Efficacy of a robotic stapler on symptomatic anastomotic leakage in robotic low anterior resection for rectal cancer

Chen, Kai; Shiomi, Akio; Kagawa, Hiroyasu; Hino, Hitoshi; Manabe, Shoichi; Yamaoka, Yusuke; Kato, Shunichiro; Hanaoka, Marie; Saito, Kenkichi; Maeda, Chikara; Kojima, Tadahiro; Shioi, Ikuma; Nanishi, Kenji; Tanaka, Yusuke; Kasai, Shunsuke

doi:10.1007/s00595-021-02313-6

Cited by 5 publications

(5 citation statements)

References 24 publications

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“…The risk factors of AL in this study were male sex, obesity, low tumor location, large tumor diameter, advanced tumor, preoperative hypoproteinemia, neoadjuvant chemoradiotherapy, smoking, diabetes, poor nutritional status, and poor blood perfusion in the anastomotic area ( 6 , 8 , 9 ). Due to the difficulty in controlling risk factors such as age, sex, tumor location, comorbidities, tumor stage and nutritional status, surgeons have to focus on anastomotic techniques, anastomotic tension, and anastomotic blood perfusion ( 27 ).…”

Section: Discussionmentioning

confidence: 73%

“…Risk factors for AL include male sex, obesity, low tumor location, large tumor diameter, advanced tumor stage, preoperative hypoproteinemia, neoadjuvant chemoradiotherapy, smoking, diabetes, poor nutritional status, and poor blood perfusion in the anastomotic area. Of these factors, anastomotic blood perfusion influences AL the most ( 6 , 8 , 9 ); therefore, the detection of ischemic anastomotic tissue is key in preventing AL during surgery. The conventional method for evaluating anastomotic perfusion is to observe color change and active bleeding of the resection margin of the intestine and the pulsation of mesenteric vessels; however, the accuracy of conventional evaluation strategies are low ( 7 ), and may be due to insufficient observation time.…”

Section: Introductionmentioning

confidence: 99%

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Novel surgical procedure for preventing anastomotic leakage following colorectal cancer surgery: A propensity score matching study

Tang

Zhang

et al. 2022

Front. Oncol.

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Hypoperfusion is the main cause of anastomotic leakage (AL) following colorectal surgery. The conventional method for evaluating anastomotic perfusion is to observe color change and active bleeding of the resection margin of the intestine and the pulsation of mesenteric vessels. However, the accuracy of this method is low, which may be due to insufficient observation time. A novel surgical procedure that separates the mesentery in advance at the intended transection site can delay the observation of anastomotic perfusion, and can potentially detect more anastomotic sites with insufficient vascular supply and reduce the rate of AL. This study aimed to investigate the effects of a novel surgical procedure on AL following sigmoid colon and rectal cancer surgeries. A total of 343 patients who underwent rectal and sigmoid colon cancer surgeries were included in the study. From August 2021 to June 2022, patients with sigmoid colon or rectal cancer underwent a new surgical procedure of pre-division of the mesentery (PDM) at the intended transection site (PDM group). Patients with colorectal cancer who underwent conventional surgical procedures from August 2018 to July 2021 were categorized as the non-PDM group. Symptomatic AL (SAL) within 30 days and other outcomes were retrospectively analyzed using propensity score matching and compared between the two groups. The incidences of SAL were 1.3% and 11.3% in the PDM and non-PDM groups, respectively. PDM significantly reduced the SAL rate in sigmoid colon and rectal cancer surgeries (P = 0.009). The incidence of total postoperative complications (P < 0.05) was significantly lower in the PDM group than that in the non-PDM group. There were no significant differences between the two groups for operative time (P = 0.662), intraoperative blood loss (P = 0.651), intraoperative blood transfusion (P = 0.316), and intensive care rate (P = 1). The length of postoperative hospital stay (P = 0.010) and first exhaust (P = 0.001) and defecation time (P < 0.05) were shorter in the PDM group than in the non-PDM group. PDM can effectively prevent AL, and this procedure can be safely performed in sigmoid colon and rectal cancer surgeries.

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Section: Discussionmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Novel surgical procedure for preventing anastomotic leakage following colorectal cancer surgery: A propensity score matching study

Tang

Zhang

et al. 2022

Front. Oncol.

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“…In recent years, the number of robotic surgeries has increased; therefore, the importance of studies focusing on robotic surgery has also increased. It has been reported that the novel technology of robotic surgery, such as a robotic stapler, contributes to the reduction of AL [8]. However, to our knowledge, there are no reports comparing the surgical outcomes between PCS and MCS in Ro-LAR alone for rectal cancer.…”

Section: Discussionmentioning

confidence: 98%

“…All robotic surgeries in this study were performed using the da Vinci Xi Ⓡ (Intuitive Surgical, Sunnyvale, CA, U.S.), and all operations were performed by five surgeons with adequate experience in ro-botic surgery. Chen et al [8] reported that robotic staplers reduce AL; therefore, only cases in which robotic staplers (SureForm stapler Ⓡ or EndoWrist stapler Ⓡ ) were used were analyzed in this study. An ECHELON CIRCULAR Ⓡ Powered Stapler (Ethicon, Bridgewater, NJ, U.S.) (147 patients) was used as the PCS, and an ECHELON CIRCULAR Ⓡ Stapler (Ethicon) (111 patients) or EEA Circular Stapler (Medtronic, Minneapolis, MN, U.S.) (13 patients) was used as the MCS.…”

Section: Patientsmentioning

confidence: 99%

Use of a Powered Circular Stapler Can Prevent Anastomotic Air Leakage in Robotic Low Anterior Resection for Rectal Cancer

Nanishi

Hino

Shiomi

et al. 2023

J Anus Rectum Colon

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Objectives: Preventing anastomotic complications during rectal cancer surgery is important. Compared with a manual circular stapler, a powered circular stapler is expected to reduce undesirable tension during anastomosis. However, whether a powered circular stapler can reduce anastomotic complications during robotic low anterior resection (Ro-LAR) remains unclear. We aimed to investigate whether the use of a powered circular stapler contributes to safe anastomosis in Ro-LAR. Methods: A total of 271 patients who underwent Ro-LAR for rectal cancer between April 2019 and April 2022 were included. Depending on the type of device employed, patients were divided into a powered circular stapler group (PCSG) and a manual circular stapler group (MCSG). Clinicopathological features and surgical outcomes were compared between the two groups. Results: There were no differences in clinicopathological characteristics and surgical outcomes, except for anastomotic outcomes, between the two groups. Patients with positive air leak tests were significantly more in the MCSG ( p =0.026; PCSG, 1.5%; MCSG, 8.0%). Frequencies of anastomotic leakage ( p =0.486; PCSG, 6.1%; MCSG, 8.9%) and anastomotic bleeding ( p =1.000; PCSG, 0.7%; MCSG, 0.8%) were similar between the two groups. Multivariate analysis showed that the use of a powered circular stapler significantly increased the negative leak tests ( p =0.020, odds ratio 6.74, 95% confidence interval 1.35-33.56). Conclusions: Use of a powered circular stapler in Ro-LAR for rectal cancer was significantly associated with a negative air leak test, suggesting that it contributes to stable and safe anastomosis.

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“…Machine learning models are flexible enough to handle nonlinear and complex data structures and can also effectively deal with the challenges of high-dimensional data and missing values. They improve the accuracy of prediction and classification by training the models on large amounts of data and continuously optimizing their performance [28][29][30][31][32]. Another significant advantage of machine learning is its ability to recognize and exploit.…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of a clinical prediction model for deep vein thrombosis in patients with digestive system tumors based on a machine learning

Zhang

2024

Am J Cancer Res

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This study developed a deep vein thrombosis (DVT) risk prediction model based on multiple machine learning methods for patients with digestive system tumors undergoing surgical treatment. Data of 1048 patients with digestive system tumors admitted to Shanxi Provincial People's Hospital (College of Shanxi Medical University) from January 2020 to January 2023 were retrospectively analyzed, and 845 cases were screened according to the inclusion and exclusion criteria. The patients were divided into a training group (586 patients), and a validation group (259 patients), then feature selection was performed using six models, including Lasso regression, XGBoost, Random Forest, Decision Tree, Support Vector Machine, and Logistics. Predictive models were subsequently constructed from column-line plots, and the predictive validity of the models was assessed using receiver operating characteristic curves, precision-recall curves, and decision-curve analysis. In the model comparison, the XGBoost model showed the largest area under the curve (AUC) on the validation set (P < 0.05), demonstrating excellent predictive performance and generalization ability. We selected the common characteristic factors in the six models to further develop the column line plots to assess the DVT risk. The model performed well in clinical validation and effectively differentiated high-risk and low-risk patients. The differences in BMI, procedure time, and D-dimer were statistically significant between patients in the thrombus group and those in the non-thrombus group (P < 0.05). However, the AUC of the Xgboost model was found to be greater than that of the column chart model by the Delong test (P < 0.05). BMI, procedure time, and D-dimer are critical predictors of DVT risk in patients with digestive system tumors. Our model is an adequate assessment tool for DVT risk, which can help improve the prevention and treatment of DVT.

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Efficacy of a robotic stapler on symptomatic anastomotic leakage in robotic low anterior resection for rectal cancer

Cited by 5 publications

References 24 publications

Novel surgical procedure for preventing anastomotic leakage following colorectal cancer surgery: A propensity score matching study

Novel surgical procedure for preventing anastomotic leakage following colorectal cancer surgery: A propensity score matching study

Use of a Powered Circular Stapler Can Prevent Anastomotic Air Leakage in Robotic Low Anterior Resection for Rectal Cancer

Construction and validation of a clinical prediction model for deep vein thrombosis in patients with digestive system tumors based on a machine learning

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