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Record W4394892654 · doi:10.1093/jbcr/irae036.241

607 Cultured Epidermal Autografts versus Spray Keratinocytes for Massive Burns—a Cost Effectiveness Analysis

2024· article· en· W4394892654 on OpenAlexaboutno aff
Pooja Yesantharao, Heli Patel, Aditya Gunturi, Rahim Nazerali, Clifford C. Sheckter

Bibliographic record

VenueJournal of Burn Care & Research · 2024
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineReimbursementCohortSurgeryAverage costCost effectivenessCost analysisEmergency medicineInternal medicineHealth careOperations research

Abstract

fetched live from OpenAlex

Abstract Introduction Massive burn injuries are challenging to treat surgically due to limited donor skin. Autologous epidermal grafts such as cultured epidermal autografts (CEAs) and spray keratinocyte suspensions are successful strategies for wound closure when donor sites are limited. There are no investigations to date that describe the differential outcomes or costs between these competing strategies. Cost-effectiveness analysis is required to guide payors, hospitals, and policy makers in determinations of care. Methods A cost-effectiveness analysis compared CEAs with spray keratinocytes in adult burn patients with >50% total body surface area deep partial thickness burns. Hybrid Monte Carlo simulation and Markov modeling studied cost-utility from the payer perspective. Study data were derived from randomized clinical trials and cohort investigations of CEAs and spray keratinocytes. The time horizon was 1 year with 1 month cycling. Model costs included the product, surgery (both physician and facility fees), and hospitalization. Surgical costs were derived from Medicare reimbursement fee schedules. Costs of epidermal autografts were determined using currently available marketing material. All costs were inflated to 2023 US dollars, with a standard 3% discounting rate. Model utilities were derived from the Vancouver Scar Scale (VSS) with 1 as the best outcome and 0 as the worst outcome. The incremental cost-effectiveness ratio (ICER) was derived from the cost difference between the two strategies divided by the difference in adjusted VSS. Deterministic and probabilistic sensitivity analyses were performed varying all model parameters. Results CEAs achieved successful wound closure in 73% of simulations compared to 88% for spray keratinocytes. Compared to treatment with CEAs, treatment with spray keratinocytes resulted in cost savings of $254,743, with no compromise in overall utility of treatment based on VSS. As such, spray keratinocyte treatment was the dominant strategy. This finding was robust upon sensitivity analyses. Conclusions Spray keratinocyte suspensions were a dominant strategy to CEAs (i.e. cost saving without compromising utility). Applicability of Research to Practice Payers and providers should consider the cost utility of spray keratinocytes as the dominant treatment strategy for massive burn epidermal grafting. CEA manufactures may want to consider cost reductions to be more economically competitive with alternative strategies.

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)0.011
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.119
GPT teacher head0.489
Teacher spread0.370 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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