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Record W2308481946 · doi:10.1089/neu.2015.4370

The Economic Burden of Autonomic Dysreflexia during Hospitalization for Individuals with Spinal Cord Injury

2016· article· en· W2308481946 on OpenAlexaffabout
Jordan W. Squair, Barry White, Grace I. Bravo, Kathleen A. Martin Ginis, Andrei V. Krassioukov

Bibliographic record

VenueJournal of Neurotrauma · 2016
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsMcMaster UniversityGF Strong Rehabilitation CentrePraxis Spinal Cord InstituteUniversity of British ColumbiaInternational Collaboration On Repair Discoveries
Fundersnot available
KeywordsMedicineAutonomic dysreflexiaInterquartile rangeSpinal cord injuryEmergency departmentHealth careEmergency medicineIndirect costsAcute careMedical emergencyActivity-based costingIntensive care medicineSpinal cordSurgery

Abstract

fetched live from OpenAlex

We sought to determine the economic burden of autonomic dysreflexia (AD) from the perspective of the Canadian healthcare system in a case series of individuals with spinal cord injury (SCI) presenting to emergency care. In doing so, we sought to illustrate the potential return on investments in the translation of evidence-informed practices and developments in the prevention, diagnosis, and management of AD. Activity-based costing methodology was employed to estimate the direct healthcare or hospitalization costs of AD following presentation to the emergency department. Differences in trends were noted between patients who were promptly diagnosed, managed, and discharged, and patients whose experience followed a less direct or ideal path to discharge. We recorded 29 emergency room visits for conditions ultimately diagnosed as AD. Overall, median length of stay was 3 days (interquartile range [IQR] = 1.25-5.75), but extended up to 103 consecutive days. Cost analysis revealed median healthcare costs of $5029 (IQR = $2397-9522) for hospital admissions for AD, with the highest estimated hospital cost for a single admission > $190,000. Emergency room admissions resulting from AD can result in dramatic healthcare costs. Delayed diagnosis and inefficient management of AD may lead to further complications, adding to the strain on already limited healthcare resources. Prompt recognition of AD; broader translation of evidence-informed practices; and novel diagnosis, self-management, and/or therapeutic/pharmaceutical applications may prove to mitigate the burden of AD and improve patient well-being.

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)0.009
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 score0.398
Threshold uncertainty score0.792

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.394
Teacher spread0.330 · 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

Citations14
Published2016
Admission routes2
Has abstractyes

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