Evidence map›Paper›PMID 36787270›Full record

ArticleInternational wound journal2023

Clinical validation of a smartphone application for automated wound measurement in patients with venous leg ulcers.

Khi Yung Fong, Tina Peiting Lai, Kai Siang Chan, Isabel Jia Le See, Cheng Cheng Goh, Sivakami Muthuveerappa, Audrey Huimin Tan, Shanying Liang, Zhiwen Joseph Lo

Open access · goldAbstract read
In one paragraph

Article in International wound journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

12 citing papers in PubMed, 17 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Khi Yung FongYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0001-8194-0800
Tina Peiting LaiWound and Stoma Care, Nursing Service, Tan Tock Seng Hospital, Singapore, Singapore.
Kai Siang ChanVascular Surgery Service, Department of General Surgery, Tan Tock Seng Hospital, Singapore, Singapore.ORCID https://orcid.org/0000-0001-9533-801X
Isabel Jia Le SeeVascular Surgery Service, Department of General Surgery, Tan Tock Seng Hospital, Singapore, Singapore.
Cheng Cheng GohWound and Stoma Care, Nursing Service, Tan Tock Seng Hospital, Singapore, Singapore.
Sivakami MuthuveerappaWound and Stoma Care, Nursing Service, Tan Tock Seng Hospital, Singapore, Singapore.
Audrey Huimin TanWound and Stoma Care, Nursing Service, Tan Tock Seng Hospital, Singapore, Singapore.
Shanying LiangDepartment of Surgery, Woodlands Health, Singapore, Singapore.
Zhiwen Joseph LoDepartment of Surgery, Woodlands Health, Singapore, Singapore.ORCID https://orcid.org/0000-0003-2289-5266
Tan Tock Seng Hospital · SGNanyang Technological University · SGNational University of Singapore · SGWoodlands Health Campus · SG

Funding

Agency for Science, Technology and Research (A*STAR): Industry Alignment Fund - Pre-Positioning; Programme H19/01/a0/0Y9National Research Medical Council (NMRC) Research Training Fellowship FLWSHP19nov-0015Tan Tock Seng Hospital FY2020 Pitch-for-Fund Program Grant PFFP20-17
6 · The paper itself

Abstract

Chronic wounds are associated with significant clinical, economic and quality-of-life burden. Despite the variety of wound imaging systems available in the market for wound assessment and surveillance, few are clinically validated among patients of Asian ethnicity. We aimed to clinically validate the accuracy of a smartphone wound application (Tissue Analytics [TA], Net Health Systems Inc, Florida, USA), versus conventional wound measurements (visual approximation and paper rulers), in patients of Asian ethnicity with venous leg ulcers (VLU). A prospective cohort study of patients presenting with VLU to a specialist wound nurse clinic over a 5-week duration was conducted. Each patient received seven wound measurements: one by a trained wound nurse clinician, and three separate wound measurements using TA on each of the iOS and Android operating systems. Inter-rater and intra-rater reliability between clinical and TA-based measurements were analysed using intra-class correlation statistics, with values of <0.5, 0.5 to 0.75, 0.75 to 0.9, and >0.9 indicating poor, moderate, good and excellent reliability, respectively. 82 patients (51% males), with a mean age at 65.8 years, completed the 5-week study duration. 25 (30%) had underlying diabetes mellitus. Chinese, Malay and Indian ethnicity comprised 68%, 12% and 11%, respectively. The VLU healed in 26 (32%) of patients within the study period. In total, 358 wound episodes with 2334 wound images were analysed. Inter-rater reliability for length, width and area between wound nurse measurements and TA application measurements was good (range 0.799-0.919, P < 0.001). Separate measurements of intra-rater reliability for length, width and area within the iOS or Android systems were excellent (range 0.967-0.985 and range 0.977-0.984 respectively, P < 0.001). Inter-rater reliability between TA used on the iOS and Android systems was also excellent (0.987-0.989, P < 0.001). Tissue Analytics, a smartphone wound application, is a useful adjunct for wound assessment and surveillance in VLU patients of Asian ethnicity.

Indexed as

Mobile ApplicationsVaricose UlcerAgedFemaleHumansMaleProspective StudiesReproducibility of ResultsSmartphonechronic venous insufficiencymachine learningvenous ulcerswound imagingwound management

Identifiers

PMID36787270
PMCPMC9927911
OpenAlexW4292452128

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.