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1.400016 重庆,重庆医科大学附属第一医院神经外科
2.404000 重庆,重庆大学附属三峡医院神经外科
[ 谢延风,E-mail:xyf3058@163.com XIE Yanfeng, E-mail: xyf3058@163.com
[ 蒋理,E-mail:drjiangli2019@163.com JIANG Li, E-mail: drjiangli2019@163.com
收稿:2023-11-13,
修回:2023-12-01,
纸质出版:2024-06-15
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林巡, 孙晓川, 石全红, 等. 自发性脑出血患者术后合并肺栓塞的预测模型的构建与验证[J]. 陆军军医大学学报, 2024,46(11):1270-1276.
Xun LIN, Xiaochuan SUN, Quanhong SHI, et al. Construction and verification of a nomogram model for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage[J]. Journal of Army Medical University, 2024, 46(11): 1270-1276.
林巡, 孙晓川, 石全红, 等. 自发性脑出血患者术后合并肺栓塞的预测模型的构建与验证[J]. 陆军军医大学学报, 2024,46(11):1270-1276. DOI: 10.16016/j.2097-0927.202311064.
Xun LIN, Xiaochuan SUN, Quanhong SHI, et al. Construction and verification of a nomogram model for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage[J]. Journal of Army Medical University, 2024, 46(11): 1270-1276. DOI: 10.16016/j.2097-0927.202311064.
目的
2
探讨自发性脑出血患者术后合并肺栓塞的危险因素,构建并验证列线图模型。
方法
2
本研究是回顾性队列研究,回顾性选取2015年1月至2023年1月于重庆医科大学附属第一医院及重庆大学附属三峡医院住院治疗的393例患者为训练组,165例患者为验证组,采用单因素和多因素逐步Logistic回归分析,筛选出与自发性脑出血术后合并肺栓塞相关的危险因素,构建并验证基于这些因素的列线图模型。
结果
2
基于年龄、出血量、格拉斯哥昏迷评分(Glasgow coma scale
GCS)、手术方式、纤维蛋白(原)降解产物(fibrinogen degradation product
FDP)、D-二聚体、血红蛋白和血浆、渗透压、有无深静脉血栓等危险因素绘制列线图模型,受试者工作特征曲线(receiver operating characteristic curve
ROC)显示模型对是否存在肺栓塞区分度良好,曲线下面积(area under curve
AUC)=0.908,验证集的Hosmer-Lemeshow拟合优度检验表明此模型对于验证集的拟合度良好(
χ
2
=14.805,
df
=8,
P
=0.063),校正曲线与理想曲线较为接近,模型的预测概率与实际发生概率接近,说明该模型准确性较高,决策曲线分析显示在较大范围的阈值概率下,建立的列线图模型均可获得收益。
结论
2
本研究建立的自发性脑出血患者术后合并肺栓塞的预测模型具有良好的预测性能,可在临床工作中准确、及时、快速识别肺栓塞的发生。
Objective
2
To investigate the risk factors for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage
and construct and verify the nomogram model.
Methods
2
A retrospective cohort study was conducted on 558 patients admitted in the First Affiliated Hospital of Chongqing Medical University and the Three Gorges Hospital Affiliated to Chongqing University. And 393 of them who hospitalized from January 2015 to January 2021 were assigned into a modeling group
and the other 165 patients from February 2021 to January 2023 into a validation group. Univariate and multivariate stepwise logistic regression analyses were used to screen out the risk factors associated with pulmonary embolism after spontaneous cerebral hemorrhage surgery. Then a nomogram model was build based on these factors and verified.
Results
2
Based on age
blood loss
Glasgow coma scale (GCS) score
surgical treatments
levels of fibrin degradation products
D-dimer and hemoglobin
plasma osmolality
and deep vein thrombosis
a risk model of pulmonary embolism was built. Receiver operating characteristic (ROC) curve analysis showed the model had good discriminability for the presence of pulmonary embolism
and the area under the curve (AUC) value was 0.908. Hosmer-Lemeshow goodness-fit test indicated that the model had a good fit to the verification set (
Chi
-square=14.805
df
=8
P
=0.063)
the correction curve was close to the ideal curve
and the prediction probability of the model was close to the actual occurrence probability
suggesting the model having good accuracy. Decision curve analysis revealed that the established nomogram model can get benefits under a large range of threshold probabilities.
Conclusion
2
We develop a prediction model for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage after surgical treatment
which shows good prediction performance in both the training and validation groups
and can be used for accurate
prompt and quick identification for the occurrence of pulmonary embolism in clinical practice.
WANG W Z, JIANG B, SUN H X, et al . Prevalence, incidence, and mortality of stroke in China: results from a nationwide population-based survey of 480 687 adults[J ] . Circulation, 2017, 135(8): 759-771. DOI: 10.1161/CIRCULATIONAHA.116.025250.
VELTKAMP R, PURRUCKER J. Management of spontaneous intracerebral hemorrhage[J]. Curr Neurol Neurosci Rep, 2017, 17(10): 80. DOI: 10.1007/s11910-017-0783-5.
DE MANOEL A L. Surgery for spontaneous intracerebral hemorrhage[J]. Crit Care, 2020, 24(1): 45. DOI: 10.1186/s13054-020-2749-2.
ESSIEN E O, RALI P, MATHAI S C. Pulmonary embolism[J]. Med Clin North Am, 2019, 103(3): 549-564. DOI: 10.1016/j.mcna.2018.12.013.
LUIJTEN D, DE JONG C M M, NINABER M K, et al . Post-pulmonary embolism syndrome and functional outcomes after acute pulmonary embolism[J ] . Semin Thromb Hemost, 2023, 49(8): 848-860. DOI: 10.1055/s-0042-1749659.
MACLEOD M, PAPI A, CONTOLI M, et al . Chronic obstructive pulmonary disease exacerbation fundamentals: diagnosis, treatment, prevention and disease impact[J ] . Respirology, 2021, 26(6): 532-551. DOI: 10.1111/resp.14041.
HEMPHILL J C Ⅲ, GREENBERG S M, ANDERSON C S, 等. 自发性脑出血诊疗指南: 美国心脏协会/美国卒中协会的健康职业者指南[J]. 中国脑血管病杂志, 2015, 12(9): 490-504. DOI: 10.3969/j.issn.1672-5921.2015.09.009.
HEMPHILL J C Ⅲ, GREENBERG S M, ANDERSON C S, et al . Guidelines for diagnosis and treatment of spontaneous cerebral hemorrhage: a guide for health professionals of American Heart Association/American Stroke Association[J ] . Chin J Cerebrovasc Dis, 2015, 12(9): 490-504. DOI: 10.3969/j.is sn.1672-5921.2015.09.009.
RASOULI M, KALANTARI K R. Comparison of methods for calculating serum osmolality: multivariate linear regression analysis[J]. Clin Chem Lab Med, 2005, 43(6): 635-640. DOI: 10.1515/CCLM.2005.109.
NGUYEN E T, HAGUE C, MANOS D, et al . Canadian Society of Thoracic Radiology/Canadian Association of Radiologists best practice guidance for investigation of acute pulmonary embolism, part 1: acquisition and safety considerations[J ] . Can Assoc Des Radiol J, 2022, 73(1): 203-213. DOI: 10.1177/08465371211000737.
LIU P J, CAI G F, GU H, et al . Diagnostic nomogram to differentiate between epididymal tuberculosis and bacterial epididymitis[J ] . Infection, 2023, 51(2): 447-454. DOI: 10.1007/s15010-022-01916-6.
FENG L L, LIU Z Y, LI C F, et al . Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study[J ] . Lancet Digit Health, 2022, 4(1): e8-e17. DOI: 10.1016/S2589-7500(21)00215-6.
VICKERS A J, VAN CALSTER B, STEYERBERG E W. A simple, step-by-step guide to interpreting decision curve analysis[J]. Diagn Progn Res, 2019, 3: 18. DOI: 10.1186/s41512-019-0064-7.
XU X Y, LI D, SONG L R, et al . Nomogram for predicting an individual prospective hemorrhage risk in untreated brainstem cavernous malformations[J ] . J Neurosurg, 2023, 138(4): 910-921. DOI: 10.3171/2022.8.JNS221228.
DONZÉ J, LABARÈRE J, MÉAN M, et al . Prognostic importance of anaemia in patients with acute pulmonary embolism[J ] . Thromb Haemost, 2011, 106(2): 289-295. DOI: 10.1160/TH11-04-0208.
BOSSON J L, BARRO C, SATGER B, et al . Quantitative high D-dimer value is predictive of pulmonary embolism occurrence independently of clinical score in a well-defined low risk factor population[J ] . J Thromb Haemost, 2005, 3(1): 93-99. DOI: 10.1111/j.1538-7836.2004.01045.x.
LIN X, LI Q L, SUN X C, et al . Effects of apolipoprotein E polymorphism on cerebral oxygen saturation, cerebral perfusion, and early prognosis after traumatic brain injury[J ] . Ann Clin Transl Neurol, 2023, 10(6): 1002-1011. DOI: 10.1002/acn3.51783.
邓天芳, 邵世蓉, 陈敏, 等. 急性脑出血病人合并肺栓塞风险预测模型的建立[J]. 护理研究, 2023, 37(6): 988-992. DOI: 10.12102/j.issn.1009-6493.2023.06.009.
DENG T F, SHAO S R, CHEN M, et al . Establishment of risk prediction model of occurrence of pulmonary embolism in patients with intracerebral hemorrhage[J ] . Chin Nurs Res, 2023, 37(6): 988-992. DOI: 10.12102/j.issn.1009-6493.2023.06.009.
ISHAAYA E, TAPSON V F. Advances in the diagnosis of acute pulmonary embolism[J]. F1000Res, 2020, 9: F1000 Faculty Rev-44. DOI: 10.12688/f1000research.21347.1.
葛晓敏, 杜磊, 马建华. 影响中青年急性缺血性卒中脑血管狭窄的危险因素研究[J]. 神经损伤与功能重建, 2018, 13(2): 62-65. DOI: 10.16780/j.cnki.sjssgncj.2018.02.003.
GE X M, DU L, MA J H. The risk factors for acute ischemic stroke in young and middle-aged patients with CerebroVascular stenosis[J]. Neural Inj Funct Reconstr, 2018, 13(2): 62-65. DOI: 10.16780/j.cnki.sjssgncj.2018.02.003.
KVHN A L, KAN P, HENNINGER N, et al . Impact of age on cerebral aneurysm occlusion after flow diversion[J ] . J Clin Neurosci, 2019, 65: 23-27. DOI: 10.1016/j.jocn.2019.04.024.
GALANAUD J P, GENTY-VERMOREL C, ROLLAND C, et al . Compression stockings to prevent postthrombotic syndrome: literature overvie w and presentation of the CELEST trial[J ] . Res Pract Thromb Haemost, 2020, 4(8): 1239-1250. DOI: 10.1002/rth2.12445.
朱雪娟, 王海霞, 申雪花, 等. 脑卒中患者发生静脉血栓栓塞症的影响因素分析[J]. 护理实践与研究, 2022, 19(11): 1634-1638. DOI: 10.3969/j.issn.1672-9676.2022.11.012.
ZHU X J, WANG H X, SHEN X H, et al . Analysis of influential factors of venous thromboembolism in stroke patients[J ] . Nurs Pract Res, 2022, 19(11): 1634-1638. DOI: 10.3969/j.issn.1672-9676.2022.11.012.
ROBLES L A, VOLOVICI V. Hypertensive primary intraventricular hemorrhage: a systematic review[J]. Neurosurg Rev, 2022, 45(3): 2013-2026. DOI: 10.1007/s10143-022-01758-8.
BOURGIOTI C, KONIDARI M, GOURTSOYIANNI S, et al . Imaging during pregnancy: what the radiologist needs to know[J ] . Diagn Interv Imaging, 2021, 102(10): 593-603. DOI: 10.1016/j.diii.2021.05.003.
熊蕾, 杨相梅. 不同类型肺血栓栓塞临床特点及预后相关因素分析[J]. 重庆医科大学学报, 2015, 40(12): 1593-1598. DOI: 10.13406/j.cnki.cyxb.000727.
XIONG L, YANG X M. Clinical characteristics and risk factors associated with prognosis of different types of pulmonary thromboembolism[J]. J Chongqing Med Univ, 2015, 40(12): 1593-1598. DOI: 10.13406/j.cnki.cyxb.000727.
KHORANA A A, KUDERER N M, CULAKOVA E, et al . Development and validation of a predictive model for chemotherapy-associated thrombosis[J ] . Blood, 2008, 111(10): 4902-4907. DOI: 10.1182/blood-2007-10-116327.
WANG Q H, ZENNADI R. Oxidative stress and thrombosis during aging: the roles of oxidative stress in RBCs in venous thrombosis[J]. Int J Mol Sci, 2020, 21(12): 4259. DOI: 10.3390/ijms21124259.
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