Evidence map›Paper›PMID 40234186›Full record

ArticleInternational wound journal2025

ASSIST: Development of a Simplified Clinician-Patient Hybrid Reporting Outcome Measure for Remote Diagnosis of Surgical Site Infection.

Ross Lathan, Louise Hitchman, Josephine Walshaw, Bharadhwaj Ravindhran, Misha Sidapra, Arthur Lim, Judith Long, Joshua Totty, Daniel Carradice, George Smith and 1 more

Abstract read
In one paragraph

Article in International wound journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ross LathanAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.ORCID https://orcid.org/0000-0001-9932-5304
Louise HitchmanAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
Josephine WalshawLeeds Institute of Medical Research, St James' University Hospital, University of Leeds, Leeds, UK.
Bharadhwaj RavindhranAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
Misha SidapraAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
Arthur LimAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
Judith LongAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
Joshua TottyCentre for Clinical Sciences, Hull York Medical School, Hull, UK.ORCID https://orcid.org/0000-0002-0063-1414
Daniel CarradiceAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
George SmithAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.
Ian ChetterAcademic Vascular Surgical Unit, Hull University Teaching Hospital NHS Trust, Hull, UK.

Funding

Leeds Biomedical Research Centre NIHR Medtech 2022
6 · The paper itself

Abstract

Remote assessment of surgical site infection(SSI) lacks sensitivity for the diagnosis of SSI, but current evidence has not evaluated whether a combination of photographs and questionnaires improves diagnostic accuracy. This study aims to develop a remote diagnostic measure to identify SSI. A two-phase mixed methods study was conducted. In phase I, five clinicians reviewed the Bluebelle wound healing questionnaire(WHQ) on a five-point Likert scale of agreement for inclusion in a remote measure. Discussion generated a hypothesis as to which items should be included. In phase II, a cohort study, whereby clinicians evaluated patient's wound images and patients completed the WHQ, were reviewed for scale structure. Principal component analysis (PCA) with scree plot examination and maximum likelihood of estimation (MLE) for one, two and three factors were evaluated. Internal consistency was assessed with Cronbach's α. Phase I: hypothesis generation estimated a measure containing between 10 and 12 items would include all relevant items without ambiguity or redundancy. Phase II: a combined sample of 570 responses provided clinician reviewed images and patient responses. PCA suggested that a 12-item measure with a combined variance of 60.2% would have the best model fit. Cronbach's α was high at 0.841. One included item was highlighted as potentially ambiguous in phase I (wound pain), providing an additional model with this removed. MLE for one, two and three factors suggested measures with 8, 10 and 11 items, respectively. Total variances were low at 29.7%, 39.8% and 41.4% and Cronbach's α were high at 0.838, 0.827 and 0.823, respectively. Three potential models for a remote diagnostic measure were identified. Each is shorter than alternative available measures, which have not been designed for combined use, ensuring this is easy to use. Further evaluation for reliability and diagnostic accuracy is needed to validate a final measure that can be implemented in clinical practice.

Indexed as

Patient Reported Outcome MeasuresSurgical Wound InfectionAdultAgedAged, 80 and overCohort StudiesFemaleHumansMaleMiddle AgedReproducibility of ResultsSurveys and QuestionnairesWound Healingdiagnosissurgical site infectiontelemedicine

Identifiers

PMID40234186
PMCPMC11999756

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.