69 Identifying Longitudinal Outcome Domains Post-Burn Injury: A Systematic Review of Validated Patient-Reported Outcome Measures
Bibliographic record
Abstract
Abstract Introduction Burn injuries represent a significant public health concern. Patient-reported outcome measures (PROMs) are used to assess physical and psychological outcomes. We reviewed the literature to identify (1) commonly-used PROMs that assess long-term outcomes and (2) domains of interest not addressed by burn-specific PROMs. Methods We searched 3 databases (PubMed, Embase, Web of Science) from 1979-July 2024. Eligible articles studied adult burn patients (≥18 years) with a follow-up period of 13-24 months using either a burn-specific or combination of burn- and non-burn-specific, validated PROMs. Six reviewers independently screened articles; three conducted quality assessments using JBI critical appraisal of bias tools. We used COVIDENCE for article screening and Microsoft Excel for data analysis. Results Our initial search yielded 29,644 articles. Following title, abstract, and full-text screening, 7 studies containing 706 patients were eligible for inclusion. Burn injury types included thermal, electrical, and chemical. TBSA was listed as a mean of ≤50% in two (n=2) studies and >50% in two (n=2) studies, a median of 5% in one (n=1) study, and not listed in two (n=2) studies. Four (n=4, 57%) studies used a combination of validated burn and non-burn-specific PROMs (“combination studies”), such as Burn Specific Health Scale (BSHS), Hospital Anxiety and Depression Scale (HADS), and Impact of Event Scales (IES). Three (n=3) studies used only validated burn-specific questionnaires: Vancouver Scar Scale (VSS) and Patient and Observer Scar Assessment Scale (POSAS)]. Studies using only burn-specific PROMs focused on outcomes related to burn scar treatment and management. Combination studies assessed psychological and functional aspects of patient recovery such as anxiety and depression (HADS, n=1) and PTSD symptoms (IES, n=2). The most common burn-specific questionnaire used in combination studies was the BSHS (n=4). Of the three (n=3) studies that used only burn-specific questionnaires, two (n=2) used one PROM each to assess burn scars [VSS (n=1), POSAS (n=1)] and one (n=1) study used both to help address “physical restriction” and “psychological strain” of scars as well as “general scar assessment.” Substantial data heterogeneity prevented meta-analysis. Conclusions Burn-specific PROMs primarily assess scar management, necessitating combined use of burn- and non-burn-specific PROMs to assess psychological, functional, and emotional impacts of burn injury and long-term outcomes. Burn research and patient care could benefit from creating and validating a burn-specific PROM assessing psychological and functional domains vital to the long-term well-being of burn survivors. Applicability of Research to Practice This research provides data on burn- and non-burn-specific PROMs to assess long-term outcomes of burn survivors. Funding for the Study N/A
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".