Evidence map›Paper›PMID 40129968›Full record

ArticleJournal of biomedical optics2025

Rokeya Khatun, Kaisei Okura, Md Anowar Parvez, Kazuhiro Yashiro, Yuki Nagahama, Yasuyuki Tsunoi, Satoko Kawauchi, Daizoh Saitoh, Shunichi Sato, Izumi Nishidate

Abstract read
In one paragraph

Article in Journal of biomedical optics, 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

10 authors.

Rokeya KhatunTokyo University of Agriculture and Technology, Graduate School of Bio-Applications and Systems Engineering, Tokyo, Japan.
Kaisei OkuraTokyo University of Agriculture and Technology, Department of Biomedical Engineering, Tokyo, Japan.
Md Anowar ParvezChittagong Veterinary and Animal Sciences University, Department of Medicine and Surgery, Chittagong, Bangladesh.
Kazuhiro YashiroTokyo University of Agriculture and Technology, Graduate School of Bio-Applications and Systems Engineering, Tokyo, Japan.
Yuki NagahamaTokyo University of Agriculture and Technology, Department of Biomedical Engineering, Tokyo, Japan.
Yasuyuki TsunoiNational Defense Medical College Research Institute, Division of Bioinformation and Therapeutic Systems, Saitama, Japan.ORCID 0000-0002-9359-2396
Satoko KawauchiNational Defense Medical College Research Institute, Division of Bioinformation and Therapeutic Systems, Saitama, Japan.
Daizoh SaitohKokushikan University, Graduate School of Emergency Medical System, Tokyo, Japan.
Shunichi SatoNational Defense Medical College Research Institute, Division of Bioinformation and Therapeutic Systems, Saitama, Japan.ORCID 0000-0002-7658-8635
Izumi NishidateTokyo University of Agriculture and Technology, Graduate School of Bio-Applications and Systems Engineering, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Burn injuries are a global public health problem and are estimated to cause more than 150,000 deaths annually. Even non-fatal burns result in prolonged hospitalization, disfigurement, and disability. The depth of the burn injury is crucial information for selecting adequate treatment for burns. The most common, convenient, and widely used method for assessing burn severity is visual examination, but the accuracy of this method is insufficient, at only 60% to 75%. Rapid and accurate assessment of burn severity is critical for optimal management and treatment of burn patients. Methods of burn severity assessment that are inexpensive, simple, rapid, non-contact, and non-invasive are thus needed. Aim: We aim to propose an approach to visualize the spatial distribution of burn severity using hemoglobin parameters estimated from a snapshot red-green-blue (RGB) color image and to demonstrate the feasibility of this proposed approach for differentiating burn severity in a rat model of scald burn injury. Approach: The approach to creating a spatial map of burn severity was based on canonical discriminant analysis (CDA) of total hemoglobin concentration, tissue oxygen saturation, and methemoglobin saturation as estimated from RGB color images. Burns of two different degrees of severity were created in rat dorsal skin by 10-s exposure to water maintained at 70°C and 78°C. RGB color images for the dorsal regions were acquired under anesthesia before burn injury and at 24, 48, and 72 h after injury. Results: Most areas of images in the groups with skin exposed to 70°C, 78°C, and 37°C water were classified as 70°C burn, 78°C burn, and non-burned normal skin, respectively, over 48 to 72 h. In contrast, classification images of the skin group exposed to 70°C water for 24 h showed a mixture of non-burned normal skin and 70°C burned areas, suggesting that burn severity was heterogeneous. Conclusions: The proposed approach combining RGB color imaging and CDA appears promising for differentiating 78°C burns from 70°C burns and non-burned normal skin and non-burned normal skin from 70°C and 78°C burns at 24 to 72 h after burn injury in a rat model of scald burn injury.

Indexed as

BurnsHemoglobinsSkinAnimalsDisease Models, AnimalMaleRatsRats, Sprague-DawleyHemoglobinsburn severitycanonical discriminant analysismethemoglobin saturationred–green–blue cameratissue oxygen saturationtotal hemoglobin

Identifiers

PMID40129968
PMCPMC11931295

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.