Skeletal Muscle Attenuation (Sarcopenia) Predicts Reduced Overall Survival in Patients with Advanced Epithelial Ovarian Cancer Undergoing Primary Debulking Surgery.

BACKGROUND: Sarcopenia was reported as a prognostic factor in cancer patients. Using computed tomography (CT), we analyzed the impact of sarcopenia on overall survival (OS) in patients with advanced epithelial ovarian cancer (EOC) after primary debulking surgery (PDS). METHODS: Preoperative CT scans of consecutive EOC patients (n = 323) were retrospectively assessed for skeletal muscle index (SMI) and muscle attenuation (MA; Hounsfield units [HU]). The optimal cut-off point for MA (32 HU) was calculated using the Martingale residuals method, and previously reported cut-offs for SMI were used. Logistic regression was used to determine univariate and multivariate factors associated with OS. RESULTS: Sarcopenia defined as SMI < 38.5, < 39, and 41 cm2/m2 was detected in 29.4, 33.7, and 47.1% of patients, respectively; however, none of these SMI cut-off levels were associated with OS. MA < 32 HU was present in 21.1% (68/323) of the total cohort. Significant differences between patients with MA < 32 and ≥ 32 HU were detected for median age (67 vs. 57 years), Eastern Cooperative Oncology Group (ECOG) > 0 (13.2 vs. 3.1%), comorbidity (age-adjusted Charlson Comorbidity Index [ACCI] ≥ 4; 36.8 vs. 13.3%), median body mass index (BMI; 27 vs. 24 kg/m2), International Federation of Gynecology and Obstetrics (FIGO) stage, histology (high-grade serous 95.6 vs. 84.7%), and complete resection (38.2 vs. 68.2%). MA < 32 HU remained a significant prognostic factor for OS in multivariate Cox regression analysis (hazard ratio 1.79, p = 0.003). Median OS in patients with MA < 32 HU versus MA ≥ 32 HU was 28 versus 56 months (p < 0.001). Furthermore, MA < 32 HU was significantly associated with OS in the prognostically poor population of patients with residual tumor (p = 0.015). CONCLUSIONS: Low MA was significantly associated with poor survival, especially in patients with residual tumor after PDS. MA assessment could be used for risk stratification after PDS.

Prognostic Value of the Age-Adjusted Charlson Comorbidity Index (ACCI) on Short- and Long-Term Outcome in Patients with Advanced Primary Epithelial Ovarian Cancer.

BACKGROUND: We evaluated the prognostic impact of the age-adjusted Charlson Comorbidity Index (ACCI) on both postoperative morbidity and overall survival (OS) in patients with advanced epithelial ovarian cancer (EOC) treated at a tertiary gynecologic cancer center. PATIENTS AND METHODS: Exploratory analysis of our prospectively documented tumor registry was performed. Data of all consecutive patients with stage IIIB-IV ovarian cancer who underwent primary cytoreductive surgery (PDS) from January 2000 to June 2016 were analyzed. Patients were divided into three groups, based on their ACCI: low (0-1), intermediate (2-3), and high (≥4), and postoperative surgical complications were graded according to the Clavien-Dindo classification (CDC). The Fisher's exact test, log-rank test, and Cox regression models were used to investigate the predictive value of the ACCI on postoperative complications and OS. RESULTS: Overall, 793 consecutive patients were identified; 328 (41.4%) patients were categorized as low ACCI, 342 (43.1%) as intermediate ACCI, and 123 (15.5%) as high ACCI. A high ACCI was significantly associated with severe postoperative complications (CDC 3-5; odds ratio 3.27, 95% confidence interval 1.97-5.43, p < 0.001). Median OS for patients with a low, intermediate, or high ACCI was 50, 40, and 23 months, respectively (p < 0.001), and the ACCI remained a significant prognostic factor for OS in multivariate analysis (p = 0.001). The same impact was observed in a sensitivity analysis including only those patients with complete tumor resection. CONCLUSION: The ACCI is associated with perioperative morbidity in patients undergoing PDS for EOC, and also has a prognostic impact on OS. The potential role of the ACCI as a selection criteria for different therapy strategies is currently under investigation in the ongoing, prospective, multicenter AGO-OVAR 19 trial.

[Anaesthesia for urological surgery - Anaesthesia for robotic assisted prostatectomies]. / Anästhesie in der Urologie - Anästhesie bei roboterassistierter Prostatektomie.

Because of excellent results, high patient satisfaction, and extraordinary surgical conditions robotic assisted prostatectomies have found a wide spread acceptance. Trendelenburg positioning, CO2-Insufflation, and installation of the robot system cause moderate hemodynamic and respiratory changes. Respiration can be compromised by significantly reduced pulmonary compliance during surgery and a marked CO2 load. Therefore, arterial blood gas controls during surgery can be recommended. Over hours edema of head and neck including the upper airways and an increase of the intraocular pressure can develop. There are no restrictions in the choice of the anesthetics. Careful positioning of the patient and critical intravenous fluid management are important determinants of a successful anesthetic management.

Simulated life-threatening emergency during robot-assisted surgery.

BACKGROUND: With the increasing use of robot-assisted techniques for urologic and gynecologic surgery in patients with severe comorbidities, the risk of a critical incidence during surgery increases. Due to limited access to the patient the start of effective measures to treat a life-threatening emergency could be delayed. Therefore, we tested the management of an acute emergency in an operating room setting with a full-size simulator in six complete teams. METHODS: A full-size simulator (ISTAN, Meti, CA), modified to hold five trocars, was placed in a regular operating room and connected to a robotic system. Six teams (each with three nurses, one anesthesiologist, two urologists or gynecologists) were introduced to the scenario. Subsequently, myocardial fibrillation occurred. Time to first chest compression, removal of the robot, first defibrillation, and stabilization of circulation were obtained. After 7 weeks the simulation was repeated. RESULTS: The time to the start of chest compressions, removal of the robotic system, and first defibrillation were significantly improved at the second simulation. Time for restoration of stable circulation was improved from 417 ± 125 seconds to 224 ± 37 seconds (P=0.0054). Unexpected delays occurred during the first simulation because trocars had been removed from the patient but not from the robot, thus preventing the robot to be moved. CONCLUSION: Following proper training, resuscitation can be started within seconds. A repetition of the simulation significantly improved time for all steps of resuscitation. An emergency simulation of a multidisciplinary team in a real operating room setting can be strongly recommended.