急性肺栓塞的预测因素分析及诊断模型的建立

Predictive factors and development of a diagnostic model for acute pulmonary embolism

  • 摘要: 背景 急性肺栓塞(acute pulmonary embolism,APE)发病率及致死率高,现有诊断手段存在侵入性或设备依赖局限,基层及重症患者诊断困难。目的 探索APE的独立预测因素,整合易获取指标构建诊断模型并完成内部验证与外部验证。方法 回顾性收集2022 年1 月 — 2024 年12 月解放军总医院第六医学中心疑诊APE并接受计算机断层扫描肺动脉血管造影(computed tomography pulmonary angiography,CTPA)的患者为训练队列,2006 年1 月 — 2019 年12 月解放军总医院第一医学中心疑诊APE并行CTPA检查的患者为外部验证队列。收集人口学特征、症状、既往史、实验室检查及心电图数据,经单因素分析、LASSO 回归与多因素Logistic 回归筛选独立预测因素,构建诊断列线图模型。采用受试者工作特征曲线(receiver operating characteristic,ROC)、校准曲线、决策曲线分析(decision curve analysis,DCA)及Bootstrap 重抽样进行内部验证,并完成外部验证,与Wells 评分、Geneva 评分等对比评估模型效能。结果 共纳入建模队列373 例(APE214 例、非APE159 例),外部验证队列63 例(APE35 例、非APE28 例)。建模队列APE组男性112 例,女性102 例,平均年龄(63.9±15.9)岁;非APE组男性98 例,女性61 例,平均年龄40 岁。纳入LASSO回归分析的变量共20 个,包括年龄、临床症状(呼吸困难、胸闷/胸痛、下肢肿胀/疼痛、晕厥/休克)、既往病史(既往肺栓塞、糖尿病、肿瘤、慢性肾脏病)、制动史、深静脉血栓形成(deep vein thrombosis,DVT)、T波改变、血红蛋白(hemoglobin,Hb)、血小板(platelet,PLT)、D-二聚体、活化部分凝血活酶时间(activated partial thromboplastin time,APTT)、国际标准化比值(international normalized ratio,INR)、血尿素氮(blood urea nitrogen,BUN)、心肌肌钙蛋白(cardiac troponin,cTn)、N 末端B 型脑钠肽前体(N‑terminal pro‑B‑type natriuretic peptide,NT‑proBNP)等;Logistic 回归结果显示,D-二聚体、既往下肢DVT、NT‑proBNP、胸闷/胸痛、既往肺栓塞、APTT延长、心电图T波改变与APE独立关联(P<0.05),预测模型为P=ex/(1+ex),其中X=0.654×D-二聚体+2.087×既往深静脉血栓形成病史+0.473×NT‑proBNP+1.735×胸闷/胸痛症状+2.263×既往肺栓塞病史+0.137×APTT+1.172×心电图T 波改变-12.483,并据此构建列线图模型。模型建成后内外验证曲线下面积(area under the curve,AUC)分别为0.944 和0.988,优于Wells(0.733)与Geneva(0.841)评分。决策曲线显示模型在阈值概率0 ~ 0.98 范围内净获益优于“全部干预/不干预”策略,适用于临床筛查决策支持。校准曲线显示预测概率与实际发生率高度一致。结论 以“D-二聚体、DVT、NT-proBNP、胸闷/胸痛、既往肺栓塞、APTT、T波改变”等7 个独立预测因子构成的列线图诊断模型对APE诊断效能高、操作简便,适于床旁快速筛查。

     

    Abstract: Background Acute pulmonary embolism (APE) has high incidence and mortality. Existing diagnostic methods are invasive or equipment-dependent, making diagnosis difficult in primary and critically ill settings. Objective To identify independent predictive factors for APE and develop a diagnostic model incorporating readily available clinical indicators. Methods  A multicenter retrospective case-control study was conducted. Patients with suspected acute pulmonary embolism (APE) who underwent computed tomography pulmonary angiography (CTPA) at the Sixth Medical Center of PLA General Hospital from January 2022 to December 2024 were enrolled as the modeling cohort, From January 2006 to December 2019, the patients who were suspected of having APE and underwent CTPA examination at the First Medical Center of the PLA General Hospital constituted the external validation cohort.. Demographic characteristics, clinical symptoms, medical history, laboratory parameters, and electrocardiographic (ECG) findings were collected. Independent predictors were identified using univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariable logistic regression, and a diagnostic nomogram was subsequently developed. Model performance was evaluated by receiver operating characteristic (ROC) curve analysis, calibration curves, decision curve analysis (DCA), and internal validation with bootstrap resampling. External validation was performed in the independent cohort, and the model was compared with the Wells score and the Geneva score. Results A total of 373 patients were included in the modeling cohort (214 APE, 159 non-APE) and 63 patients in the external validation cohort (35 APE, 28 non-APE). In the APE group, there were 112 males and 102 females, with a mean age of 63.9±15.9 years; in the non-APE group, there were 98 males and 61 females, with a mean age of 40 years. Logistic regression analysis showed that D-dimer, history of lower-extremity deep vein thrombosis (DVT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), chest tightness/chest pain, history of pulmonary embolism, prolonged activated partial thromboplastin time (APTT), and T-wave abnormalities on ECG were independently associated with APE (P<0.05). The predictive probability was modeled as P= eX/(1+eX), where X=0.654×(D-dimer)+ 2.087×(prior DVT)+0.473×(NT-proBNP) + 1.735×(chest tightness/chest pain)+2.263×(prior PE)+0.137×(APTT)+1.172×(T-wave change) -12.483. A nomogram was constructed based on this equation. The area under the ROC curve (AUC) for the model was 0.944 in internal validation and 0.988 in external validation, both outperforming the Wells score (0.733) and the Geneva score (0.841). Conclusion The seven factor nomogram demonstrates excellent diagnostic performance and is easy to use, making it suitable for rapid bedside screening of suspected APE, particularly in critically ill patients and in primary healthcare settings.

     

/

返回文章
返回