Oxidative Stress and Surgical Recovery

Overview

Chronic pain, functional impairment and slow rates of recovery are key issues for patients after surgery and trauma. No preventative strategy in current use unequivocally modifies these rates, and few novel approaches have been tested. Furthermore, persistent postsurgical pain is a major route to chronic opioid use, opioid use disorder and, regrettably, opioid overdose. Most strategies designed to limit chronic pain or enhance functional recovery after surgery are directed at modulating peripheral and central nervous system activity and do not strongly modify the underlying tissue pathophysiology or fundamental systemic responses. Strategies limiting oxidative stress in the perioperative period, on the other hand, might limit tissue damage, organ dysfunction and immune system activation. N-acetyl cysteine (NAC) is an antioxidant well-studied in the perioperative period; it is very safe, relatively inexpensive and widely available. The central hypothesis is, therefore, that perioperative administration of NAC will reduce perioperative oxidative stress, limit immune system activation and improve key indices of surgical recovery. Although the planned work will not comprehensively address this hypothesis, it will identify the most useful tools and help the researchers estimate the required sample sizes for more definitive externally funded efforts.

This is a randomized, double-blind, placebo controlled interventional pilot study in 20 patients undergoing first-time total hip arthroplasty (THA) for chronic osteoarthritis at Stanford Medicine. The researchers will screen, enroll and collect biologic and behavioral data from 20 participants as outlined in previous observational and interventional clinical studies undertaken in close collaboration with the Department of Orthopedic Surgery. In particular, standard operating procedures for screening, recruiting, laboratory assessments, and clinical data collection are in place including eligibility screening via EPIC (EHR) ahead of patients' preoperative visit, coordinated recruitment and consenting during the pre-surgery visit including study- related laboratory work, further preoperative assessments after the visit (e.g. remote completion of questionnaires and direct import of results into REDCap), and real-time tracking of the data collection and storage process (e.g. including phone/email reminders if data are missing). Repeated assessments of pain, physical function, and analgesic medication will be made before surgery, daily on postoperative days 1-3, and then twice a week in post-op weeks 1 - 6. Delirium will be measured days 1-3 while in-hospital. Additional data will include demographics (age, BMI, sex, race, and ethnicity), surgical/anesthesia data (e.g. duration), and medical/medication history. Peripheral blood samples will be collected before surgery and 1hr and 24hr after surgery based on our prior study showing that monocyte activation (including STAT3, CREB and NFkB signaling responses in CD14+CD16- monocytes) early after surgery strongly correlates with delayed pain resolution and functional impairment. Exhaled breath samples will be collected intraoperatively prior to incision and at wound closure as well as at 1 and 24 hours after surgery. N-Acetylcysteine infusion: A loading dose of 50 mg/kg will be started as a 1-hour infusion before surgical incision, and will be followed by a maintenance dose of 50 mg/kg administered over 4 hours. This is a standard dosing paradigm that is safe when used intraoperatively and rarely causes significant adverse effects (mainly allergic reactions). Surgery and anesthesia: Participants will undergo unilateral hip arthroplasty performed by three surgeons using the same approach. The anesthetic and perioperative management of patients is standardized and follows ERAS-based recommendations. Measures: Well-validated instruments will be used to assess pain, pain interference and function of the affected and operated joint including the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) adapted for patients undergoing lower extremity joint surgery, the Brief Pain Inventory (BPI) and the Surgical Recovery Scale (SRS). Opioid consumption will be quantified as intravenous hydromorphone equivalents (milligram/day) using widely accepted opioid conversion tables. Sample analysis: Blood and plasma will be collected and processed for analysis with mass cytometry as previously described. A 39-parameter human CyTOF antibody panel will be applied that will allow the simultaneous analysis of 1) all major immune cell phenotypes 2) endogenous intracellular signaling responses (including the pSTAT3, pCREB and pNF-kB signal) and 3) intracellular markers of reactive aldehydes (i.e. 4-HNE and MDA signal). Breath samples will be analyzed for aldehydes including formaldehyde, crotenaldehyde, and benzaldehyde using mass spectroscopy in the laboratory of Dr. Gross. Plasma samples will be analyzed for free MDA and 4- HNE in baseline, 1 and 24-hour plasma samples in the laboratory of Dr. Clark. Analysis and modeling of outcome data: Self-reported outcomes will be analyzed using the validated models associated with each outcome to extract a quantified and normalized number associated with recovery. The 60Htz actigraphy data will first be mined for patterns associated with daily activities (e.g. step counts) and intensity levels. Next, a baseline will be established using the data collected during and prior to surgery, for each variable. All variables will be normalized to this baseline to account for patient-specific effects. Finally, a multivariate linear model (with days passed since surgery as the response variable) will be used to model the entire actigraphy dataset. The area under the respective recovery curve of each patient according to this model will be used as an objective recovery outcome. In our preliminary studies (data not shown) this outcome has been found to be correlated with several aspects of the immune system. Analysis and modeling of CyTOF data: The large number of data points (millions of cells per patient) and measured variables (tens of signaling pathways in hundreds of cell types) pose unique computational challenges that cannot be addressed using traditional bioinformatics tools. The researchers will develop a Bayesian framework that will combine a priori knowledge of the immune system with state-of-the-art mass cytometry profiling to build a predictive model of innate and adaptive immune cell signaling responses for each of the recovery outcomes.