Myocardial Injury and Intraoperative Tissue Oximetry in Patients Undergoing Spine Surgery (MONITOR)
Myocardial Injury and Intraoperative Tissue Oximetry in Patients Undergoing Spine Surgery (MONITOR)
Myocardial injury after non-cardiac surgery (MINS) is common in patients undergoing major surgery. Many of the events are undetected and associated with a high 30-day mortality risk. Knowledge of which perioperative factors that predicts MINS is lacking. Decrease in tissue oxygenation (StO2) is common in patients undergoing major spine surgery and is associated with postoperative complications in these patients. However, an association between decrease in tissue oxygenation and MINS has not been examined. This group of patients may have other potential predictors of postoperative complications that the study group would like to investigate. In this observational cohort study, we will include 70 patients undergoing major spine surgery at University of California San Francisco. The primary hypothesis is that decrease in intraoperative tissue oxygenation is associated with postoperative myocardial injury.
Significance:
Each year 10 million people worldwide suffer from myocardial injury after non-cardiac surgery (MINS). The majority of these events are undetected because they are asymptomatic and there is sparse knowledge about triggering causes. Major surgery is associated with a high risk of postoperative complications. These include covert stroke, myocardial injury and -infarction, and are all major contributors to mortality. The 30-day post-operative mortality in patients suffering from covert stroke is increased up to eight-fold compared with matched controls and is 10% in patients with MINS, which makes it a substantial public health problem. Approximately 33% of patients undergoing major spine surgery suffer from major postoperative complications, including stroke and myocardial infarction. However, knowledge is lacking regarding which perioperative factors predict myocardial injury and -infarction, covert and overt stroke, and mortality in high-risk patients such as those undergoing major spine surgery.
Measure of tissue oxygenation with near-infrared spectroscopy (NIRS) is non-invasive and uncomplicated. Tissue desaturation is common in spine surgery patients. Previous studies found that a decrease in tissue oxygenation (StO2) was associated with postoperative complications such as creatinine elevation, hypotension and prolonged hospitalization. However, current knowledge of how tissue oxygenation affects other clinical outcomes is lacking.
Thus, to address these knowledge gaps the investigators propose a cohort study to examine the association between tissue oxygenation and MINS in patients undergoing major spine surgery.
Methods This is a prospective observational cohort study. Participants are patients undergoing major spine surgery. Measurements include blood samples, non-invasive tissue oximetry and collection of general perioperative factors from the anesthesia machine. First measurements are made on the day of surgery and further measurements are conducted on the first two postoperative days. Secondary outcomes from medical records (e.g. 30-day mortality) are collected retrospectively.
Patients will be screened from Operation Room Surgery Schedule at University of California, San Francisco (UCSF) prior to surgery. The informed consent will be obtained at the preoperative area about 30-60 min prior to surgery. Eligible patients will sign a written consent form and HIPAA Authorization for study participation. If the subject is determined to have diminished or lack a capacity to consent, a surrogate/legally authorized representative will need to be present to authorize their participation in the study and complete the applicable forms as required by UCSF and Californian law.
Data from medical records are entered by certified study personnel into REDCap (a HIPAA compliant online data collection tool) to assure all data is complete and stored correctly. Included in REDCap is a data dictionary with descriptions of every individual variable. Standard Operating Procedures (SOP's) for patient recruitment and enrollment, data collection and data extraction have been created and are available. Tissue Oximetry data is collected separately with the laboratory's oximeters. After each case/study the data is uploaded to an online secure box. As all data are collected case-by-case in the course of the study, all missing data are registered immediately as missing in REDCap and will be treated as missing data in the final data analysis.
Sample size:
The sample size assessment is based on previous studies investigation tissue oximetry and clinical outcomes.
Effect size: 0.36 (SD=0.50) based on Meng et al. (Br J Anaesth. 2017 Apr 1;118(4):551-562. doi: 10.1093/bja/aex008.):
Muscle tissue oxygenation (SmO2) time weighted area under the curve (AUC) (%*min*hr-1 (SD)):
<3 complications: 1.4 (0.8) >3 complications: 1.9 (1.2) p-value: 0.07 Proportion of patients with >3 composite complications = 33% Alpha: 0.05 Beta: 0.2 (power=0.8) Sample size: 68. We expect to include 70 patients in this study.
By convention the 5% level of alpha and 20% level of beta have been used. As this study is explorative and hypothesis-testing, the investigators consider the above calculation to contain sufficient information.
Statistical analysis:
Primary analysis will be multiple regression with adjustment for age, sex and pre-existing conditions including cardiovascular disease, coronary heart disease, heart failure, diabetes mellitus and obstructive respiratory diseases. The following pre-specified potential confounders will be tested separately: age, gender, BMI, smoking status, history of coronary artery disease, congestive heart failure, stroke, transient ischemic attacks, chronic obstructive pulmonary disease, insulin therapy, hypertension, preoperative creatinine elevation above normal, and length of surgery. Since this relationship may or may not be linear, the data will first visually be assessed by plotting the estimated probability (on the logit scale) of having the outcome as a function of StO2, using a univariable logistic regression incorporating a smooth (thin-plate regression spline) term for StO2 (smoothing parameter obtained via cross-validation). The fit of each model will be assessed by the Hosmer-Lemeshow goodness-of-fit test. STATA software will be used for the statistical procedures.
Inclusion Criteria:
Exclusion Criteria: