北京生物醫(yī)學(xué)工程

泌尿腫瘤住院患者DVT發(fā)生風(fēng)險(xiǎn)相關(guān)性因素及預(yù)后模型研究

Research on risk-related factors and prognostic models of deep vein thrombosis in patients with urinary tumors during hospitalization

作者：王正源張姬黃宗浩王奕

單位：復(fù)旦大學(xué)附屬腫瘤醫(yī)院信息中心-復(fù)旦大學(xué)上海醫(yī)學(xué)院腫瘤學(xué)系(上海 200032)<br />復(fù)旦大學(xué)附屬腫瘤醫(yī)院護(hù)理部-復(fù)旦大學(xué)上海醫(yī)學(xué)院腫瘤學(xué)系(上海 200032)<br />上海腫瘤疾病人工智能工程技術(shù)研究中心(上海 200032)<br />通信作者：王奕，高級(jí)工程師。E-mail: [email protected]

關(guān)鍵詞：泌尿腫瘤；深靜脈血栓形成；預(yù)后；分類器

分類號(hào)：R318

出版年·卷·期（頁(yè)碼）：2023·42·2（144-151）

摘要：

目的基于泌尿外科腫瘤患者，對(duì)其深靜脈血栓形成（deep vein thrombosis, DVT）發(fā)生風(fēng)險(xiǎn)相關(guān)性因素及預(yù)后模型進(jìn)行探究，以此輔助臨床更好地進(jìn)行風(fēng)險(xiǎn)評(píng)估，作出準(zhǔn)確的預(yù)后判斷并采取相應(yīng)預(yù)防措施。方法抽取選用復(fù)旦大學(xué)附屬腫瘤醫(yī)院2019年12月—2021年12月收治的泌尿外科腫瘤患者住院期間建立的3 814條DVT發(fā)生風(fēng)險(xiǎn)評(píng)估表單記錄的數(shù)據(jù)。首先，對(duì)數(shù)據(jù)樣本進(jìn)行相關(guān)性因素提取，并行數(shù)據(jù)清洗、脫敏及結(jié)構(gòu)化處理；然后，使用Mann-Whitney U檢驗(yàn)對(duì)特征數(shù)據(jù)進(jìn)行單因素分析，使用Logistic回歸模型進(jìn)行回歸性分析，得到患者DVT發(fā)生風(fēng)險(xiǎn)的顯著性相關(guān)因素；最后，基于機(jī)器學(xué)習(xí)支持向量機(jī)(support vector machine, SVM）算法和決策樹算法，采用交叉驗(yàn)證方法訓(xùn)練分類器并檢驗(yàn)相關(guān)性因素對(duì)患者DVT發(fā)生風(fēng)險(xiǎn)的預(yù)測(cè)能力。結(jié)果 Mann-Whitney U檢驗(yàn)分析結(jié)果顯示，體質(zhì)量指數(shù)（BMI）、活動(dòng)、特殊風(fēng)險(xiǎn)以及外科手術(shù)與患者DVT發(fā)生風(fēng)險(xiǎn)相關(guān)（P<0.05）。Logistic回歸分析顯示，BMI、活動(dòng)、特殊風(fēng)險(xiǎn)以及外科手術(shù)與患者DVT發(fā)生風(fēng)險(xiǎn)顯著相關(guān)（P<0.05），SVM分類器分類結(jié)果顯示最高分類準(zhǔn)確率為87.6%，最大曲線下的面積(area under curve, AUC）為0.904，即這4種特征可以對(duì)患者的DVT發(fā)生風(fēng)險(xiǎn)作出較為準(zhǔn)確的預(yù)測(cè)。結(jié)論 BMI、活動(dòng)、特殊風(fēng)險(xiǎn)以及外科手術(shù)4種因素是泌尿外科腫瘤患者DVT發(fā)生風(fēng)險(xiǎn)的顯著性相關(guān)因素。

Objective Based on urological tumor patients to explore the risk-related factors and prognostic models of Deep Vein Thrombosis (DVT), to assist the clinic can better assess the risk, make accurate prognostic judgments, and take corresponding preventive measures. Methods The data collected from 3814 DVT risk assessment forms established during the hospitalization of urological tumor patients admitted to Fudan University Shanghai Cancer Center from December 2019 to December 2021 were selected. First, extract the relevant factors of the data sample, parallel data cleaning, desensitization and structuring; then, use the Mann-Whitney U test to perform single factor analysis on the characteristic data, and use the logistic regression model to perform regression analysis to obtain the urology Significant factors related to the risk of DVT in cancer patients; finally, based on machine learning support vector machine (SVM) algorithm and decision tree algorithm, The cross-validation method is used to train the classifier and test the predictive ability of related factors on the risk of DVT in urological tumor patients. Results Mann-Whitney U test analysis showed that body mass index (BMI), activity, special risks, and surgery were related to the risk of DVT in patients with urological tumors (P<0.05). Logistic regression analysis showed that BMI, activity, special risks, and surgical procedures were significantly related to the risk of DVT in patients with urological tumors (P<0.05). The classification results of SVM classifier showed that the highest classification accuracy rate was 87.6%, the largest curve The area under curve (AUC) is 0.904, which means that these four characteristics can make a more accurate prediction of the risk of DVT in patients with urinary tumors. Conclusions The four factors of BMI, activity, special risk, and surgery are significant factors related to the risk of DVT in patients with urinary tumors.

參考文獻(xiàn)：

[1] 葉定偉, 秦曉健. “互聯(lián)網(wǎng)+”時(shí)代泌尿腫瘤多學(xué)科診治模式探索——“中國(guó)泌尿腫瘤MDT會(huì)診平臺(tái)”簡(jiǎn)介[J]. 現(xiàn)代泌尿外科雜志, 2018, 23(1): 1-2.
[2] 祁莎莎, 曹鑫, 徐寧寧, 等. 深靜脈血栓關(guān)鍵基因AP2B1和miRNAs及其相關(guān)通路的篩選[J]. 北京生物醫(yī)學(xué)工程, 2022, 41(4): 344-351, 367.
Qi SS, Cao X, Xu NN, et al. Screening of key gene AP2B1, miRNAs and related pathways in deep venous thrombosis[J]. Beijing Biomedical Engineering, 2022, 41(4): 344-351, 367.
[3] 楊揚(yáng)揚(yáng), 張曉紅, 申麗. 3種風(fēng)險(xiǎn)評(píng)估量表對(duì)泌尿外科術(shù)后患者深靜脈血栓形成的風(fēng)險(xiǎn)預(yù)測(cè)分析[J]. 中國(guó)民間療法, 2021, 29(16): 91-94.
[4] Guanella R, Ducruet T, Johri M, et al. Economic burden and cost determinants of deep vein thrombosis during 2 years following diagnosis: a prospective evaluation[J]. Journal of Thrombosis and Haemostasis, 2011, 9(12): 2397-2405.
[5] 蔡永俊, 閆士舉, 宋成利. 深靜脈取栓器流體動(dòng)力碎栓數(shù)值模擬[J]. 北京生物醫(yī)學(xué)工程, 2018, 37(1): 27-33.
Cai YJ, Yan SJ, Song CL. Fluid dynamics numerical simulation of thrombectomy device for deep vein[J]. Beijing Biomedical Engineering, 2018, 37(1): 27-33.
[6] Walker AJ, Card TR, West J, et al. Incidence of venous thromboembolism in patients with cancer - a cohort study using linked United Kingdom databases[J]. European Journal of Cancer, 2013, 49(6): 1404-1413.
[7] Gee E. The National VTE Exemplar Centres Network response to implementation of updated NICE guidance: venous thromboembolism in over 16s: reducing the risk of hospital-acquired deep vein thrombosis or pulmonary embolism (NG89)[J]. British Journal of Haematology, 2019, 186(5): 792-793.
[8] Falck-Ytter Y, Francis CW, Johanson NA, et al. Prevention of VTE in orthopedic surgery patients: antithrombotic therapy and prevention of thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines[J]. Chest, 2012, 141(2): e278S-e325S.
[9] Lobastov K, Barinov V, Schastlivtsev I, et al. Validation of the Caprini risk assessment model for venous thromboembolism in high-risk surgical patients in the background of standard prophylaxis[J]. Journal of Vascular Surgery: Venous and Lymphatic Disorders, 2016, 4(2): 153-160.
[10] Barber EL, Clarke-Pearson DL. The limited utility of currently available venous thromboembolism risk assessment tools in gynecological oncology patients[J]. American Journal of Obstetrics & Gynecology, 2016, 215(4): 445.E1-445.E9.
[11] Khorana AA, Kuderer NM, Culakova E, et al. Development and validation of a predictive model for chemotherapy-associated thrombosis[J]. Blood, 2008, 111(10): 4902-4907.
[12] Metcalf RL, Al-Hadithi E, Hopley N, et al. Characterisation and risk assessment of venous thromboembolism in gastrointestinal cancers[J]. World Journal of Gastrointestinal Oncology, 2017, 9(9): 363-371.
[13] Rogers Jr SO, Kilaru RK, Hosokawa P, et al. Multivariable predictors of postoperative venous thromboembolic events after general and vascular surgery: results from the patient safety in surgery study[J]. Journal of the American College of Surgeons, 2007, 204(6): 1211-1221.
[14] 田博, 宋春鳳, 李輝, 等. Caprini和Rogers風(fēng)險(xiǎn)評(píng)估模型聯(lián)合使用可以提高胸外科術(shù)后患者篩選靜脈血栓栓塞癥的準(zhǔn)確性[J]. 中華胸部外科電子雜志, 2017, 4(3): 186-189.
Tian B, Song CF, Li H, et al. The combination of Caprini and Rogers risk assessment models can improve the accuracy of screening for venous thromboembolism in patients undergoing thoracic surgery[J]. Chinese Journal of Thoracic Surgery(Electronic Edition), 2017, 4(3): 186-189.
[15] 郭海, 方強(qiáng), 黃建鳴, 等. Caprini和Rogers血栓風(fēng)險(xiǎn)評(píng)估模型在胸外科肺癌患者圍手術(shù)期應(yīng)用的驗(yàn)證研究[J]. 腫瘤預(yù)防與治療, 2019, 32(8): 660-667.
Guo H, Fang Q, Huang JM, et al. Application of Caprini and Rogers risk assessment models in the perioperative management of lung cancer patients[J]. Journal of Cancer Control and Treatment, 2019, 32(8): 660-667.
[16] Autar R. Nursing assessment of clients at risk of deep vein thrombosis (DVT): the Autar DVT scale[J]. Journal of Advanced Nursing, 1996, 23(4): 763-770.
[17] Wang MM, Qin XJ, He XX, et al. Comparison and screening of different risk assessment models for deep vein thrombosis in patients with solid tumors[J]. Journal of Thrombosis and Thrombolysis, 2019, 48(2): 292-298.
[18] Müller G, Fritz E, Them C. Translation of the "Autar Deep Vein Thrombosis Scale" to assess the risk of thrombosis[J]. Pflege Zeitschrift, 2008, 61(2): 94-99.
[19] 肖冕,賈汝福,尹桂梅, 等.下肢深靜脈血栓形成患者自我感受負(fù)擔(dān)現(xiàn)狀及其影響因素分析[J].中國(guó)醫(yī)藥導(dǎo)報(bào),2022,19(8): 43-47.
Xiao M, Jia RF, Yin GM, et al. Analysis of status quo and influencing factors of self-perceived burden in patients with lower extremity deep vein thrombosis[J]. China Medical Herald, 2022,19(8): 43-47.

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