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      Analgesic effect of oral ibuprofen 400, 600, and 800 mg; paracetamol 500 and 1000 mg; and paracetamol 1000 mg plus 60 mg codeine in acute postoperative pain: a single-dose, randomized, placebo-controlled, and double-blind study

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          Abstract

          Purpose

          Effect size estimates of analgesic drugs can be misleading. Ibuprofen (400 mg, 600 mg, 800 mg), paracetamol (1000 mg, 500 mg), paracetamol 1000 mg/codeine 60 mg, and placebo were investigated to establish the multidimensional pharmacodynamic profiles of each drug on acute pain with calculated effect size estimates.

          Methods

          A randomized, double-blind, single-dose, placebo-controlled, parallel-group, single-centre, outpatient, and single-dose study used 350 patients (mean age 25 year, range 18 to 30 years) of homogenous ethnicity after third molar surgery. Primary outcome was sum pain intensity over 6 h. Secondary outcomes were time to analgesic onset, duration of analgesia, time to rescue drug intake, number of patients taking rescue drug, sum pain intensity difference, maximum pain intensity difference, time to maximum pain intensity difference, number needed to treat values, adverse effects, overall drug assessment as patient-reported outcome measure (PROM), and the effect size estimates NNT and NNTp.

          Results

          Ibuprofen doses above 400 mg do not significantly increase analgesic effect. Paracetamol has a very flat analgesic dose–response profile. Paracetamol 1000/codeine 60 mg gives similar analgesia as ibuprofen from 400 mg, but has a shorter time to analgesic onset. Active drugs show no significant difference in maximal analgesic effect. Other secondary outcomes support these findings. The frequencies of adverse effects were low, mild to moderate in all active groups. NNT and NTTp values did not coincide well with PROMs.

          Conclusion

          Ibuprofen doses above 400 mg for acute pain offer limited analgesic gain. Paracetamol 1000 mg/codeine 60 mg is comparable to ibuprofen doses from 400 mg. Calculated effect size estimates and PROM in our study seem not to relate well as clinical analgesic efficacy estimators.

          Trial registration

          NCT00699114.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00228-021-03231-9.

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          Most cited references31

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          Pain: a review of three commonly used pain rating scales.

          This review aims to explore the research available relating to three commonly used pain rating scales, the Visual Analogue Scale, the Verbal Rating Scale and the Numerical Rating Scale. The review provides information needed to understand the main properties of the scales. Data generated from pain-rating scales can be easily misunderstood. This review can help clinicians to understand the main features of these tools and thus use them effectively. A MedLine review via PubMed was carried out with no restriction of age of papers retrieved. Papers were examined for methodological soundness before being included. The search terms initially included pain rating scales, pain measurement, Visual Analogue Scale, VAS, Verbal Rating Scale, VRS, Numerical/numeric Rating Scale, NRS. The reference lists of retrieved articles were used to generate more papers and search terms. Only English Language papers were examined. All three pain-rating scales are valid, reliable and appropriate for use in clinical practice, although the Visual Analogue Scale has more practical difficulties than the Verbal Rating Scale or the Numerical Rating Scale. For general purposes the Numerical Rating Scale has good sensitivity and generates data that can be statistically analysed for audit purposes. Patients who seek a sensitive pain-rating scale would probably choose this one. For simplicity patients prefer the Verbal Rating Scale, but it lacks sensitivity and the data it produces can be misunderstood. In order to use pain-rating scales well clinicians need to appreciate the potential for error within the tools, and the potential they have to provide the required information. Interpretation of the data from a pain-rating scale is not as straightforward as it might first appear.
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            Ethnic differences in pain and pain management.

            Considerable evidence demonstrates substantial ethnic disparities in the prevalence, treatment, progression and outcomes of pain-related conditions. Elucidating the mechanisms underlying these group differences is of crucial importance in reducing and eliminating disparities in the pain experience. Over recent years, accumulating evidence has identified a variety of processes, from neurophysiological factors to structural elements of the healthcare system, that may contribute to shaping individual differences in pain. For example, the experience of pain differentially activates stress-related physiological responses across various ethnic groups, members of different ethnic groups appear to use differing coping strategies in managing pain complaints, providers' treatment decisions vary as a function of patient ethnicity and pharmacies in predominantly minority neighborhoods are far less likely to stock potent analgesics. These diverse factors, and others may all play a role in facilitating elevated levels of pain-related suffering among individuals from ethnic minority backgrounds. Here, we present a brief, nonexhaustive review of the recent literature and potential physiological and sociocultural mechanisms underlying these ethnic group disparities in pain outcomes.
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              Power and sample size calculations. A review and computer program.

              Methods of sample size and power calculations are reviewed for the most common study designs. The sample size and power equations for these designs are shown to be special cases of two generic formulae for sample size and power calculations. A computer program is available that can be used for studies with dichotomous, continuous, or survival response measures. The alternative hypotheses of interest may be specified either in terms of differing response rates, means, or survival times, or in terms of relative risks or odds ratios. Studies with dichotomous or continuous outcomes may involve either a matched or independent study design. The program can determine the sample size needed to detect a specified alternative hypothesis with the required power, the power with which a specific alternative hypothesis can be detected with a given sample size, or the specific alternative hypotheses that can be detected with a given power and sample size. The program can generate help messages on request that facilitate the use of this software. It writes a log file of all calculated estimates and can produce an output file for plotting power curves. It is written in FORTRAN-77 and is in the public domain.
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                Author and article information

                Contributors
                gaute.lyngstad@odont.uio.no
                laskoglund@icloud.com
                Journal
                Eur J Clin Pharmacol
                Eur J Clin Pharmacol
                European Journal of Clinical Pharmacology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0031-6970
                1432-1041
                16 October 2021
                16 October 2021
                2021
                : 77
                : 12
                : 1843-1852
                Affiliations
                [1 ]GRID grid.5510.1, ISNI 0000 0004 1936 8921, Section of Dental Pharmacology and Pharmacotherapy, Institute of Clinical Dentistry, Faculty of Dentistry, , University of Oslo, ; Blindern, P. O. Box 1119, N-0317 Nydalen Oslo, Norway
                [2 ]GRID grid.55325.34, ISNI 0000 0004 0389 8485, Department of Maxillofacial Surgery, , Oslo University Hospital, ; P. O. Box 4950, Nydalen N-0424 Oslo, Norway
                [3 ]GRID grid.55325.34, ISNI 0000 0004 0389 8485, Oslo Centre for Biostatistics and Epidemiology, , Oslo University Hospital, ; Blindern, P.O. Box 1122, N-0317 Oslo, Norway
                Author information
                http://orcid.org/0000-0003-1863-2738
                http://orcid.org/0000-0002-5193-7827
                http://orcid.org/0000-0003-3174-1656
                http://orcid.org/0000-0003-3169-3287
                Article
                3231
                10.1007/s00228-021-03231-9
                8585829
                34655316
                bd25fd3b-528f-48ac-9a80-25ad209a0881
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 June 2021
                : 8 October 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100005366, universitetet i oslo;
                Funded by: University of Oslo (incl Oslo University Hospital)
                Categories
                Pharmacodynamics
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2021

                Pharmacology & Pharmaceutical medicine
                ibuprofen,paracetamol,codeine,postoperative pain,third molar

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