This study was approved by the Institutional Review Board at the University of California Irvine Medical Center (UCI IRB HS# 2017-4099).
We performed a retrospective single-centered chart review of all patients undergoing open abdominal surgery between 2010 and 2017 (Figure 1). Inclusion criteria for the search were any non-emergent open abdominal procedures including: gastrointestinal procedure (colorectal, gastric, small bowel, hepatic, and pancreatic involvement), urological procedure including nephrectomy or cystectomy, renal transplant, general exploratory laparotomy with or without lysis of adhesion, open removal of retroperitoneal mass, gynecological procedures involving open hysterectomy with or without oophorectomy, open gynecologic-oncological tumor debulking, and all other open abdominal surgeries that involved a combination of the procedures mentioned above. Procedures that involved major vascular surgery such as involvement of the abdominal aorta or inferior vena cava were not included in this cohort. The study only included adult patients between the age of 18 and 89. We defined high-risk patients as those who were identified as American Society of Anesthesiologist (ASA) Physical Status Classification of III or IV. Finally, we included only patients with a preoperative echocardiogram performed within one-year of the indexed surgery and for which the study report included evaluation and determination of the RV function. In patients who had multiple echo studies within one-year of the indexed surgery, we selected the study that was closest to the indexed surgery for final review.
To collect patients’ demographic and perioperative data, we performed manual chart review using the hospital’s electronic record. While intraoperative variables were collected from Surgical Information Systems (Surgical Information Systems Corp, Alpharetta GA), demographic and postoperative variables were obtained from Quest (Allscripts Corporation, Alpharetta GA). For those who met the inclusion criteria, the following preoperative variables were collected: age, gender, body mass index (BMI), preoperative hemoglobin level, presence or absence of history of congestive heart failure (CHF), coronary artery disease (CAD), hypertension (HTN), cerebrovascular accident (CVA), diabetes (DM), chronic obstructive pulmonary disease (COPD), obstructive sleep apnea (OSA), and pulmonary hypertension. Since abdominal procedures can often be performed as part of a cancer treatment plan, presence of active cancer requiring the indexed abdominal surgery was also collected. Finally, an RCRI score was calculated and collected based on presence of its six clinical predictors.
For intraoperative variables, length of surgery, need for intraoperative transfusion of allogeneic blood products, intraoperative total fluid balance, intraoperative hypotension, and intraoperative infusion of inotropic or vasopressor agents were collected. Furthermore, postoperative variables including postoperative development of respiratory complications and acute kidney injury, as well as, post-operative infections and need for subsequent surgeries during the same admission were also collected so they could be evaluated as confounding factors. Finally, diagnosis of sepsis made anytime during the entire hospital admission was also collected and evaluated as a confounder since presence of sepsis continues to be an important risk factor for morbidity and mortality in surgical patients.
For assessment of intraoperative hypotension, both noninvasive and invasive blood pressure measurements were extracted from the Surgical Information System (SIS). Data points without both a systolic and diastolic value were excluded. In addition, any systolic values outside of 20 – 300 mmHg and diastolic values outside of 5 – 200 mmHg were excluded as they were considered to be non-physiological. Blood pressure data from the noninvasive and invasive monitor were then combined in the following manner: if a systolic or diastolic value had another observation of the same type (systolic or diastolic) regardless of the source (noninvasive or invasive) and was within one minute of each other, the two values would be replaced with the average of the two. Mean arterial pressure (MAP) was calculated for each systolic/diastolic pair according to the following equation: 1/3 x systolic blood pressure + 2/3 x diastolic blood pressure. Intraoperative hypotension was defined using MAP < 60mmHg as the threshold. This threshold was chosen because previous studies have been able to show an increased risk for myocardial injury and mortality when MAP is less than an absolute threshold of 60 for various duration during general surgery. An episode of intraoperative hypotension was derived by calculating area under the threshold (AUT). AUT was calculated in the same manner as previously described by Vernooij et al.  Finally, total AUT was obtained by adding all AUTs for each surgical encounter. All blood pressure data processing described was performed via Python version 2.7 using SciPy and NumPy library of packages (Python Software Foundation, Wilmington, DE).
Postoperative MACE was defined broadly as composite events including non-fatal cardiac arrest, myocardial infarction, development of congestive heart failure, cerebrovascular accident (Stroke), and cardiovascular mortality defined as death attributable to any- or a combination of the adverse cardiovascular events just described[4-6]. Post-operative respiratory complication was defined as prolonged intubation for more than 24 hours or need for re-intubation or tracheostomy. Post-operative acute kidney injury was defined as patients with a post-operative rise of creatinine greater than 60% from the baseline. Post-operative need for subsequent surgeries included all procedures that required anesthesia care. Post-operative infection was defined as a composite event including wound or surgical site infection, urinary tract infection, pulmonary infection, and systemic infection. Finally, diagnosis of sepsis was made according to guidelines set by the International Sepsis Definitions Conference.
The preoperative echocardiogram obtained within one year of the index surgery was used to identify patients with RV systolic dysfunction. All of the echo studies were originally performed by the cardiology service at the study institution. The majority of the echo studies were performed via transthoracic echocardiogram (96%). All of the echo images were interpreted by the cardiologist from the study institution with the final results reported and stored in the institution’s cardiovascular imaging database (Syngo Dynamics – Siemens Healthcare, Tarrytown, NY). All study reports were reviewed and the following collected: LVEF, right ventricular systolic pressure (RVSP), any valvular pathology categorized as severe, presence of LV diastolic dysfunction, and RV function. RV function was reported as a binary variable (normal versus abnormal). RV function collected from the official report was determined based on visual estimation by the cardiologists. Visual estimation of the RV function was determined based on multiple acoustic windows including apical 4-chamber (lateral wall of the RV and RV apex), parasternal short-axis (anterior, lateral, and inferior wall of the RV), parasternal RV inflow (anterior and inferior wall of the RV), and subcostal 4-chamber (inferior wall of the RV).
All statistical analysis was performed using SPSS for windows version 24 (SPSS Inc, Chicago, IL). The cohort was divided into 2 groups: those with and without RV systolic dysfunction. For comparative analysis, Fisher’s exact test was used for dichotomous variables while Student t-test or Mann-Whitney U test were used for continuous variables with normal and non-normal distribution respectively. For test of normality, Shapiro-Wilk test was employed. Dichotomous variables are reported as counts and percentages while continuous variables are described as either mean and standard deviation for normal distribution or median with interquartile range for non-normal distribution.
Logistic regression analysis was performed to estimate odds ratio (OR) and 95% confidence interval (CI) for effect of RV systolic dysfunction on binary outcomes. The selection of variables to include in the univariable logistic model was based on both group differences and a priori predictors. Variables that were individually associated with outcome of interest with p-value <0.1 in univariable analysis were further included into multivariable analysis in a step-wise manner. Since RV systolic dysfunction, CHF, and RCRI are highly correlated with each other and are expected to exhibit multicollinearity, they were not included in the same regression models during the step-wise multivariable analysis. For goodness-of-fit of the regression model, Hosmer and Lemeshow test was employed. For all tests, a p-value <0.05 was considered statistically significant.