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Record W3010079967 · doi:10.1093/jbcr/iraa024.152

522 Skin Graft Donor-site Morbidity: A Systematic Literature Review

2020· article· en· W3010079967 on OpenAlexaboutno aff
Malachy Asuku, Yan Qi, Tzy‐Chyi Yu, E. Boing, Helen Hahn, Sara Hovland, Matthias B. Donelan

Bibliographic record

VenueJournal of Burn Care & Research · 2020
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObservational studyRandomized controlled trialVisual analogue scaleSurgeryMEDLINESystematic reviewTotal body surface areaInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Although split-thickness skin grafts (STSGs) are part of standard treatment for burn, traumatic, and chronic wounds, the harvesting of STSGs creates iatrogenic injuries at the donor sites. This review summarizes the scientific literature on morbidity associated with STSG donor sites. Methods A systematic literature search from 2014 to 2019 was performed in MEDLINE, Embase, and Chemical Abstracts to identify English-language articles reporting on the clinical-study findings, complications, management, financial burden, and patient-reported outcomes pertaining to STSG donor sites. Results Of 1426 articles identified, 44 met eligibility criteria and were included in the analysis. Most studies (n=31; randomized controlled trials [RCTs], n=26; observational studies, n=5) compared the outcomes of donor-site wounds that were treated with different dressings. Several studies (n=9; RCTs, n=5; observational studies, n=4) evaluated new agents or methods to improve donor-site outcomes. Only 3 studies focused on patient- or physician-reported outcomes. No studies reported on the length of hospital stay or the financial burden associated with donor-site wounds. Among the studies that indicated donor site location (n=34), the thigh was the most common. The most frequently reported donor-site outcome was the mean time to wound healing (n=21), which was 4.7±0.2 to 28.2±5.6 days. In some studies (n=13), the pain score assessed by visual analog scale (0–10 scoring, 0 being no pain and 10 being extreme pain) was 1.46 to 10.0 on postoperative day (POD) 1 and was 0.2 to 8.0 between POD 10 and 12. In a few studies (n=5), donor-site scar assessment using the Vancouver Scar Scale (0–13 scoring, 0 being normal skin and 13 being the worst scar) showed scores ranged from 0 to 10.9 at postoperative year 1. One study reported a 48.3% incidence of donor-site scar hypertrophy at 8 years. Infection rates were generally low but ranged from 0%-50%. Less frequently reported outcomes included pruritus, stiffness, and patient esthetic dissatisfaction. Conclusions This systemic literature search revealed a wide range of healing variation noted in STSG donor-site outcomes. Despite optimal wound care, donor sites required days to heal and were frequently associated with morbidities, including pain and scarring. Less frequently, donor sites were linked with severe morbidities, such as wound infection. Since majority of articles were RCTs with short follow-up, more research is warranted to assess the long-term outcome of hypertrophic scarring, another serious complication. These negative outcomes impose a substantial burden on patients and may impact their quality of life. Applicability of Research to Practice The elimination or reduction of STSG donor sites and their associated morbidity have long been identified by patients and providers as an unmet need deserving urgent attention.

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)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0150.014
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.088
GPT teacher head0.422
Teacher spread0.335 · 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 designSystematic review
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

Citations5
Published2020
Admission routes1
Has abstractyes

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