Analysis of risk factors for the prediction of short-term adverse event associated with acute non-high-risk pulmonary embolism_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

SUN Borui , HU Jiaxin , GE Shanhui , REN Jianwei ,  ZHU Guangfa

Department of Respiratory and Critical Care Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, P. R. China;

Corresponding author：

ZHU Guangfa, Email: gfzhu63@hotmail.com

Keywords：

Pulmonary thromboembolism; adverse event; risk factor

DOI：

10.7507/1671-6205.202110058

Video：

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Objective To evaluate the prognostic value of several indexes of laboratory and ultrasonic cardiogram for adverse events in 3 months following the diagnosis of acute non-high-risk pulmonary embolism. Methods A total of 266 cases of acute non-high-risk pulmonary embolism patients diagnosed and treated in Beijing Anzhen Hospital during 2016 to 2017 were retrospectively analyzed. The patients were divided into a bad event group and a control group according to whether there was a bad event happened in 3 months following the diagnosis. The general data, indexes of laboratory and ultrasonic cardiogram were compared. Univariate and multivariate COX regression analysis were conducted to explore independent risk factors for 3 months’ poor prognosis. Results The bad outcome group had a significantly higher value of the proportion of suffering from connective disease and active cancer, C-reaction protein, monocyte/lymphocyte ratio (MLR) and urea while a significantly lower level of red blood cell count and hemoglobin compared with the control group (all P<0.05). Univariate and multivariate COX regression analysis showed that both the MLR (hazard ratio 14.59, 95% confidence interval 1.48 - 143.69, P=0.02) and suffering from connective disease (hazard ratio 5.85, 95% confidence interval 1.11 - 30.81, P=0.04) remain significantly different between the bad events group and the control group. Conclusion MLR at the admission may be related to the 3 months death of acute non-high-risk pulmonary embolism.

Citation： SUN Borui, HU Jiaxin, GE Shanhui, REN Jianwei, ZHU Guangfa. Analysis of risk factors for the prediction of short-term adverse event associated with acute non-high-risk pulmonary embolism. Chinese Journal of Respiratory and Critical Care Medicine, 2022, 21(1): 37-42. doi: 10.7507/1671-6205.202110058 Copy

1.	乔力松, 许小毛, 杨鹤, 等. 肺血栓栓塞症合并下肢深静脉血栓临床分析. 中国呼吸与危重监护杂志, 2021, 20(7): 509-512.
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4.	沈芳, 张景熙, 刘锦铭, 等. 慢性阻塞性肺疾病加重期合并静脉血栓栓塞症的危险因素分析. 中国呼吸与危重监护杂志, 2019, 18(5): 427-431.
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6.	Owens AP 3 rd, Mackman N. Microparticles in hemostasis and thrombosis. Circ Res, 2011, 108(10): 1284-1297.
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8.	Khan F, Tritschler T, Kahn SR, et al. Venous thromboembolism. Lancet, 2021, 398(10294): 64-77.
9.	王梦瑶, 张薇, 郭友芳, 等. 单核细胞/淋巴细胞比值与呼吸系统疾病评估相关性的研究进展. 医学综述, 2021, 27(15): 3045-3049.
10.	Köse N, Yıldırım T, Akın F, et al. Prognostic role of NLR, PLR, and LMR in patients with pulmonary embolism. Bosnian J Basic Med, 2020, 20(2): 248-253.
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12.	Jurin I, Trkulja V, Ajduk M, et al. Red cell distribution width in acute pulmonary embolism patients: a simple aid for improvement of the 30-day mortality risk stratification based on the pulmonary embolism severity index. Heart Lung, 2019, 48(5): 436-445.
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14.	王渝胜, 王华蕊, 朱玲. sPESI联合RDW和NLR对急性非高危肺栓塞患者预后的预测价值. 中国急救医学, 2021, 41(4): 302-306.
15.	肖华叶, 梁斌苗, 欧雪梅. 中性粒细胞与淋巴细胞比值在慢性阻塞性肺疾病急性加重期中的价值. 中国呼吸与危重监护杂志, 2021, 20(2): 85-90.
16.	秦志均, 刘磊, 孙群, 等. 新型冠状病毒肺炎患者外周血细胞动态变化特征及预测价值. 中国呼吸与危重监护杂志, 2020, 19(5): 457-462.
17.	徐英, 蒋萍, 杨明金, 等. 红细胞分布宽度与老年支气管扩张症急性加重期严重程度的相关性分析. 中国呼吸与危重监护杂志, 2019, 18(4): 348-351.
18.	Bedel C, Korkut M, Armağan HH. Can NLR, PLR and LMR be used as prognostic indicators in patients with pulmonary embolism? A commentary. Bosnian J Basic Med, 2021, 21(4): 501.
19.	Jiménez D, Yusen RD, Otero R, et al. Prognostic models for selecting patients with acute pulmonary embolism for initial outpatient therapy. Chest, 2007, 132(1): 24-30.
20.	Weeda ER, Caranfa JT, Lyman GH, et al. External validation of three risk stratification rules in patients presenting with pulmonary embolism and cancer. Support Care Cancer, 2019, 27(3): 921-925.
21.	Quezada CA, Bikdeli B, Villén T, et al. Accuracy and interobserver reliability of the simplified pulmonary embolism severity index versus the Hestia criteria for patients with pulmonary embolism. Acad Emerg Med, 2019, 26(4): 394-401.
22.	Vuilleumier N, Simona A, Méan M, et al. Comparison of cardiac and non-cardiac biomarkers for risk stratification in elderly patients with non-massive pulmonary embolism. PLoS One, 2016, 11(5): e0155973.

1. 乔力松, 许小毛, 杨鹤, 等. 肺血栓栓塞症合并下肢深静脉血栓临床分析. 中国呼吸与危重监护杂志, 2021, 20(7): 509-512.
2. Konstantinides SV, Meyer G, Becattini C, et al. 2019 ESC Guidelines for the Diagnosis and Management of Acute Pulmonary Embolism Developed in Collaboration with the European Respiratory Society (ERS). Eur Heart J, 2020, 41(4): 543-603.
3. Wenger N, Sebastian T, Engelberger RP, et al. Pulmonary embolism and deep vein thrombosis: similar but different. Thromb Res, 2021, 206: 88-98.
4. 沈芳, 张景熙, 刘锦铭, 等. 慢性阻塞性肺疾病加重期合并静脉血栓栓塞症的危险因素分析. 中国呼吸与危重监护杂志, 2019, 18(5): 427-431.
5. Thålin C, Hisada Y, Lundström S, et al. Neutrophil extracellular traps: villains and targets in arterial, venous, and cancer-associated thrombosis. Arterioscl Throm Vas, 2019, 39(9): 1724-1738.
6. Owens AP 3 rd, Mackman N. Microparticles in hemostasis and thrombosis. Circ Res, 2011, 108(10): 1284-1297.
7. Engelmann B, Massberg S. Thrombosis as an intravascular effector of innate immunity. Nat Rev Immunol, 2013, 13(1): 34-45.
8. Khan F, Tritschler T, Kahn SR, et al. Venous thromboembolism. Lancet, 2021, 398(10294): 64-77.
9. 王梦瑶, 张薇, 郭友芳, 等. 单核细胞/淋巴细胞比值与呼吸系统疾病评估相关性的研究进展. 医学综述, 2021, 27(15): 3045-3049.
10. Köse N, Yıldırım T, Akın F, et al. Prognostic role of NLR, PLR, and LMR in patients with pulmonary embolism. Bosnian J Basic Med, 2020, 20(2): 248-253.
11. Telo S, Kuluöztürk M, Deveci F, et al. The relationship between platelet-to-lymphocyte ratio and pulmonary embolism severity in acute pulmonary embolism. Int Angiol, 2019, 38(1): 4-9.
12. Jurin I, Trkulja V, Ajduk M, et al. Red cell distribution width in acute pulmonary embolism patients: a simple aid for improvement of the 30-day mortality risk stratification based on the pulmonary embolism severity index. Heart Lung, 2019, 48(5): 436-445.
13. 王渝胜. sPESI联合纤维蛋白原/白蛋白比值对急性非高危肺栓塞患者的预后价值. 山东大学, 2021. DOI: 10.27272/d.cnki.gshdu.2021.001110.
14. 王渝胜, 王华蕊, 朱玲. sPESI联合RDW和NLR对急性非高危肺栓塞患者预后的预测价值. 中国急救医学, 2021, 41(4): 302-306.
15. 肖华叶, 梁斌苗, 欧雪梅. 中性粒细胞与淋巴细胞比值在慢性阻塞性肺疾病急性加重期中的价值. 中国呼吸与危重监护杂志, 2021, 20(2): 85-90.
16. 秦志均, 刘磊, 孙群, 等. 新型冠状病毒肺炎患者外周血细胞动态变化特征及预测价值. 中国呼吸与危重监护杂志, 2020, 19(5): 457-462.
17. 徐英, 蒋萍, 杨明金, 等. 红细胞分布宽度与老年支气管扩张症急性加重期严重程度的相关性分析. 中国呼吸与危重监护杂志, 2019, 18(4): 348-351.
18. Bedel C, Korkut M, Armağan HH. Can NLR, PLR and LMR be used as prognostic indicators in patients with pulmonary embolism? A commentary. Bosnian J Basic Med, 2021, 21(4): 501.
19. Jiménez D, Yusen RD, Otero R, et al. Prognostic models for selecting patients with acute pulmonary embolism for initial outpatient therapy. Chest, 2007, 132(1): 24-30.
20. Weeda ER, Caranfa JT, Lyman GH, et al. External validation of three risk stratification rules in patients presenting with pulmonary embolism and cancer. Support Care Cancer, 2019, 27(3): 921-925.
21. Quezada CA, Bikdeli B, Villén T, et al. Accuracy and interobserver reliability of the simplified pulmonary embolism severity index versus the Hestia criteria for patients with pulmonary embolism. Acad Emerg Med, 2019, 26(4): 394-401.
22. Vuilleumier N, Simona A, Méan M, et al. Comparison of cardiac and non-cardiac biomarkers for risk stratification in elderly patients with non-massive pulmonary embolism. PLoS One, 2016, 11(5): e0155973.

Chinese Journal of Respiratory and Critical Care Medicine

Analysis of risk factors for the prediction of short-term adverse event associated with acute non-high-risk pulmonary embolism

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