Laparoscopic sacrocolpopexy complication: Ilio-femoral deep vein thrombosis

Gutzeit, Ola; Lauterbach, Roy; Loberman, Zeev; Sachner, Robert; Karram, Tony; Löwenstein, Lior

doi:10.1016/j.ejogrb.2020.02.040

Cited by 4 publications

(5 citation statements)

References 3 publications

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“…The complications of DVT are pulmonary embolism and adverse impact on the limb motor function of patients. 8 In this report, we present a patient with DVT after recovery from COVID-19.…”

Section: Introductionmentioning

confidence: 96%

Distal Deep Vein Thrombosis in a Patient Cured of Severe COVID-19 Pneumonia at Jimma, Oromia, Ethiopia 2021: A Rare Case Report

Debela¹,

Ababulgu²,

Desu³

et al. 2021

IMCRJ

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Background Deep vein thrombosis (DVT) is commonly identified and diagnosed in the emergency department. Factors including sedentary life (immobility), pregnancy in women, cancer, postoperation, admission to ICU, smoking, and obesity are identified risks for thrombosis development. We report a case of a 35-year-old man who presented to the emergency department developing left lower leg swelling and pain, low-grade fever, and headache after he was treated and discharged, cured of severe COVID-19. Then venous and arterial Doppler ultrasound of the lower leg revealed dilated, absent flow and luminal thrombus in the distal popliteal, anterior and posterior tibial veins and perforator vessels were diagnosed as leg DVT. Conclusion DVT is a hematological emergency that needs serious consideration in prevention as well early diagnosis in patients with possible risk factors. This case report aims to arouse the clinician’s awareness of the occurrence of deep vein thrombosis during and after COVID-19.

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“…The complications of DVT are pulmonary embolism and adverse impact on the limb motor function of patients. 8 In this report, we present a patient with DVT after recovery from COVID-19.…”

Section: Introductionmentioning

confidence: 96%

Distal Deep Vein Thrombosis in a Patient Cured of Severe COVID-19 Pneumonia at Jimma, Oromia, Ethiopia 2021: A Rare Case Report

Debela¹,

Ababulgu²,

Desu³

et al. 2021

IMCRJ

View full text Add to dashboard Cite

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“…[ 5 ] The main veins of the whole body can be affected, especially in the lower limbs. [ 4 ] Severe DVT can promote the occurrence of pulmonary embolism and then endanger life. Previous studies have reported that the incidence of DVT after gynecological laparoscopic surgery ranges from 7.6% to 11.55%.…”

Section: Discussionmentioning

confidence: 99%

“…[ 3 ] According to previous research reports, the risk of DVT after laparoscopic surgery is not lower than that of traditional gynecological surgery. [ 4 , 5 ] The most serious complication of DVT is pulmonary embolism, which is closely related to higher mortality and poor prognosis. In addition, the formation of DVT can have irreversible effects on the patient’s limb motor function, thereby reducing their daily activity ability and quality of life.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based model for prediction of deep vein thrombosis after gynecological laparoscopy: A retrospective cohort study

Chen,

Hou,

Wang

2024

Medicine

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Successful monitoring of deep vein thrombosis (DVT) remains a challenging problem after gynecological laparoscopy. Thus, this study aimed to create and validate predictive models for DVT with the help of machine learning (ML) algorithms. A total of 489 patients from the Cancer Biology Research Center, Tongji Hospital were included in the study between January 2017 and February 2023, and 35 clinical indicators from electronic health records (EHRs) were collected within 24h of patient admission. Risk factors were identified using the least absolute shrinkage and selection operator (LASSO) regression. Then, the three commonly used DVT prediction models are random forest model (RFM), generalized linear regression model (GLRM), and artificial neural network model (ANNM). In addition, the predictive performance of various prediction models (i.e. the robustness and accuracy of predictions) is evaluated through the receiver operating characteristic curve (ROC) and decision curve analysis (DCA), respectively. We found postoperative DVT in 41 (8.38%) patients. Based on the ML algorithm, a total of 13 types of clinical data were preliminarily screened as candidate variables for DVT prediction models. Among these, age, body mass index (BMI), operation time, intraoperative pneumoperitoneum pressure (IPP), diabetes, complication and D-Dimer independent risk factors for postoperative DVT and can be used as variables in ML prediction models. The RFM algorithm can achieve the optimal DVT prediction performance, with AUC values of 0.851 (95% CI: 0.793–0.909) and 0.862 (95% CI: 0.804–0.920) in the training and validation sets, respectively. The AUC values of the other two prediction models (ANNM and GLRM) range from 0.697 (95% CI: 0.639–0.755) and 0.813 (95% CI: 0.651–0.767). In summary, we explored the potential risk of DVT after gynecological laparoscopy, which helps clinicians identify high-risk patients before gynecological laparoscopy and make nursing interventions. However, external validation will be needed in the future.

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“…Deep vein thrombosis (DVT) is a common complication that typically occurs within one week after surgery. If venous thrombosis dislodges, it can cause acute pulmonary embolism, which poses a serious threat to the patient’s life ( Gutzeit et al, 2020 ; Hui et al, 2020 ; Kaya et al, 2021 ). Recently, with the advancements in surgical technology and equipment, laparoscopic surgery has gained popularity in gynecology due to its advantages such as lesser physical damage, reduced stress response, lower blood loss, and faster recovery ( Vedantham, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

A nomogram model for predicting lower extremity deep vein thrombosis after gynecologic laparoscopic surgery: a retrospective cohort study

Zhao,

Wang,

et al. 2023

PeerJ

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Objective To investigate the risk factors associated with lower extremity deep vein thrombosis (LEDVT) and to establish a predictive model for patients who undergo gynecologic laparoscopic surgery. Methods A review of clinical data was conducted on patients who underwent gynecologic laparoscopic surgery between November 1, 2020, and January 31, 2022. Patients who developed LEDVT after surgery were included as the observation group, while the control group comprised patients who did not experience complications. Multivariate forward stepwise logistic regression models were used to identify independent risk factors associated with LEDVT. A nomogram model was then developed based on these risk factors. Results A total of 659 patients underwent gynecologic laparoscopic surgery during the study period, and 52 (7.89%) of these patients developed postoperative LEDVT. Multivariate logistic regression analysis showed that older age (adjusted OR, 1.085; 95% CI [1.034–1.138]; P < 0.05), longer operation duration (adjusted OR, 1.014; 95% CI [1.009–1.020]; P < 0.05), shorter activated partial thromboplastin time (APTT) (adjusted OR, 0.749; 95% CI [0.635–0.884]; P < 0.05), higher D-dimer (adjusted OR, 4.929; 95% CI [2.369–10.255]; P < 0.05), higher Human Epididymis Protein 4 (HE4) (adjusted OR, 1.007; 95% CI [1.001–1.012]; P < 0.05), and history of hypertension (adjusted OR, 3.732; 95% CI [1.405–9.915]; P < 0.05) were all independent risk factors for LEDVT in patients who underwent gynecologic laparoscopic surgery. A nomogram model was then created, which had an area under the curve of 0.927 (95% CI [0.893–0.961]; P < 0.05), a sensitivity of 96.1%, and a specificity of 79.5%. Conclusions A nomogram model that incorporates information on age, operation duration, APTT, D-dimer, history of hypertension, and HE4 could effectively predict the risk of LEDVT in patients undergoing gynecologic laparoscopic surgery, potentially helping to prevent the development of this complication.

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Laparoscopic sacrocolpopexy complication: Ilio-femoral deep vein thrombosis

Cited by 4 publications

References 3 publications

Distal Deep Vein Thrombosis in a Patient Cured of Severe COVID-19 Pneumonia at Jimma, Oromia, Ethiopia 2021: A Rare Case Report

Distal Deep Vein Thrombosis in a Patient Cured of Severe COVID-19 Pneumonia at Jimma, Oromia, Ethiopia 2021: A Rare Case Report

Machine learning-based model for prediction of deep vein thrombosis after gynecological laparoscopy: A retrospective cohort study

A nomogram model for predicting lower extremity deep vein thrombosis after gynecologic laparoscopic surgery: a retrospective cohort study

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