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Record W4282921683 · doi:10.1186/s12916-022-02395-0

International surveillance study in acute spinal cord injury confirms viability of multinational clinical trials

2022· article· en· W4282921683 on OpenAlexaff
Lucie Bourguignon, Bobo Tong, Fred H. Geisler, Martin Schubert, Frank Röhrich, Marion Saur, Norbert Weidner, Rüdiger Rupp, Yorck-Bernhard Kalke, Rainer Abel, Doris Maier, Lukas Grassner, Harvinder Singh Chhabra, Thomas Liebscher, Jacquelyn J. Cragg, John K. G. Kramer, Armin Curt, Catherine R. Jutzeler

Bibliographic record

VenueBMC Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsCentre for Advancing Health OutcomesVancouver Coastal HealthUniversity of SaskatchewanInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungWings for LifeHorizon 2020 Framework ProgrammeInternational Foundation for Research in ParaplegiaCraig H. Neilsen Foundation
KeywordsMedicineSpinal cord injuryClinical trialRehabilitationEpidemiologyPhysical medicine and rehabilitationPhysical therapySpinal cordInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The epidemiological international landscape of traumatic spinal cord injury (SCI) has evolved over the last decades along with given inherent differences in acute care and rehabilitation across countries and jurisdictions. However, to what extent these differences may influence neurological and functional recovery as well as the integrity of international trials is unclear. The latter also relates to historical clinical data that are exploited to inform clinical trial design and as potential comparative data. METHODS: Epidemiological and clinical data of individuals with traumatic and ischemic SCI enrolled in the European Multi-Center Study about Spinal Cord Injury (EMSCI) were analyzed. Mixed-effect models were employed to account for the longitudinal nature of the data, efficiently handle missing data, and adjust for covariates. The primary outcomes comprised demographics/injury characteristics and standard scores to quantify neurological (i.e., motor and sensory scores examined according to the International Standards for the Neurological Classification of Spinal Cord Injury) and functional recovery (walking function). We externally validated our findings leveraging data from a completed North American landmark clinical trial. RESULTS: A total of 4601 patients with acute SCI were included. Over the course of 20 years, the ratio of male to female patients remained stable at 3:1, while the distribution of age at injury significantly shifted from unimodal (2001/02) to bimodal distribution (2019). The proportional distribution of injury severities and levels remained stable with the largest percentages of motor complete injuries. Both, the rate and pattern of neurological and functional recovery, remained unchanged throughout the surveillance period despite the increasing age at injury. The findings related to recovery profiles were confirmed by an external validation cohort (n=791). Lastly, we built an open-access and online surveillance platform ("Neurosurveillance") to interactively exploit the study results and beyond. CONCLUSIONS: Despite some epidemiological changes and considerable advances in clinical management and rehabilitation, the neurological and functional recovery following SCI has remained stable over the last two decades. Our study, including a newly created open-access and online surveillance tool, constitutes an unparalleled resource to inform clinical practice and implementation of forthcoming clinical trials targeting neural repair and plasticity in acute spinal cord injury.

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)0.418
metaresearch head score (Gemma)0.536
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.718

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4180.536
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.006
Science and technology studies0.0010.004
Scholarly communication0.0060.005
Open science0.0030.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.307
GPT teacher head0.580
Teacher spread0.272 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations64
Published2022
Admission routes1
Has abstractyes

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