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A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome
OBJECTIVE: Post-thrombotic syndrome (PTS) is the most common long-term complication in patients with deep venous thrombosis, and the prevention of PTS remains a major challenge in clinical practice. Some studies have explored early predictors and constructed corresponding prediction models, whereas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484413/ https://www.ncbi.nlm.nih.gov/pubmed/37692043 http://dx.doi.org/10.3389/fcvm.2023.1250480 |
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author | Yu, Tong Song, Jialin Yu, LingKe Deng, Wanlin |
author_facet | Yu, Tong Song, Jialin Yu, LingKe Deng, Wanlin |
author_sort | Yu, Tong |
collection | PubMed |
description | OBJECTIVE: Post-thrombotic syndrome (PTS) is the most common long-term complication in patients with deep venous thrombosis, and the prevention of PTS remains a major challenge in clinical practice. Some studies have explored early predictors and constructed corresponding prediction models, whereas their specific application and predictive value are controversial. Therefore, we conducted this systematic evaluation and meta-analysis to investigate the incidence of PTS and the feasibility of early prediction. METHODS: We systematically searched databases of PubMed, Embase, Cochrane and Web of Science up to April 7, 2023. Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included articles, and the OR values of the predictors in multi-factor logistic regression were pooled to assess whether they could be used as effective independent predictors. RESULTS: We systematically included 20 articles involving 8,512 subjects, with a predominant onset of PTS between 6 and 72 months, with a 2-year incidence of 37.5% (95% CI: 27.8–47.7%). The results for the early predictors were as follows: old age OR = 1.840 (95% CI: 1.410–2.402), obesity or overweight OR = 1.721 (95% CI: 1.245–2.378), proximal deep vein thrombosis OR = 2.335 (95% CI: 1.855–2.938), history of venous thromboembolism OR = 3.593 (95% CI: 1.738–7.240), history of smoking OR = 2.051 (95% CI: 1.305–3.224), varicose veins OR = 2.405 (95% CI: 1.344–4.304), and baseline Villalta score OR = 1.095(95% CI: 1.056–1.135). Meanwhile, gender, unprovoked DVT and insufficient anticoagulation were not independent predictors. Seven studies constructed risk prediction models. In the training set, the c-index of the prediction models was 0.77 (95% CI: 0.74–0.80) with a sensitivity of 0.75 (95% CI: 0.68–0.81) and specificity of 0.69 (95% CI: 0.60–0.77). In the validation set, the c-index, sensitivity and specificity of the prediction models were 0.74(95% CI: 0.69–0.79), 0.71(95% CI: 0.64–0.78) and 0.72(95% CI: 0.67–0.76), respectively. CONCLUSIONS: With a high incidence after venous thrombosis, PTS is a complication that cannot be ignored in patients with venous thrombosis. Risk prediction scoring based on early model construction is a feasible option, which helps to identify the patient's condition and develop an individualized prevention program to reduce the risk of PTS. |
format | Online Article Text |
id | pubmed-10484413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104844132023-09-08 A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome Yu, Tong Song, Jialin Yu, LingKe Deng, Wanlin Front Cardiovasc Med Cardiovascular Medicine OBJECTIVE: Post-thrombotic syndrome (PTS) is the most common long-term complication in patients with deep venous thrombosis, and the prevention of PTS remains a major challenge in clinical practice. Some studies have explored early predictors and constructed corresponding prediction models, whereas their specific application and predictive value are controversial. Therefore, we conducted this systematic evaluation and meta-analysis to investigate the incidence of PTS and the feasibility of early prediction. METHODS: We systematically searched databases of PubMed, Embase, Cochrane and Web of Science up to April 7, 2023. Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included articles, and the OR values of the predictors in multi-factor logistic regression were pooled to assess whether they could be used as effective independent predictors. RESULTS: We systematically included 20 articles involving 8,512 subjects, with a predominant onset of PTS between 6 and 72 months, with a 2-year incidence of 37.5% (95% CI: 27.8–47.7%). The results for the early predictors were as follows: old age OR = 1.840 (95% CI: 1.410–2.402), obesity or overweight OR = 1.721 (95% CI: 1.245–2.378), proximal deep vein thrombosis OR = 2.335 (95% CI: 1.855–2.938), history of venous thromboembolism OR = 3.593 (95% CI: 1.738–7.240), history of smoking OR = 2.051 (95% CI: 1.305–3.224), varicose veins OR = 2.405 (95% CI: 1.344–4.304), and baseline Villalta score OR = 1.095(95% CI: 1.056–1.135). Meanwhile, gender, unprovoked DVT and insufficient anticoagulation were not independent predictors. Seven studies constructed risk prediction models. In the training set, the c-index of the prediction models was 0.77 (95% CI: 0.74–0.80) with a sensitivity of 0.75 (95% CI: 0.68–0.81) and specificity of 0.69 (95% CI: 0.60–0.77). In the validation set, the c-index, sensitivity and specificity of the prediction models were 0.74(95% CI: 0.69–0.79), 0.71(95% CI: 0.64–0.78) and 0.72(95% CI: 0.67–0.76), respectively. CONCLUSIONS: With a high incidence after venous thrombosis, PTS is a complication that cannot be ignored in patients with venous thrombosis. Risk prediction scoring based on early model construction is a feasible option, which helps to identify the patient's condition and develop an individualized prevention program to reduce the risk of PTS. Frontiers Media S.A. 2023-08-24 /pmc/articles/PMC10484413/ /pubmed/37692043 http://dx.doi.org/10.3389/fcvm.2023.1250480 Text en © 2023 Yu, Song, Yu and Deng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Yu, Tong Song, Jialin Yu, LingKe Deng, Wanlin A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
title | A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
title_full | A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
title_fullStr | A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
title_full_unstemmed | A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
title_short | A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
title_sort | systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484413/ https://www.ncbi.nlm.nih.gov/pubmed/37692043 http://dx.doi.org/10.3389/fcvm.2023.1250480 |
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