Evidence map›Paper›PMID 30427892›Full record

Observational studyPloS one2018

Development and validation of an algorithm to predict the treatment modality of burn wounds using thermographic scans: Prospective cohort study.

Mario Aurelio Martínez-Jiménez, Jose Luis Ramirez-GarciaLuna, Eleazar Samuel Kolosovas-Machuca, Justin Drager, Francisco Javier González

Registry-linked trialOpen access · goldAbstract readObservational StudyValidation Study
In one paragraph

Observational study in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03876340 (Impact of a Clinical Decision Algorithm on Length of Hospital Stay and Costs of Care of Burned Patients), which is not on this map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.4field-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.

NCT03876340 naunknown statusnot on this map

Impact of a Clinical Decision Algorithm on Length of Hospital Stay and Costs of Care of Burned Patients: a Pragmatic Clinical Trial

TypeinterventionalSponsorHospital Central "Dr. Ignacio Morones Prieto"Ran2018 to 2020Enrolled44ConditionsBurnsArmsTreatment algorithm, Current treatment
3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Facial Burn Healing With a Polylactic Acid Dermal Matrix: A Case Report on Wound Modulation and Graft-Free Epithelialization.Journal of burn care & research : official publication of the American Burn Association · 2025
    Article
  4. Article
  5. Observational
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Review
  14. Thermotropic Liquid Crystals for Temperature Mapping.Frontiers in bioengineering and biotechnology · 2022
    Article
  15. Article
  16. Observational
  17. DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021
    Article
  18. Article
  19. Article
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

5 authors at 2 institutions in 2 countries.

Mario Aurelio Martínez-JiménezDepartment of Surgery, Faculty of Medicine, Universidad Autónoma de San Luis Potosí, San Luis Potosí, SLP, Mexico.
Jose Luis Ramirez-GarciaLunaDepartment of Surgery, Faculty of Medicine, Universidad Autónoma de San Luis Potosí, San Luis Potosí, SLP, Mexico.ORCID 0000-0002-3953-9762
Eleazar Samuel Kolosovas-MachucaCoordinación para la Innovación y Aplicación de la Ciencia y la Tecnología, Universidad Autónoma San Luis Potosí, San Luis Potosí, SLP, Mexico.
Justin DragerDivision of Experimental Surgery, Faculty of Medicine, McGill University. Montreal, QC, Canada.
Francisco Javier GonzálezCoordinación para la Innovación y Aplicación de la Ciencia y la Tecnología, Universidad Autónoma San Luis Potosí, San Luis Potosí, SLP, Mexico.ORCID 0000-0002-1346-9073
Autonomous University of San Luis Potosí · MXMcGill University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe clinical evaluation of a burn wound alone may not be adequate to predict the severity of the injury nor to guide clinical decision making. Infrared thermography provides information about soft tissue viability and has previously been used to assess burn depth. The objective of this study was to determine if temperature differences in burns assessed by infrared thermography could be used predict the treatment modality of either healing by re-epithelization, requiring skin grafts, or requiring amputations, and to validate the clinical predication algorithm in an independent cohort. METHODS AND

findingsTemperature difference (ΔT) between injured and healthy skin were recorded within the first three days after injury in previously healthy burn patients. After discharge, the treatment modality was categorized as re-epithelization, skin graft or amputation. Potential confounding factors were assessed through multiple linear regression models, and a prediction algorithm based on the ΔT was developed using a predictive model using a recursive partitioning Random Forest machine learning algorithm. Finally, the prediction accuracy of the algorithm was compared in the development cohort and an independent validation cohort. Significant differences were found in the ΔT between treatment modality groups. The developed algorithm correctly predicts into which treatment category the patient will fall with 85.35% accuracy. Agreement between predicted and actual treatment for both cohorts was weighted kappa 90%.

conclusionInfrared thermograms obtained at first contact with a wounded patient can be used to accurately predict the definitive treatment modality for burn patients. This method can be used to rationalize treatment and streamline early wound closure.

Indexed as

AlgorithmsThermographyAdultBurnsCohort StudiesFemaleHumansMaleProspective StudiesTemperatureTreatment OutcomeWound HealingYoung Adult

Identifiers

PMID30427892
PMCPMC6235294
OpenAlexW2901944459

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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.