Rofecoxib for dysmenorrhoea: meta-analysis using individual patient data

BACKGROUND: Individual patient meta-analysis to determine the analgesic efficacy and adverse effects of single-dose rofecoxib in primary dysmenorrhoea. METHODS: Individual patient information was available from three randomised, double blind, placebo and active controlled trials of rofecoxib. Data were combined through meta-analysis. Number-needed-to-treat (NNT) for at least 50% pain relief and the proportion of patients who had taken rescue medication over 12 hours were calculated. Information was collected on adverse effects. RESULTS: For single-dose rofecoxib 50 mg compared with placebo, the NNTs (with 95% CI) for at least 50% pain relief were 3.2 (2.4 to 4.5) at six, 3.1 (2.4 to 9.0) at eight, and 3.7 (2.8 to 5.6) at 12 hours. For naproxen sodium 550 mg they were 3.1 (2.4 to 4.4) at six, 3.0 (2.3 to 4.2) at eight, and 3.8 (2.7 to 6.1) at 12 hours. The proportion of patients who needed rescue medication within 12 hours was 27% with rofecoxib 50 mg, 29% with naproxen sodium 550 mg, and 50% with placebo. In the single-dose trial, the proportion of patients reporting any adverse effect was 8% (4/49) with rofecoxib 50 mg, 12% (6/49) with ibuprofen 400 mg, and 6% (3/49) with placebo. In the other two multiple dose trials, the proportion of patients reporting any adverse effect was 23% (42/179) with rofecoxib 50 mg, 24% (45/181) with naproxen sodium 550 mg, and 18% (33/178) with placebo. CONCLUSIONS: Single dose rofecoxib 50 mg provided similar pain relief to naproxen sodium 550 mg over 12 hours. The duration of analgesia with rofecoxib 50 mg was similar to that of naproxen sodium 550 mg. Adverse effects were uncommon suggesting safety in short-term use of rofecoxib and naproxen sodium. Future research should include restriction on daily life and absence from work or school as outcomes

A Randomised Placebo-Controlled Trial of a Traditional Chinese Herbal Formula in the Treatment of Primary Dysmenorrhoea

BACKGROUND: Most traditional Chinese herbal formulas consist of at least four herbs. Four-Agents-Decoction (Si Wu Tang) is a documented eight hundred year old formula containing four herbs and has been widely used to relieve menstrual discomfort in Taiwan. However, no specific effect had been systematically evaluated. We applied Western methodology to assess its effectiveness and safety for primary dysmenorrhoea and to evaluate the compliance and feasibility for a future trial. METHODOLOGY/PRINCIPAL FINDINGS: A randomised, double-blind, placebo-controlled, pilot clinical trial was conducted in an ad hoc clinic setting at a teaching hospital in Taipei, Taiwan. Seventy-eight primary dysmenorrheic young women were enrolled after 326 women with self-reported menstrual discomfort in the Taipei metropolitan area of Taiwan were screened by a questionnaire and subsequently diagnosed by two gynaecologists concurrently with pelvic ultrasonography. A dosage of 15 odorless capsules daily for five days starting from the onset of bleeding or pain was administered. Participants were followed with two to four cycles for an initial washout interval, one to two baseline cycles, three to four treatment cycles, and three follow-up cycles. Study outcome was pain intensity measured by using unmarked horizontal visual analog pain scale in an online daily diary submitted directly by the participants for 5 days starting from the onset of bleeding or pain of each menstrual cycle. Overall-pain was the average pain intensity among days in pain and peak-pain was the maximal single-day pain intensity. At the end of treatment, both the overall-pain and peak-pain decreased in the Four-Agents-Decoction (Si Wu Tang) group and increased in the placebo group; however, the differences between the two groups were not statistically significant. The trends persisted to follow-up phase. Statistically significant differences in both peak-pain and overall-pain appeared in the first follow-up cycle, at which the reduced peak-pain in the Four-Agents-Decoction (Si Wu Tang) group did not differ significantly by treatment length. However, the reduced peak-pain did differ profoundly among women treated for four menstrual cycles (2.69 (2.06) cm, mean (standard deviation), for the 20 women with Four-Agents-Decoction and 4.68 (3.16) for the 22 women with placebo, p = .020.) There was no difference in adverse symptoms between the Four-Agents-Decoction (Si Wu Tang) and placebo groups. CONCLUSION/SIGNIFICANCE: Four-Agents-Decoction (Si Wu Tang) therapy in this pilot post-market clinical trial, while meeting the standards of conventional medicine, showed no statistically significant difference in reducing menstrual pain intensity of primary dysmenorrhoea at the end of treatment. Its use, with our dosage regimen and treatment length, was not associated with adverse reactions. The finding of statistically significant pain-reducing effect in the first follow-up cycle was unexpected and warrants further study. A larger similar trial among primary dysmenorrheic young women with longer treatment phase and multiple batched study products can determine the definitive efficacy of this historically documented formula. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN23374750

Plants in aquatic ecosystems: current trends and future directions

Aquatic plants fulfil a wide range of ecological roles, and make a substantial contribution to the structure, function and service provision of aquatic ecosystems. Given their well-documented importance in aquatic ecosystems, research into aquatic plants continues to blossom. The 14th International Symposium on Aquatic Plants, held in Edinburgh in September 2015, brought together 120 delegates from 28 countries and six continents. This special issue of Hydrobiologia includes a select number of papers on aspects of aquatic plants, covering a wide range of species, systems and issues. In this paper we present an overview of current trends and future directions in aquatic plant research in the early 21st century. Our understanding of aquatic plant biology, the range of scientific issues being addressed and the range of techniques available to researchers have all arguably never been greater; however, substantial challenges exist to the conservation and management of both aquatic plants and the ecosystems in which they are found. The range of countries and continents represented by conference delegates and authors of papers in the special issue illustrate the global relevance of aquatic plant research in the early 21st century but also the many challenges that this burgeoning scientific discipline must address

An open workflow to gain insights about low-likelihood high impact weather events from initialised predictions

Low-likelihood weather events can cause dramatic impacts, especially when they are unprecedented. In 2020, amongst other high impact weather events, UK floods caused more than £300 million damage, prolonged heat over Siberia led to infrastructure failure and permafrost thawing, whilst wildfires ravaged California. Such rare phenomena cannot be studied well from historical records or reanalysis data. One way to improve our awareness is to exploit ensemble prediction systems, which represent large samples of simulated weather events. This ‘UNSEEN’ method has been successfully applied in several scientific studies, but uptake is hindered by large data and processing requirements, and by uncertainty regarding the credibility of the simulations. Here, we provide a a protocol to apply and ensure credibility of UNSEEN for studying low-likelihood high impact weather events globally, including an open workflow based on Copernicus Climate Change Services (C3S) seasonal predictions. Demonstrating the workflow using ECMWF SEAS5, we find that the 2020 March-May Siberian heat wave was predicted by one of the ensemble members; and that the record-shattering August 2020 California-Mexico temperatures were part of a strong increasing trend. However, each of the case studies exposes challenges with respect to the credibility of UNSEEN and the sensitivity of the outcomes to user decisions. We conclude that UNSEEN can provide new insights about low-likelihood weather events when the decisions are transparent, and the challenges and sensitivities are acknowledged. Anticipating plausible low-likelihood extreme events and uncovering unforeseen hazards under a changing climate warrants further research at the science-policy interface to manage high-impacts

Interpreting extreme climate impacts from large ensemble simulations – are they unseen or unrealistic?

Large-ensemble climate model simulations can provide deeper understanding of the characteristics and causes of extreme events than historical observations, due to their larger sample size. However, adequate evaluation of simulated 'unseen' events that are more extreme than those seen in historical records is complicated by observational uncertainties and natural variability. Consequently, conventional evaluation and correction methods cannot determine whether simulations outside observed variability are correct for the right physical reasons. Here, we introduce a three-step procedure to assess the realism of simulated extreme events based on the model properties (step 1), statistical features (step 2), and physical credibility of the extreme events (step 3). We illustrate these steps for a 2000 year Amazon monthly flood ensemble simulated by the global climate model EC-Earth and global hydrological model PCR-GLOBWB. EC-Earth and PCR-GLOBWB are adequate for large-scale catchments like the Amazon, and have simulated 'unseen' monthly floods far outside observed variability. We find that the realism of these simulations cannot be statistically explained. For example, there could be legitimate discrepancies between simulations and observations resulting from infrequent temporal compounding of multiple flood peaks, rarely seen in observations. Physical credibility checks are crucial to assessing their realism and show that the unseen Amazon monthly floods were generated by an unrealistic bias correction of precipitation. We conclude that there is high sensitivity of simulations outside observed variability to the bias correction method, and that physical credibility checks are crucial to understanding what is driving the simulated extreme events. Understanding the driving mechanisms of unseen events may guide future research by uncovering key climate model deficiencies. They may also play a vital role in helping decision makers to anticipate unseen impacts by detecting plausible drivers