Correlation study of venous thromboembolism with SAA, IL-1, and TNF-a levels and gene polymorphisms in Chinese population

Abuduhalike, Refukaiti; Sun, Jing; Zhao, Li; Mahemuti, Ailiman

doi:10.21037/jtd.2019.11.26

Cited by 9 publications

(11 citation statements)

References 30 publications

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“…IL-1, SAA, IL-6, TNF-α, and CRP, as a class of pro-inflammatory factors, are important mediators of inflammation activation, and after inflammation, their activation may lead to slowed blood flow, vascular endothelial damage, and coagulation disorders that promote the occurrence of VTE. 12,[25][26][27][28] IL-1, SAA, TNF-α, and CRP levels were elevated in the VTE endpoint event group in the current study, suggesting that the poor prognosis caused by intense vascular injury after inflammation activation. As an important signal of IL-33/ST2L axis activation, ST2 is triggered and expressed during fibrosis, tissue damage, inflammation activation and cardiovascular remodeling.…”

Section: Dovepressmentioning

confidence: 79%

“…Using Shanghai Tianhao Company’s improved multiplex ligation detection reaction (iMLDR) Multiple Allelic Typing Kit, 8 genotypes were screened for in all samples with capillary peak electrophoresis using the iMLDR technique. 12 , 14 …”

Section: Methodsmentioning

confidence: 99%

“…[4][5][6][7][8][9][10][11] To date, there have been any research on the association between inflammatory gene polymorphisms and the prognosis of VTE. Our previous study 12 showed that plasma levels of serum amyloid A protein (SAA), interleukin-1 (IL-1) and tumor necrosis factor-a (TNF-a) in the VTE group were significantly higher than those in the control group. The TT genotype of the IL-1 rs2234650 variant was an independent risk factor for VTE.…”

Section: Introductionmentioning

confidence: 99%

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<p>Correlation Study of the Long-Term Prognosis of Venous Thromboembolism and Inflammatory Gene Polymorphisms</p>

Abuduhalike¹,

Sun²,

Mahemuti³

2020

IJGM

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Background Venous thromboembolism (VTE) is the third most common cause of cardiovascular death worldwide, following coronary heart disease and stroke, and many risk factors for VTE are not yet clear. Our study investigated the association between multiple inflammatory gene polymorphisms and VTE prognosis, aiming to find a new predictor of VTE prognosis. Methods Based on our previous studies, we detected the plasma levels of serum amyloid A protein (SAA), interleukin-1 (IL-1) and tumor necrosis factor-a (TNF-a) and their 8 gene polymorphisms by ELISA and a multiplex ligation detection reaction (iMLDR) method in 284 patients with VTE. All subjects were followed up for 5 years. Results The 5-year follow-up results of this study showed that 62 of the 284 patients (21.83%) had reached the endpoint (all-cause death). Kaplan–Meier survival analyses revealed that the mortality rate of VTE patients with a high Simplified Pulmonary Embolism Severity Index (SPESI) score and carrying IL-1 rs1800587 mutation genotypes was significantly increased (log-rank p=0.000 and 0.034 respectively). The multifactor Cox regression results confirmed that the mortality rate of patients who carrying IL-1 rs1800587 mutation genotypes was significantly increased (HR=2.982; 95% CI: 1.681–5.100). The mortality rate of those carrying IL-1 rs1143634 mutation genotypes was significantly decreased (HR=0.294; 95% CI: 0.132–0.652). There were no significant differences in mortality rates between wild-type and mutant genotypes of IL-1 rs1143634, IL-1 rs2234650, SAA rs11603089, and TNF-α rs1800629 (P>0.05). Conclusion A high SPESI score and the presence of the IL-1 rs1800587 mutant genotype predict shorter survival in patients with VTE, whereas the IL-1 rs1143634 genotype is associated with a lower mortality rate. Screening for mutations in inflammation-related genes has prognostic value in the clinical management of VTE.

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Section: Dovepressmentioning

confidence: 79%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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<p>Correlation Study of the Long-Term Prognosis of Venous Thromboembolism and Inflammatory Gene Polymorphisms</p>

Abuduhalike¹,

Sun²,

Mahemuti³

2020

IJGM

Self Cite

View full text Add to dashboard Cite

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“…Medical records which contain rich information about disease progression, are useful in mining new risk factors related to VTE patients. Each patient will undergo a series of laboratory tests upon admission, and the blood test indicators of VTE patients will be abnormal in varying degrees [26][27][28]. The timely detection of abnormal change will facilitate the VTE occurrence risk assessment and enable early warning and intervention.…”

Section: Introductionmentioning

confidence: 99%

Predicting the occurrence of venous thromboembolism: construction and verification of risk warning model

Shen

Liu

et al. 2020

BMC Cardiovasc Disord

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Background: The onset of venous thromboembolism is insidious and the prognosis is poor. In this study, we aimed to construct a VTE risk warning model and testified its clinical application value. Methods: Preliminary construction of the VTE risk warning model was carried out according to the independent risk warning indicators of VTE screened by Logistic regression analysis. The truncated value of screening VTE was obtained and the model was evaluated. ROC curve analysis was used to compare the test of Caprini risk assessment scale and VTE risk warning model. The cutoff value of the VTE risk warning model was used to evaluate the test effectiveness of the model for VTE patients with validation data set. Results: The VTE risk warning model is p = e x / (1+ e x), x = − 4.840 + 2.557 • X 10(1) + 1.432 • X 14(1) + 2.977 • X 15(1) + 3.445 • X 18(1) + 1.086 • X 25(1) + 0.249 • X 34 + 0.282 • X 41. ROC curve results show that: AUC (95%CI), cutoff value, sensitivity, specificity, accuracy, Youden index, Caprini risk assessment scale is 0.596 (0.552, 0.638), 5, 26.07, 96.50, 61.3%, 0.226, VTE risk warning model is 0.960 (0.940, 0.976), 0.438, 92.61, 91.83, 92.2%, 0.844, respectively, with statistically significant differences (Z = 14.521, P < 0.0001). The accuracy and Youden index of VTE screening using VTE risk warning model were 81.8 and 62.5%, respectively. Conclusions: VTE risk warning model had high accuracy in predicting VTE occurrence in hospitalized patients. Its test performance was better than Caprini risk assessment scale. It also had high test performance in external population.

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“…Medical records which contain rich information about disease progression, are useful in mining new risk factors related to VTE patients. Each patient will undergo a series of laboratory tests upon admission, and the blood test indicators of VTE patients will be abnormal to varying degrees [26][27][28]. The timely detection of these abnormal changes will help to assess the risk of VTE occurrence and enable early warning and intervention.…”

mentioning

confidence: 99%

Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

Shen

Liu

et al. 2020

Preprint

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Background: The onset of venous thromboembolism is insidious and the prognosis is poor. In this study, we aimed to construct a VTE risk early warning model and explore the clinical application value of the VTE risk early warning model. Methods: Preliminary construction of the VTE risk warning model was carried out according to the independent risk warning indicators of VTE screened by Logistic regression analysis in previous studies. The truncated value of screening VTE was obtained and the model was evaluated. ROC curve analysis was used to compare the test performance of Caprini risk assessment scale and VTE risk warning model on VTE. The validation data set was established, and the cut-off value of the VTE risk warning model was used to evaluate the test effectiveness of the model for VTE patients with validation data set. Results: The VTE risk warning model is p = ex / ( 1+ ex ) , x = -4.840 + 2.557 • X10(1) + 1.432 • X14(1) + 2.977 • X15(1) + 3.445 • X18(1) + 1.086 • X25(1) + 0.249 • X34 + 0.282 • X41. ROC curve results show that: AUC (95%CI), cutoff value (95%CI), accuracy, Youden index (95%), sensitivity, specificity and other evaluation indexes, Caprini risk assessment scale is 0.596 (0.552, 0.638), > 5 (> 4, > 5), 61.3%, 0.226 (0.167, 0.290), 26.07%, 96.50%, VTE risk warning model is 0.960 (0.940, 0.976), > 0.438 (> 0.263), respectively. >, 0.504), 92.2%, 0.844 (0.789, 0.879), 92.61%, 91.83%, with statistically significant differences (Z=14.521, P < 0.0001). The accuracy and Youden index of VTE screening using VTE risk warning model were 81.8% and 62.5%, respectively. Conclusions: VTE risk warning model has high accuracy in predicting the occurrence of VTE in hospitalized patients, and its test performance is higher than Caprini risk assessment scale. It also has high test performance for VTE in external population.

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Correlation study of venous thromboembolism with SAA, IL-1, and TNF-a levels and gene polymorphisms in Chinese population

Cited by 9 publications

References 30 publications

<p>Correlation Study of the Long-Term Prognosis of Venous Thromboembolism and Inflammatory Gene Polymorphisms</p>

<p>Correlation Study of the Long-Term Prognosis of Venous Thromboembolism and Inflammatory Gene Polymorphisms</p>

Predicting the occurrence of venous thromboembolism: construction and verification of risk warning model

Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

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