MétaCan
Menu
Back to cohort
Record W4220981328 · doi:10.1093/jbcr/irac012.009

5 Admission Frailty Is Associated with Acute Respiratory Failure and Mortality in Burn Patients > 50

2022· article· en· W4220981328 on OpenAlexaboutno aff
Colette Galet, KE Lawrence, Kathleen S Romanowski, Dionne A. Skeete, Neil Mashruwala

Bibliographic record

VenueJournal of Burn Care & Research · 2022
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTotal body surface areaAcute kidney injuryRetrospective cohort studyBurn injuryCohortInternal medicineKidney diseaseCohort studyRespiratory failureEmergency medicineSurgery

Abstract

fetched live from OpenAlex

Abstract Introduction Pre-injury frailty has been shown to predict mortality of older burn patients. Herein, we assessed the utility of the Canadian Study of Health and Aging Clinical Frailty Scale (CSHA-CFS) to predict burn-specific outcomes. We hypothesize that frail patients are at greater risk for complications such as graft loss, acute respiratory failure, and acute kidney injury and will require increased healthcare support at discharge. Methods This is a retrospective cohort study. Patients 50 years and older admitted to our Institution for burn injuries between July 2009 and June 2019 were included. Patients with inhalation injury only, no data on total burn surface area, or for whom medical history was incomplete were excluded. Demographics; comorbidities; pre-injury functional status; admission, injury, and hospitalization information; complications (graft loss, acute respiratory failure, and acute kidney disease (AKI)); mortality, and discharge disposition were collected. Patients were scored on the CSHA-CFS based on pre-admission health and functional status. The frail and non-frail groups were compared. Multivariate analyses were performed to assess the association between admission frailty and outcomes. P < 0.05 was considered significant. Results We included 851 patients, 697 were not frail and 154 were frail. Frail patients were significantly older (66.1 ± 10.8 vs. 63.5 ± 10.9, p = 0.002), more likely Caucasian (98.1% vs. 91%, p = 0.027) and to have suffered flame burn injuries (68.8% vs. 59.8%, p < 0.001). Frail patients had a lower %TBSA (4.4 ± 8.1% vs. 10.1 ± 13.1, p < 0.001) but were more likely to stay longer in hospital relative to %TBSA (3.6 ± 6.7 vs. 1.9 ± 3.1, p < 0.001). Frail patients were less likely to have had skin graft procedures (27.3% vs. 57.4, p < 0.001). On multivariate analysis, controlling for age, sex, race, mechanism of injury, %TBSA, 2nd degree and 3rd degree burn surface, inhalation injury, frailty was associated with acute respiratory failure (OR = 2.599 [1.460-4.628], p = 0.001). Frailty was also associated with mortality (OR = 6.915 [2.455-19.980]; p < 0.001) when controlling for the same variables as well as acute respiratory failure and AKI. Frailty was also associated with discharge to home with healthcare services (OR = 2.678 [1.491-4.809], p = 0.001), to SNF, rehabilitation, or long-term acute care facilities (OR = 3.572 [1.933-6.602], p < 0.001), and to hospice (OR = 5.759 [1.519-21.827], p = 0.010) when compared to home without healthcare services. Conclusions Frailty is associated with increased risk of acute respiratory failure, mortality, and requiring increased healthcare support post-discharge. Our data suggest frailty as a tool to predict morbidity and mortality as well as for goals of care discussions for the burn patient.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.080
GPT teacher head0.398
Teacher spread0.318 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Burn Care & ResearchSame topicBurn Injury Management and OutcomesFrench-language works237,207