1.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
2.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
3.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
4.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
5.Application Value of Neoadjuvant Targeted Therapy in Patients with EGFR-mutant Resectable Lung Adenocarcinoma.
Shijie HUANG ; Mengying FAN ; Kaiming PENG ; Wanpu YAN ; Boyang CHEN ; Wu WANG ; Tianbao YANG ; Keneng CHEN ; Mingqiang KANG ; Jinbiao XIE
Chinese Journal of Lung Cancer 2025;28(7):487-496
BACKGROUND:
The proportion of patients with non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations is relatively high in China. However, these patients currently lack significant benefits from available neoadjuvant treatment options. This study aims to explore the potential application value of neoadjuvant targeted therapy by evaluating its efficacy and safety in patients with EGFR-mutant resectable lung adenocarcinoma.
METHODS:
A multicenter retrospective study was used to analyze the treatment effect of patients with stage IIA-IIIB EGFR-mutant lung adenocarcinoma who underwent surgical resection after receiving neoadjuvant targeted therapy from July 2019 to October 2024.
RESULTS:
A total of 24 patients with EGFR-mutant lung adenocarcinoma from three centers were included in this study. All patients successfully underwent surgery and achieved R0 resection of 100.0%. The objective response rate (ORR) was 83.3% (20/24) . The major pathologic response (MPR) rate was 37.5% (9/24), with 2 patients (8.3%) achieving pathological complete response (pCR). During neoadjuvant therapy, 13 out of 24 patients (54.2%) experienced adverse events of grade 1-2, with no occurrences of ≥ grade 3. The most common treatment-related adverse events were rash (n=4, 16.7%), mouth sores (n=2, 8.3%), and diarrhea (n=2, 8.3%). The median follow-up time was 33.0 months, no deaths occurred in all patients, and the overall survival (OS) rate was 100.0%. The 1-year disease-free survival (DFS) rate was 91.1%, and the 2-year DFS rate remained at 86.2%.
CONCLUSIONS
The application of neoadjuvant targeted therapy in patients with EGFR-mutant resectable lung adenocarcinoma is safe and feasible, and is expected to become a highly promising neoadjuvant treatment option for the patients with EGFR-mutant lung adenocarcinoma.
Humans
;
ErbB Receptors/metabolism*
;
Male
;
Female
;
Middle Aged
;
Adenocarcinoma of Lung/surgery*
;
Neoadjuvant Therapy
;
Lung Neoplasms/surgery*
;
Aged
;
Retrospective Studies
;
Mutation
;
Adult
6.POLG inhibitor suppresses migration and invasion of triple-negative breast cancer cells via blocking mitochondrial biogenesis
Xing LIU ; Shuangqin FAN ; Xiaomin YAN ; Shijie ZHAO ; Rong WANG ; Xiangchun SHEN ; Xue ZHOU ; Yue ZHANG ; Yan CHEN
Acta Universitatis Medicinalis Anhui 2024;59(10):1720-1728
Objective To investigate the effects of zalcitabine(ddC),a mitochondrial DNA polymerase γ(POLG)inhibitor,on the migration,invasion,and to preliminarily explore mitochondrial biogenesis of human tri-ple-negative breast cancer MDA-MB-231 cells.Methods The effect of ddC on cell viability was detected using the MTT assay.The migration and invasion abilities of the cells were evaluated using the cell scratch and Transwell in-vasion assays.Cell apoptosis was determined using flow cytometry and a V-FITC/PI cell apoptosis detection kit.The protein expression of POLG,NADH dehydrogenase subunit Ⅰ(NADH1),NADH dehydrogenase subunit Ⅱ(NADH2),ATP synthase subunit 6(ATPase6),cytochrome c oxidase subunit Ⅰ(COX-1)and cytochrome c ox-idase subunit Ⅲ(COX-3)were determined using Western blot.The POLG mRNA level and mtDNA copy number were determined using qPCR.The mitochondrial content and ATP levels were determined using MitoTracker Green fluorescent probe staining and an ATP determination kit.MDA-MB-231 cells were transfected with pcDNA3.1-EG-FP-POLG plasmids to overexpress POLG.The inhibitory effects of ddC on cell migration and invasion were detected in POLG-overexpressed MDA-MB-231 cells.Results POLG expression was higher in MDA-MB-231 cells than in normal mammary epithelial cells(MCF-10A)(P<0.01).ddC inhibited cell viability in a dose-dependent man-ner.ddC inhibited the migration(P<0.01)and invasion(P<0.01)of MDA-MB-231 cells;however,it dis-played no significant inhibitory effects on cell viability in normal mammary epithelial cells(MCF-10A)at the same concentration.ddC downregulated the protein(P<0.01)and mRNA(P<0.01)levels of POLG,reduced mtD-NA copy number(P<0.01)and downregulated mtDNA-coded NADH1,NADH2,ATPase6,COX-1 and COX-3 protein expression(P<0.01)in MDA-MB-231 cells.Furthermore ddC inhibited mitochondrial content(P<0.01)and ATP(P<0.01)levels in MDA-MB-231 cells.POLG overexpression increased the migration(P<0.05)and invasion(P<0.05)abilities of MDA-MB-231 cells,while ddC did not significantly inhibit the migra-tion and invasion abilities of MDA-MB-231 cells overexpressing POLG.Conclusion ddC downregulates POLG ex-pression in MDA-MB-231 cells and inhibits mitochondrial biogenesis and ATP levels,thereby inhibiting the migra-tion and invasion of MDA-MB-231 cells.
7.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
8.Correlation between CHA 2DS 2-VASC score and recurrence of paroxysmal atrial fibrillation after radiofrequency ablation
Ruijuan DU ; Qingmin WEI ; Yanming FAN ; Shijie WANG ; Yanlong ZHANG ; Guoqing GE
Chinese Journal of General Practitioners 2024;23(1):52-56
Objective:To investigate the correlation between CHA 2DS 2-VASC score and the recurrence risk of paroxysmal atrial fibrillation after radiofrequency ablation. Methods:It was a retrospective cohort study. A total of 150 patients who underwent radiofrequency ablation for paroxysmal atrial fibrillation in Xingtai People′s Hospital from January 2017 to January 2021 were consecutively included in the study. According to the preoperative CHA 2DS 2-VASC score, patients were divided into high score group (≥3 points, n=90) and low score group (<3 points, n=60). Baseline clinical data was collected. All patients underwent circumferential pulmonary vein isolation, and those with atrial flutter before ablation also underwent tricuspid isthmus isolation. Holter and electrocardiogram examinations were performed at 3, 6 months and 1 year after ablation to evaluate whether there was recurrence of atrial fibrillation. Univariate and multivariate Cox regression was used to analyze the risk factors for recurrence of atrial fibrillation after radiofrequency ablation. Results:Among 150 patients 90 were males and 60 were females with a mean age of (64.0±3.6) years. There were no significant differences in age, sex, and proportion of hypertension, diabetes, chronic heart failure and stroke or transient ischemic attack (TIA), medication of antiarrhythmic and anticoagulant drugs between the two groups (all P>0.05). The longest duration of atrial fibrillation in the high score group was significantly longer than that in the low score group (26.0±6.1) hours vs. (10.0±2.1) hours, P<0.05). There were no patients with cardiac tamponade, atrial esophageal fistula and severe vascular puncture complications in the two groups. During the follow-up period, the recurrence rate in the high score group was significantly higher than that in the low score group (16.7% (15/90) vs. 8.3% (5/60), P<0.05). Multivariate Cox regression analysis showed that CHA 2DS 2-VASC score≥3 was an independent risk factor for atrial fibrillation recurrence in patients with paroxysmal atrial fibrillation after radiofrequency ablation ( HR=3.84, 95% CI: 1.87-7.89, P=0.02). Conclusion:CHA 2DS 2-VASC score≥3 is an independent risk factor for atrial fibrillation recurrence in patients with paroxysmal atrial fibrillation after radiofrequency ablation.
9.Risk factors of atrial fibrillation in patients with typical atrial flutter after radiofrequency ablation
Ruijuan DU ; Yanming FAN ; Qingmin WEI ; Shijie WANG ; Fei CHENG
Chinese Journal of General Practitioners 2024;23(4):375-378
Objective:To investigate the risk factors of atrial fibrillation (AF) in patients with typical atrial flutter after radiofrequency ablation.Methods:This study was a case-control study. The clinical data of 120 patients with typical atrial flutter who underwent radiofrequency ablation in Xingtai People′s Hospital from January 2017 to January 2021 were retrospectively analyzed. Patients were followed up every 3-6 months for a period of 2 years, and AF occurred in 30 patients (25.0%). The risk factors of AF were analyzed with univariate and multivariate logistic regressions.Results:The mean age of patients was (62.0±6.5) years and 64(53.3%) were males. No patients in the two groups had complications such as cardiac tamponade, pulmonary embolism and cerebral infarction after radiofrequency ablation. Compared with non-AF patients, patients in AF group had older age and higher CHA 2DS 2-VASC score ( P<0.001). Multivariate regression analysis showed that age ( HR=1.09, 95% CI:1.01-1.17) and CHA 2DS 2-VASC score ( HR=3.84, 95% CI:1.87-7.89) were independent risk factors for the occurrence of atrial fibrillation after radiofrequency ablation in patients with atrial flutter. Conclusion:After radiofrequency ablation of typical atrial flutter, nearly 25% of patients will relapse into AF, old age and higher CHA 2DS 2-VASC score increase the risk of AF recurrent.
10.Value of TLR/NF-κB signaling axis in predicting bone infection in patients with open fractures
Hang QIN ; Shijie FAN ; Zhicheng LUO ; Hong LUO
Journal of Clinical Medicine in Practice 2024;28(21):82-88
Objective To analyze the predictive value of dynamic changes in key factors of the toll-like receptor (TLR)/nuclear factor-κB (NF-κB) signaling axis during the perioperative period for bone infection inpatients with open fractures. Methods A total of 55 patients with open fractures who developed bone infections during the perioperative period were selected as infection group, and 110 patients with open fractures who did not develop infections during the same period were selected as non-infection group. Clinical data, pre-and post-operative serum levels of routine inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6) and procalcitonin (PCT)] and key factors of the TLR/NF-κB signaling axis (TLR4, NF-κB) were compared between the two groups. Logistic multivariate regression analysis was used to identify risk factors for bone infection during the perioperative period in patients with open fractures. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of the absolute change (the absolute value of the changes was expressed as △) in the levels of key factors of the TLR/NF-κB signaling axis before and after surgery for bone infection, and these results were compared with the predictive value of routine inflammatory markers. A nomogram prediction model was developed based on the identified risk factors, and its value in predicting perioperative bone infection was analyzed. Results The time from fracture to surgery and the duration of surgery were significantly longer, and the proportion of Gustilo type Ⅲ fractures and wounds with a depth ≥2 cm was significantly higher in the infection group compared to the non-infection group (


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