Intraoperative Complications and Perioperative and Surgical Outcomes of Single-Port Robotics-Assisted Sacrocolpopexy.

INTRODUCTION AND HYPOTHESIS: The objective was to assess intraoperative and postoperative complication rates, along with perioperative and surgical outcomes, following single-port robotics-assisted sacrocolpopexy. METHODS: This retrospective case series included 200 patients who underwent single-port robotics-assisted sacrocolpopexy to treat Pelvic Organ Prolapse Quantification (POPQ) stage 2-4 symptomatic prolapse between April 2020 and August 2023 by a single surgeon. Intraoperative and postoperative complications and perioperative outcomes were evaluated for all the patients, whereas surgical outcomes for 74 patients were assessed at 1-year follow-up. Surgical failure was defined as the presence of any of the following: the presence of vaginal bulging symptoms, any prolapse beyond the hymen, or retreatment for prolapse. RESULTS: During the study period, 200 single-port robotics-assisted sacrocolpopexies were performed. The median age and body mass index were 65.0 years and 24.6 kg/m2 respectively. Most patients had POPQ stage 3 or 4 prolapse and underwent concomitant total hysterectomy. The median total operation time was 212.0 min, and none of the patients required conversion to laparoscopy or laparotomy. The intraoperative cystotomy rate was 2.5%, and one patient had a blood transfusion owing to presacral vessel injury. Postoperative complications of mesh exposure and wound hernia were 0.5% and 2.0% respectively. At 1 year postoperatively, the rate of composite surgical failure was 9.5%, with a 5.4% anatomical recurrence rate. None of the patients experienced apical prolapse recurrence, and one received anterior colporrhaphy for anterior compartment prolapse recurrence. CONCLUSIONS: Single-port robotics-assisted sacrocolpopexy is safe and effective, with low complication rates and favorable perioperative and surgical outcomes.

Development and validation of a prediction model for postoperative urinary retention after prolapse surgery: A retrospective cohort study.

BACKGROUND: Postoperative urinary retention (POUR), a common condition after prolapse surgery with potential serious sequelae if left untreated, lacks a clearly established optimal timing for catheter removal. This study aimed to develop and validate a predictive model for postoperative urinary retention lasting > 2 and > 4 days after prolapse surgery. METHODS: We conducted a retrospective review of 1,122 patients undergoing prolapse surgery. The dataset was divided into training and testing cohorts. POUR was defined as the need for continuous intermittent catheterization resulting from a failed spontaneous voiding trial, with passing defined as two consecutive voids ≥ 150 mL and a postvoid residual urine volume ≤ 150 mL. We performed logistic regression and the predicted model was validated using both training and testing cohorts. RESULTS: Among patients, 31% and 12% experienced POUR lasting > 2 and > 4 days, respectively. Multivariable logistic model identified 6 predictors. For predicting POUR, internal validation using cross-validation approach showed good performance, with accuracy lasting > 2 (area under the curve [AUC] 0.73) and > 4 days (AUC 0.75). Split validation using pre-separated dataset also showed good performance, with accuracy lasting > 2 (AUC 0.73) and > 4 days (AUC 0.74). Calibration curves demonstrated that the model accurately predicted POUR lasting > 2 and > 4 days (from 0 to 80%). CONCLUSIONS: The proposed prediction model can assist clinicians in personalizing postoperative bladder care for patients undergoing prolapse surgery by providing accurate individual risk estimates.

Changes in anti-Müllerian hormone values for ovarian reserve after minimally invasive benign ovarian cystectomy: comparison of the Da Vinci robotic systems (Xi and SP) and the laparoscopic system.

To investigate the impact on the ovarian reserve after minimally invasive ovarian cystectomy using two platforms, the Da Vinci robotic system (Xi and SP) and the laparoscopic system. Patients underwent laparoscopic or Da Vinci robotic (Xi or SP) ovarian cystectomy for benign ovarian cysts between January 1, 2018, and December 31, 2022 at Guro Hospital, Korea University Medical center. We measured the change of AMH values (%) = [(postAMH - preAMH)] × 100/preAMH. No significant differences in preoperative age, cyst size, estimated blood loss during surgery, hemoglobin drop, length of hospital stay, adhesion detachment rate and cyst rupture rate were observed. However, the operative time was significantly shorter in the laparoscopic group than that in the robotic group (67.78 ± 30.58 min vs. 105.17 ± 38.87 min, p < 0.001) The mean preAMH and postAMH were significantly higher with the Da Vinci robotic group than with the laparoscopic group (preAMH: 5.89 ± 4.81 ng/mL vs. 4.01 ± 3.59 ng/mL, p = 0.02, postAMH: 4.36 ± 3.31 ng/mL vs. 3.08 ± 2.60 ng/mL, p = 0.02). However, the mean ΔAMH was not significantly different between two groups. ΔAMH also did not demonstrate significant differences among the three groups; laparoscopic, Xi and SP robotic. Even in the patient groups with preAMH < 2 and diagnosed with endometriosis, the ΔAMH did not show significant differences between the laparoscopic and robotic groups. The Da Vinci robotic system is no inferior to conventional laparoscopic systems in preserving ovarian function.

Hypomethylation of ATP1A1 Is Associated with Poor Prognosis and Cancer Progression in Triple-Negative Breast Cancer.

Dysregulated DNA methylation in cancer is critical in the transcription machinery associated with cancer progression. Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, but no treatment targeting TNBC biomarkers has yet been developed. To identify specific DNA methylation patterns in TNBC, methyl-binding domain protein 2 (MBD) sequencing data were compared in TNBC and the three other major breast cancer subtypes. Integrated analysis of DNA methylation and gene expression identified a gene set showing a correlation between DNA methylation and gene expression. ATPase Na+/K+-transporting subunit alpha 1 (ATP1A1) was found to be specifically hypomethylated in the coding sequence (CDS) region and to show increased expression in TNBC. The Cancer Genome Atlas (TCGA) database also showed that hypomethylation and high expression of ATP1A1 were strongly associated with poor survival in patients with TNBC. Furthermore, ATP1A1 knockdown significantly reduced the viability and tumor-sphere formation of TNBC cells. These results suggest that the hypomethylation and overexpression of ATP1A1 could be a prognostic marker in TNBC and that the manipulation of ATP1A1 expression could be a therapeutic target in this disease.

Identification of signature gene set as highly accurate determination of metabolic dysfunction-associated steatotic liver disease progression.

BACKGROUND/AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. METHODS: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. RESULTS: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. CONCLUSION: We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.