Beyond Total Mesorectal Excision: Compartment-based Anatomy of the Pelvis Revisited for Exenterative Pelvic Surgery.

OBJECTIVE: Magnetic resonance imaging-based subdivision of the pelvis into 7 compartments has been proposed for pelvic exenteration. The aim of the present anatomical study was to describe the topographic anatomy of these compartments and define relevant landmarks and surgical dissection planes. BACKGROUND: Pelvic anatomy as it relates to exenterative surgery is complex. Demonstration of the topographic peculiarities of the pelvis based on the operative situs is hindered by the inaccessibility of the small pelvis and the tumor bulk itself. MATERIALS AND METHODS: Thirteen formalin-fixed pelvic specimens were meticulously dissected according to predefined pelvic compartments. Pelvic exenteration was simulated and illustrated in a stepwise manner. Different access routes were used for optimal demonstration of the regions of interest. RESULTS: All the 7 compartments (peritoneal reflection, anterior above peritoneal reflection, anterior below peritoneal reflection, central, posterior, lateral, inferior) were investigated systematically. The topography of the pelvic fasciae and ligaments; vessels and nerves of the bladder, prostate, uterus, and vagina; the internal iliac artery and vein; the course of the ureter, somatic (obturator nerve, sacral plexus), and autonomic pelvic nerves (inferior hypogastric plexus); pelvic sidewall and floor, ischioanal fossa; and relevant structures for sacrectomy were demonstrated. CONCLUSIONS: A systematic approach to pelvic anatomy according to the 7 magnetic resonance imaging-defined compartments clearly revealed crucial anatomical landmarks and key structures facilitating pelvic exenterative surgery. Compartment-based pelvic anatomy proved to be a sound concept for beyond TME surgery and provides a basis for tailored resection procedures.

Detection of Deteriorating Patients on Surgical Wards Outside the ICU by an Automated MEWS-Based Early Warning System With Paging Functionality.

BACKGROUND: The establishment of early warning systems in hospitals was strongly recommended in recent guidelines to detect deteriorating patients early and direct them to adequate care. Upon reaching predefined trigger criteria, Medical Emergency Teams (MET) should be notified and directed to these patients. The present study analyses the effect of introducing an automated multiparameter early warning score (MEWS)-based early warning system with paging functionality on 2 wards hosting patients recovering from highly complex surgical interventions. METHODS: The deployment of the system was accompanied by retrospective data acquisition during 12 months (intervention) using 4 routine databases: Hospital patient data management, anesthesia database, local data of the German Resuscitation Registry, and measurement logs of the deployed system (intervention period only). A retrospective 12-month data review using the same aforementioned databases before the deployment of the system served as control. Control and intervention phases were separated by a 6-month washout period for the installation of the system and for training. RESULTS: Data from 3827 patients could be acquired from 2 surgical wards during the two 12-month periods, 1896 patients in the control and 1931 in the intervention cohorts. Patient characteristics differed between the 2 observation phases. American Society of Anesthesiologists risk classification and duration of surgery as well as German DRG case-weight were significantly higher in the intervention period. However, the rate of cardiac arrests significantly dropped from 5.3 to 2.1 per 1000 admissions in the intervention period (P < 0.001). This observation was paralleled by a reduction of unplanned ICU admissions from 3.6% to 3.0% (P < 0.001), and an increase of notifications of critical conditions to the ward surgeon. The primary triggers for MET activation were abnormal ECG alerts, specifically asystole (n = 5), and pulseless electric activity (n = 8). CONCLUSION: In concert with a well-trained and organized MET, the early deterioration detection of patients on surgical wards outside the ICU may be improved by introducing an automated MEWS-based early warning system with paging functionality.