Study on predicting the risk of retinal vein occlusion based on nomogram model and systemic risk factors_Chinese Journal of Ocular Fundus Diseases

Authors：

Shao Meilin , Ren Meimei , Zhang Wenyi , Yang Zhuoyan , Wu Yidan , Wang Jianming ,  Wang Lijun

Department of Ophthalmology, The Second Affiliated Hospital of Xi' an Jiaotong University, Xi'an 710004, China;

Corresponding author：

Wang Lijun, Email: wanglijun201008@sina.com

Keywords：

Retinal vein occlusion; Nomogram; Risk model

DOI：

10.3760/cma.j.cn511434-20230110-00017

Video：

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Objective To establish and preliminarily validate a nomogram model for predicting the risk of retinal vein occlusion (RVO). Methods A retrospective clinical study. A total of 162 patients with RVO (RVO group) diagnosed by ophthalmology examination in The Second Affiliated Hospital of Xi'an Jiaotong University from January 2017 to April 2022 and 162 patients with age-related cataract (nRVO group) were selected as the modeling set. A total of 45 patients with branch RVO, 45 patients with central RVO and 45 patients with age-related cataract admitted to Xi 'an Fourth Hospital from January 2022 to February 2023 were used as the validation set. There was no significant difference in gender composition ratio (χ²=2.433) and age (Z=1.006) between RVO group and nRVO group (P=0.120, 0.320). Age, gender, blood routine (white blood cell count, hemoglobin concentration, platelet count, neutrophil count, monocyte count, lymphocyte count, erythrocyte volume, mean platelet volume, platelet volume distribution width), and four items of thrombin (prothrombin time, activated partial thrombin time, fibrinogen, and thrombin time) were collected in detail ), uric acid, blood lipids (total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, lipoprotein a), hypertension, diabetes mellitus, coronary heart disease, and cerebral infarction. Neutrophil/lymphocyte ratio and platelet/lymphocyte ratio were calculated. The single logistic regression was used to analyze the clinical parameters of the two groups of patients in the modeling set, and the stepwise regression method was used to screen the variables, and the column graph for predicting the risk of RVO was constructed. The Bootstrap method was used to repeated sample 1 000 times for internal and external verification. The H-L goodness-of-fit test and receiver operating characteristic (ROC) curve were used to evaluate the calibration and discrimination of the nomogram model. Results After univariate logistic regression and stepwise regression analysis, high density lipoprotein, neutrophil count and hypertension were included in the final prediction model to construct the nomogram. The χ² values of the H-L goodness-of-fit test of the modeling set and the validation set were 0.711 and 4.230, respectively, and the P values were 0.701 and 0.121, respectively, indicating that the nomogram model had good prediction accuracy. The area under the ROC curve of the nomogram model for predicting the occurrence of post-stroke depression in the modeling set and the verification set was 0.741 [95% confidence interval (CI) 0.688-0.795] and 0.741 (95%CI 0.646-0.836), suggesting that the nomogram model had a good discrimination. Conclusions Low high density lipoprotein level, high neutrophil count and hypertension are independent risk factors for RVO. The nomogram model established based on the above risk factors can effectively assess and quantify the risk of post-stroke depression in patients with cerebral infarction.

Citation： Shao Meilin, Ren Meimei, Zhang Wenyi, Yang Zhuoyan, Wu Yidan, Wang Jianming, Wang Lijun. Study on predicting the risk of retinal vein occlusion based on nomogram model and systemic risk factors. Chinese Journal of Ocular Fundus Diseases, 2023, 39(5): 381-386. doi: 10.3760/cma.j.cn511434-20230110-00017 Copy

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2.	Leoncini G, Bruzzese D, Signorello MG, et al. Platelet activation by collagen is increased in retinal vein occlusion[J]. Thromb Haemost, 2007, 97(2): 218-227. DOI: 10.1160/TH06-05-0257.
3.	Sofi F, Marcucci R, Fedi S, et al. High lipoprotein (a) levels are associated with an increased risk of retinal vein occlusion[J]. Atherosclerosis, 2010, 210(1): 278-281. DOI: 10.1016/j.atherosclerosis.2009.11.006.
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12.	Zhao Y, Yu R, Sun C, et al. Nomogram model predicts the risk of visual impairment in diabetic retinopathy: a retrospective study[J]. BMC Ophthalmology, 2022, 22(1): 478. DOI: 10.1186/s12886-022-02710-6.
13.	Zeng Q, Yao Y, Zhao M. Development and validation of a nomogram to predict cancer-specific survival of uveal melanoma[J]. BMC Ophthalmology, 2021, 21(1): 230. DOI: 10.1186/s12886-021-01968-6.
14.	Elman MJ, Bhatt AK, Quinlan PM, et al. The risk for systemic vascular diseases and mortality in patients with central retinal vein occlusion[J]. Ophthalmology, 1990, 97(11): 1543-1548. DOI: 10.1016/s0161-6420(90)32379-5.
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16.	Kim HR, Lee NK, Lee CS, et al. Retinal vascular occlusion risks in high blood pressure and the benefits of blood pressure control[J/OL]. Am J Ophthalmol, 2023, 250: 111-119. DOI: 10.1016/j.ajo.2023.01.023.
17.	Stojakovic T, Scharnagl H, März W, et al. Low density lipoprotein triglycerides and lipoprotein(a) are risk factors for retinal vascular occlusion[J]. Clin Chim Acta, 2007, 382(1-2): 77-81. DOI: 10.1016/j.cca.2007.03.024.
18.	Ponto KA, Elbaz H, Peto T, et al. Prevalence and risk factors of retinal vein occlusion: the Gutenberg Health Study[J]. J Thromb Haemost, 2015, 13(7): 1254-1263. DOI: 10.1111/jth.12982.
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20.	Camont L, Lhomme M, Rached F, et al. Small, dense high-density lipoprotein-3 particles are enriched in negatively charged phospholipids: relevance to cellular cholesterol efflux, antioxidative, antithrombotic, anti-inflammatory, and antiapoptotic functionalities[J]. Arterioscler Thromb Vasc Biol, 2013, 33(12): 2715-2723. DOI: 10.1161/ATVBAHA.113.301468.
21.	Riwanto M, Rohrer L, Roschitzki B, et al. Altered activation of endothelial anti- and proapoptotic pathways by high-density lipoprotein from patients with coronary artery disease: role of high-density lipoprotein-proteome remodeling[J]. Circulation, 2013, 127(8): 891-904. DOI: 10.1161/CIRCULATIONAHA.112.108753.
22.	Paliogiannis P, Fois AG, Sotgia S, et al. Neutrophil to lymphocyte ratio and clinical outcomes in COPD: recent evidence and future perspectives[J/OL]. Eur Respir Rev, 2018, 27(147): 170113[2018-02-07]. https://europepmc.org/article/MED/29436405. DOI: 10.1183/16000617.0113-2017.
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1. Zhou JQ, Xu L, Wang S, et al. The 10-year incidence and risk factors of retinal vein occlusion: the Beijing eye study[J]. Ophthalmology, 2013, 120(4): 803-808. DOI: 10.1016/j.ophtha.2012.09.033.
2. Leoncini G, Bruzzese D, Signorello MG, et al. Platelet activation by collagen is increased in retinal vein occlusion[J]. Thromb Haemost, 2007, 97(2): 218-227. DOI: 10.1160/TH06-05-0257.
3. Sofi F, Marcucci R, Fedi S, et al. High lipoprotein (a) levels are associated with an increased risk of retinal vein occlusion[J]. Atherosclerosis, 2010, 210(1): 278-281. DOI: 10.1016/j.atherosclerosis.2009.11.006.
4. Hayreh SS, Podhajsky PA, Zimmerman MB. Retinal artery occlusion: associated systemic and ophthalmic abnormalities[J]. Ophthalmology, 2009, 116(10): 1928-1936. DOI: 10.1016/j.ophtha.2009.03.006.
5. Lyu M, Lee Y, Kim BS, et al. Clinical significance of subclinical atherosclerosis in retinal vein occlusion[J/OL]. Sci Rep, 2021, 11(1): 11905[2021-06-07]. https://europepmc.org/article/MED/34099806. DOI: 10.1038/s41598-021-91401-1.
6. Park SY. Nomogram: an analogue tool to deliver digital knowledge[J]. J Thorac Cardiovasc Surg, 2018, 155(4): 1793. DOI: 10.1016/j.jtcvs.2017.12.107.
7. Flaxel CJ, Adelman RA, Bailey ST, et al. Retinal vein occlusions preferred practice pattern®[J]. Ophthalmology, 2020, 127(2): 288-320. DOI: 10.1016/j.ophtha.2019.09.029.
8. Song P, Xu Y, Zha M, et al. Global epidemiology of retinal vein occlusion: a systematic review and meta-analysis of prevalence, incidence, and risk factors[J/OL]. J Glob Health, 2019, 9(1): 010427[2019-06-01]. https://europepmc.org/article/MED/31131101. DOI: 10.7189/jogh.09.010427.
9. Balachandran VP, Gonen M, Smith JJ, et al. Nomograms in oncology: more than meets the eye[J]. Lancet Oncol, 2015, 16(4): 173-180. DOI: 10.1016/S1470-2045(14)71116-7.
10. Liang G, Chen X, Zha X, et al. A nomogram to improve predictability of small-incision lenticule extraction surgery[J]. Med Sci Monit, 2017, 23: 5168-5175. DOI: 10.12659/msm.904598.
11. Li Z, Deng X, Zhou L, et al. Nomogram-based prediction of clinically significant macular edema in diabetes mellitus patients[J]. Acta Diabetologica, 2022, 59(9): 1179-1188. DOI: 10.1007/s00592-022-01901-3.
12. Zhao Y, Yu R, Sun C, et al. Nomogram model predicts the risk of visual impairment in diabetic retinopathy: a retrospective study[J]. BMC Ophthalmology, 2022, 22(1): 478. DOI: 10.1186/s12886-022-02710-6.
13. Zeng Q, Yao Y, Zhao M. Development and validation of a nomogram to predict cancer-specific survival of uveal melanoma[J]. BMC Ophthalmology, 2021, 21(1): 230. DOI: 10.1186/s12886-021-01968-6.
14. Elman MJ, Bhatt AK, Quinlan PM, et al. The risk for systemic vascular diseases and mortality in patients with central retinal vein occlusion[J]. Ophthalmology, 1990, 97(11): 1543-1548. DOI: 10.1016/s0161-6420(90)32379-5.
15. O'Mahoney PR, Wong DT, Ray JG. Retinal vein occlusion and traditional risk factors for atherosclerosis[J/OL]. Arch Ophthalmol, 2008, 126(5): 692-699. DOI: 10.1001/archopht.126.5.692.
16. Kim HR, Lee NK, Lee CS, et al. Retinal vascular occlusion risks in high blood pressure and the benefits of blood pressure control[J/OL]. Am J Ophthalmol, 2023, 250: 111-119. DOI: 10.1016/j.ajo.2023.01.023.
17. Stojakovic T, Scharnagl H, März W, et al. Low density lipoprotein triglycerides and lipoprotein(a) are risk factors for retinal vascular occlusion[J]. Clin Chim Acta, 2007, 382(1-2): 77-81. DOI: 10.1016/j.cca.2007.03.024.
18. Ponto KA, Elbaz H, Peto T, et al. Prevalence and risk factors of retinal vein occlusion: the Gutenberg Health Study[J]. J Thromb Haemost, 2015, 13(7): 1254-1263. DOI: 10.1111/jth.12982.
19. Kim J, Lim DH, Han K, et al. Retinal vein occlusion is associated with low blood high-density lipoprotein cholesterol: a nationwide cohort study[J]. Am J Ophthalmol, 2019, 205: 35-42. DOI: 10.1016/j.ajo.2019.04.001.
20. Camont L, Lhomme M, Rached F, et al. Small, dense high-density lipoprotein-3 particles are enriched in negatively charged phospholipids: relevance to cellular cholesterol efflux, antioxidative, antithrombotic, anti-inflammatory, and antiapoptotic functionalities[J]. Arterioscler Thromb Vasc Biol, 2013, 33(12): 2715-2723. DOI: 10.1161/ATVBAHA.113.301468.
21. Riwanto M, Rohrer L, Roschitzki B, et al. Altered activation of endothelial anti- and proapoptotic pathways by high-density lipoprotein from patients with coronary artery disease: role of high-density lipoprotein-proteome remodeling[J]. Circulation, 2013, 127(8): 891-904. DOI: 10.1161/CIRCULATIONAHA.112.108753.
22. Paliogiannis P, Fois AG, Sotgia S, et al. Neutrophil to lymphocyte ratio and clinical outcomes in COPD: recent evidence and future perspectives[J/OL]. Eur Respir Rev, 2018, 27(147): 170113[2018-02-07]. https://europepmc.org/article/MED/29436405. DOI: 10.1183/16000617.0113-2017.
23. Laridan E, Martinod K, De Meyer SF. Neutrophil extracellular traps in arterial and venous thrombosis[J]. Semin Thromb Hemost, 2019, 45(1): 86-93. DOI: 10.1055/s-0038-1677040.
24. Nicholson L, Talks SJ, Amoaku W, et al. Retinal vein occlusion (rvo) guideline: executive summary[J]. Eye (Lond), 2022, 36(5): 909-912. DOI: 10.1038/s41433-022-02007-4.

Chinese Journal of Ocular Fundus Diseases

Study on predicting the risk of retinal vein occlusion based on nomogram model and systemic risk factors

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