Managing postoperative pain in adult outpatients: a systematic review and meta-analysis comparing codeine with NSAIDs

BACKGROUND:Analgesics that contain codeine are commonly prescribed for postoperative pain, but it is unclear how they compare with nonopioid alternatives. We sought to compare the effectiveness of codeine and nonsteroidal anti-inflammatory drugs (NSAIDs) for adults who underwent outpatient surgery.METHODS:We conducted a systematic review and meta-analysis of randomized controlled trials comparing codeine and NSAIDs for postoperative pain in outpatient surgery. We searched MEDLINE and Embase from inception to October 2019 for eligible studies. Our primary outcome was the patient pain score, converted to a standard 10-point intensity scale. Our secondary outcomes were patient-reported global assessments and adverse effects. We used random-effects models and grading of recommendations assessment, development and evaluation (GRADE) to assess the quality of evidence.RESULTS:Forty studies, including 102 trial arms and 5116 patients, met inclusion criteria. The studies had low risk of bias and low-to-moderate heterogeneity. Compared with codeine, NSAIDs were associated with better pain scores at 6 hours (weighted mean difference [WMD] 0.93 points, 95% confidence interval [CI] 0.71 to 1.15) and at 12 hours (WMD 0.79, 95% CI 0.38 to 1.19). Stronger NSAID superiority at 6 hours was observed among trials where acetaminophen was coadministered at equivalent doses between groups (WMD 1.18, 95% CI 0.87 to 1.48). NSAIDs were associated with better global assessments at 6 hours (WMD −0.88, 95% CI −1.04 to −0.72) and at 24 hours (WMD −0.67, 95% CI −0.95 to −0.40), and were associated with fewer adverse effects, including bleeding events.INTERPRETATION:We found that adult outpatients report better pain scores, better global assessments and fewer adverse effects when their postoperative pain is treated with NSAIDs than with codeine. Clinicians across all specialties can use this information to improve both pain management and opioid stewardship.

Outpatient surgical procedures are now more common than inpatient procedures, given the development of less invasive techniques, the drive for health care efficiency, and improvements in anesthesia and pain management. ^1–4 Postoperative pain management after outpatient procedures often includes low-potency or low-dose opioids.⁵ Codeine use is widespread in this setting and codeine remains the most commonly prescribed opioid in many countries, including Canada.^6–9 However, its efficacy is variable, its potency is low and its use is associated with risks of severe adverse effects and misuse.¹⁰ Amid the ongoing opioid crisis, management of pain and potential opioid misuse is important across all medical and dental specialties.¹¹Nonsteroidal anti-inflammatory drugs (NSAIDs) are an alternative to low-potency opioids. The potency, effects and toxicity of NSAIDs depend on the degree to which they inhibit cyclooxygenase 1 and 2 activity. Their main adverse effects are gastrointestinal bleeding, renal impairment and myocardial infarction with long-term use.^12–15 Postoperative pain can be effectively managed with NSAIDs, and NSAIDs have been shown to reduce opioid consumption in postoperative patients.¹⁶Given how commonly these medications are used, and the uncertainty in their comparative efficacy and safety, we sought to compare pain and safety outcomes for codeine-based medications and NSAIDs among adults who underwent outpatient surgery through a systematic review and meta-analysis of randomized controlled trials (RCTs).     

The role of oxidative stress and NADPH oxidase in cerebrovascular disease

The study of reactive oxygen species (ROS) and oxidative stress remains a very active area of biological research, particularly in relation to cellular signaling and the role of ROS in disease. In the cerebral circulation, oxidative stress occurs in diverse forms of disease and with aging. Within the vessel wall, ROS produce complex structural and functional changes that have broad implications for regulation of cerebral perfusion and permeability of the blood-brain barrier. These oxidative-stress-induced changes are thought to contribute to the progression of cerebrovascular disease. Here, we highlight recent findings in relation to oxidative stress in the cerebral vasculature, with an emphasis on the emerging role for NADPH oxidases as a source of ROS and the role of ROS in models of disease.     

Role of Nox isoforms in angiotensin II-induced oxidative stress and endothelial dysfunction in brain

Angiotensin II (Ang II) promotes vascular disease through several mechanisms including by producing oxidative stress and endothelial dysfunction. Although multiple potential sources of reactive oxygen species exist, the relative importance of each is unclear, particularly in individual vascular beds. In these experiments, we examined the role of NADPH oxidase (Nox1 and Nox2) in Ang II-induced endothelial dysfunction in the cerebral circulation. Treatment with Ang II (1.4 mg·kg(-1)·day(-1) for 7 days), but not vehicle, increased blood pressure in all groups. In wild-type (WT; C57Bl/6) mice, Ang II reduced dilation of the basilar artery to the endothelium-dependent agonist acetylcholine compared with vehicle but had no effect on responses in Nox2-deficient (Nox2(-/y)) mice. Ang II impaired responses to acetylcholine in Nox1 WT (Nox1(+/y)) and caused a small reduction in responses to acetylcholine in Nox1-deficient (Nox1(-/y)) mice. Ang II did not impair responses to the endothelium-independent agonists nitroprusside or papaverine in either group. In WT mice, Ang II increased basal and phorbol-dibutyrate-stimulated superoxide production in the cerebrovasculature, and these increases were abolished in Nox2(-/y) mice. Overall, these data suggest that Nox2 plays a relatively prominent role in mediating Ang II-induced oxidative stress and cerebral endothelial dysfunction, with a minor role for Nox1.     

Using historical data for bioprocess optimization: modeling wine characteristics using artificial neural networks and archived process information

Optimization of fermentation processes is a difficult task that relies on an understanding of the complex effects of processing inputs on productivity and quality outputs. Because of the complexity of these biological systems, traditional optimization methods utilizing mathematical models and statistically designed experiments are less effective, especially on a production scale. At the same time, information is being collected on a regular basis during the course of normal manufacturing and process development that is rarely fully utilized. We are developing an optimization method in which historical process data is used to train an artificial neural network for correlation of processing inputs and outputs. Subsequently, an optimization routine is used in conjunction with the trained neural network to find optimal processing conditions given the desired product characteristics and any constraints on inputs. Wine processing is being used as a case study for this work. Using data from wine produced in our pilot winery over the past 3 years, we have demonstrated that trained neural networks can be used successfully to predict the yeast-fermentation kinetics, as well as chemical and sensory properties of the finished wine, based solely on the properties of the grapes and the intended processing. To accomplish this, a hybrid neural network training method, Stop Training with Validation (STV), has been developed to find the most desirable neural network architecture and training level. As industrial historical data will not be evenly spaced over the entire possible search space, we have also investigated the ability of the trained neural networks to interpolate and extrapolate with data not used during training. Because a company will utilize its own existing process data for this method, the result of this work will be a general fermentation optimization method that can be applied to fermentation processes to improve quality and productivity.     

Kinetic model for nitrogen-limited wine fermentations.

A physical and mathematical model for wine fermentation kinetics has been developed to predict sugar utilization curves based on experimental data from wine fermentations with various initial nitrogen and sugar concentrations in the juice. The model is based on: (1) yeast cell growth limited by nitrogen; (2) sugar utilization rates and ethanol production rates proportional solely to the number of viable cells; and (3) a death rate for cells proportional to alcohol content. All but one parameter in the model can be estimated from existing data. However, experiments to find this final parameter, a constant describing cell death, indicate that cell death may not be the critical factor in determining fermentation kinetics as cell viability remains significant until sugar utilization has ceased. The model, nevertheless, predicts a transition from normal to sluggish to stuck fermentations as initial nitrogen levels decrease. It also predicts that fermentations with high initial Brix levels may go to completion when supplemented with nitrogen in the form of ammonia. Therefore, we hypothesize that the model is valid but that ethanol causes the yeast cells to become inactive while remaining viable. Experimental verification of the model has been performed using flask-scale experiments. The model has also been used to evaluate the possibility of using nitrogen or viable cell additions to avoid or correct problem (i.e., sluggish or stuck) fermentations.