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A Survey of Risk Factors for Burns in the Elderly and Prevention Strategies

2002· article· en· W1989402918 on OpenAlexaff
F. Redlick, A. R. Cooke, Manuel Gómez, Joanne Banfield, Robert Cartotto, Joel Fish

Bibliographic record

VenueJournal of Burn Care & Rehabilitation · 2002
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBurn injuryInjury preventionEtiologyOccupational safety and healthPoison controlSuicide preventionMedical emergencyEmergency medicinePhysical therapySurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Elderly burn patients suffer from greater morbidity and mortality than younger patients with similar burn extents. The purpose of this study was to identify risk factors for burn injuries in the elderly to develop an effective preventive program. A cross-sectional survey was conducted among 20 elderly (> or =65 years of age) burn survivors on the circumstances surrounding their burn injury and on burn prevention. A control group of 20 nonburned elderly completed a similar survey only on burn prevention. The majority of burned subjects believed that their injury was preventable (85%). The home was the commonest location for burn injury (70%), and scalds (50%) and flame burns (25%) were the most common etiologies. Most subjects felt that a burn prevention program would be useful (95%) and television, news, and posters were the preferred sources of prevention information. Compared with the burn group, the control group had more risk factors for burn injury. However, the control group also took more active preventive measures. Burn prevention campaigns for elderly should focus on reducing flame and scald burns that occur in the home, preferably using television, news, and poster media.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.074
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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

Citations52
Published2002
Admission routes1
Has abstractyes

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