{"title":"Development of a major amputation prediction model and nomogram in patients with diabetic foot.","authors":"Yi Chen, Jun Zhuang, Caizhe Yang","doi":"10.1093/postmj/qgae087","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Diabetes mellitus, as one of the world's fastest-growing diseases, is a chronic metabolic disease that has now become a public health problem worldwide. The purpose of this research was to develop a predictive nomogram model to demonstrate the risk of major amputation in patients with diabetic foot.</p><p><strong>Methods: </strong>A total of 634 Type 2 Diabetes Mellitus (T2DM) patients with diabetic foot ulcer hospitalized at the Air Force Medical Center between January 2018 and December 2023 were included in our retrospective study. There were 468 males (73.82%) and 166 females (26.18%) with an average age of 61.64 ± 11.27 years and average body mass index of 24.45 ± 3.56 kg/m2. The predictive factors were evaluated by single factor logistic regression and multiple logistic regression and the predictive nomogram was established with these features. Receiver operating characteristic (subject working characteristic curve) and their area under the curve, calibration curve, and decision curve analysis of this major amputation nomogram were assessed. Model validation was performed by the internal validation set, and the receiver operating characteristic curve, calibration curve, and decision curve analysis were used to further evaluate the nomogram model performance and clinical usefulness.</p><p><strong>Results: </strong>Predictors contained in this predictive model included body mass index, ulcer sites, hemoglobin, neutrophil-to-lymphocyte ratio, blood uric acid (BUA), and ejection fraction. Good discrimination with a C-index of 0.957 (95% CI, 0.931-0.983) in the training group and a C-index of 0.987 (95% CI, 0.969-1.000) in the validation cohort were showed with this predictive model. Good calibration were displayed. The decision curve analysis showed that using the nomogram prediction model in the training cohort and validation cohort would respectively have clinical benefits.</p><p><strong>Conclusion: </strong>This new nomogram incorporating body mass index, ulcer sites, hemoglobin, neutrophil-to-lymphocyte ratio, BUA, and ejection fraction has good accuracy and good predictive value for predicting the risk of major amputation in patients with diabetic foot.</p>","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":"908-916"},"PeriodicalIF":3.6000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Postgraduate Medical Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/postmj/qgae087","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Diabetes mellitus, as one of the world's fastest-growing diseases, is a chronic metabolic disease that has now become a public health problem worldwide. The purpose of this research was to develop a predictive nomogram model to demonstrate the risk of major amputation in patients with diabetic foot.
Methods: A total of 634 Type 2 Diabetes Mellitus (T2DM) patients with diabetic foot ulcer hospitalized at the Air Force Medical Center between January 2018 and December 2023 were included in our retrospective study. There were 468 males (73.82%) and 166 females (26.18%) with an average age of 61.64 ± 11.27 years and average body mass index of 24.45 ± 3.56 kg/m2. The predictive factors were evaluated by single factor logistic regression and multiple logistic regression and the predictive nomogram was established with these features. Receiver operating characteristic (subject working characteristic curve) and their area under the curve, calibration curve, and decision curve analysis of this major amputation nomogram were assessed. Model validation was performed by the internal validation set, and the receiver operating characteristic curve, calibration curve, and decision curve analysis were used to further evaluate the nomogram model performance and clinical usefulness.
Results: Predictors contained in this predictive model included body mass index, ulcer sites, hemoglobin, neutrophil-to-lymphocyte ratio, blood uric acid (BUA), and ejection fraction. Good discrimination with a C-index of 0.957 (95% CI, 0.931-0.983) in the training group and a C-index of 0.987 (95% CI, 0.969-1.000) in the validation cohort were showed with this predictive model. Good calibration were displayed. The decision curve analysis showed that using the nomogram prediction model in the training cohort and validation cohort would respectively have clinical benefits.
Conclusion: This new nomogram incorporating body mass index, ulcer sites, hemoglobin, neutrophil-to-lymphocyte ratio, BUA, and ejection fraction has good accuracy and good predictive value for predicting the risk of major amputation in patients with diabetic foot.
期刊介绍:
Postgraduate Medical Journal is a peer reviewed journal published on behalf of the Fellowship of Postgraduate Medicine. The journal aims to support junior doctors and their teachers and contribute to the continuing professional development of all doctors by publishing papers on a wide range of topics relevant to the practicing clinician and teacher. Papers published in PMJ include those that focus on core competencies; that describe current practice and new developments in all branches of medicine; that describe relevance and impact of translational research on clinical practice; that provide background relevant to examinations; and papers on medical education and medical education research. PMJ supports CPD by providing the opportunity for doctors to publish many types of articles including original clinical research; reviews; quality improvement reports; editorials, and correspondence on clinical matters.