Objective To investigate the application value of a multi‑dimensional digital moni-toring platform for perioperative period in gastric cancer patients.

Methods The retrospective cohort study was conducted. The clinical data of 50 patients who underwent laparoscopic radical gastrec-tomy in The Affiliated Hospital of Nanjing University of Chinese Medicine from July 2022 to January 2024 were collected. There were 35 males and 15 females, aged (64±12)years. All patients followed the concept of enhanced recovery after surgery, and the multi‑dimensional digital monitoring platform based on wearable monitoring equipment was used to implement perioperative management measures. Observation indicators: (1) results of heart rate variability (HRV) monitoring; (2) results of blood glucose and blood oxygen monitoring; (3) results of exercise and sleep monitoring; (4) results of body composition monitoring. Measurement data with normal distribution were represented as Mean±SD, and measurement data with skewed distribution were represented as M(IQR). Repeated measurement data were analyzed using the repeated ANOVA. Measurement data with skewed distri-bution were transformed to normal distribution by SPSS transformation function before testing. For comparison between pre‑ and postoperation, paired sample t test was used for measurement data with normal distribution, and nonparametric Wilcoxon signed rank sum test was used for measure-ment data with skewed distribution.

Results (1) Results of HRV monitoring. From preoperation to the third day after surgery, the standard deviation normal to normal heart beat of 50 patients was changed from(103±26)ms to(101±36)ms, the mean of the standard deviations of normal to normal heart beat calculated per 5 min segment was changed from (45±16)ms to(33±12)ms, the number of pairs of adjacent NN intervals differing by more than 50 ms in the entire recording was changed from 6.02%(4.96%) to 5.79%(4.20%), the low frequency power was changed from 376.78(468.96)ms² to 742.79(525.20)ms², the high frequency power was changed from 273.61(273.58)ms² to 397.48(164.87)ms², the ratio of low frequency power to high frequency power was changed from 1.6±0.5 to 1.6±0.6, showing significant differences in above indicators before and after operation (F=34.43, 26.15, 24.58, 5.51, 6.11, 6.02, P<0.05). (2) Results of blood glucose and blood oxygen monitoring. From preoperation to the third day after surgery, the blood glucose of 50 patients was changed from 6.75(2.05)mmol/L to 6.90(2.63)mmol/L, showng a significant difference before and after operation (F=45.84, P<0.05). The blood oxygen was changed from 97.00%(5.00%) to 97.50%(3.00%), showing no significant difference before and after operation (F=2.25, P>0.05). (3) Results of exercise and sleep monitoring. From preoperation to the third day after surgery, the number of steps fo 50 pati-ents was changed from 3 043(1 224) to 1 473(767), sleep duration was changed from(8.2±1.1)hours to(7.3±0.8)hours, sleep score was changed from 80±10 to 78±5,showing significant differences in above indicators before and after operation (F=716.46, 29.02, 47.32,P<0.05).(4) Results of body composition monitoring. The body weight of 50 patients was changed from (63±8)kg to(61±8)kg before and after operation, body fat rate was changed from 24%±8% to 22%±9%, muscle mass was changed from 43 (12)kg to 41(17)kg, body mass index was changed from (23.0±2.6)kg/m² to(22.1±2.5)kg/m², showing significant differences in above indicators before and after operation (t=8.19, 3.00, Z=-2.78, t=7.34, P<0.05), while there was no significant difference in basal metabolic indicators from (1 390±134)kcal to (1 379±139)kcal before and after operation (t=1.02, P>0.05).

Conclusion The multi‑dimensional digital monitoring platform for preoperative period can accurately monitor the perioperative stress level and evaluate the postoperative recovery of gastric cancer patients, which can present the visual results.