Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment
Objective To begin to understand how to prevent deep vein thrombosis (DVT) after an innovative operation termed intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder, we explored the factors that influence DVT following surgery, with the aim of constructing a model for predicting...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2022-01-01
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| Series: | Journal of International Medical Research |
| Online Access: | https://doi.org/10.1177/03000605211067688 |
| _version_ | 1798035356143058944 |
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| author | Xing Liu Abai Xu Jingwen Huang Haiyan Shen Yazhen Liu |
| author_facet | Xing Liu Abai Xu Jingwen Huang Haiyan Shen Yazhen Liu |
| author_sort | Xing Liu |
| collection | DOAJ |
| description | Objective To begin to understand how to prevent deep vein thrombosis (DVT) after an innovative operation termed intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder, we explored the factors that influence DVT following surgery, with the aim of constructing a model for predicting DVT occurrence. Methods This retrospective study included 151 bladder cancer patients who underwent intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder. Data describing general clinical characteristics and other common parameters were collected and analyzed. Thereafter, we generated model evaluation curves and finally cross-validated their extrapolations. Results Age and body mass index were risk factors for DVT, whereas postoperative use of hemostatic agents and postoperative passive muscle massage were significant protective factors. Model evaluation curves showed that the model had high accuracy and little bias. Cross-validation affirmed the accuracy of our model. Conclusion The prediction model constructed herein was highly accurate and had little bias; thus, it can be used to predict the likelihood of developing DVT after surgery. |
| first_indexed | 2024-04-11T20:57:04Z |
| format | Article |
| id | doaj.art-07197d24a8f84aba86853866dce5bb43 |
| institution | Directory Open Access Journal |
| issn | 1473-2300 |
| language | English |
| last_indexed | 2024-04-11T20:57:04Z |
| publishDate | 2022-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of International Medical Research |
| spelling | doaj.art-07197d24a8f84aba86853866dce5bb432022-12-22T04:03:39ZengSAGE PublishingJournal of International Medical Research1473-23002022-01-015010.1177/03000605211067688Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatmentXing LiuAbai XuJingwen HuangHaiyan ShenYazhen LiuObjective To begin to understand how to prevent deep vein thrombosis (DVT) after an innovative operation termed intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder, we explored the factors that influence DVT following surgery, with the aim of constructing a model for predicting DVT occurrence. Methods This retrospective study included 151 bladder cancer patients who underwent intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder. Data describing general clinical characteristics and other common parameters were collected and analyzed. Thereafter, we generated model evaluation curves and finally cross-validated their extrapolations. Results Age and body mass index were risk factors for DVT, whereas postoperative use of hemostatic agents and postoperative passive muscle massage were significant protective factors. Model evaluation curves showed that the model had high accuracy and little bias. Cross-validation affirmed the accuracy of our model. Conclusion The prediction model constructed herein was highly accurate and had little bias; thus, it can be used to predict the likelihood of developing DVT after surgery.https://doi.org/10.1177/03000605211067688 |
| spellingShingle | Xing Liu Abai Xu Jingwen Huang Haiyan Shen Yazhen Liu Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment Journal of International Medical Research |
| title | Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment |
| title_full | Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment |
| title_fullStr | Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment |
| title_full_unstemmed | Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment |
| title_short | Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment |
| title_sort | effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment |
| url | https://doi.org/10.1177/03000605211067688 |
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