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Background: Opioids are still being prescribed to manage acute postsurgical pain. Unnecessary opioid prescriptions can lead to addiction and death, as unused tablets are easily diverted.

Methods: To determine whether combination nonopioid analgesics are at least as good as opioid analgesics, a multisite, double-blind, randomized, stratified, noninferiority comparative effectiveness trial was conducted, which examined patient-centered outcomes after impacted mandibular third-molar extraction surgery.

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Background: Patellar instability is frequently encountered by orthopaedic surgeons. One of the major risk factors of this condition is underlying trochlear dysplasia (TD). Recent trends have indicated the use of multiple procedures to correct patellar instability under these conditions.

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Background: Many studies have examined the prevalence of acetabular version (AV) and femoral version (FV) abnormalities and their effect on patient-reported outcomes (PROs) after hip arthroscopy for femoroacetabular impingement syndrome (FAIS), but few have explored the prevalence and influence of combined version (CV) abnormalities.

Purpose: To (1) describe the distribution of AV, FV, and CV in the largest cohort to date and (2) determine the relationship between AV, FV, and CV and PROs after hip arthroscopy for FAIS.

Study Design: Cohort study; Level of evidence, 3.

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Background: Early neurological deterioration (END) is associated with a poor prognosis in acute ischemic stroke (AIS). Effectively lowering low-density lipoprotein cholesterol (LDL-C) can improve the stability of atherosclerotic plaque and reduce post-stroke inflammation, which may be an effective means to lower the incidence of END. The objective of this study was to determine the preventive effects of evolocumab on END in patients with non-cardiogenic AIS.

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Cognitive load stimulates neural activity, essential for understanding the brain's response to stress-inducing stimuli or mental strain. This study examines the feasibility of evaluating cognitive load by extracting, selection, and classifying features from electroencephalogram (EEG) signals. We employed robust local mean decomposition (R-LMD) to decompose EEG data from each channel, recorded over a four-second period, into five modes.

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