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Record W2526454199

PATIENT RECRUITMENT INTO ACUTE SPINAL CORD INJURY CLINICAL TRIALS OF EARLY THERAPEUTIC INTERVENTIONS - HOW MANY PATIENTS CAN REALLY BE ENROLLED?

2012· article· en· W2526454199 on OpenAlexaff
Robert Lee, Marcel F. Dvorak, Brian K. Kwon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsSpinal Cord Injury BCVancouver General Hospital
Fundersnot available
KeywordsMedicineClinical trialSpinal cord injuryPsychological interventionPhysical therapyEmergency medicineSpinal cordInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Introduction While there is a desperate need for effective treatments for acute spinal cord injury (SCI), the clinical validation of novel therapeutic interventions is severely hampered by the need to recruit relatively large numbers of patients into clinical trials for sufficient statistical power. While a centre might annually admit 100 acute SCI patients, only a fraction may satisfy the basic inclusion criteria for an acute clinical trial, which typically requires patients of a certain injury severity (eg ASIA A), within a specific time window (eg. 12 hours from injury), and without other major injuries or conditions that would cloud the baseline neurologic assessment. This study was conducted to define that “fraction” of SCI patients that would theoretically satisfy standard inclusion criteria of an acute clinical trial. Methods Using a local database, we reviewed patients admitted to our Level 1 trauma center with a complete (ASIA A) or an incomplete (ASIA B, C and D) acute SCI involving bony spinal levels between C0 and sacrum. All patients admitted over the 4 year period from 2005 to 2009 were reviewed. Demographic information and data about the patients9 SCI and other injuries were reviewed. We then determined how many of the total number of SCI patients would be eligible for enrolment into a hypothetical acute clinical trial that required a valid baseline assessment of neurologic impairment, and an enrolment window of either 12 hours, 24 hours, or 48 hours. Results 408 acute traumatic SCI patients were admitted over the 4 year period. 253 of 408 (62%) patients presented within 12 hours of injury, 60 (15%) between 12–24 hours, and 28 (7%) between 24–48 hours. 42% of patients were ASIA A, 13% B, 18% C and 27% D. The number of patients who presented with injuries or other conditions that would exclude them from enrolment was relatively high: 4% had penetrating injuries, 12% had illicit drug use, and 20% had either alcohol intoxication or head injuries which precluded a valid baseline neurologic examination. Conclusions Out of a total of 408 patients admitted over 4 years, the number who would have been optimistically eligible for an acute neuroprotective trial was disappointingly small. Given that acute clinical trials are increasingly interested in cervical ASIA A patients (in whom segmental motor recovery can be assessed), the number of such patients who would actually be eligible for an acute intervention was surprisingly low. Given that additional inclusion/exclusion criteria would also be applicable in a real clinical trial, the true number of “eligible” or “recruitable” patients is conservatively even lower. This study is the first to quantify this challenging aspects of conducting acute SCI clinical trials, and provides valuable information for those planning such initiative

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)0.237
metaresearch head score (Gemma)0.370
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.941

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2370.370
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.003
Science and technology studies0.0020.004
Scholarly communication0.0060.008
Open science0.0040.004
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0080.003

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 head0.432
GPT teacher head0.560
Teacher spread0.128 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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