The Association Between Intestinal Perfusion and Prolonged Mechanical Ventilation in Patients After Cardiac Valve Surgery

Patient enrollment This prospective observational study was performed in the 15-bed adult critical care unit in Adult General Hospital from January 2021 to March 2022.

The inclusion criteria were as follows: 1) patients admitted to ICU immediately after cardiac valve surgery; 2) age 18-80 years; 3) sinus rhythm; 4) without active bleeding or pneumothorax, and 5) complete measurement data.

The exclusion criteria were as follows: 1) history of peripheral vascular disease, 2) patients with severe stenosis defined as SMA peak systolic velocity (SMA-PSV >275 cm/s or SMA-PSV/abdominal aorta peak velocity of >3, 3) hepatic dysfunction or liver cirrhosis, portal hypertension, 4) cancer or end-stage renal diseases, 5) poor quality of abdominal ultrasound images.

Doppler ultrasound monitoring Doppler ultrasound was performed with an ultrasound system consisting of a 2-5 MHz C60xp Probe (X-Porte Ultrasound System, FUJIFILM SONOSITE, INC., USA). Blood flow parameters were measured by two physicians, each physician measured twice and averaged, and then averaged the two results. Each of the two ICU physicians had more than four years of experience in critical ultrasound and obtained certification from the Chinese Critical Ultrasound Study Group. Two skilled physicians conducted a total of 40 measurements on ten patients after cardiac valve surgery to evaluate inter-observer reproducibility.

The SMA flow was measured 1 cm proximal to the abdominal aorta. The angle of insonation was < 60°. The time-velocity waveform readings were used to measure the peak systolic velocity (PSV), end-diastolic velocity(EDV), resistance index(RI), time-averaged mean velocity(TAMV), pulsatility index (PI), according to the calculation software carried by the ultrasound. PI=(PSV-EDV)/TAMV, and RI=(PSV-EDV)/PSV.

Data collection Demographic information was recorded for further analyses (e.g., age, gender, EuroSCORE-II, sequential organ failure assessment (SOFA) score, body mass index (BMI), and hemodynamic parameters and blood gas analysis data). In addition, types of operation and operation time were collected. Moreover, outcome variables (e.g., hospital mortality, time of MV, length of ICU stay) were recorded for further comparison.

Statistical analysis The median plus the interquartile range (IQR) or mean standard deviation is used to show demographic data. The Shapiro-Wilk test was used to evaluate normality. The differences between groups were compared using the student's t-test for continuous variables with normality distribution and the Mann-Whitney U test for those without normality distribution. The differences between groups for categorical variables were compared by performing a Chi-square test. Correlations between variables and PMV were assessed by conducting logistic regression analysis. Variables showing statistical significance in the univariate logistic regression were selected covered in the multivariate logistic regression. Furthermore, to evaluate the predictive ability of the variables for PMV, a receiver operating characteristic (ROC) curve was applied. Statistical significance was set at P < 0.05. All analyzed P-values were two-sided. Statistical analyses were performed using the SPSS 25.0 software package (SPSS, Chicago). Bland-Altman plots with the mean difference and 95 percent limit of agreement (LOA) were used to assess inter-observer agreement, and statistical analyses were done using MedCalc Statistical software.

Inclusion criteria

• patients admitted to ICU immediately after cardiac valve surgery; 2) age 18-80 years; 3) sinus rhythm; 4) without active bleeding or pneumothorax, and 5) complete measurement data.

Exclusion criteria

• history of peripheral vascular disease, 2) patients with severe stenosis defined as SMA peak systolic velocity (SMA-PSV >275 cm/s or SMA-PSV/abdominal aorta peak velocity of >310, 3) hepatic dysfunction or liver cirrhosis, portal hypertension, 4) cancer or end-stage renal diseases, 5) poor quality of abdominal ultrasound images.