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Record W2797468735 · doi:10.1093/jbcr/iry006.008

4 Need for Mechanical Ventilation is More Predictive of Mortality than Age, %TBSA, and Frailty Score in Elderly Burn Patients

2018· article· en· W2797468735 on OpenAlexaboutno aff
A.M.E Kistner Garza, William Adams, Michael M. Mosier

Bibliographic record

VenueJournal of Burn Care & Research · 2018
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTotal body surface areaMechanical ventilationBurn injuryRetrospective cohort studySmoke inhalationEmergency medicineVentilation (architecture)Internal medicineInhalationAnesthesiaSurgery

Abstract

fetched live from OpenAlex

The multifactorial frailty index (FI) has shown to better predict elderly burn outcomes than traditional predictive models that do not incorporate pre-injury physiological condition. Additionally, inhalation injury correlates with worse outcomes. If FI and need for mechanical ventilation serve as independent predictors of adverse outcomes, they can be used as a clinical tool for patient management. A retrospective review was conducted on 114 patients 65 years of age and older admitted with a burn injury >5% total body surface area (TBSA) from March 2010 to March 2017. Data collected included age, gender, %TBSA, inhalation injury, in hospital mortality, 90 day mortality, hospital length of stay, length of mechanical ventilation, number of surgical procedures, insurance status, and discharge disposition. Patient history documentation was used to assess preinjury physiological condition. The Canadian Study of Health and Aging clinical frailty scale was used to determine FI scores. Univariable analysis demonstrated significant mortality associations with mechanical ventilation, %TBSA, FI, and burn with inhalation injury. Multivariable analysis confirmed need for mechanical ventilation, %TBSA, and FI remained hazardous. For every one-unit increase in the index score the risk of death increased by approximately 75% (HR = 1.75, 95% CI: 1.25 - 2.45; p<.001). Similarly, for every % increase in TBSA, the risk of death increased by 5.7% (HR = 1.06, 95% CI: 1.03 - 1.08; p<.001). Lastly, patients who were vented were 6.7 (95% CI: 1.52 - 29.44) times more likely to die (p=.01). Interestingly, surgical interventions were protective (HR = 0.04, 95% CI: 0.01 - 0.33; p=.003). These findings indicate that the most important predictor of mortality in elderly burn patients is the need for mechanical ventilation; FI is more accurate than age at predicting outcomes for mortality; and burn with inhalation injury is associated with a greater mortality risk than burn alone. Additionally, the risk of mortality increases as burn size does, and decreases with one or more surgeries versus no surgeries. FI and need for mechanical ventilation have a significant negative impact on clinical outcomes in elderly burn patients and can aid clinicians in their discussions regarding expected outcomes and goals of care.

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 score0.014

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.110
GPT teacher head0.428
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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