Continuous epidural infusion of morphine versus single epidural injection of extended-release morphine for postoperative pain control after arthroplasty: a retrospective analysis

Background:This study retrospectively compared the continuous epidural infusion of morphine with a single epidural injection of extended-release morphine for postoperative pain control after arthroplasty.Methods:Medical records were reviewed for subjects who had total knee or hip arthroplasty (THA) under spinal anesthesia and received either a continuous epidural infusion of morphine (Group EPID; n = 101) or an extended-release epidural morphine (Group EREM; n = 109) for postoperative pain. Data were collected for three postoperative days (POD) on: pain scores; supplemental opioids; medications for respiratory depression, nausea, and pruritus, and distance ambulated during physical therapy.Results:Pain scores were similar until subjects were transitioned to another analgesic approach on POD 2; after that time, pain scores increased in Group EPID, although they decreased in Group EREM. Supplemental opioids were used more on POD1 in Group EREM than in Group EPID, although time to first opioid and total daily morphine equivalents were similar. Naloxone and antiemetics, not antipruritics, were used more in Group EREM. Distance ambulated after THA was greater in Group EREM than in Group EPID.Conclusions:These results suggest that EREM is associated with better postoperative ambulation and analgesia during the transition to oral or intravenous analgesics, although a higher incidence of side-effects was evident

Continuous epidural infusion of morphine versus single epidural injection of extended-release morphine for postoperative pain control after arthroplasty: a retrospective analysis

Stephanie Vanterpool, Randall Coombs, Karamarie FechoDepartment of Anesthesiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USABackground: This study retrospectively compared the continuous epidural infusion of morphine with a single epidural injection of extended-release morphine for postoperative pain control after arthroplasty.Methods: Medical records were reviewed for subjects who had total knee or hip arthroplasty (THA) under spinal anesthesia and received either a continuous epidural infusion of morphine (Group EPID; n = 101) or an extended-release epidural morphine (Group EREM; n = 109) for postoperative pain. Data were collected for three postoperative days (POD) on: pain scores; supplemental opioids; medications for respiratory depression, nausea, and pruritus, and distance ambulated during physical therapy.Results: Pain scores were similar until subjects were transitioned to another analgesic approach on POD 2; after that time, pain scores increased in Group EPID, although they decreased in Group EREM. Supplemental opioids were used more on POD1 in Group EREM than in Group EPID, although time to first opioid and total daily morphine equivalents were similar. Naloxone and antiemetics, not antipruritics, were used more in Group EREM. Distance ambulated after THA was greater in Group EREM than in Group EPID.Conclusions: These results suggest that EREM is associated with better postoperative ambulation and analgesia during the transition to oral or intravenous analgesics, although a higher incidence of side-effects was evident.Keywords: continuous epidural morphine infusion, extended-release epidural morphine, lower extremity arthroplasty, ambulation, postoperative pain, side-effect

In-hospital resuscitation: opioids and other factors influencing survival

Karamarie Fecho1, Freeman Jackson1, Frances Smith1, Frank J Overdyk21Department of Anesthesiology, University of North Carolina, Chapel Hill, North Carolina, USA; 2Department of Anesthesia and Perioperative Medicine, Medical University of South Carolina, Charleston, South Carolina, USAPurpose: “Code Blue” is a standard term used to alertt hospital staff that a patient requires resuscitation. This study determined rates of survival from Code Blue events and the role of opioids and other factors on survival.Methods: Data derived from medical records and the Code Blue and Pharmacy databases were analyzed for factors affecting survival.Results: During 2006, rates of survival from the code only and to discharge were 25.9% and 26.4%, respectively, for Code Blue events involving cardiopulmonary resuscitation (CPR; N = 216). Survival rates for events not ultimately requiring CPR (N = 77) were higher, with 32.5% surviving the code only and 62.3% surviving to discharge. For CPR events, rates of survival to discharge correlated inversely with time to chest compressions and defibrillation, precipitating event, need for airway management, location and age. Time of week, witnessing, postoperative status, gender and opioid use did not influence survival rates. For non-CPR events, opioid use was associated with decreased survival. Survival rates were lowest for patients receiving continuous infusions (P < 0.01) or iv boluses of opioids (P < 0.05).Conclusions: One-quarter of patients survive to discharge after a CPR Code Blue event and two-thirds survive to discharge after a non-CPR event. Opioids may influence survival from non-CPR events.Keywords: code blue, survival, opioids, cardiopulmonary resuscitation, cardiac arrest, patient safet

Postoperative mortality after inpatient surgery: Incidence and risk factors

Karamarie Fecho1, Anne T Lunney1, Philip G Boysen1, Peter Rock2, Edward A Norfleet11Department of Anesthesiology, School of Medicine, University of North Carolina, Chapel Hill, NC, USA; 2Department of Anesthesiology, University of Maryland, Baltimore, MD, USAPurpose: This study determined the incidence of and identified risk factors for 48 hour (h) and 30 day (d) postoperative mortality after inpatient operations.Methods: A retrospective cohort study was conducted using Anesthesiology’s Quality Indicator database as the main data source. The database was queried for data related to the surgical procedure, anesthetic care, perioperative adverse events, and birth/death/operation dates. The 48 h and 30 d cumulative incidence of postoperative mortality was calculated and data were analyzed using Chi-square or Fisher’s exact test and generalized estimating equations.Results: The 48 h and 30 d incidence of postoperative mortality was 0.57% and 2.1%, respectively. Higher American Society of Anesthesiologists physical status scores, extremes of age, emergencies, perioperative adverse events and postoperative Intensive Care Unit admission were identified as risk factors. The use of monitored anesthesia care or general anesthesia versus regional or combined anesthesia was a risk factor for 30 d postoperative mortality only. Time under anesthesia care, perioperative hypothermia, trauma, deliberate hypotension and invasive monitoring via arterial, pulmonary artery or cardiovascular catheters were not identified as risk factors.Conclusions: Our findings can be used to track postoperative mortality rates and to test preventative interventions at our institution and elsewhere.Keywords: postoperative mortality, risk factors, operations, anesthesia, inpatient surger

Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an Open API

The Integrated Clinical and Environmental Exposures Service (ICEES) provides open regulatory-compliant access to clinical data, including electronic health record data, that have been integrated with environmental exposures data. While ICEES has been validated in the context of an asthma use case and several other use cases, the regulatory constraints on the ICEES open application programming interface (OpenAPI) result in data loss when using the service for multivariate analysis. In this study, we investigated the robustness of the ICEES OpenAPI through a comparative analysis, in which we applied a generalized linear model (GLM) to the OpenAPI data and the constraint-free source data to examine factors predictive of asthma exacerbations. Consistent with previous studies, we found that the main predictors identified by both analyses were sex, prednisone, race, obesity, and airborne particulate exposure. Comparison of GLM model fit revealed that data loss impacts model quality, but only with select interaction terms. We conclude that the ICEES OpenAPI supports multivariate analysis, albeit with potential data loss that users should be aware of

Catechol-O-methyltransferase inhibition increases pain sensitivity through activation of both β2- and β3-adrenergic receptors

Catechol-O-methyltransferase (COMT), an enzyme that metabolizes catecholamines, has recently been implicated in the modulation of pain. Our group demonstrated that human genetic variants of COMT are predictive for the development of Temporomandibular Joint Disorder (TMJD) and are associated with heightened experimental pain sensitivity (Diatchenko et al. 2005). Variants associated with heightened pain sensitivity produce lower COMT activity. Here we report the mechanisms underlying COMT-dependent pain sensitivity. To characterize the means whereby elevated catecholamine levels, resulting from reduced COMT activity, modulate heightened pain sensitivity, we administered a COMT inhibitor to rats and measured behavioral responsiveness to mechanical and thermal stimuli. We show that depressed COMT activity results in enhanced mechanical and thermal pain sensitivity. This phenomenon is completely blocked by the nonselective β-adrenergic antagonist propranolol or by the combined administration of selective β2- and β3-adrenergic antagonists, while administration of β1-adrenergic, α-adrenergic, or dopaminergic receptor antagonists fail to alter COMT-dependent pain sensitivity. These data provide the first direct evidence that low COMT activity leads to increased pain sensitivity via a β2/3-adrenergic mechanism. These findings are of considerable clinical importance, suggesting that pain conditions resulting from low COMT activity and/or elevated catecholamine levels can be treated with pharmacological agents that block both β2- and β3-adrenergic receptors

Leveraging Open Electronic Health Record Data and Environmental Exposures Data to Derive Insights Into Rare Pulmonary Disease

Research on rare diseases has received increasing attention, in part due to the realized profitability of orphan drugs. Biomedical informatics holds promise in accelerating translational research on rare disease, yet challenges remain, including the lack of diagnostic codes for rare diseases and privacy concerns that prevent research access to electronic health records when few patients exist. The Integrated Clinical and Environmental Exposures Service (ICEES) provides regulatory-compliant open access to electronic health record data that have been integrated with environmental exposures data, as well as analytic tools to explore the integrated data. We describe a proof-of-concept application of ICEES to examine demographics, clinical characteristics, environmental exposures, and health outcomes among a cohort of patients enriched for phenotypes associated with cystic fibrosis (CF), idiopathic bronchiectasis (IB), and primary ciliary dyskinesia (PCD). We then focus on a subset of patients with CF, leveraging the availability of a diagnostic code for CF and serving as a benchmark for our development work. We use ICEES to examine select demographics, co-diagnoses, and environmental exposures that may contribute to poor health outcomes among patients with CF, defined as emergency department or inpatient visits for respiratory issues. We replicate current understanding of the pathogenesis and clinical manifestations of CF by identifying co-diagnoses of asthma, chronic nasal congestion, cough, middle ear disease, and pneumonia as factors that differentiate patients with poor health outcomes from those with better health outcomes. We conclude by discussing our preliminary findings in relation to other published work, the strengths and limitations of our approach, and our future directions

Clinical Data: Sources and Types, Regulatory Constraints, Applications.

Access to clinical data is critical for the advancement of translational research. However, the numerous regulations and policies that surround the use of clinical data, although critical to ensure patient privacy and protect against misuse, often present challenges to data access and sharing. In this article, we provide an overview of clinical data types and associated regulatory constraints and inferential limitations. We highlight several novel approaches that our team has developed for openly exposing clinical data

Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery.

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies