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Record W4386032105 · doi:10.1227/neu.0000000000002642

The Impact of Interhospital Transfer on the Extent of Neurological Recovery in Acute Traumatic Spinal Cord Injury: Analysis of a Prospective Multicenter Data Set in 970 Cases

2023· article· en· W4386032105 on OpenAlexaffabout
Alex B. Bak, Ali Moghaddamjou, James S. Harrop, Bizhan Aarabi, Michael G. Fehlings

Bibliographic record

VenueNeurosurgery · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMedicineMcNemar's testPropensity score matchingSpinal cord injuryTrauma centerInjury Severity ScoreProspective cohort studyTraumatic brain injuryCohortCohort studyAbbreviated Injury ScalePoison controlRetrospective cohort studyEmergency medicinePhysical therapyInjury preventionSpinal cordSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Interhospital transfer from community hospitals to centers specialized in managing traumatically injured individuals can strain patients, healthcare systems, and delay appropriate care. The purpose was to compare long-term neurological outcomes in transferred or directly admitted patients with traumatic spinal cord injury (SCI). METHODS: An ambispective cohort study was conducted using prospectively collected data (between 2005 and 2018) from 11 specialized level 1 trauma centers across the United States and Canada. All patients who underwent surgical management for SCI were included and placed into 2 comparison cohorts: (1) direct admission and (2) transfer from intermediate hospital. Outcomes were change in American Spinal Injury Association Impairment Scale grade and its components: upper-extremity motor, lower-extremity motor, pinprick, and light touch scores from baseline (assessed ≤72 hours after injury) to follow-up (12-52 weeks). Nearest-neighbor 1:1 propensity score matching between the transferred and directly admitted cohorts was performed. Paired analysis using McNemar's test and paired Student's t -test was used to determine the extent of the difference in neurological outcomes. RESULTS: Nine hundred seventy patients (55.5% male, 55.2 ± 18.9 years) with traumatic SCI were directly admitted to a specialized trauma center (N = 474, 48.9%) or transferred from an intermediate hospital (N = 496, 51.1%). After propensity score matching, 283 pairs were matched. Compared with a matched cohort of transferred patients, American Spinal Injury Association Impairment Scale grade improved more in directly admitted patients (56.2% vs 46.3%, P = .024), as did upper-extremity motor score (13.7 ± 12.8 vs 10.4 ± 11.5, P = .018) and light touch score (22.0 ± 29.7 vs 16.9 ± 26.6, P = .034). CONCLUSION: Patients with SCI directly admitted to specialized trauma centers have greater neurological recovery compared with patients transferred from an intermediate hospital. Feasibility of direct admission to a center specialized in the management of acute SCI through implementation of a standardized code program must be further investigated. LEVEL OF EVIDENCE: Therapeutic level II.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.431
Teacher spread0.303 · 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".

Quick stats

Citations3
Published2023
Admission routes2
Has abstractyes

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