Evidence map›Paper›PMID 34817552›Full record

ArticleJAMA surgery2022

Practical Computer Vision Application to Compute Total Body Surface Area Burn: Reappraising a Fundamental Burn Injury Formula in the Modern Era.

Jeff Choi, Advait Patil, Edward Vendrow, Gavin Touponse, Layla Aboukhater, Joseph D Forrester, David A Spain

Open access · greenAbstract read
In one paragraph

Article in JAMA surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Enhanced Trauma Video Review With Computer Vision: Trauma Resuscitation Phase Segmentation and Procedure Detection.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2025
    Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Jeff ChoiDepartment of Surgery, Stanford University, Stanford, California.
Advait PatilSurgeons Writing About Trauma, Stanford University, Stanford, California.
Edward VendrowSurgeons Writing About Trauma, Stanford University, Stanford, California.
Gavin TouponseSurgeons Writing About Trauma, Stanford University, Stanford, California.
Layla AboukhaterSurgeons Writing About Trauma, Stanford University, Stanford, California.
Joseph D ForresterDepartment of Surgery, Stanford University, Stanford, California.
David A SpainDepartment of Surgery, Stanford University, Stanford, California.
Stanford University · USFielding Graduate University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Critical burn management decisions rely on accurate percent total body surface area (%TBSA) burn estimation. Existing %TBSA burn estimation models (eg, Lund-Browder chart and rule of nines) were derived from a linear formula and a limited number of individuals a century ago and do not reflect the range of body habitus of the modern population. Objective: To develop a practical %TBSA burn estimation tool that accounts for exact burn injury pattern, sex, and body habitus. Design, Setting, and Participants: This population-based cohort study evaluated the efficacy of a computer vision algorithm application in processing an adult laser body scan data set. High-resolution surface anthropometry laser body scans of 3047 North American and European adults aged 18 to 65 years from the Civilian American and European Surface Anthropometry Resource data set (1998-2001) were included. Of these, 1517 participants (49.8%) were male. Race and ethnicity data were not available for analysis. Analyses were conducted in 2020. Main Outcomes and Measures: The contributory %TBSA for 18 body regions in each individual. Mobile application for real-time %TBSA burn computation based on sex, habitus, and exact burn injury pattern. Results: Of the 3047 individuals aged 18 to 65 years for whom body scans were available, 1517 (49.8%) were male. Wide individual variability was found in the extent to which major body regions contributed to %TBSA, especially in the torso and legs. Anterior torso %TBSA increased with increasing body habitus (mean [SD], 15.1 [0.9] to 19.1 [2.0] for male individuals; 15.1 [0.8] to 18.0 [1.7] for female individuals). This increase was attributable to increase in abdomen %TBSA (mean [SD], 5.3 [0.7] to 8.7 [1.8]) among male individuals and increase in abdomen (mean [SD], 4.6 [0.6] to 6.8 [1.7]) and pelvis (mean [SD], 1.5 [0.2] to 2.9 [0.9]) %TBSAs among female individuals. For most body regions, Lund-Browder chart and rule of nines estimates fell outside the population's measured interquartile ranges. The mobile application tested in this study, Burn Area, facilitated accurate %TBSA burn computation based on exact burn injury pattern for 10 sex and body habitus-specific models. Conclusions and Relevance: Computer vision algorithm application to a large laser body scan data set may provide a practical tool that facilitates accurate %TBSA burn computation in the modern era.

Indexed as

Body Surface AreaLasersMobile ApplicationsAdolescentAdultAgedAlgorithmsBurnsFemaleHumansImaging, Three-DimensionalMaleMiddle Aged

Identifiers

PMID34817552
PMCPMC8613700
OpenAlexW3215499644

What OpenQuestion holds

Textmetadata
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.