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A Simple Fall in the Elderly: Not So Simple

2006· article· en· W2052529196 on OpenAlexaffabout
Éric Bergeron, Julien Clément, Sebastien Ratte, Jean‐Marie Bamvita, Francois Aumont, David Clas

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2006
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsHôpital de l'Enfant-JésusFonds de Recherche du Québec - SantéHôpital Charles-Le Moyne
Fundersnot available
KeywordsMedicineTrauma centerThorax (insect anatomy)BluntElderly peopleInjury Severity ScoreInjury preventionSurgeryPoison controlEmergency medicinePediatricsGerontologyRetrospective cohort study

Abstract

fetched live from OpenAlex

BACKGROUND: The goal of this study was to evaluate the burden of falls in the elderly in a Canadian tertiary trauma center. METHODS: Patients admitted to Charles-LeMoyne Hospital with a low velocity fall (LVF) from April 1, 1993 to March 31, 2000 were individually reviewed. Elderly was defined as age 65 years and older. A region was considered to be injured if Abbreviated Injury Scale was greater than or equal to 2. RESULTS: There were 2,333 patients with LVF, 41.4% of all blunt trauma admissions. Median Injury Severity Score was 9 for elderly compared with 5 for young (p < 0.001). Injuries were significantly more frequent to head, face, thorax, and lower limbs in the elderly. Mortality (13.4% versus 0.9%; p < 0.001), length of stay (median = 15 versus 3 days; p < 0.001) and long-term care facility reference (19.3% versus 1.1%, p < 0.001) were significantly higher in the elderly. CONCLUSIONS: LVF is a frequent cause of admission for trauma in the elderly. Despite the apparent benign nature of the mechanism, LVF is associated with more severe injuries and worse outcome.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.021
GPT teacher head0.327
Teacher spread0.306 · 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 designCase report
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

Citations117
Published2006
Admission routes2
Has abstractyes

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