Thrombosis research · 2025
Predictors of pulmonary infarction in pediatric pulmonary embolism: A retrospective cohort study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Li Shuxuan, Wang Min, Xu Yongsheng
Аннотация
OBJECTIVE: Pulmonary infarction (PI) complicating pulmonary embolism (PE) is rarely reported in pediatric populations. This study aimed to identify risk factors associated with PI development and evaluate the diagnostic utility of predictive indicators.
METHODS: This retrospective study enrolled patients aged <18 years diagnosed with PE by CTA. Data collected included demographics, medical histories, clinical manifestations, laboratory findings, and imaging results. Patients were assessed using simplified Wells score, simplified revised Geneva score, and Pulmonary Embolism Severity Index. Logistic regression and receiver operating characteristic curves were employed to evaluate risk factors and diagnostic efficacy.
RESULTS: Among 41 pediatric patients diagnosed with PE (26 non-PI vs. 15 PI), 95 % (39/41) showed no signs or history of deep vein thrombosis. The three scoring systems performed poorly in predicting pediatric PE or PI. Features nominally associated with PI (p < 0.05 but q > 0.05) included pleural effusion, maximum temperature, lymphocyte ratio, chest pain, blood urea nitrogen (BUN), neutrophil ratio, maximum D-dimer, leukocyte count, and neutrophil count. Chest pain (aOR = 6.85, p < 0.05), BUN (aOR = 2.77, p = 0.04), and maximum temperature (aOR = 3.83, p = 0.03) were identified as independent risk factors for the occurrence of PI. The logistic regression model for predicting PI (AUC = 0.846) significantly outperformed the simplified Wells model (AUC = 0.640).
CONCLUSIONS: In situ pulmonary artery thrombosis represents the primary form of PE in pediatric patients. Chest pain, BUN, and maximum temperature were identified as independent risk factors for the occurrence of PI. The logistic regression model demonstrates excellent efficacy and may serve as a tool for the future development of a PI scoring system.
METHODS: This retrospective study enrolled patients aged <18 years diagnosed with PE by CTA. Data collected included demographics, medical histories, clinical manifestations, laboratory findings, and imaging results. Patients were assessed using simplified Wells score, simplified revised Geneva score, and Pulmonary Embolism Severity Index. Logistic regression and receiver operating characteristic curves were employed to evaluate risk factors and diagnostic efficacy.
RESULTS: Among 41 pediatric patients diagnosed with PE (26 non-PI vs. 15 PI), 95 % (39/41) showed no signs or history of deep vein thrombosis. The three scoring systems performed poorly in predicting pediatric PE or PI. Features nominally associated with PI (p < 0.05 but q > 0.05) included pleural effusion, maximum temperature, lymphocyte ratio, chest pain, blood urea nitrogen (BUN), neutrophil ratio, maximum D-dimer, leukocyte count, and neutrophil count. Chest pain (aOR = 6.85, p < 0.05), BUN (aOR = 2.77, p = 0.04), and maximum temperature (aOR = 3.83, p = 0.03) were identified as independent risk factors for the occurrence of PI. The logistic regression model for predicting PI (AUC = 0.846) significantly outperformed the simplified Wells model (AUC = 0.640).
CONCLUSIONS: In situ pulmonary artery thrombosis represents the primary form of PE in pediatric patients. Chest pain, BUN, and maximum temperature were identified as independent risk factors for the occurrence of PI. The logistic regression model demonstrates excellent efficacy and may serve as a tool for the future development of a PI scoring system.