An immune signature of postoperative cognitive decline in elderly patients.

Postoperative cognitive decline (POCD) is the predominant complication affecting elderly patients following major surgery, yet its prediction and prevention remain challenging. Understanding biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This longitudinal study involving 26 elderly patients undergoing orthopedic surgery aimed to characterize the impact of peripheral immune cell responses to surgical trauma on POCD. Trajectory analyses of single-cell mass cytometry data highlighted early JAK/STAT signaling exacerbation and diminished MyD88 signaling post-surgery in patients who developed POCD. Further analyses integrating single-cell and plasma proteomic data collected before surgery with clinical variables yielded a sparse predictive model that accurately identified patients who would develop POCD (AUC = 0.80). The resulting POCD immune signature included one plasma protein and ten immune cell features, offering a concise list of biomarker candidates for developing point-of-care prognostic tests to personalize perioperative management of at-risk patients. The code and the data are documented and available at https://github.com/gregbellan/POCD . Teaser: Modeling immune cell responses and plasma proteomic data predicts postoperative cognitive decline.

Variability and relative contribution of surgeon- and anesthesia-specific time components to total procedural time in cardiac surgery.

BACKGROUND: Decreasing variability in time-intensive tasks during cardiac surgery may reduce total procedural time, lower costs, reduce clinician burnout, and improve patient access. The relative contribution and variability of surgeon control time (SCT) and anesthesia control time (ACT) to total procedural time is unknown. METHODS: A total of 669 patients undergoing coronary artery bypass graft (CABG) surgery were enrolled. Using linear regression, we estimated adjusted SCTs and ACTs, controlling for patient and procedural covariates. The primary endpoint compared overall SCTs and ACTs. The secondary endpoint compared the variability in adjusted SCTs and ACTs. Sensitivity analyses quantified the relative importance of the specific surgeon and anesthesiologist in the adjusted linear models. RESULTS: The median SCT was 4.1 hours (interquartile range [IQR], 3.4-4.9 hours) compared to a median ACT of 1.0 hours (IQR, 0.8-1.2 hours; P < .001). Using linear regression, the variability in adjusted SCT among surgeons (range, 1.8 hours) was 3.5-fold greater than the variability in adjusted ACT among anesthesiologists (range, 0.5 hour; P < .001). The specific surgeon and anesthesiologist accounted for 50% of the explanatory power of the predictive model (P < .001). CONCLUSIONS: SCT variability is significantly greater than ACT variability and is strongly associated with the surgeon performing the procedure. Although these results suggest that SCT variability is an attractive operational target, further studies are needed to determine practitioner specific and modifiable attributes to reduce variability and improve efficiency.

Objective Activity Parameters Track Patient-specific Physical Recovery Trajectories After Surgery and Link With Individual Preoperative Immune States.

OBJECTIVE: The longitudinal assessment of physical function with high temporal resolution at a scalable and objective level in patients recovering from surgery is highly desirable to understand the biological and clinical factors that drive the clinical outcome. However, physical recovery from surgery itself remains poorly defined and the utility of wearable technologies to study recovery after surgery has not been established. BACKGROUND: Prolonged postoperative recovery is often associated with long-lasting impairment of physical, mental, and social functions. Although phenotypical and clinical patient characteristics account for some variation of individual recovery trajectories, biological differences likely play a major role. Specifically, patient-specific immune states have been linked to prolonged physical impairment after surgery. However, current methods of quantifying physical recovery lack patient specificity and objectivity. METHODS: Here, a combined high-fidelity accelerometry and state-of-the-art deep immune profiling approach was studied in patients undergoing major joint replacement surgery. The aim was to determine whether objective physical parameters derived from accelerometry data can accurately track patient-specific physical recovery profiles (suggestive of a 'clock of postoperative recovery'), compare the performance of derived parameters with benchmark metrics including step count, and link individual recovery profiles with patients' preoperative immune state. RESULTS: The results of our models indicate that patient-specific temporal patterns of physical function can be derived with a precision superior to benchmark metrics. Notably, 6 distinct domains of physical function and sleep are identified to represent the objective temporal patterns: ''activity capacity'' and ''moderate and overall activity (declined immediately after surgery); ''sleep disruption and sedentary activity (increased after surgery); ''overall sleep'', ''sleep onset'', and ''light activity'' (no clear changes were observed after surgery). These patterns can be linked to individual patients preopera-tive immune state using cross-validated canonical-correlation analysis. Importantly, the pSTAT3 signal activity in monocytic myeloid-derived suppressor cells predicted a slower recovery. CONCLUSIONS: Accelerometry-based recovery trajectories are scalable and objective outcomes to study patient-specific factors that drive physical recovery.

In-silico generation of high-dimensional immune response data in patients using a deep neural network.

Technologies for single-cell profiling of the immune system have enabled researchers to extract rich interconnected networks of cellular abundance, phenotypical and functional cellular parameters. These studies can power machine learning approaches to understand the role of the immune system in various diseases. However, the performance of these approaches and the generalizability of the findings have been hindered by limited cohort sizes in translational studies, partially due to logistical demands and costs associated with longitudinal data collection in sufficiently large patient cohorts. An evolving challenge is the requirement for ever-increasing cohort sizes as the dimensionality of datasets grows. We propose a deep learning model derived from a novel pipeline of optimal temporal cell matching and overcomplete autoencoders that uses data from a small subset of patients to learn to forecast an entire patient's immune response in a high dimensional space from one timepoint to another. In our analysis of 1.08 million cells from patients pre- and post-surgical intervention, we demonstrate that the generated patient-specific data are qualitatively and quantitatively similar to real patient data by demonstrating fidelity, diversity, and usefulness.

Stimulant use for self-management of pain among safety-net patients with chronic non-cancer pain.

BACKGROUND: Chronic pain affects one-fifth of US adults. Reductions in opioid prescribing have been associated with increased non-prescription opioid use and, chronologically, increased stimulant (methamphetamine and cocaine) use. While non-prescription opioid use is commonly attributed to pain self-management, the role of stimulants in managing pain is unclear. METHODS: We analyzed baseline data from a longitudinal study of patients with chronic non-cancer pain in an urban safety-net healthcare system who had been prescribed an opioid for ≥3 of the last 12 months, and had a history of non-prescription opioid, cocaine, or amphetamine use (N = 300). We estimated the prevalence and identified correlates of stimulant use to treat pain among a subgroup of patients who reported past-year stimulant use (N = 105). Data sources included computer-assisted questionnaire (demographics, substance use, pain), clinical exam and procedures (pain, pain tolerance), and chart abstraction (opioid prescriptions). We conducted bivariate analyses to assess associations between demographics, pain characteristics, non-opioid therapies, substance use, opioid prescriptions, and self-reported symptoms, with reporting using stimulants to treat pain. Demographic variables and those with significant bivariate associations were included in a multivariable logistic regression model. RESULTS: Fifty-two percent of participants with past-year stimulant use reported using stimulants in the past year to treat pain. Participants who used stimulants for pain reported slightly higher average pain in the past 3 months (median of 8 (IQR: 6-8) vs 7 (7-9) out of 10, p = 0.049). In the multivariable analysis, female gender (AOR= 3.20, 95% CI: 1.06-9.63, p = 0.039) and higher score on the Douleur Neuropathique 4 neuropathic pain questionnaire (AOR = 1.34, 95% CI: 1.05-1.70, p = 0.017) were associated with past-year stimulant use to treat pain. CONCLUSION: Stimulants may be used for pain self-management, particularly for neuropathic pain and among women. Our findings suggest an underexplored motivation for stimulant use in an era of reduced access to prescribed opioids.

Integrated Single-cell and Plasma Proteomic Modeling to Predict Surgical Site Complications: A Prospective Cohort Study.

OBJECTIVE: The aim of this study was to determine whether single-cell and plasma proteomic elements of the host's immune response to surgery accurately identify patients who develop a surgical site complication (SSC) after major abdominal surgery. SUMMARY BACKGROUND DATA: SSCs may occur in up to 25% of patients undergoing bowel resection, resulting in significant morbidity and economic burden. However, the accurate prediction of SSCs remains clinically challenging. Leveraging high-content proteomic technologies to comprehensively profile patients' immune response to surgery is a promising approach to identify predictive biological factors of SSCs. METHODS: Forty-one patients undergoing non-cancer bowel resection were prospectively enrolled. Blood samples collected before surgery and on postoperative day one (POD1) were analyzed using a combination of single-cell mass cytometry and plasma proteomics. The primary outcome was the occurrence of an SSC, including surgical site infection, anastomotic leak, or wound dehiscence within 30 days of surgery. RESULTS: A multiomic model integrating the single-cell and plasma proteomic data collected on POD1 accurately differentiated patients with (n = 11) and without (n = 30) an SSC [area under the curve (AUC) = 0.86]. Model features included coregulated proinflammatory (eg, IL-6- and MyD88- signaling responses in myeloid cells) and immunosuppressive (eg, JAK/STAT signaling responses in M-MDSCs and Tregs) events preceding an SSC. Importantly, analysis of the immunological data obtained before surgery also yielded a model accurately predicting SSCs (AUC = 0.82). CONCLUSIONS: The multiomic analysis of patients' immune response after surgery and immune state before surgery revealed systemic immune signatures preceding the development of SSCs. Our results suggest that integrating immunological data in perioperative risk assessment paradigms is a plausible strategy to guide individualized clinical care.

Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes.

PURPOSE OF REVIEW: Postoperative complications including infections, cognitive impairment, and protracted recovery occur in one-third of the 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on our healthcare system. However, the accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain as major clinical challenges. RECENT FINDINGS: Although multifactorial in origin, the dysregulation of immunological mechanisms that occur in response to surgical trauma is a key determinant of postoperative complications. Prior research, primarily focusing on inflammatory plasma markers, has provided important clues regarding their pathogenesis. However, the recent advent of high-content, single-cell transcriptomic, and proteomic technologies has considerably improved our ability to characterize the immune response to surgery, thereby providing new means to understand the immunological basis of postoperative complications and to identify prognostic biological signatures. SUMMARY: The comprehensive and single-cell characterization of the human immune response to surgery has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers, ultimately providing patients and surgeons with actionable information to improve surgical outcomes. Although recent studies have generated a wealth of knowledge, laying the foundation for a single-cell atlas of the human immune response to surgery, larger-scale multiomic studies are required to derive robust, scalable, and sufficiently powerful models to accurately predict the risk of postoperative complications in individual patients.

Predicting Acute Pain After Surgery: A Multivariate Analysis.

OBJECTIVES: To identify perioperative practice patterns that predictably impact postoperative pain. BACKGROUND: Despite significant advances in perioperative medicine, a significant portion of patients still experience severe pain after major surgery. Postoperative pain is associated with serious adverse outcomes that are costly to patients and society. METHODS: The presented analysis took advantage of a unique observational data set providing unprecedented detailed pharmacological information. The data were collected by PAIN OUT, a multinational registry project established by the European Commission to improve postoperative pain outcomes. A multivariate approach was used to derive and validate a model predictive of pain on postoperative day 1 (POD1) in 1008 patients undergoing back surgery. RESULTS: The predictive and validated model was highly significant (P = 8.9E-15) and identified modifiable practice patterns. Importantly, the number of nonopioid analgesic drug classes administered during surgery predicted decreased pain on POD1. At least 2 different nonopioid analgesic drug classes (cyclooxygenase inhibitors, acetaminophen, nefopam, or metamizol) were required to provide meaningful pain relief (>30%). However, only a quarter of patients received at least 2 nonanalgesic drug classes during surgery. In addition, the use of very short-acting opioids predicted increased pain on POD1, suggesting room for improvement in the perioperative management of these patients. Although the model was highly significant, it only accounted for a relatively small fraction of the observed variance. CONCLUSION: The presented analysis offers detailed insight into current practice patterns and reveals modifications that can be implemented in today's clinical practice. Our results also suggest that parameters other than those currently studied are relevant for postoperative pain including biological and psychological variables.

Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma.

Glucocorticoids (GC) are a controversial yet commonly used intervention in the clinical management of acute inflammatory conditions, including sepsis or traumatic injury. In the context of major trauma such as surgery, concerns have been raised regarding adverse effects from GC, thereby necessitating a better understanding of how GCs modulate the immune response. Here we report the results of a randomized controlled trial (NCT02542592) in which we employ a high-dimensional mass cytometry approach to characterize innate and adaptive cell signaling dynamics after a major surgery (primary outcome) in patients treated with placebo or methylprednisolone (MP). A robust, unsupervised bootstrap clustering of immune cell subsets coupled with random forest analysis shows profound (AUC = 0.92, p-value = 3.16E-8) MP-induced alterations of immune cell signaling trajectories, particularly in the adaptive compartments. By contrast, key innate signaling responses previously associated with pain and functional recovery after surgery, including STAT3 and CREB phosphorylation, are not affected by MP. These results imply cell-specific and pathway-specific effects of GCs, and also prompt future studies to examine GCs' effects on clinical outcomes likely dependent on functional adaptive immune responses.

Best Practices for Postoperative Brain Health: Recommendations From the Fifth International Perioperative Neurotoxicity Working Group.

As part of the American Society of Anesthesiology Brain Health Initiative goal of improving perioperative brain health for older patients, over 30 experts met at the fifth International Perioperative Neurotoxicity Workshop in San Francisco, CA, in May 2016, to discuss best practices for optimizing perioperative brain health in older adults (ie, >65 years of age). The objective of this workshop was to discuss and develop consensus solutions to improve patient management and outcomes and to discuss what older adults should be told (and by whom) about postoperative brain health risks. Thus, the workshop was provider and patient oriented as well as solution focused rather than etiology focused. For those areas in which we determined that there were limited evidence-based recommendations, we identified knowledge gaps and the types of scientific knowledge and investigations needed to direct future best practice. Because concerns about perioperative neurocognitive injury in pediatric patients are already being addressed by the SmartTots initiative, our workshop discussion (and thus this article) focuses specifically on perioperative cognition in older adults. The 2 main perioperative cognitive disorders that have been studied to date are postoperative delirium and cognitive dysfunction. Postoperative delirium is a syndrome of fluctuating changes in attention and level of consciousness that occurs in 20%-40% of patients >60 years of age after major surgery and inpatient hospitalization. Many older surgical patients also develop postoperative cognitive deficits that typically last for weeks to months, thus referred to as postoperative cognitive dysfunction. Because of the heterogeneity of different tools and thresholds used to assess and define these disorders at varying points in time after anesthesia and surgery, a recent article has proposed a new recommended nomenclature for these perioperative neurocognitive disorders. Our discussion about this topic was organized around 4 key issues: preprocedure consent, preoperative cognitive assessment, intraoperative management, and postoperative follow-up. These 4 issues also form the structure of this document. Multiple viewpoints were presented by participants and discussed at this in-person meeting, and the overall group consensus from these discussions was then drafted by a smaller writing group (the 6 primary authors of this article) into this manuscript. Of course, further studies have appeared since the workshop, which the writing group has incorporated where appropriate. All participants from this in-person meeting then had the opportunity to review, edit, and approve this final manuscript; 1 participant did not approve the final manuscript and asked for his/her name to be removed.

A proteomic clock of human pregnancy.

BACKGROUND: Early detection of maladaptive processes underlying pregnancy-related pathologies is desirable because it will enable targeted interventions ahead of clinical manifestations. The quantitative analysis of plasma proteins features prominently among molecular approaches used to detect deviations from normal pregnancy. However, derivation of proteomic signatures sufficiently predictive of pregnancy-related outcomes has been challenging. An important obstacle hindering such efforts were limitations in assay technology, which prevented the broad examination of the plasma proteome. OBJECTIVE: The recent availability of a highly multiplexed platform affording the simultaneous measurement of 1310 plasma proteins opens the door for a more explorative approach. The major aim of this study was to examine whether analysis of plasma collected during gestation of term pregnancy would allow identifying a set of proteins that tightly track gestational age. Establishing precisely timed plasma proteomic changes during term pregnancy is a critical step in identifying deviations from regular patterns caused by fetal and maternal maladaptations. A second aim was to gain insight into functional attributes of identified proteins and link such attributes to relevant immunological changes. STUDY DESIGN: Pregnant women participated in this longitudinal study. In 2 subsequent sets of 21 (training cohort) and 10 (validation cohort) women, specific blood specimens were collected during the first (7-14 weeks), second (15-20 weeks), and third (24-32 weeks) trimesters and 6 weeks postpartum for analysis with a highly multiplexed aptamer-based platform. An elastic net algorithm was applied to infer a proteomic model predicting gestational age. A bootstrapping procedure and piecewise regression analysis was used to extract the minimum number of proteins required for predicting gestational age without compromising predictive power. Gene ontology analysis was applied to infer enrichment of molecular functions among proteins included in the proteomic model. Changes in abundance of proteins with such functions were linked to immune features predictive of gestational age at the time of sampling in pregnancies delivering at term. RESULTS: An independently validated model consisting of 74 proteins strongly predicted gestational age (P = 3.8 × 10-14, R = 0.97). The model could be reduced to 8 proteins without losing its predictive power (P = 1.7 × 10-3, R = 0.91). The 3 top ranked proteins were glypican 3, chorionic somatomammotropin hormone, and granulins. Proteins activating the Janus kinase and signal transducer and activator of transcription pathway were enriched in the proteomic model, chorionic somatomammotropin hormone being the top-ranked protein. Abundance of chorionic somatomammotropin hormone strongly correlated with signal transducer and activator of transcription-5 signaling activity in CD4 T cells, the endogenous cell-signaling event most predictive of gestational age. CONCLUSION: Results indicate that precisely timed changes in the plasma proteome during term pregnancy mirror a proteomic clock. Importantly, the combined use of several plasma proteins was required for accurate prediction. The exciting promise of such a clock is that deviations from its regular chronological profile may assist in the early diagnoses of pregnancy-related pathologies, and point to underlying pathophysiology. Functional analysis of the proteomic model generated the novel hypothesis that chrionic somatomammotropin hormone may critically regulate T-cell function during pregnancy.

Deep Immune Profiling of an Arginine-Enriched Nutritional Intervention in Patients Undergoing Surgery.

Application of high-content immune profiling technologies has enormous potential to advance medicine. Whether these technologies reveal pertinent biology when implemented in interventional clinical trials is an important question. The beneficial effects of preoperative arginine-enriched dietary supplements (AES) are highly context specific, as they reduce infection rates in elective surgery, but possibly increase morbidity in critically ill patients. This study combined single-cell mass cytometry with the multiplex analysis of relevant plasma cytokines to comprehensively profile the immune-modifying effects of this much-debated intervention in patients undergoing surgery. An elastic net algorithm applied to the high-dimensional mass cytometry dataset identified a cross-validated model consisting of 20 interrelated immune features that separated patients assigned to AES from controls. The model revealed wide-ranging effects of AES on innate and adaptive immune compartments. Notably, AES increased STAT1 and STAT3 signaling responses in lymphoid cell subsets after surgery, consistent with enhanced adaptive mechanisms that may protect against postsurgical infection. Unexpectedly, AES also increased ERK and P38 MAPK signaling responses in monocytic myeloid-derived suppressor cells, which was paired with their pronounced expansion. These results provide novel mechanistic arguments as to why AES may exert context-specific beneficial or adverse effects in patients with critical illness. This study lays out an analytical framework to distill high-dimensional datasets gathered in an interventional clinical trial into a fairly simple model that converges with known biology and provides insight into novel and clinically relevant cellular mechanisms.

Patient-specific Immune States before Surgery Are Strong Correlates of Surgical Recovery.

BACKGROUND: Recovery after surgery is highly variable. Risk-stratifying patients based on their predicted recovery profile will afford individualized perioperative management strategies. Recently, application of mass cytometry in patients undergoing hip arthroplasty revealed strong immune correlates of surgical recovery in blood samples collected shortly after surgery. However, the ability to interrogate a patient's immune state before surgery and predict recovery is highly desirable in perioperative medicine. METHODS: To evaluate a patient's presurgical immune state, cell-type-specific intracellular signaling responses to ex vivo ligands (lipopolysaccharide, interleukin [IL]-6, IL-10, and IL-2/granulocyte macrophage colony-stimulating factor) were quantified by mass cytometry in presurgical blood samples. Selected ligands modulate signaling processes perturbed by surgery. Twenty-three cell surface and 11 intracellular markers were used for the phenotypic and functional characterization of major immune cell subsets. Evoked immune responses were regressed against patient-centered outcomes, contributing to protracted recovery including functional impairment, postoperative pain, and fatigue. RESULTS: Evoked signaling responses varied significantly and defined patient-specific presurgical immune states. Eighteen signaling responses correlated significantly with surgical recovery parameters (|R| = 0.37 to 0.70; false discovery rate < 0.01). Signaling responses downstream of the toll-like receptor 4 in cluster of differentiation (CD) 14 monocytes were particularly strong correlates, accounting for 50% of observed variance. Immune correlates identified in presurgical blood samples mirrored correlates identified in postsurgical blood samples. CONCLUSIONS: Convergent findings in pre- and postsurgical analyses provide validation of reported immune correlates and suggest a critical role of the toll-like receptor 4 signaling pathway in monocytes for the clinical recovery process. The comprehensive assessment of patients' preoperative immune state is promising for predicting important recovery parameters and may lead to clinical tests using standard flow cytometry.

Clinical recovery from surgery correlates with single-cell immune signatures.

Delayed recovery from surgery causes personal suffering and substantial societal and economic costs. Whether immune mechanisms determine recovery after surgical trauma remains ill-defined. Single-cell mass cytometry was applied to serial whole-blood samples from 32 patients undergoing hip replacement to comprehensively characterize the phenotypic and functional immune response to surgical trauma. The simultaneous analysis of 14,000 phosphorylation events in precisely phenotyped immune cell subsets revealed uniform signaling responses among patients, demarcating a surgical immune signature. When regressed against clinical parameters of surgical recovery, including functional impairment and pain, strong correlations were found with STAT3 (signal transducer and activator of transcription), CREB (adenosine 3',5'-monophosphate response element-binding protein), and NF-κB (nuclear factor κB) signaling responses in subsets of CD14(+) monocytes (R = 0.7 to 0.8, false discovery rate <0.01). These sentinel results demonstrate the capacity of mass cytometry to survey the human immune system in a relevant clinical context. The mechanistically derived immune correlates point to diagnostic signatures, and potential therapeutic targets, that could postoperatively improve patient recovery.

Changes resembling complex regional pain syndrome following surgery and immobilization.

UNLABELLED: The study of complex regional pain syndrome (CRPS) in humans is complicated by inhomogeneities in available study cohorts. We hoped to characterize early CRPS-like features in patients undergoing hand surgery. Forty-three patients were recruited from a hand surgery clinic that had elective surgeries followed by cast immobilization. On the day of cast removal, patients were assessed for vasomotor, sudomotor, and trophic changes, and edema and pain sensitization using quantitative sensory testing. Pain intensity was assessed at the time of cast removal and after 1 additional month, as was the nature of the pain using the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS). Skin biopsies were harvested for the analysis of expression of inflammatory mediators. We identified vascular and trophic changes in the surgical hands of most patients. Increased sensitivity to punctate, pressure, and cold stimuli were observed commonly as well. Moreover, levels of IL-6, TNF-alpha, and the mast cell marker tryptase were elevated in the skin of hands ipsilateral to surgery. Moderate-to-severe pain persisted in the surgical hands for up to 1 month after cast removal. Exploratory analyses suggested interrelationships between the physical, quantitative sensory testing, and gene expression changes and pain-related outcomes. PERSPECTIVE: This study has identified CPRS-like features in the limbs of patients undergoing surgery followed by immobilization. Further studies using this population may be useful in refining our understanding of CRPS mechanisms and treatments for this condition.

Postoperative subcutaneous instillation of low-dose ketorolac but not hydromorphone reduces wound exudate concentrations of interleukin-6 and interleukin-10 and improves analgesia following cesarean delivery.

UNLABELLED: The objectives of this study were to test the effects of low-dose ketorolac and hydromorphone added to continuous local anesthetic wound instillation on surgical-site inflammatory mediators, postoperative pain, and opioid consumption. Sixty healthy women undergoing cesarean delivery were enrolled in this randomized, double-blinded study. Patients were randomized to receive a subcutaneous wound instillation of bupivacaine .5% at 10 mg/hour (active control), bupivacaine .5% with ketorolac .6 mg/hour, or bupivacaine .5% with hydromorphone .04 mg/hour for 48 hours postcesarean. Wound exudate was sampled at 4, 24, and 48 hours postcesarean and assayed for interleukins IL-1ß, IL-2, IL-6, IL-8, IL-10, and IL-12, tumor necrosis factor (TNF-α), interferon (INF-γ), and granulocyte-macrophage colony stimulating factor (GM-CSF). The addition of ketorolac to bupivacaine significantly decreased IL-6 (P = .012) and IL-10 (P = .005) compared to plain bupivacaine. Ketorolac, but not hydromorphone, was associated with a decrease in pain (P = .018) and analgesic use (P = .020) following cesarean delivery. Our results are compatible with the view that significant analgesics effects are mediated through local modulation of inflammatory events. Low-dose ketorolac administered into surgical wounds exert significant anti-inflammatory and analgesic effects and may be a valuable analgesic alternative to systemic nonsteroidal anti-inflammatories (NSAIDs) but with potentially fewer side effects. PERSPECTIVE: This article demonstrates that low-dose ketorolac administered into wounds modulates local inflammatory events, decreases postoperative pain, and reduces opioid consumption. These results suggest that administration of NSAIDs into surgical wounds may be an analgesic alternative to higher systemic dosing of NSAIDs.

The role of interleukin-1 in wound biology. Part I: Murine in silico and in vitro experimental analysis.

BACKGROUND: Wound healing is a multistep, complex process that involves the coordinated action of multiple cell types. Conflicting results have been obtained when conventional methods have been used to study wound biology. Therefore, we analyzed the wound response in a mouse genetic model. METHODS: We analyzed inflammatory mediators produced within incisional wounds induced in 16 inbred mouse strains. Computational haplotype-based genetic analysis of inter-strain differences in the level of production of 2 chemokines in wounds was performed. An in vitro experimental analysis system was developed to investigate whether interleukin (IL)-1 could affect chemokine production by 2 different types of cells that are present within wounds. RESULTS: The level of 2 chemokines, keratinocyte-derived chemokine (KC) and macrophage inflammatory protein 1α, exhibited very large (75- and 463-fold, respectively) interstrain differences within wound tissue across this inbred strain panel. Genetic variation within Nalp1, an inflammasome component that regulates IL-1 production, correlated with the interstrain differences in KC and macrophage inhibitory protein 1α production. Consistent with the genetic correlation, IL-1ß was shown to stimulate KC production by murine keratinocyte and fibroblast cell lines in vitro. CONCLUSIONS: Genetic variation within Nalp1 could contribute to interstrain differences in wound chemokine production by altering the amount of IL-1 produced.

The role of interleukin-1 in wound biology. Part II: In vivo and human translational studies.

BACKGROUND: In the accompanying paper, we demonstrate that genetic variation within Nalp1 could contribute to interstrain differences in wound chemokine production through altering the amount of interleukin (IL)-1 produced. We further investigate the role of IL-1 in incisional wound biology and its effect on wound chemokine production in vivo and whether this mechanism could be active in human subjects. METHODS: A well-characterized murine model of incisional wounding was used to assess the in vivo role of IL-1 in wound biology. The amount of 7 different cytokines/chemokines produced within an experimentally induced skin incision on a mouse paw and the nociceptive response was analyzed in mice treated with an IL-1 inhibitor. We also investigated whether human IL-1ß or IL-1α stimulated the production of chemokines by primary human keratinocytes in vitro, and whether there was a correlation between IL-1ß and chemokine levels in 2 experimental human wound paradigms. RESULTS: Administration of an IL-1 receptor antagonist to mice decreased the nociceptive response to an incisional wound, and reduced the production of multiple inflammatory mediators, including keratinocyte-derived chemokine (KC) and macrophage inhibitory protein (MIP)-1α, within the wounds. IL-1α and IL-1ß stimulated IL-8 and GRO-α (human homologues of murine keratinocyte-derived chemokine) production by primary human keratinocytes in vitro. IL-1ß levels were highly correlated with IL-8 in human surgical wounds, and at cutaneous sites of human ultraviolet B-induced sunburn injury. CONCLUSIONS: IL-1 plays a major role in regulating inflammatory mediator production in wounds through a novel mechanism; by stimulating the production of multiple cytokines and chemokines, it impacts clinically important aspects of wound biology. These data suggest that administration of an IL-1 receptor antagonist within the perioperative period could decrease postsurgical wound pain.