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Record W4394929986 · doi:10.1093/jbcr/irae036.003

3 Hand Burn Injuries and Occupational Impairment: Impact of Burn Injuries on Return-to-Work Outcomes

2024· article· en· W4394929986 on OpenAlexaff
Barclay T. Stewart, Bernadette Nedelec, Charles Kopp, Nikhitha Thrikutam, Caitlin Orton, Alyssa M. Bamer, Jeffrey C Schneider, Kyra Solis-Beach, Lewis E. Kazis, Haig A Yenikomshian, Karen Kowalske

Bibliographic record

VenueJournal of Burn Care & Research · 2024
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineBurn injuryOccupational safety and healthBurn unitsInjury preventionPoison controlMedical emergencyEmergency medicinePhysical therapySurgeryPathology

Abstract

fetched live from OpenAlex

Abstract Introduction Return to work (RTW) after burn injury is dependent on many variables, including type and location of burn injury, access to care, and pre-injury mental and physical health. Noting that prior studies were limited by small sample sizes, we aimed to use a large database to explore the associations between hand burn severity, functional hand outcomes, and RTW post-injury. Methods Data from a multicenter prospective longitudinal study were analyzed. Adults with burn injuries were classified into 5 groups ranking in severity of hand injury: (0) no hand burns, (1) single hand burn no grafting, (2) bilateral hand burn no grafting, (3) single hand burn requiring grafting, (4) bilateral hand burn requiring unilateral graft, (5) bilateral hand burn requiring bilateral grafts. Grafting was used as a proxy for burn severity. Self-reported employment status, Patient-Reported Outcomes Measurement Information System (PROMIS) Upper Extremity (UE) scores, and reported request for work accommodations were collected at discharge, 6, 12, and 24 months post-injury. Descriptive statistics and analysis of variance (ANOVA) with post-hoc Tukey Test were completed to examine differences in outcomes by hand injury severity. Results A total of 4,621 participants met inclusion criteria. Group 5, those with the most severe burns, had significantly longer mean RTW times than Groups 0-3 (p < 0.005). Group 5’s average RTW (242.6, Standard deviation (SD): 417.9) was greater, however not significantly, compared to group 4 (175.8 SD: 207.0). At 6 months, the mean PROMIS UE scores for grafted groups (Group 3, 40.6 SD: 11.4; Group 5, 35.4 SD: 12.8) were significantly worse than non-grafted groups (Group 1, 46.8; Group 2, 45.0; (p < 0.0001). At 12 months, Groups 5 (39.1 SD: 13.6) and 1 (48.7 SD: 8.6) remained significantly different. At 24 months, mean PROMIS UE scores were worse for grafted groups, though differences were no longer significant compared to non-grafted groups. At every time point, the majority of respondents did not request accommodations for their injuries from their employers (p-value 0.26, 0.66, and 0.86 for 6, 12, and 24 months respectively). Conclusions Burn severity plays a significant role in both RTW and hand function for participants with hand burns. Additionally, the lack of correlation between burn severity and request for work accommodations hints at the baseline vulnerability of these populations. These findings suggest a need for systematic improvements in the way these patients are cared for and re-integrated into the workforce. Applicability of Research to Practice These findings suggest a complex association between burn location, severity, patient functionality, and RTW. Furthermore, this study unveiled the disconnect between burn severity and request for work accommodations. Our data points to the need for further study into current methods of post-burn vocational rehabilitation.

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)0.003
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.049
GPT teacher head0.429
Teacher spread0.380 · 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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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