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Enregistrement W2772708925 · doi:10.1097/01.asw.0000527352.75716.70

Infrared Skin Thermometry: Validating and Comparing Techniques to Detect Periwound Skin Infection

2017· article· en· W2772708925 sur OpenAlexaffabout
Asfandyar Mufti, Ranjani Somayaji, Patricia Coutts, R. Gary Sibbald

Notice bibliographique

RevueAdvances in Skin & Wound Care · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueThermal Regulation in Medicine
Établissements canadiensToronto Public HealthUniversity of CalgaryPetro-Canada
Organismes subventionnairesnon disponible
Mots-clésMedicineSkin temperatureDermatologyWound careSurgeryMedical physics

Résumé

récupéré en direct d'OpenAlex

OBJECTIVE: Diagnosis of wound infection can be challenging because it relies on a combination of clinical signs and symptoms that are often nonspecific. Increased periwound cutaneous temperature is a classic sign of deep and surrounding wound infection, and its quantitative measurement is one of the most reliable and valid clinical signs of deep and surrounding skin infection at the bedside. Skin surface temperature differences may be detected using commercially available noncontact infrared thermometers. However, techniques to detect temperature using noncontact infrared thermometers vary, and no studies have evaluated these methods. Two such measurement techniques include the "4-point" and "whole-wound" scanning methods. This study assessed the ability of different infrared thermometers using the aforementioned techniques to detect clinically meaningful differences in periwound cutaneous temperatures used in the diagnosis of wound infection. METHODS: A prospective cohort study was conducted from 2015 to 2016 of consenting adult patients 18 years or older with an open wound attending a regional wound care clinic. One hundred patients with wounds underwent surface temperature measurement. Infection was not a specific inclusion criterion as the primary objective was to conduct a comparative assessment of infrared thermometry devices. Demographic data (age, height, weight, gender, and ethnicity) were also collected. Each wound was measured using 4 different noncontact infrared thermometers: Exergen DermaTemp 1001 (Exergen Corporation, Watertown, Massachusetts), Mastercraft Digital Temperature Reader (Mastercraft, Toronto, Ontario, Canada), Mastercool MSC52224-A (Mastercool Inc, Randolph, New Jersey), and Etekcity ETC-8250 Temperature Heat Pen (Etekcity, Anaheim, California). Data analysis was based on a comparison of 4 periwound skin surface temperature measurement differences (ΔT in degrees Fahrenheit) between the wound site and an equivalent contralateral control site. OUTCOME MEASURES: The primary outcome of the ability of each thermometer to detect a clinically significant difference in temperature was assessed with χ analysis. Paired t tests were conducted to compare the ΔT measurements of each specific thermometry device between the 2 measurement techniques. Pearson product moment correlation coefficients were calculated for the temperature ΔT for both measuring techniques for all devices to determine level of agreement. A 1-way analysis of variance was conducted to compare temperature measurements among the infrared thermometry devices. MAIN RESULTS: There was no significant difference in the ability of each thermometer to detect a clinically meaningful difference of 3° F by either the 4-point (P = .10) or whole-wound techniques (P = .67). When a definition of 4° F was used, results were similar (4-point, P = .15; whole wound, P = .20). Comparisons among devices and techniques showed strong correlations (>0.80). Etekcity ETC-8250 and the 4-point measurement compared with the Exergen device using the whole-wound technique had a correlation coefficient of 0.72. Spearman ρ demonstrated a similarly high degree of correlation between techniques and devices, and only the Etekcity ETC-8250 device had a coefficient of 0.71 to 0.90 when compared with others. Paired t testing for each thermometry device comparing measurement techniques for raw temperatures ΔT demonstrated no significant difference (P > .05). No statistical differences among the ΔT values for the 3 different thermometers were noted when using the whole-wound method (P = .095). Similarly, no significant differences among the ΔT values were noted for the 4 different thermometers when using the 4-point method (P = .10). CONCLUSIONS: The results of this study demonstrate that both the 4-point and whole-wound methods of temperature acquisition using cost-efficient infrared thermometers provide accurate and similar results in clinical wound care settings.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,596
Score d'incertitude au seuil0,956

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,341
Écart entre enseignants0,326 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations22
Publié2017
Routes d'admission2
Résumé présentoui

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