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Record W4389223402 · doi:10.1227/neu.0000000000002767

Treatment of Acute Traumatic Central Cord Syndrome: A Study of North American Trauma Centers

2023· article· en· W4389223402 on OpenAlexaff
Jetan H. Badhiwala, Christopher D. Witiw, Jefferson R. Wilson, Leodante da Costa, Avery B. Nathens, Michael G. Fehlings

Bibliographic record

VenueNeurosurgery · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsToronto Western HospitalUniversity Health NetworkSunnybrook Health Science CentreSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineOdds ratioInjury Severity ScoreSpinal cord injuryEmergency departmentEmergency medicinePediatricsSurgeryInjury preventionPoison controlInternal medicineSpinal cord

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Central cord syndrome (CCS) is expected to become the most common traumatic spinal cord injury, yet its optimal management remains unclear. This study aimed to evaluate variability in nonoperative vs operative treatment for CCS between trauma centers in the American College of Surgeons Trauma Quality Improvement Program, identify patient- and hospital-level factors associated with treatment, and determine the association of treatment with outcomes. METHODS: Adults with CCS were identified from the Trauma Quality Improvement Program database (2014-2016). Mixed-effects modeling with a random intercept for trauma centers was used to examine the adjusted association of patient- and hospital-level variables with nonoperative treatment. The random-effects output of the model assessed the risk-adjusted variability in nonoperative treatment across centers. Outlier hospitals were identified, and the median odds ratio was calculated. The adjusted effect of nonoperative treatment on mortality, morbidity, and hospital length of stay (LOS) was examined at the patient and hospital level by mixed-effects regression. RESULTS: Three thousand, nine hundred twenty-eight patients across 255 centers were eligible; of these, 1523 (38.8%) were treated nonoperatively. Older age, noncommercial insurance (odds ratio [OR] 1.26, 95% CI 1.08-1.48, P = .004), absence of fracture (OR 0.58, 95% CI 0.49-0.68, P < .001), severe head injury (OR 1.41, 95% CI 1.09-1.82, P = .008), and comatose presentation (1.82, 95% CI 1.15-2.89, P = .011) were associated with nonoperative treatment. Twenty-eight hospitals were outliers, and the median odds ratio was 2.02. Patients receiving nonoperative treatment had shorter LOS (mean difference -4.65 days). Nonoperative treatment was associated with lesser in-hospital morbidity (OR 0.49, 95% CI 0.37-0.63, P < .001) at the patient level. There was no difference in mortality. CONCLUSION: Operative decision-making for CCS is influenced by patient factors. There remains substantial variability between trauma centers not explained by case-mix differences. Nonoperative treatment was associated with shorter hospital LOS and lesser inpatient morbidity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.036
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.073
GPT teacher head0.367
Teacher spread0.293 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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