Stress and autonomic nerve dysfunction monitoring in perioperative gastric cancer patients using a smart device.

BACKGROUND: Heart rate variability (HRV), a sensitive marker of stress and autonomic nervous disorders, was significantly decreased in cardiovascular disease, inflammation, and surgical injury. However, the effect of radical gastrectomy on HRV parameters needs to be further investigated. METHODS: A prospective, observational study including 45 consecutive enrolled patients undergoing radical gastrectomy in our enhanced recovery after surgery (ERAS) programs was conducted. Frequency- and time-domain parameters of HRV from 1 day prior to operation to 4 days postoperatively were continuously measured. Meanwhile, plasma cortisol and inflammatory markers were recorded and correlated to HRV parameters. RESULTS: Heart rate variability showed a solidly circadian rhythm. Anesthesia severely disturbed HRV parameters, resulting in a reduction of most of the HRV parameters. Frequency-domain parameter (including VLF) and time-domain parameters (including the SDNN, SDANN, and triangular index) of HRV demonstrated a significant reduction compared to preoperative values on the postoperative day 1 (Pod1), and these HRV parameters could return to baseline on Pod2 or Pod3, indicating surgical stress and autonomic nerve dysfunction existed in the early postoperative period. Inflammatory biomarkers were significantly elevated on Pod1 and Pod3. Plasma cortisol decreased significantly on Pod1 and Pod3. Both inflammatory biomarkers and plasma cortisol had no significant correlation with HRV parameters. CONCLUSIONS: Compared with plasma cortisol and inflammation biomarkers, HRV is more sensitive to detect surgical stress and autonomic nervous dysfunction induced by radical gastrectomy in patients with gastric cancer.

A novel nomogram based on the prognostic nutritional index for predicting postoperative outcomes in patients with stage I-III gastric cancer undergoing robotic radical gastrectomy.

Background: The inflammation and nutrition status are crucial factors influencing the outcome of patients with gastric cancer. This study aims to investigate the prognostic value of the preoperative prognostic nutritional index (PNI) in patients with stage I-III gastric cancer undergoing robotic radical gastrectomy combined with Enhanced Recovery after Surgery (ERAS), and further to create a clinical prognosis prediction model. Study: 525 patients with stage I-III gastric cancer who underwent ERAS combined with RRG from July 2010 to June 2018 were included in this work, and were divided randomly into training and validating groups in a 7-to-3 ratio. The association between PNI and overall survival (OS) was assessed by Kaplan-Meier analysis and the log-rank test. Independent risk factors impacting postoperative survival were analyzed with the Cox proportional hazards regression model. A nomogram for predicting OS was constructed based on multivariate analysis, and its predictive performance was evaluated using Harrell's concordance index (C-index), calibration plots, ROC curve, decision curve analysis (DCA), and time-dependent ROC curve analysis. Results: Survival analyses revealed the presence of a significant correlation between low preoperative PNI and shortened postoperative survival (P = 0.001). According to multivariate analysis, postoperative complications (P < 0.001), pTNM stage (II: P = 0.007; III: P < 0.001), PNI (P = 0.048) and lymph node ratio (LNR) (P = 0.003) were independent prognostic factors in patients undergoing ERAS combined with RRG. The nomogram constructed based on PNI, pTNM stage, complications, and LNR was superior to the pTNM stage model in terms of predictive performance. The C-indexes of the nomogram model were respectively 0.765 and 0.754 in the training and testing set, while AUC values for 1-year, 3-year, and 5-year OS were 0.68, 0.71, and 0.74 in the training set and 0.60, 0.67, and 0.72 in the validation set. Conclusion: Preoperative PNI is an independent prognostic factor for patients with stage I-III gastric cancer undergoing ERAS combined with robotic radical gastrectomy. Based on PNI, we constructed a nomogram for predicting postoperative outcomes of gastric cancer patients, which might be utilized clinically.