Effect of RARC-ERAS nursing program on clinical outcomes in patients undergoing RARC surgery: a retrospective, propensity matching study

After obtaining approval from the Ethics Committee of Zhejiang Provincial People's Hospital (Approval NO: 2023-217), 216 consecutive adult patients who underwent RARC were retrospectively collected from January 1, 2022 to December 30, 2023 in the hospital. We established based on the ERAS concept nursing measures since January 1, 2023. Therefore, a traditional group without the ERAS concept was identified as the control group from January 1, 2022 to December 31, 2022 and the ERAS group was identified as the observation group From January 1, 2023 to December 31, 2023.

All the patients conformed to the following conditions: 1) Patients diagnosed with invasive bladder urothelial carcinoma based on preoperative imaging, cystoscopy biopsy, or diagnostic bladder electroresection, with no evidence of systemic organ metastasis; 2) undergoing complete robot-assisted STAPLER method radical cystectomy, standard pelvic lymph node dissection, and in situ ileal U-shaped neobladder construction and all surgical procedures performed using the robot-assisted surgical system; 3) Absence of a history of external radiation therapy or intravenous chemotherapy before surgery, and no history of traditional open abdominal surgery; 4) Normal body temperature within the last 3 days and upon admission; 5) and color doppler ultrasound confirming unobstructed venous blood flow in the lower extremities before anesthesia.

Exclusion criteria comprised: 1) Intraoperative change of surgical approach to laparoscopy or open surgery; 2) History of VTE and prior anticoagulant or thrombolytic therapy before surgery; 3) Cardiovascular conditions prone to thrombosis, such as atrial fibrillation, congestive heart failure, pulmonary edema, etc.; 4) Disorders related to temperature regulation and metabolism; 5) Abnormalities in the local condition of the lower limbs, including swelling, gangrene, dermatitis, prior skin graft surgery, severe lower limb deformities, and ischemic vascular diseases like arterial sclerosis; 6) Transfusion of blood products during surgery; 7) Incomplete surgical data.

(1) Firstly, one day before surgery, the circulating nurse adhered to the preoperative visit protocol of the department in line with the surgical notice. (2) On the day of surgery, the circulating nurse played a crucial role in escorting the patient to the operating room. They confirmed the anesthesia method and coordinated with the surgeon to set up the operating room layout, following procedures analogous to conventional surgeries of the same type. (3) Once successful anesthesia was achieved, the patient was positioned according to the principles of the surgical position. (4) During the surgery, the circulating nurse took measures to enhance patient care. (5) At the conclusion of surgery, besides following routine procedures for surgeries of the same type, the number of uses of robotic instruments was documented using a marking pen. Detail of the traditional nursing model was listed in S1 Supplemental Appendix 1.

Establishment of a Robot-Assisted Surgical Nursing Team Based on the ERAS Concept and detail was listed in S1 Supplemental Appendix 1.

On the basis of the traditional nursing model, we established a robot-assisted surgical nursing team aligned with the principles of ERAS. The team comprises a nurse manager responsible for overseeing robot-assisted surgeries and five nurses specialized in robot-assisted surgery. One nurse serves as the coordinator of RARC-ERAS nursing program.

Responsibilities of nursing coordinator: (1) Surgical Progress Management: Coordinate pickup and transfer times for each surgical patient based on the pre-arranged surgical plan for the day before and the current day's progress. Minimize patient waiting times in the operating room to avoid prolonged waits and potentially extended anesthesia periods. (2) Robot-Assisted Surgical System Maintenance and Management: Ensure the accuracy of robot-assisted surgical system operation. Manage inventory of supplies and consumables. (3) Clinical Support: Assist in patient surgical preparation processes. Supervise nurses' technical skills during surgery. Provide help and advice for any issues that arise during surgical collaboration. (4) Education and Training: Conduct continuous training for the robot-assisted surgical nursing team in ERAS principles and specialized skills. Include training on preoperative visit content, processes, communication techniques, guidance for completing survey questionnaires, and methods for collecting evaluation data. Ensure the team's core competencies and job capabilities align with the evolving development of robot-assisted surgical techniques. (5) Quality Control: Communicate with the head of the robot-assisted surgery department, anesthesiology department, disinfection supply center, and engineers every 4 weeks to provide updates on the latest developments in robot-assisted surgery. Hold a quality control meeting after every 10 completed surgeries to discuss issues encountered during surgical collaboration, including any technical malfunctions during surgery. Conduct root cause analysis and sharing of corrective measures. Robot nurses should promptly report any issues discovered during their clinical practice to the coordinator while carrying out their routine surgical nursing duties.

Perioperative variables including demographic characteristic, individual history, preexisting risk factors, preoperative medications, co-morbidities, intraoperative data and other postoperative complications were retrieved from the hospital medical records, which occurred during the hospitalization, including the entire postoperative period up to discharge even if > 30 days. Laboratory test and part of preoperative characteristics were automated deriving from a computer database. Researchers were trained before data collection and an independent investigator reviewed all data. The researchers collecting postoperative endpoints were blinded to preoperative and intraoperative characteristics.

The primary outcome was the rate of unobstructed venous blood flow in the lower extremities by color doppler ultrasound during the postoperative period. Vascular conditions by color doppler ultrasound were assessed and reported as patency (unobstructed venous blood flow), stasis, and deep vein thrombosis (DVT) by an independent sonographer [6].

Other end points included in-hospital mortality and morbidities, duration of intensive care unit (ICU) stay, length of hospital stay (LOS) and duration of mechanical ventilation. Hospital morbidities included the following parts: (1) degree of preoperative anxiety score and surgical information demand score, were calculated according to the Amsterdam Preoperative Anxiety and Information Scale (APAIS) [7] at the first visit and before anesthesia induction. (2) perioperative hypothermia, defined as a core temperature dropping below 36 °C at any point from the beginning of the operation to leaving the Post-Anesthesia Care Unit (PACU) [8]. (3) the first time of getting out of bed, the first time of anal discharge, the first time of defecation after returning to the ward. (4) Postoperative pain using the numerical rating scale (NRS) [9].

Descriptive analyses of variables were used to summarize data. The normal distributed variables were expressed as mean ± standard deviation (SD) and compared with student’s t-test. Abnormal continuous variables were expressed as median (interquartile range (IQR)) and evaluated with Mann–Whitney U-test. respectively. Chi-square or Fisher's exact test was used to compare proportions between the two groups. Missing continuous variables of baseline parameters were less than 10% and were replaced by the median in Table 1. All reported p values were two sided, and values of p < 0.05 were considered to be statistically significant. Statistical analysis was performed with SPSS version 25.

To minimize the effect of selection bias on outcomes, we used propensity score matching for clinical characteristics to reduce distortion by confounding factors. Using propensity score analysis by the method of nearest-neighbor matching, we generated a set of matched cases (ERAS) and controls (non-ERAS). A propensity score was generated for each patient from a multivariable logistic regression model on the basis of the covariates using clinical characteristics data (Table 1) from the institutional registry as independent variables, with treatment type (ERAS vs. non-ERAS) as a binary dependent variable. We matched patients using a greedy-matching algorithm with a caliper width of 0.1 of the estimated propensity score. A matching ratio of 1:1 was used. The inclusion matching indicators between the two groups included: gender, age, insulin dosage, BMI, ASA, Diabetes, and HCT value. We evaluated post-match covariate balance by comparing the balance of baseline covariates between patients with ERAS and non-ERAS before and after matching using absolute standardized differences [10].

A total of 216 patients were identified and divided into two groups: patients who received RARC-ERAS nursing program (ERAS group, n = 59, 42.8%) and those who did not receive RARC-ERAS nursing program (non-ERAS group, n = 79, 57.2%) during the study period (Fig. 1). Compared with those in the control group, the BMI were lower and the propensity score was higher before matching in the ERAS group than that in the control group (p < 0.05). After matching, there were no significant differences in the general data between the two groups (p > 0.05, Table 1). According to the standardized difference, the covariate balance between the matched pairs was confirmed (Fig. 2).

No case of deep vein thrombosis (DVT) was observed under color Doppler ultrasound examination during the postoperative period. The ERAS group exhibited a significantly higher rate of unobstructed venous blood flow in the lower extremities by color doppler ultrasound during the postoperative period as compared to the control group (94.6% VS 80.4%, p = 0.042, Table 2).

Before anesthesia induction, lower preoperative anxiety and surgical information needs scores were observed in the ERAS group than in the control group (p < 0.05, Table 1). Compared to the control group, the ERAS group demonstrated a shorter surgical duration, a lower incidence of perioperative hypothermia, less time needed for the first time to get out of bed, the first time of anal exhaust, and the first time of defecation after returning to the ward (p < 0.05, Table 2).