Use of Infrared Thermometry to Observe Temperature Variation Associated with the Healing Process in Wounds and Ulcers: TIHUAP Cohort Study Protocol
Abstract
:1. Introduction
Aims
- To determine if there is consistency between the size of the lesion as measured with the equation for the percentage reduction of wound area over time and the size category of the Resvech 2.0 scale.
- To identify the concordance between temperature differences between the perilesional skin and the wound bed and the risk of infection category on the Resvech 2.0 scale.
2. Materials and Methods
2.1. Design
2.2. Study Settings
2.3. Participants
- -
- 18 years of age or older at the time of joining the study.
- -
- Presenting one or more wounds with a surface area greater than 1 cm2 and less than 34 cm2 anywhere on the body surface.
- -
- Willing to sign the written informed consent.
- -
- Presenting wounds with a tumoral, infectious, arterial etiology, burns, extensive cellulitis, or exudative edemas.
- -
- Having a disease with a life expectancy of less than 18 months.
2.4. Variables and Instruments
- -
- Prediction of the healing process based on lesion size changes.
- -
- Healing index
- -
- Healing process, based on temperature differences.
Variables | Instruments |
---|---|
Prediction of the healing process based on changes in lesion size. | Percentage reduction of wound area over time. Calculated as VA = A0 − A1/t. Where Av is the variation of the lesion area, A0 is the reference control area (1st calculation of Kundin M0), A1 is the monthly control area (M1, M2…), and t is the time variable between A0 and A1 expressed in days [18]. |
Healing index | Resvech 2.0 scale [12] |
Healing process based on temperature differences. | Thermal index (TI) [18] TI = (([intralesional_median] − [ perilesional_median]) × [isotherm_area])/[monthly_kundin] |
Temperature point coordinate | Grid available in 3 sizes with coordinates (Figure 1). |
Temperatures (wound bed, perilesional, body) | Hand-held, 4-in-1 infrared thermometer, IDOIT brand. |
Wound size | Kundin formula. Calculated as: length × width × 0.785 (cm) Performed using a metric template, available for download on the institution’s intranet. |
Photograph of wound | Canon PowerShot 1300 16-megapixel camera (Canon, Tokyo, Japan). Taken without flash. |
Comorbidity | Dyslipidemia, high blood pressure, heart disease, venous insufficiency, nephropathy, thyroid disorders, peripheral artery disease, immunodeficiency, diabetes mellitus. |
Sociodemographic and clinical data | Sex, age, weight, body mass index, limited mobility, physical activity (sufficiently or insufficiently active) |
Dependence level | Barthel Index, which assesses 10 activities with scores between 0 and 100, with 0 being maximum dependence and 100 being maximum independence [30]. |
Nutritional status | Mini Nutritional Assessment (MNA), a questionnaire with 6 items and scores between 0 and 12, with 0 being normal nutritional status and 12 malnutrition status [31]. |
Wound-related variables | Type of lesion (open wound, surgical dehiscence, sebaceous cyst debridement, pilonidalcystectomy, pressure ulcer, vascular ulcer, diabetic foot ulcer.) Infection of the wound prior to study Prior antibiotic treatment of the wound Wound healing time expressed in days (from the start of the wound to the day of inclusion in the study). Need for wound debridement. |
2.5. Recruitment, Consent and Data Collection
2.6. Study Procedures
2.7. Sample Size Calculation
2.8. Validity and Reliability
2.9. Statistical Analysis
3. Expected Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- National Pressure Ulcer Advisory Panel; EPUAP; PPPIA. Prevention and Treatment of Pressure Ulcers: Quick Reference Guide; Clinical Practice Guideline; National Pressure Ulcer Advisory Panel: Westford, MA, USA, 2014; pp. 1–75. [Google Scholar]
- Roldán Valenzuela, A.; Ibáñez Clemente, P.; Alba Moratilla, C.; Roviralta Gómez, S.; Tormo, M.T.C.; Vargas, P.G.; Barreno, D.P.; Caballero, M.A.N.; Imas, G.E.; Agúndez, A.F.; et al. Guía de Práctica Clínica Consenso sobre Úlceras Vasculares y Pie Diabético de la Asociación Española de Enfermería Vascular y Heridas (AEEVH). Asociación Española de Enfermería Vascular y Heridas. 2017. Available online: https://aeevh.org/wp-content/uploads/2020/04/Guia-de-Practica-Clinica-web.pdf (accessed on 23 May 2023).
- García Fernández, F.P.; Soldevilla Ágreda, J.; Verdú Soriano, J.; López Casanova, P.; Rodríguez Palma, M.; Torra Bou, J.E. Documento Técnico No II “Clasificación-Cetegorización de las Lesiones Citáneas Relacionadas con la Dependencia”, 3rd ed.; Grupo Nacional para el Estudio y Asesoramiento en Úlceras Por Presión y Heridas Cónicas: Logroño, Spain, 2021; pp. 1–62. [Google Scholar]
- Laura, M.; Maja, O.; Ram, B.; Zee, U.; Schmidtchen Artur, C.J. Prevalence of Chronic Wounds SR—Accepted Manuscript 2019. Available online: http://hdl.handle.net/10044/1/66134 (accessed on 22 May 2023).
- García Fernández, F.P.; Pancorbo Hidalgo, P.L.; Soldevilla Agreda, J.J.; Torra i Bou, J.E.; Verdú Soriano, J. Epidemiología de las úlceras por Presión en España en 2013. Gerokomos 2014, 25, 162–170. Available online: http://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S1134-928X2014000400006 (accessed on 1 March 2023).
- Agreda, J.J.S.; Torra, I.; Bou, J.E.; Soriano, J.V.; Casanova, P.L. 3rd national survey of the prevalence of pressure ulcers in Spain, 2009. Epidemiology and defining variables in lesions and patients. Gerokomos 2011, 22, 77–790. [Google Scholar]
- Olsson, M.; Järbrink, K.; Divakar, U.; Bajpai, R.; Upton, Z.; Schmidtchen, A.; Car, J. The humanistic and economic burden of chronic wounds: A systematic review. Wound Repair Regen. 2019, 27, 114–125. [Google Scholar] [CrossRef] [Green Version]
- Díaz-Herrera, M.A.; Baltà-Domínguez, L.; Blasco-García, M.C.; Fernández-Garzón, M.; Fuentes-Camps, E.M. Guia de Pràctica Clínica: Grup de Ferides Cròniques. Institut Català de la Salut. 2018. Available online: http://ics.gencat.cat/web/.content/documents/assistencia/gpc/gpc_ulceres_extremitats_inferiors.pdf (accessed on 2 March 2023).
- Phillips, C.J.; Humphreys, I.; Fletcher, J.; Harding, K.; Chamberlain, G.; Macey, S. Estimating the costs associated with the management of patients with chronic wounds using linked routine data. Int. Wound J. 2016, 13, 1193–1197. [Google Scholar] [CrossRef] [PubMed]
- Coleman, S.; Gorecki, C.; Nelson, E.A.; Closs, S.J.; Defloor, T.; Halfens, R.; Farrin, A.; Brown, J.; Schoonhoven, L.; Nixon, J. Patient risk factors for pressure ulcer development: Systematic review. Int. J. Nurs. Stud. 2013, 50, 974–1003. [Google Scholar] [CrossRef] [Green Version]
- Lachenbruch, C.; Tzen, Y.-T.; Brienza, D.; Karg, P.E.; Lachenbruch, P.A. Relative contributions of interface pressure, shear stress, and temperature on ischemic-induced, skin-reactive hyperemia in healthy volunteers: A repeated measures laboratory study. Ostomy Wound Manag. 2015, 61, 16–25. [Google Scholar]
- Restrepo-Medrano, J.C.; Verdú Soriano, J. Desarrollo de un índice de medida de la evolución hacia la cicatrización de las heridas crónicas. Gerokomos 2011, 22, 176–183. [Google Scholar] [CrossRef] [Green Version]
- Crawford, F.; Nicolson, D.J.; Amanna, A.E.; Martin, A.; Gupta, S.; Leese, G.P.; Heggie, R.; Chappell, F.M.; McIntosh, H.H. Preventing foot ulceration in diabetes: Systematic review and meta-analyses of RCT data. Diabetologia 2020, 63, 49–64. [Google Scholar] [CrossRef] [Green Version]
- Sen, C.K.; Ghatak, S.; Gnyawali, S.C.; Roy, S.; Gordillo, G.M. Cutaneous Imaging Technologies in Acute Burn and Chronic Wound Care. Plast. Reconstr. Surg. 2016, 138, 119S–128S. [Google Scholar] [CrossRef] [Green Version]
- Gottrup, F.; Apelqvist, J.; Bjarnsholt, T.; Cooper, R.; Moore, Z.; Peters, E.; Probst, S. EWMA Document: Evidence, controversies and suggestions. J. Wound Care 2013, 22, S1–S89. [Google Scholar] [CrossRef]
- Bhargava, A.; Chanmugam, A.; Herman, C. Heat transfer model for deep tissue injury: A step towards an early thermographic diagnostic capability. Diagn. Pathol. 2014, 9, 36. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fierheller, M.; Sibbald, R.G. A clinical investigation into the relationship between increased periwound skin temperature and local wound infection in patients with chronic leg ulcers. Adv. Ski. Wound Care 2010, 23, 369–379. [Google Scholar] [CrossRef] [PubMed]
- Bharara, M.; Schoess, J.; Nouvong, A.; Armstrong, D.G. Wound inflammatory index: A “proof of concept” study to assess wound healing trajectory. J. Diabetes Sci. Technol. 2010, 4, 773–779. [Google Scholar] [CrossRef] [Green Version]
- Adam, M.; Ng, E.Y.K.; Tan, J.H.; Heng, M.L.; Tong, J.W.K.; Acharya, U.R. Computer aided diagnosis of diabetic foot using infrared thermography: A review. Comput. Biol. Med. 2017, 91, 326–336. [Google Scholar] [CrossRef] [PubMed]
- Armstrong, D.G.; Holtz-Neiderer, K.; Wendel, C.; Mohler, M.J.; Kimbriel, H.R.; Lavery, L.A. Skin Temperature Monitoring Reduces the Risk for Diabetic Foot Ulceration in High-risk Patients. Am. J. Med. 2007, 120, 1042–1046. Available online: https://linkinghub.elsevier.com/retrieve/pii/S0002934307007395 (accessed on 30 March 2020). [CrossRef]
- Lu, M.; Yee, A.; Meng, F.; Harmon, J.; Hinduja, S.; Yi, S. Enhance wound healing monitoring through a thermal imaging based smartphone app. In Proceedings of the Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, Houston, TX, USA, 10–15 February 2018. [Google Scholar]
- Maliyar, K.; Persaud-Jaimangal, R.; Sibbald, R.G. Associations among Skin Surface pH, Temperature, and Bacterial Burden in Wounds. Adv. Ski. Wound Care 2020, 33, 180–185. [Google Scholar] [CrossRef]
- Mufti, A.; Coutts, P.; Sibbald, R.G. Validation of commercially available infrared thermometers for measuring skin surface temperature associated with deep and surrounding wound infection. Adv. Ski. Wound Care 2015, 28, 11–16. [Google Scholar] [CrossRef]
- García De La Peña, R.; Benhamú Benhamú, S.; Jiménez Cristino, M.D.; Grande del Arco, J.; Gijón Noguerón, G. La temperatura del pie como factor predictivo de aparición de úlceras en la Diabetes Mellitus. Rev. Int. Cienc. Podol. 2019, 13, 115–129. [Google Scholar] [CrossRef]
- Hoogeveen, R.C.; Dorresteijn, J.A.; Kriegsman, D.M.; Valk, G.D. Complex interventions for preventing diabetic foot ulceration. Cochrane Database Syst. Rev. 2015, 2015, CD007610. [Google Scholar] [CrossRef]
- Medrano Jiménez, R.; Mar, M.; Rius, G.; Castillo, O.G.; Ruiz Messeguer, M.; Medrano Baeza, B.; Vendrellet, M.A. Plantar Thermometry and Diabetic Foot Risk in Primary Care. Results of the Thermopiedi Study. Butlletí l’Atenció Primària Catalunya 2023, 36, 1–9. [Google Scholar]
- Soldevilla Agreda, J.J.; Bou, J.E.T.I.; Posnett, J.; Soriano, J.V.; San Miguel, L.; Santos, J.M.M. An approach to the economic impact of the treatment of pressure ulcers in Spain. Gerokomos 2007, 18, 201–210. [Google Scholar]
- Gatt, A.; Cassar, K.; Falzon, O.; Ellul, C.; Camilleri, K.P.; Gauci, J.; Mizzi, S.; Mizzi, A.; Sturgeon, C.; Chockalingam, N.; et al. The identification of higher forefoot temperatures associated with peripheral arterial disease in type 2 diabetes mellitus as detected by thermography. Prim. Care Diabetes 2018, 12, 312–318. [Google Scholar] [CrossRef] [PubMed]
- Xue, E.Y.; Chandler, L.K.; Viviano, S.L.; Keith, J.D. Use of FLIR ONE Smartphone Thermography in Burn Wound Assessment. Ann. Plast. Surg. 2018, 80, S236–S238. [Google Scholar] [CrossRef]
- Bernaola-Sagardui, I. Validation of the Barthel Index in the Spanish population. Enferm. Clin. 2018, 28, 210–211. [Google Scholar] [CrossRef] [PubMed]
- Castro-Vega, I.; Veses Martín, S.; Cantero Llorca, J.; Salom Vendrell, C.; Bañuls, C.; Hernández-Mijares, A. Validación del cribado nutricional malnutrition screening tool comparado con la valoración nutricional completa y otros cribados en distintos ámbitos sociosanitarios. Nutr. Hosp. 2018, 35, 351–358. [Google Scholar] [PubMed] [Green Version]
- Harris, P.A.; Taylor, R.; Thielke, R.; Payne, J.; Gonzalez, N.; Conde, J.G. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 2009, 42, 377–381. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Atkin, L.; Bućko, Z.; Montero, E.C.; Cutting, K.; Moffatt, C.; Probst, A.; Romanelli, M.; Schultz, G.S.; Tettelbach, W. Implementing TIMERS: The race against hard-to-heal wounds Inflammation/infection Social factors Edge Regeneration Moisture Tissue. J. Wound Care 2019, 28, S1–S50. [Google Scholar] [CrossRef] [Green Version]
- Carrière, M.E.; de Haas, L.E.; Pijpe, A.; Vries, A.M.; Gardien, K.L.M.; Zuijlen, P.P.M.; Jaspers, M.E. Validity of thermography for measuring burn wound healing potential. Wound Repair Regen. 2020, 28, 347–354. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Howell-Jones, R.S.; Wilson, M.J.; Hill, K.E.; Howard, A.J.; Price, P.E.; Thomas, D. A review of the microbiology, antibiotic usage and resistance in chronic skin wounds. J. Antimicrob. Chemother. 2005, 55, 143–149. [Google Scholar] [CrossRef] [Green Version]
- Cosgrove, S.E.; Carmeli, Y. The impact of antimicrobial resistance on health and economic outcomes. Clin. Infect. Dis. 2003, 36, 1433–1437. [Google Scholar]
Activities | Recruitment | 1st Visit | Weekly | Monthly | Final |
---|---|---|---|---|---|
Information | X | X | |||
Informed consent | X | ||||
General data | X | ||||
Photograph | X | X | X | ||
Resvesh 2.0 scale | X | X | X | ||
Kundin Formula | X | X | X | ||
Percentage reduction of wound area over time | X | X | |||
Control temperature | X | X | X | X | |
Wound bed temperature | X | X | X | X | |
Perilesional temperature | X | X | X | X | |
Thermal index | X | X |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Iruela Sánchez, M.; García-Sierra, R.; Medrano-Jiménez, R.; Bonachela-Mompart, D.; Maella-Rius, N.; Soria-Martín, E.; Isnard-Blanchar, M.; Torán-Monserrat, P. Use of Infrared Thermometry to Observe Temperature Variation Associated with the Healing Process in Wounds and Ulcers: TIHUAP Cohort Study Protocol. Healthcare 2023, 11, 1750. https://doi.org/10.3390/healthcare11121750
Iruela Sánchez M, García-Sierra R, Medrano-Jiménez R, Bonachela-Mompart D, Maella-Rius N, Soria-Martín E, Isnard-Blanchar M, Torán-Monserrat P. Use of Infrared Thermometry to Observe Temperature Variation Associated with the Healing Process in Wounds and Ulcers: TIHUAP Cohort Study Protocol. Healthcare. 2023; 11(12):1750. https://doi.org/10.3390/healthcare11121750
Chicago/Turabian StyleIruela Sánchez, Mercè, Rosa García-Sierra, Rafael Medrano-Jiménez, Diana Bonachela-Mompart, Natalia Maella-Rius, Esther Soria-Martín, Mar Isnard-Blanchar, and Pere Torán-Monserrat. 2023. "Use of Infrared Thermometry to Observe Temperature Variation Associated with the Healing Process in Wounds and Ulcers: TIHUAP Cohort Study Protocol" Healthcare 11, no. 12: 1750. https://doi.org/10.3390/healthcare11121750
APA StyleIruela Sánchez, M., García-Sierra, R., Medrano-Jiménez, R., Bonachela-Mompart, D., Maella-Rius, N., Soria-Martín, E., Isnard-Blanchar, M., & Torán-Monserrat, P. (2023). Use of Infrared Thermometry to Observe Temperature Variation Associated with the Healing Process in Wounds and Ulcers: TIHUAP Cohort Study Protocol. Healthcare, 11(12), 1750. https://doi.org/10.3390/healthcare11121750