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Record W3004182078 · doi:10.1093/jbcr/irz163

State of the Science Burn Research: Burns in the Elderly

2020· review· en· W3004182078 on OpenAlexfundno aff
Marc G. Jeschke, Herb A. Phelan, Steven Wolf, Kathleen S Romanowski, Sarah Rehou, Alisa Saetamal, Joan Weber, John Schulz, Crystal New, Arek J Wiktor, Lyndsay Deeter, Kelly Tuohy

Bibliographic record

VenueJournal of Burn Care & Research · 2020
Typereview
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMedicinePopulationBurn outGerontologyBurn injurySurgeryNursing

Abstract

fetched live from OpenAlex

Advances in burn care have led to significant improvements in the outcomes of burn patients except in the elderly: burn patients 65 years of age. 1,2 This is reflected in the LD50 for elderly burn patients, which has not significantly changed over the last three decades and is around 30 to 35% TBSA burn. 4,8 The lack of improvements is even more impactful when considering that elderly represent the fastest growing population, indicating the expected substantial increase in elderly burn patients over the next decades. Additionally, the amount of burn patients in elderly will not only grow due to the growing population of elderly but also have much higher incidence as elderly are at an increased risk for burn injuries due to thinning skin, decreased sensation, mental alterations, pre-existing comorbidities, and numerous other contributing factors. [1] ][3][4][5][6] The high risk of suffering from burns in the elderly population with the rapid growth of this population will require change to the burn treatment paradigm but, at this time, burn care providers lack treatment guidelines or protocols tailored to the special needs of the elderly burn patient. Complicating elderly burn care is the lack of knowledge about maintaining quality of life, independence, and acceptable long-term outcomes. 9,10 As aforementioned, despite the recognition of burn care providers regarding poor outcomes of elderly burn patients, reasons for these detrimental outcomes have yet to be determined. Unfortunately, until 2016, there were no concerted or directed research efforts to improve outcomes. In 2016, past President of the American Burn Association (ABA) Dr. Tredget held the State of Science meeting in Washington, DC, with elderly burn care being one of the main areas of interest and priorities. Subsequently a white paper was published in the Journal of Burn Care & Research (JBCR) that briefly delineated the perceived needs of elderly burn patients and areas ripe for investigations in order to improve outcomes. 11 In addition, ABA past Presidents Dr. Peck and Dr. Tredget initiated an ad hoc Committee on Elderly Burn Care, which changed to a standing committee in 2018.

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)0.022
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.007
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0000.007
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 head0.300
GPT teacher head0.516
Teacher spread0.216 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2020
Admission routes1
Has abstractyes

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