Abstract: Objective To investigate the effect of the application of pulse contour cardiac output (PiCCO) monitoring technology on delayed resuscitation of patients with extensive burn in a mass casualty. Methods The clinical data of 41 patients injured in Kunshan dash explosion hospitalized in the First Affiliated Hospital of Soochow University, the 100th Hospital of the People's Liberation Army, and Suzhou Municipal Hospital were retrospectively analyzed. The patients were divided into traditional monitoring group (T, n=22) and PiCCO monitoring group (P, n=19) according to the monitoring technic during delayed resuscitation. The input volumes of electrolyte, colloids, and water of patients in the two groups within 2 hours after admission, the first, second, and third 8 hours post injury (HPI), and the first 24 HPI were recorded. The fluid infusion coefficients of patients in the two groups within 2 hours after admission, the first, second, and third 8 HPI, and the first, second, third, and fourth 24 HPI were calculated. The urine volume, mean arterial pressure (MAP), and central venous pressure (CVP) of patients in the two groups at post injury hour (PIH) 8, 16, 24, 48, 72, and 96 were recorded. The blood lactate, base excess, hematocrit (HCT), and platelet count of patients in the two groups at PIH 24, 48, 72, and 96 were recorded. Complications and death of patients in the two groups were recorded. Data were processed with analysis of variance for repeated measurement, Chi-square test, t test, and Wilcoxon test. The deviations between figure 2 and the fluid infusion coefficients of the first or second 24 HPI, and the deviations between figure 1 and the fluid infusion coefficients of the second, third or fourth 24 HPI were calculated, and the three groups deviations were analyzed by Pearson correlation analysis. Results (1) The input volumes of electrolyte of patients in group P were significantly more than those in group T within the first 8 and 24 HPI (with Z values respectively -3.506 and -2.654, P<0.05 or P<0.01), and the input volumes of electrolyte of patients in the two groups were similar within the other time periods (with Z values from -1.871 to -0.680, P values above 0.05). The input volumes of colloid of patients in group P were significantly less than those in group T within the second, third 8 HPI, and the first 24 HPI (with Z values from -4.720 to -2.643, P<0.05 or P<0.01), and the input volumes of colloid of patients in the two groups were similar within the other time periods (with Z values respectively -2.376 and -2.303, P values above 0.05). The input volumes of water of patients in the two groups were similar within each time period (with Z values from -1.959 to -0.241, P values above 0.05). (2) The fluid infusion coefficients of patients in group T within 2 hours after admission, the first, second, and third 8 HPI, and the first, second, third, and fourth 24 HPI were respectively (0.59±0.18), (0.70±0.23), (0.94±0.24), (0.74±0.14), (2.38±0.44), (1.70±0.56), (1.35±0.67), and (0.92±0.46) mL·kg^-1·%TBSA^-1, and the values in group P were respectively (0.59±0.29), (0.82±0.37), (0.86±0.38), (0.59±0.24), (2.27±0.85), (2.13±0.68), (1.59±3.78), and (1.46±0.56) mL·kg^-1·%TBSA^-1. The fluid infusion coefficients of patients in the two groups were similar within 2 hours after admission, the first, second 8 HPI, and the first, third 24 HPI (with t values from -1.262 to 0.871, P values above 0.05). The fluid infusion coefficient of patients in group P was significantly lower than that in group T within the third 8 HPI (t=2.456, P<0.05), and the fluid infusion coefficient of patients in group P were significantly higher than that in group T within the second and fourth 24 HPI (with t values respectively -2.234 and -3.370, P<0.05 or P<0.01). There was obviously negative correlation between the deviations of figure 2 and the fluid infusion coefficient of the first 24 HPI and that of the second 24 HPI (r=-0.438, P<0.01). There was no obvious correlation between the deviations of figure 1 and the fluid infusion coefficient of the second 24 HPI and that of the third 24 HPI (r=0.091, P>0.05). There was obviously positive correlation between the deviations of figure 1 and the fluid infusion coefficient of the second 24 HPI and that of the fourth 24 HPI (r=0.695, P<0.01). (3) The urine volumes and MAP of patients in the two groups were similar at each time point (with Z values from -1.884 to 0, P values above 0.05). The CVP of patients in group P were significantly higher than that in group T at PIH 16, 24, 48, and 72 (with Z values from -4.341 to -2.213, P<0.05 or P<0.01), and the CVP of patients in the two groups were similar at the other time points (with Z values respectively -0.132 and -1.208, P values above 0.05). The blood lactate of patients in group P was significantly higher than that in group T at PIH 72 (Z= -2.958, P<0.01) , and the blood lactate of patients in the two groups were similar at the other time points (with Z values from -1.742 to -0.433, P values above 0.05). The base excess of patients in group P were significantly lower than that in group T at PIH 24, 48, 72, and 96 (with Z values from -4.970 to -4.734, P values below 0.01). The HCT of patients in the two groups were similar at PIH 24, 48, 72, and 96 (with Z values from -2.239 to -0.196, P values above 0.05). There were significant differences in the platelet count of patients in the two groups at PIH 24, 72, and 96 (with Z values from -4.578 to -2.512, P<0.05 or P<0.01). (4) There were 15 cases in group T accompanied by complications, and 7 cases died, while 13 cases in group P accompanied by complications, and 9 cases died. The occurrence of complications and death of patients in the two groups were similar (with χ² values respectively <0.001 and 1.306, P values above 0.05). Conclusions On the basis of traditional burn shock monitoring index, the effect of fluid resuscitation in patients with severe burn monitored by PiCCO technology is not so good and still needs further clinical research.