| 摘要: |
| ［摘要］ 目的 基于创伤严重程度评分（ISS）和凝血相关指标构建胸腹联合伤急诊患者开胸术后腹腔内再出血的列线图模型，并分析其临床应用价值。方法 回顾性分析2021年9月至2023年6月西安交通大学附属红会医院收治的205例胸腹联合伤急诊患者的临床资料，均经开胸手术治疗。根据患者术后腹腔内再出血发生情况将其分为再出血组（n=73）和非再出血组（n=132）。比较两组术前血小板与淋巴细胞比值（PLR）、血小板α颗粒膜蛋白-140（GMP-140）、ISS、凝血酶原时间（PT）、活化部分凝血活酶时间（APTT）和纤维蛋白原（FIB）等资料。通过多因素logistic回归分析影响胸腹联合伤急诊患者开胸术后腹腔内再出血的因素。基于多因素logistic回归分析结果构建预测胸腹联合伤急诊患者开胸术后腹腔内再出血的列线图模型。通过受试者工作特征（ROC）曲线、校准曲线以及决策曲线分析列线图模型的预测效能和应用价值。结果 再出血组ISS、PT、APTT、PLR以及GMP-140水平高于非再出血组，FIB水平低于非再出血组，差异有统计学意义（P<0.05）。多因素logistic回归分析结果显示，较高水平的ISS、PT、APTT、FIB、PLR以及GMP-140是胸腹联合伤急诊患者开胸术后腹腔内再出血的独立危险因素（P<0.05）。基于ISS、PT、APTT、FIB、PLR、GMP-140指标构建预测胸腹联合伤急诊患者开胸术后腹腔内再出血的列线图模型，ROC曲线分析结果显示，列线图模型具有较好的预测效能［AUC（95%CI）=0.913（0.874～0.952）］，灵敏度为86.30%，特异度为89.39%。校准曲线分析结果显示，实际曲线与校准曲线基本贴合，提示列线图模型具有较好的预测效能。决策曲线分析结果显示，在阈值概率0.10～0.81内，列线图的临床效用良好。结论 该研究构建的预测胸腹联合伤急诊患者开胸术后腹腔内再出血的列线图模型具有较好的临床应用价值，有助于临床筛查高危患者，为早期干预提供指导，降低二次手术率及病死率。 |
| 关键词: 胸腹联合伤 急诊 腹腔内再出血 列线图模型 风险评估 |
| DOI：10.3969/j.issn.1674-3806.2025.10.08 |
| 分类号:R 641 |
| 基金项目:陕西省重点研发计划项目（编号：2021SF-307） |
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| Construction of a nomogram model based on ISS and coagulation-related indicators to predict intra-abdominal rebleeding after thoracotomy in emergency patients with thoracoabdominal injuries |
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WU Dinghua1, YAO Tingting2, ZHENG Yan1, ZHOU Ting3, YANG Ya′nan4
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1.Department of Thoracic Surgery, Honghui Hospital Affiliated to Xi′an Jiaotong University, Xi′an 710054, China; 2.Department of Quality Control, Honghui Hospital Affiliated to Xi′an Jiaotong University, Xi′an 710054, China; 3.Department of Surgery, Civil Aviation Xi′an Hospital, Xi′an 710082, China; 4.Department of Emergency, Honghui Hospital Affiliated to Xi′an Jiaotong University, Xi′an 710054, China
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| Abstract: |
| ［Abstract］ Objective To construct a nomogram model based on Injury Severity Scores(ISS) and coagulation-related indicators to predict intra-abdominal rebleeding after thoracotomy in emergency patients with thoracoabdominal injuries, and to analyze its clinical application value. Methods A retrospective analysis was conducted on the clinical data of 205 emergency patients with thoracoabdominal injuries who were admitted to Honghui Hospital Affiliated to Xi′an Jiaotong University from September 2021 to June 2023. All the patients were treated with thoracotomy. According to the occurrence of intra-abdominal rebleeding after surgery, the patients were divided into rebleeding group(n=73) and non-rebleeding group(n=132). The data such as preoperative platelet-to-lymphocyte ratio(PLR), platelet alpha granule membrane protein-140(GMP-140), ISS, prothrombin time(PT), activated partial thromboplastin time(APTT) and fibrinogen(FIB) were compared between the two groups. Multivariate logistic regression was used to analyze the factors influencing intra-abdominal rebleeding after thoracotomy in the emergency patients with thoracoabdominal injuries. Based on the results of multivariate logistic regression analysis, a nomogram model was constructed to predict intra-abdominal rebleeding after thoracotomy in the emergency patients with thoracoabdominal injuries. The predictive efficacy and application value of the nomogram model were analyzed by using receiver operating characteristic(ROC) curve, calibration curve and decision curve. Results The levels of ISS, PT, APTT, PLR and GMP-140 in the rebleeding group were higher than those in the non-rebleeding group, and the level of FIB in the rebleeding group was lower than that in the non-rebleeding group, with statistically significant differences between the two groups(P<0.05). The results of multivariate logistic regression analysis showed that higher levels of ISS, PT, APTT, FIB, PLR and GMP-140 were independent risk factors for intra-abdominal rebleeding after thoracotomy in the emergency patients with thoracoabdominal injuries(P<0.05). A nomogram model for predicting intra-abdominal rebleeding after thoracotomy in the emergency patients with thoracoabdominal injuries was constructed based on ISS, PT, APTT, FIB, PLR and GMP-140 indicators. The results of ROC curve analysis showed that the nomogram model had good predictive efficacy［AUC(95%CI)=0.913(0.874-0.952)］, with a sensitivity of 86.30% and a specificity of 89.39%. The results of calibration curve analysis showed that the actual curve was basically in line with the calibration curve, suggesting that the nomogram model had good predictive efficacy. The results of decision curve analysis showed that within the threshold probability ranging from 0.10 to 0.81, the clinical utility of the nomogram was good. Conclusion The nomogram model constructed in this study has good clinical application value for predicting intra-abdominal rebleeding after thoracotomy in emergency patients with thoracoabdominal injuries. It is helpful for clinical screening of high-risk patients, providing guidance for early intervention, and reducing the rate of secondary surgery and mortality. |
| Key words: Thoracoabdominal injuries Emergency Intra-abdominal rebleeding Nomogram model Risk assessment |
