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Record W4293104067 · doi:10.12968/jowc.2022.31.8.634

Measuring subepidermal moisture to detect early pressure ulcer development: a systematic review

2022· review· en· W4293104067 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Wound Care · 2022
Typereview
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsSKiN Health
Fundersnot available
KeywordsMedicineCINAHLConfidence intervalDentistryInternal medicinePsychological interventionNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim was to assess evidence related to the measuring of subepidermal moisture (SEM) to detect early, nonvisible development of pressure ulcers (PUs). METHOD: Using systematic review methodology, all quantitative animal and human research studies written in English were considered. In January 2021, PubMed, CINAHL, SCOPUS, Cochrane and EMBASE databases were searched. The primary outcome of interest was the validity of SEM measurement to detect early PU development. The secondary outcome was time to PU detection, sensitivity and specificity of SEM measurement, and the impact of SEM measurements on PU prevention. Data analysis was undertaken using RevMan and narrative synthesis. RESULTS: A total of 17 articles met the inclusion criteria. In all studies, a consistent abnormal deviation in SEM measurements corresponded with evidence of visual PU development. Time to PU development, explored in four studies, showed earlier detection of PU development using SEM measurement. RevMan analysis identified the mean difference in time to PU development (SEM measurement versus visual skin assessment, VSA) was 4.61 days (95% confidence interval: 3.94-5.28; p=0.0001) in favour of SEM measurements. The sensitivity of SEM measurements was reported in four studies, and scores varied from 48.3% to 100.0%. Specificity was also reported in four studies and scores ranged from 24.4% to 83.0%. The impact of the detection of abnormal SEM measurements on PU prevention was explored by one study. Results showed a 93% decrease in PU rates when staff acted on the results of the SEM readings. CONCLUSION: The findings of this review identified that SEM measurement detects PU development earlier than VSA. Furthermore, when staff responded to abnormal SEM measurements, prevention strategies were enhanced, with a subsequent reduction in visible PU development. SEM measurement may therefore be a useful addition to PU prevention strategies. DECLARATION OF INTEREST: The School of Nursing & Midwifery, RCSI has a research agreement with Bruin Biometrics. Funding for the study was through an Irish Research Council PhD Enterprise Partnership Scheme with Bruin Biometrics. The authors have no other conflicts of interest.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.126
GPT teacher head0.412
Teacher spread0.287 · 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