Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism
Objective This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. Methods Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyze...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2020-10-01
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| Series: | Journal of International Medical Research |
| Online Access: | https://doi.org/10.1177/0300060519893173 |
| _version_ | 1818920347828748288 |
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| author | Xindan Wang Jing Huang Zhao Bingbing Shape Li Li Li |
| author_facet | Xindan Wang Jing Huang Zhao Bingbing Shape Li Li Li |
| author_sort | Xindan Wang |
| collection | DOAJ |
| description | Objective This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. Methods Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyzed. Patients were risk-stratified with three different risk assessment models individually, including the Caprini model, Wells DVT model, and Khorana model. Results The difference in risk level evaluated by the Caprini model was not different between the DVT and control groups. However, the DVT group had a significantly higher risk level than the control group with the Wells DVT or Khorana model. The Wells DVT model was more effective for stratifying patients in the DVT group into the higher risk level and for stratifying those in the control group into the lower risk level. Receiver operating curve analysis showed that the area under the curve of the Wells DVT, Khorana, and Caprini models was 0.995 ± 0.002, 0.642 ± 0.038, and 0.567 ± 0.039, respectively. Conclusion The Wells DVT model is the most suitable risk assessment model for predicting DVT. Clinicians could also combine the Caprini and Wells DVT models to effectively identify high-risk patients and eliminate patients without DVT. |
| first_indexed | 2024-12-20T01:20:19Z |
| format | Article |
| id | doaj.art-e9a1cb0ab20e4ba88e9701652126c678 |
| institution | Directory Open Access Journal |
| issn | 1473-2300 |
| language | English |
| last_indexed | 2024-12-20T01:20:19Z |
| publishDate | 2020-10-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of International Medical Research |
| spelling | doaj.art-e9a1cb0ab20e4ba88e9701652126c6782022-12-21T19:58:28ZengSAGE PublishingJournal of International Medical Research1473-23002020-10-014810.1177/0300060519893173Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolismXindan WangJing HuangZhao BingbingShape LiLi LiObjective This study aimed to investigate a suitable risk assessment model to predict deep vein thrombosis (DVT) in patients with gynecological cancer. Methods Data from 212 patients with gynecological cancer in the Affiliated Tumor Hospital of Guangxi Medical University were retrospectively analyzed. Patients were risk-stratified with three different risk assessment models individually, including the Caprini model, Wells DVT model, and Khorana model. Results The difference in risk level evaluated by the Caprini model was not different between the DVT and control groups. However, the DVT group had a significantly higher risk level than the control group with the Wells DVT or Khorana model. The Wells DVT model was more effective for stratifying patients in the DVT group into the higher risk level and for stratifying those in the control group into the lower risk level. Receiver operating curve analysis showed that the area under the curve of the Wells DVT, Khorana, and Caprini models was 0.995 ± 0.002, 0.642 ± 0.038, and 0.567 ± 0.039, respectively. Conclusion The Wells DVT model is the most suitable risk assessment model for predicting DVT. Clinicians could also combine the Caprini and Wells DVT models to effectively identify high-risk patients and eliminate patients without DVT.https://doi.org/10.1177/0300060519893173 |
| spellingShingle | Xindan Wang Jing Huang Zhao Bingbing Shape Li Li Li Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism Journal of International Medical Research |
| title | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
| title_full | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
| title_fullStr | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
| title_full_unstemmed | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
| title_short | Risk factors, risk assessment, and prognosis in patients with gynecological cancer and thromboembolism |
| title_sort | risk factors risk assessment and prognosis in patients with gynecological cancer and thromboembolism |
| url | https://doi.org/10.1177/0300060519893173 |
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