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Record W4240996649 · doi:10.14740/jnr609

Association Between Trauma Center Designation and Spinal Cord Injury Admission in the USA

2020· article· en· W4240996649 on OpenAlexvenueno aff
Ross-Jordon S. Elliott, Anand Dharia, Ali Seifi

Bibliographic record

VenueJournal of Neurology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmergency departmentTrauma centerEmergency medicineSpinal cord injuryRetrospective cohort studyPediatricsInternal medicineSpinal cord

Abstract

fetched live from OpenAlex

Background: After spinal cord injury (SCI), patients are seen in either trauma center emergency departments (EDs) or non-trauma center EDs, and then selectively admitted for hospitalization. The association between SCI and admission to designated trauma centers is currently unknown. In this study, we assess the trends in admission between designated trauma centers after SCI from a large multi-center nationwide registry. Methods: In this retrospective analysis of the Nationwide Emergency Department Sample (NEDS), we identified visits with SCI from 2006 to 2014. Z-test analyses were used to compare patients diagnosed with SCI at EDs with an associated trauma center designated hospital (TC-visits) against patients diagnosed with SCI at EDs without an associated trauma center designated hospital (NTC-visits). Results: A total of 516,716 reported visits were identified with SCI. The annual total ED visits with admission to the same hospital for patients diagnosed with SCI increased significantly from 39,129 to 50,127 from 2006 to 2014 (P < 0.001). From 2006 to 2014, the annual ED visits and admissions from TC-visits increased significantly from 27,781 to 43,926 and 23,445 to 35,635, respectively (P < 0.0001, P < 0.0001). However, the annual ED visits and admissions from NTC-visits did not change significantly from 23,938 to 22,107 and 15,683 to 14,493, respectively (P = 0.09 and P = 0.1). Throughout the entire study period, the annual total ED visits with admissions to the same hospital was significantly higher for TC-visits than NTC-visits diagnosed with SCI (P < 0.0001). The mean length of stay (14.1 days vs. 8.1 days), annual total in-hospital mortality (6.8% vs. 6.0%), and annual total discharges to another institution (53.8% vs. 46.8%) were significantly higher in TC-visits throughout the study period (P < 0.001). However, the annual total routine discharges (27.2% vs. 26.4%), annual total discharges to short-term hospital (12.4% vs. 7.2%), and annual total discharges to home health care (7.7% vs. 4.4%) were significantly higher in NTC-visits throughout the study period (P < 0.001). Conclusions: Of the population of patients with SCI who visit EDs, those seen at trauma centers have a significant parallel association with incidence and patient outcome compared against those seen at non-trauma centers. Prospective research is warranted to make recommendations for required healthcare infrastructures based on an institution’s trauma center designation. J Neurol Res. 2020;10(5):193-198 doi: https://doi.org/10.14740/jnr609

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)0.001
metaresearch head score (Gemma)0.004
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.240
GPT teacher head0.466
Teacher spread0.225 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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