{"title":"基于PGC-1α、NOS和Runx2的胫腓骨骨折延迟愈合预测模型。","authors":"Bin Wang, Zhiyuan Shi, Derong Li, Jinwei Yu","doi":"10.1186/s40001-025-03247-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To explore the associations between the levels of Peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), Nitric oxide synthase (NOS), Runt-related transcription factor 2 (Runx2) and the delayed union of tibiofibular fractures, and to construct and validate a model for predicting the delayed union of tibiofibular fractures.</p><p><strong>Methods: </strong>A total of 351 patients with tibiofibular fractures who were treated in the hospital from January 2022 to June 2024 were selected as the study subjects. They were randomly divided into a training set (n = 246) and a validation set (n = 105) at a ratio of 7:3. Experimental techniques such as ELISA were used to accurately detect the serum of patients, and multiple clinical data of the patients were comprehensively collected. Key influencing factors were screened out by statistical methods, such as univariate analysis and multivariate logistic regression analysis. Plot a nomogram and construct a prediction model, and use evaluation indicators to comprehensively evaluate and validate the model.</p><p><strong>Results: </strong>In the training set, 72 cases (29.27%) had delayed union of tibiofibular fracture. Multivariate logistic analysis showed that fracture complexity, time from injury to surgery, levels of PGC-1α, NOS, Runx2, and OPG were independent influencing factors for the delayed union of tibiofibular fractures (all P < 0.05). In the training set and the validation set, the C-index of the nomogram model was 0.760 and 0.711, respectively. The calibration curve showed moderate agreement between the predicted values and the actual values. The results of the Hosmer-Lemeshow test were χ<sup>2</sup> = 5.277, P = 0.728 and χ<sup>2</sup> = 10.540, P = 0.229, respectively. The ROC curve showed that in the training set and the validation set, the AUC of the nomogram model for predicting the delayed union of tibiofibular fractures was 0.760 (95%CI 0.680-0.839) and 0.711 (95%CI 0.581-0.842), respectively, and the sensitivity and specificity were 0.796, 0.645 and 0.739, 0.500, respectively.</p><p><strong>Conclusions: </strong>This study provides a new perspective and method for the assessment of the delayed union of tibiofibular fractures, which is helpful for clinicians to potentially assist in risk stratification and closer follow-up for high-risk patients.</p>","PeriodicalId":11949,"journal":{"name":"European Journal of Medical Research","volume":"30 1","pages":"978"},"PeriodicalIF":3.4000,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12522435/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictive model of delayed union of tibial and fibular fractures based on PGC-1α, NOS, and Runx2.\",\"authors\":\"Bin Wang, Zhiyuan Shi, Derong Li, Jinwei Yu\",\"doi\":\"10.1186/s40001-025-03247-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>To explore the associations between the levels of Peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), Nitric oxide synthase (NOS), Runt-related transcription factor 2 (Runx2) and the delayed union of tibiofibular fractures, and to construct and validate a model for predicting the delayed union of tibiofibular fractures.</p><p><strong>Methods: </strong>A total of 351 patients with tibiofibular fractures who were treated in the hospital from January 2022 to June 2024 were selected as the study subjects. They were randomly divided into a training set (n = 246) and a validation set (n = 105) at a ratio of 7:3. Experimental techniques such as ELISA were used to accurately detect the serum of patients, and multiple clinical data of the patients were comprehensively collected. Key influencing factors were screened out by statistical methods, such as univariate analysis and multivariate logistic regression analysis. Plot a nomogram and construct a prediction model, and use evaluation indicators to comprehensively evaluate and validate the model.</p><p><strong>Results: </strong>In the training set, 72 cases (29.27%) had delayed union of tibiofibular fracture. Multivariate logistic analysis showed that fracture complexity, time from injury to surgery, levels of PGC-1α, NOS, Runx2, and OPG were independent influencing factors for the delayed union of tibiofibular fractures (all P < 0.05). In the training set and the validation set, the C-index of the nomogram model was 0.760 and 0.711, respectively. The calibration curve showed moderate agreement between the predicted values and the actual values. The results of the Hosmer-Lemeshow test were χ<sup>2</sup> = 5.277, P = 0.728 and χ<sup>2</sup> = 10.540, P = 0.229, respectively. The ROC curve showed that in the training set and the validation set, the AUC of the nomogram model for predicting the delayed union of tibiofibular fractures was 0.760 (95%CI 0.680-0.839) and 0.711 (95%CI 0.581-0.842), respectively, and the sensitivity and specificity were 0.796, 0.645 and 0.739, 0.500, respectively.</p><p><strong>Conclusions: </strong>This study provides a new perspective and method for the assessment of the delayed union of tibiofibular fractures, which is helpful for clinicians to potentially assist in risk stratification and closer follow-up for high-risk patients.</p>\",\"PeriodicalId\":11949,\"journal\":{\"name\":\"European Journal of Medical Research\",\"volume\":\"30 1\",\"pages\":\"978\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12522435/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Medical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40001-025-03247-2\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Medical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40001-025-03247-2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Predictive model of delayed union of tibial and fibular fractures based on PGC-1α, NOS, and Runx2.
Objectives: To explore the associations between the levels of Peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), Nitric oxide synthase (NOS), Runt-related transcription factor 2 (Runx2) and the delayed union of tibiofibular fractures, and to construct and validate a model for predicting the delayed union of tibiofibular fractures.
Methods: A total of 351 patients with tibiofibular fractures who were treated in the hospital from January 2022 to June 2024 were selected as the study subjects. They were randomly divided into a training set (n = 246) and a validation set (n = 105) at a ratio of 7:3. Experimental techniques such as ELISA were used to accurately detect the serum of patients, and multiple clinical data of the patients were comprehensively collected. Key influencing factors were screened out by statistical methods, such as univariate analysis and multivariate logistic regression analysis. Plot a nomogram and construct a prediction model, and use evaluation indicators to comprehensively evaluate and validate the model.
Results: In the training set, 72 cases (29.27%) had delayed union of tibiofibular fracture. Multivariate logistic analysis showed that fracture complexity, time from injury to surgery, levels of PGC-1α, NOS, Runx2, and OPG were independent influencing factors for the delayed union of tibiofibular fractures (all P < 0.05). In the training set and the validation set, the C-index of the nomogram model was 0.760 and 0.711, respectively. The calibration curve showed moderate agreement between the predicted values and the actual values. The results of the Hosmer-Lemeshow test were χ2 = 5.277, P = 0.728 and χ2 = 10.540, P = 0.229, respectively. The ROC curve showed that in the training set and the validation set, the AUC of the nomogram model for predicting the delayed union of tibiofibular fractures was 0.760 (95%CI 0.680-0.839) and 0.711 (95%CI 0.581-0.842), respectively, and the sensitivity and specificity were 0.796, 0.645 and 0.739, 0.500, respectively.
Conclusions: This study provides a new perspective and method for the assessment of the delayed union of tibiofibular fractures, which is helpful for clinicians to potentially assist in risk stratification and closer follow-up for high-risk patients.
期刊介绍:
European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.