Comparison of different nonsteroidal anti-inflammatory drugs for cesarean section: a systematic review and network meta-analysis.

BACKGROUND: Cesarean section is associated with moderate to severe pain and nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly employed. The optimal NSAID, however, has not been elucidated. In this network meta-analysis and systematic review, we compared the influence of control and individual NSAIDs on the indices of analgesia, side effects, and quality of recovery. METHODS: CDSR, CINAHL, CRCT, Embase, LILACS, PubMed, and Web of Science were searched for randomized controlled trials comparing a specific NSAID to either control or another NSAID in elective or emergency cesarean section under general or neuraxial anesthesia. Network plots and league tables were constructed, and the quality of evidence was evaluated with Grading of Recommendations Assessment, Development and Evaluation (GRADE) analysis. RESULTS: We included 47 trials. Cumulative intravenous morphine equivalent consumption at 24 h, the primary outcome, was examined in 1,228 patients and 18 trials, and control was found to be inferior to diclofenac, indomethacin, ketorolac, and tenoxicam (very low quality evidence owing to serious limitations, imprecision, and publication bias). Indomethacin was superior to celecoxib for pain score at rest at 8-12 h and celecoxib + parecoxib, diclofenac, and ketorolac for pain score on movement at 48 h. In regard to the need for and time to rescue analgesia COX-2 inhibitors such as celecoxib were inferior to other NSAIDs. CONCLUSIONS: Our review suggests the presence of minimal differences among the NSAIDs studied. Nonselective NSAIDs may be more effective than selective NSAIDs, and some NSAIDs such as indomethacin might be preferable to other NSAIDs.

Comparison of the International Crowding Measure in Emergency Departments (ICMED) and the National Emergency Department Overcrowding Score (NEDOCS) to measure emergency department crowding: pilot study.

INTRODUCTION: There is uncertainty about the best way to measure emergency department crowding. We have previously developed a consensus-based measure of crowding, the International Crowding Measure in Emergency Departments (ICMED). We aimed to obtain pilot data to evaluate the ability of a shortened form of the ICMED, the sICMED, to predict senior emergency department clinicians' concerns about crowding and danger compared with a very well-studied measure of emergency department crowding, the National Emergency Department Overcrowding Score (NEDOCS). METHODS: We collected real-time observations of the sICMED and NEDOCS and compared these with clinicians' perceptions of crowding and danger on a visual analogue scale. Data were collected in four emergency departments in the East of England. Associations were explored using simple regression, random intercept models and models accounting for correlation between adjacent time points. RESULTS: We conducted 82 h of observation in 10 observation sets. Naive modelling suggested strong associations between sICMED and NEDOCS and clinician perceptions of crowding and danger. Further modelling showed that, due to clustering, the association between sICMED and danger persisted, but the association between these two measures and perception of crowding was no longer statistically significant. CONCLUSIONS: Both sICMED and NEDOCS can be collected easily in a variety of English hospitals. Further studies are required but initial results suggest both scores may have potential use for assessing crowding variation at long timescales, but are less sensitive to hour-by-hour variation. Correlation in time is an important methodological consideration which, if ignored, may lead to erroneous conclusions. Future studies should account for such correlation in both design and analysis.