoked potentials (SSEP): N = 313; nerve conduction studies (NCS): N = 280]. We show the first evidence of the importance of CST sparing for proportional recovery in SCI, which is known in stroke survivors to represent the biological limits of structural and functional plasticity. In AIS D, baseline strength is a good predictor of segmental muscle strength recovery, while the proportionality in relation to baseline strength is lower for AIS B/C and breaks for AIS A. More severely impaired individuals showed non-linear and more variable recovery profiles, especially for hand muscles, while measures of CST sparing (by means of MEP) improved the prediction of hand muscle strength recovery. Therefore, assessment strategies for muscle-specific motor recovery in acute SCI improve by accounting for CST sparing and complement gross person-level predictions. The latter is of paramount importance for clinical trial outcomes and to target neurorehabilitation of upper limb function, where any single muscle function impacts the outcome of independence in cervical SCI. Graphical abstract Segmental analysis in cervical spinal cord injury reveals the recovery potential of hand muscles with preserved corticospinal tract: Insights beyond impairment scales. (A, upper panels) Cervical SCI (yellow) may cause impairment of motor function below the level of lesion depending on the completeness of the injury. Individuals with a sensorimotor complete lesion (AIS A), as defined by the absence of sacral sparing, show a non-proportional strength recovery as related to the baseline strength, in contrast to less severely affected patients (AIS B-D) - reflecting the limitations on structural and functional plasticity in this group. (A, lower panel) The area of spinal cord damage typically extents across several segments below the level of lesion with variable preservation of muscle innervation and is described as zone of partial preservation (ZPP). (B) The recovery of hand muscle strength is more challenged compared to more proximal muscles when accounting for the distance from the level of lesion. (C, upper panel) The strength recovery of proximal muscles is proportional to the baseline strength in AIS D (great R 2 values) but limited in AIS A, likely indicating the limits of recovery in severe SCI. (C, lower panel) Also, additional clinical baseline variables [e.g., distance from the motor level of injury (DST); pin prick (PP) and light touch (LT) sensation] primarily increased the prediction of strength recovery for proximal muscles, becoming less effective in more distal muscles, such as the intrinsic hand muscles. (D) Overall, the proportional prediction of strength recovery in distal hand muscles is less strong while failing in AIS A (inversion of proportionality). (D, lower panel) The addition of neurophysiological baseline measures related to CST integrity (by means of MEP) increased the prediction of strength recovery of hand muscles, indicating the importance of residual CST projections to spinal motoneurons for hand strength recovery. Clinical studies aiming at restitution of hand function after SCI may benefit from the addition of MEP assessments early after the SCI, to unveil hand muscles with a potential for recovery.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,030
Tête enseignante GPT0,334
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2021
Routes d'admission1
Résumé présentoui

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