MétaCan
Menu
Back to cohort
Record W4409919330 · doi:10.1016/j.clnesp.2025.04.002

Energy expenditure following biodegradable dermal matrix application in severe burn injury: A pilot study

2025· article· en· W4409919330 on OpenAlexaboutno aff
Susan Dowling, Rochelle Kurmis, Jessica Gauro, Lee‐anne S. Chapple, Patrick Coghlan, Elizabeth Concannon, Marcus Wagstaff, Alison M. Hill

Bibliographic record

VenueClinical Nutrition ESPEN · 2025
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
FundersMedical Research CouncilRoyal Adelaide HospitalNational Health and Medical Research CouncilUniversity of South AustraliaHospital Research Foundation
KeywordsMedicineBurn injuryEnergy expenditureMatrix (chemical analysis)Intensive care medicineSurgeryInternal medicineComposite material

Abstract

fetched live from OpenAlex

BACKGROUND: Biodegradable temporising matrix (BTM) is a dermal substitute developed to reconstruct full thickness burns, yet the subsequent metabolic effects are unknown. This pilot study aimed to 1) measure variation in energy expenditure using indirect calorimetry (IC) in response to BTM application across the continuum of acute burns management and 2) assess accuracy of predictive energy equations commonly used in Australia in adult patients with severe burns. METHODS: Energy expenditure was measured (MEE) using IC during distinct time-periods: 'acute surgery'; 'BTM integration'; following 'skin grafting'; and 'acute recovery' and compared to predictive equations (Toronto, Schofield plus injury factor (IF), and the Ratio method from a minimum of 25 kcal/kg/day to a maximum of 40 kcal/kg/day). Agreement was assessed using Lin's concordance correlation coefficient (CCC) and Bland-Altman methods. RESULTS: Eighteen patients were included (median [Interquartile range] 44 [29-70] years; 39 % [25-56 %] total body surface area burns). MEE reported as estimated marginal means (95 % confidence intervals) for each time-period were: 'acute surgery' 2048 (1847, 2248) kcal; 'BTM integration' 2244 (2071, 2416) kcal; 'skin grafting' 2297 (2123, 2471) kcal; 'acute recovery' 2102 (1918, 2287) kcal, equating to 25 %, 37 %, 41 % and 29 % above predicted basal metabolic rate (Schofield, no injury factor), respectively (all p < 0.001). During 'acute surgery' all equations (Schofield x IF, Minimum and Maximum Ratio method), overestimated energy requirements by 24-42 % (all p < 0.001), except Toronto (-12 %, p = 0.071). Similarly, all equations overestimated energy requirements by 11-27 % throughout 'BTM integration' (all p ≤ 0.01), except Toronto (-5 %, p = 0.12). Following 'skin grafting' Schofield and Maximum Ratio equations overpredicted, while Toronto underpredicted requirements (+16 %, +21 % and -11 %, respectively, p ≤ 0.001). The Maximum Ratio overestimated and Toronto underestimated requirements during 'acute recovery' (+19 %, p = 0.04 and -9 %, p = 0.014, respectively). Average CCC (all time periods) was highest for Toronto at 0.77, with Bland-Altman plots also showing highest accuracy and reliability. CONCLUSIONS: A substantial hypermetabolic response was not observed following BTM application. While the Toronto equation most closely predicted energy requirements, considerable variability was observed, highlighting the value of IC to guide nutrition support in severe burns where nutritional needs change over time. A larger multicentre study is required to substantiate the effect of BTM application on energy expenditure.

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)0.000
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 score0.396
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.412
Teacher spread0.366 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueClinical Nutrition ESPENSame topicWound Healing and TreatmentsFrench-language works237,207