Perioperative and mid-term outcomes of robotic-assisted versus video-assisted minimally invasive esophagectomy for esophageal cancer: a retrospective propensity-matched analysis of 842 patients.

Aim: Comparing the safety, effectiveness, and mid-term survival rates of robot-assisted minimally invasive esophagectomy (RAMIE) and video-assisted minimally invasive esophagectomy (VAMIE). Methods: A total of 842 patients undergoing minimally invasive esophagectomy were analyzed, including 694 patients in VAMIE group and 148 in RAMIE group. PSM analysis was applied to generate matched pairs for further comparison. Operative outcomes, postoperative complications and Mid-term outcomes were compared between all patients in matched groups. Results: After 1:4 PSM, 148 patients in the RAMIE and 592 patients in the VAMIE. Compared to VAMIE, RAMIE exhibited earlier removal of chest and neck drainage tubes, shorter postoperative hospital stays, and a higher number of lymph node dissections. However, the surgical duration of RAMIE was longer than that of VAMIE. Postoperative complications were no statistically significant between the RAMIE and VAMIE groups. There was no statistically significant difference in the 3-year OS and DFS between the two groups. Conclusion: Compared to VAMIE, RAMIE emerges as a viable and safe surgical approach and suggests RAMIE as a potential alternative to minimally invasive esophagectomy.

Identification of a novel prognostic cuproptosis-associated LncRNA signature for predicting prognosis and immunotherapy response in patients with esophageal cancer.

Nowadays, effective prognostic models for esophageal cancer (ESCA) are still lacking. Long noncoding RNAs (lncRNAs) are commonly utilized as indicators for diagnosing cancer and forecasting patient outcomes. Cuproptosis is regulated by multiple genes and is crucial to the progression of ESCA. However, it is not yet clear what role the cuproptosis-associated lncRNAs (CuALs) play in ESCA. To tackle this problem, a prognostic signature incorporating three CuALs was created. This signature was constructed by the use of the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Subsequently, the signature effectively stratified ESCA samples into a high-risk group and a low-risk group. Those in the low-risk group demonstrated extended overall survival (OS), as well as increased infiltration of T cells, macrophages, and NK cells, suggesting a potentially enhanced response to immunotherapy. The ROC curve analysis demonstrated that this prognostic signature outperformed conventional clinical factors in predicting patient prognosis (AUC = 0.708). K-M survival analysis and correlation analysis identified UGDH-AS1 (a CuAL) as a protective factor positively associated with patient prognosis. The results of RT-qPCR and wound healing assays indicated that UGDH-AS1 is overexpressed in ESCA and could inhibit cancer cell migration. In general, the prognostic signature of CuALs demonstrated a robust capability in forecasting the immune environment and patient prognosis, highlighting its potential as a tool for enhancing personalized treatment strategies in ESCA.

Comprehensively evaluate the short outcome of small bowel obstruction: A novel medical-economic score system.

BACKGROUND: Small bowel obstruction (SBO) still imposes a substantial burden on the health care system. Traditional evaluation systems for SBO outcomes only focus on a single element. The comprehensive evaluation of outcomes for patients with SBO remains poorly studied. Early intensive clinical care would effectively improve the short-term outcomes for SBO, however, the full spectrum of the potential risk status regarding the high complication-cost burden is undetermined. AIM: We aim to construct a novel system for the evaluation of SBO outcomes and the identification of potential risk status. METHODS: Patients who were diagnosed with SBO were enrolled and stratified into the simple SBO (SiBO) group and the strangulated SBO (StBO) group. A principal component (PC) analysis was applied for data simplification and the extraction of patient characteristics, followed by separation of the high PC score group and the low PC score group. We identified independent risk status on admission via a binary logistic regression and then constructed predictive models for worsened management outcomes. Receiver operating characteristic curves were drawn, and the areas under the curve (AUCs) were calculated to assess the effectiveness of the predictive models. RESULTS: Of the 281 patients, 45 patients (16.0%) were found to have StBO, whereas 236 patients (84.0%) had SiBO. Regarding standardized length of stay (LOS), total hospital cost and the presence of severe adverse events (SAEs), a novel principal component was extracted (PC score = 0.429 × LOS + 0.444 × total hospital cost + 0.291 × SAE). In the multivariate analysis, risk statuses related to poor results for SiBO patients, including a low lymphocyte to monocyte ratio (OR = 0.656), radiological features of a lack of small bowel feces signs (OR = 0.316) and mural thickening (OR = 1.338), were identified as risk factors. For the StBO group, higher BUN levels (OR = 1.478) and lower lymphocytes levels (OR = 0.071) were observed. The AUCs of the predictive models for poor outcomes were 0.715 (95%CI: 0.635-0.795) and 0.874 (95%CI: 0.762-0.986) for SiBO and StBO stratification, respectively. CONCLUSION: The novel PC indicator provided a comprehensive scoring system for evaluating SBO outcomes on the foundation of complication-cost burden. According to the relative risk factors, early tailored intervention would improve the short-term outcomes.

Prediction and management of strangulated bowel obstruction: a multi-dimensional model analysis.

BACKGROUND: Distinguishing strangulated bowel obstruction (StBO) from simple bowel obstruction (SiBO) still poses a challenge for emergency surgeons. We aimed to construct a predictive model that could distinctly discriminate StBO from SiBO based on the degree of bowel ischemia. METHODS: The patients diagnosed with intestinal obstruction were enrolled and divided into SiBO group and StBO group. Binary logistic regression was applied to identify independent risk factors, and then predictive models based on radiological and multi-dimensional models were constructed. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were calculated to assess the accuracy of the predicted models. Via stratification analysis, we validated the multi-dimensional model in the prediction of transmural necrosis both in the training set and validation set. RESULTS: Of the 281 patients with SBO, 45 (16.0%) were found to have StBO, while 236(84.0%) with SiBO. The AUC of the radiological model was 0.706 (95%CI, 0.617-0.795). In the multivariate analysis, seven risk factors including pain duration ≤ 3 days (OR = 3.775), rebound tenderness (OR = 5.201), low-to-absent bowel sounds (OR = 5.006), low levels of potassium (OR = 3.696) and sodium (OR = 3.753), high levels of BUN (OR = 4.349), high radiological score (OR = 11.264) were identified. The AUC of the multi-dimensional model was 0.857(95%CI, 0.793-0.920). In the stratification analysis, the proportion of patients with transmural necrosis was significantly greater in the high-risk group (24%) than in the medium-risk group (3%). No transmural necrosis was found in the low-risk group. The AUC of the validation set was 0.910 (95%CI, 0.843-0.976). None of patients in the low-risk and medium-risk score group suffered with StBO. However, all patients with bowel ischemia (12%) and necrosis (24%) were resorted into high-risk score group. CONCLUSION: The novel multi-dimensional model offers a useful tool for predicting StBO. Clinical management could be performed according to the multivariate score.