Articles: opioid-analgesics.
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Affective disorders (ADs) are common and have a profound impact on surgical recovery, though few have studied the impact of ADs on inpatient narcotic consumption. The aim of this study was to assess the impact of ADs on inpatient narcotic consumption and healthcare resource utilization in patients undergoing spinal fusion for adult spinal deformity. ⋯ ADs may be associated with increased inpatient opioid consumption and healthcare resource utilization.
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Reg Anesth Pain Med · Feb 2023
Review Meta AnalysisAnalgesic benefits of single-shot versus continuous adductor canal block for total knee arthroplasty: a systemic review and meta-analysis of randomized trials.
Adductor canal block (ACB) can provide important analgesic benefits following total knee arthroplasty (TKA), however, the extent to which these benefits can be enhanced or prolonged by a continuous catheter-based infusion compared with a single-shot injection of local anesthetic is unclear. ⋯ Our results suggest that continuous catheter-based ACB does not enhance or prolong the analgesic benefits when compared with single-shot ACB for TKA over the first 48 hours postoperatively. Overall, the results of our meta-analysis do not support the routine use of continuous ACB for postoperative analgesia after TKA.
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J Clin Monit Comput · Feb 2023
Randomized Controlled TrialPrediction of acute postoperative pain based on intraoperative nociception level (NOL) index values: the impact of machine learning-based analysis.
The relationship between intraoperative nociception and acute postoperative pain is still not well established. The nociception level (NOL) Index (Medasense, Ramat Gan, Israel) uses a multiparametric approach to provide a 0-100 nociception score. The objective of the ancillary analysis of the NOLGYN study was to evaluate the ability of a machine-learning aglorithm to predict moderate to severe acute postoperative pain based on intraoperative NOL values. ⋯ Our results, even if limited by the small number of patients, suggest that acute postoperative pain is better predicted by a multivariate machine-learning algorithm rather than individual intraoperative nociception variables. Further larger multicentric trials are highly recommended to better understand the relationship between intraoperative nociception and acute postoperative pain. Trial registration Registered on ClinicalTrials.gov in October 2018 (NCT03776838).
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The 0 to 10 numeric rating scale of pain intensity is a standard outcome in randomized controlled trials (RCTs) of pain treatments. For individuals taking analgesics, there may be a disparity between "observed" pain intensity (pain intensity with concurrent analgesic use) and pain intensity without concurrent analgesic use (what the numeric rating scale would be had analgesics not been taken). Using a contemporary causal inference framework, we compare analytic methods that can potentially account for concurrent analgesic use, first in statistical simulations, and second in analyses of real (non-simulated) data from an RCT of lumbar epidural steroid injections. ⋯ We propose alternative methods that should be considered in the analysis of pain RCTs. PERSPECTIVE: This article presents the conceptual framework behind a new quantitative pain and analgesia composite outcome, the QPAC1.5, and the results of statistical simulations and analyses of trial data supporting improvements in power and bias using the QPAC1.5. Methods of this type should be considered in the analysis of pain RCTs.
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State policies can impact opioid prescribing or dispensing. Some state opioid policies have been widely examined in empirical studies, including prescription drug monitoring programs and pain clinic licensure requirements. Other relevant policies might exist that have received limited attention. Our objective was to identify and categorize a wide range of state policies that could affect opioid prescribing/dispensing. ⋯ Policy categories within each dimension of opioid prescribing/dispensing laws could become a foundation for creating variables to support empirical analyses of policy effects, improving operationalization of policies in empirical studies, and helping to disentangle the effects of multiple state laws enacted at similar times to address the opioid crisis. Several of the policy categories we identified have been underexplored in previous empirical studies.