A nomogram model for predicting risk factors and the outcome of skin ulcer
Background Wound healing is a complex process, and numerous factors affect the healing of skin ulcers.Objectives In order to identify the factors associated with wound healing, it is necessary to establish a visualized predictive model for evaluating the risk factors of patients with skin ulcers and...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2025.2525404 |
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| author | Honglin Jia Yang Tan Hong Li Xiaoqing Bu Lingfei Li Xia Lei |
| author_facet | Honglin Jia Yang Tan Hong Li Xiaoqing Bu Lingfei Li Xia Lei |
| author_sort | Honglin Jia |
| collection | DOAJ |
| description | Background Wound healing is a complex process, and numerous factors affect the healing of skin ulcers.Objectives In order to identify the factors associated with wound healing, it is necessary to establish a visualized predictive model for evaluating the risk factors of patients with skin ulcers and to validate its effectiveness.Methods A retrospective observational study was conducted on 453 patients with skin ulcers admitted to the Dermatology ward of the Army Medical Center (Daping Hospital) in Chongqing, China, from January 2011 to July 2022. The nomogram was formulated according to a multivariate logistic regression analysis identifying seven potential predictors of prognosis, including age, area, pre-admission course, etiology, diabetes, medical treatment, and self-medication. This nomogram model was validated by bootstrap internal validation (1000 replicated samplings).Results Logistic regression analysis showed that age, skin ulcer area, pre-admission course, etiology, comorbidity of diabetes, medical treatment, and self-medication were independently related to skin ulcer prognosis. These indicators were utilized to develop nomogram models. The predictive ability for skin ulcer prognosis was 0.814 based on the area under the curve values. The calibration curve showed a close match between the actual and predicted probabilities. Decision-making analysis demonstrated the clinical application value of this nomogram.Conclusion The prediction nomogram developed in this study exhibits good accuracy in predicting the risk factors of skin ulcers and provides an objective tool for clinical staff to assess and target the risk factors concerning the prognosis of skin ulcers. |
| format | Article |
| id | doaj-art-8bcc33fb176949ed80c039a461ce36e8 |
| institution | Kabale University |
| issn | 0785-3890 1365-2060 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj-art-8bcc33fb176949ed80c039a461ce36e82025-08-20T03:31:41ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602025-12-0157110.1080/07853890.2025.2525404A nomogram model for predicting risk factors and the outcome of skin ulcerHonglin Jia0Yang Tan1Hong Li2Xiaoqing Bu3Lingfei Li4Xia Lei5Department of Dermatology, Army Medical Center (Daping Hospital), Army Medical University, Chongqing, PR ChinaDepartment of Dermatology, Army Medical Center (Daping Hospital), Army Medical University, Chongqing, PR ChinaSchool of Public Health, Chongqing Medical University, Chongqing, PR ChinaSchool of Public Health, Chongqing Medical University, Chongqing, PR ChinaDepartment of Dermatology, Army Medical Center (Daping Hospital), Army Medical University, Chongqing, PR ChinaDepartment of Dermatology, Army Medical Center (Daping Hospital), Army Medical University, Chongqing, PR ChinaBackground Wound healing is a complex process, and numerous factors affect the healing of skin ulcers.Objectives In order to identify the factors associated with wound healing, it is necessary to establish a visualized predictive model for evaluating the risk factors of patients with skin ulcers and to validate its effectiveness.Methods A retrospective observational study was conducted on 453 patients with skin ulcers admitted to the Dermatology ward of the Army Medical Center (Daping Hospital) in Chongqing, China, from January 2011 to July 2022. The nomogram was formulated according to a multivariate logistic regression analysis identifying seven potential predictors of prognosis, including age, area, pre-admission course, etiology, diabetes, medical treatment, and self-medication. This nomogram model was validated by bootstrap internal validation (1000 replicated samplings).Results Logistic regression analysis showed that age, skin ulcer area, pre-admission course, etiology, comorbidity of diabetes, medical treatment, and self-medication were independently related to skin ulcer prognosis. These indicators were utilized to develop nomogram models. The predictive ability for skin ulcer prognosis was 0.814 based on the area under the curve values. The calibration curve showed a close match between the actual and predicted probabilities. Decision-making analysis demonstrated the clinical application value of this nomogram.Conclusion The prediction nomogram developed in this study exhibits good accuracy in predicting the risk factors of skin ulcers and provides an objective tool for clinical staff to assess and target the risk factors concerning the prognosis of skin ulcers.https://www.tandfonline.com/doi/10.1080/07853890.2025.2525404Skin ulcernomogrampredictive modelretrospective study |
| spellingShingle | Honglin Jia Yang Tan Hong Li Xiaoqing Bu Lingfei Li Xia Lei A nomogram model for predicting risk factors and the outcome of skin ulcer Annals of Medicine Skin ulcer nomogram predictive model retrospective study |
| title | A nomogram model for predicting risk factors and the outcome of skin ulcer |
| title_full | A nomogram model for predicting risk factors and the outcome of skin ulcer |
| title_fullStr | A nomogram model for predicting risk factors and the outcome of skin ulcer |
| title_full_unstemmed | A nomogram model for predicting risk factors and the outcome of skin ulcer |
| title_short | A nomogram model for predicting risk factors and the outcome of skin ulcer |
| title_sort | nomogram model for predicting risk factors and the outcome of skin ulcer |
| topic | Skin ulcer nomogram predictive model retrospective study |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2025.2525404 |
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