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Record W4323350129 · doi:10.1093/jbcr/irad032

Poverty and Frailty Are Not Related to Each Other With Regard to Outcomes in Middle-Aged and Older Patients with Burn Injuries

2023· article· en· W4323350129 on OpenAlexaboutno aff
David R. Wallace, Keturah Sloan, Deborah Williams, Jason Heard, Soman Sen, Tina L. Palmieri, David Greenhalgh, Kathleen S Romanowski

Bibliographic record

VenueJournal of Burn Care & Research · 2023
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGerontologyPovertyDemography

Abstract

fetched live from OpenAlex

The purpose of this study was to determine the relationship between frailty and poverty in burn patients ≥50 years old, and their association with patient outcomes. This was a single-center retrospective chart review from 2009 to 2018 of patients ≥50 years old admitted with acute burn injuries. Frailty was assigned using the Canadian Study of Health and Aging Clinical Frailty Scale. Poverty was defined as a patient from a zip code that had >20% of people living in poverty. The relationship between frailty and poverty, as well as each variable independently on mortality, length of stay (LOS), and disposition location, was examined. Of 953 patients, the median age was 61 years, 70.8% were male, and the median total body surface area burn was 6.6%. Upon admission, 26.4% and 35.2% of patients were frail and from impoverished neighborhoods, respectively. The mortality rate was 8.8%. Univariate analysis demonstrated that nonsurvivors had significantly higher chances of living in poverty (P = .02) and were more likely to be frail compared to survivors. There was no significant correlation between poverty and frailty (P = .08). Multivariate logistic regression confirmed the relationship between lack of poverty and mortality (OR .47, 95% CI 0.25-0.89) and frailty and mortality (OR 1.62, 95% CI 1.24-2.12). Neither poverty (P = .26) nor frailty (P = .52) was associated with LOS. Both poverty and frailty were associated with a patient's discharge location (P = .03; P < .0001). Poverty and frailty each independently predict mortality and discharge destination in burn patients ≥50, but they are not associated with LOS nor each other.

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)0.000
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 score0.007
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.353
Teacher spread0.303 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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