Assessing the quality of water quality assessments: An analytical quality control protocol for benthic diatoms

In this paper, the background to the development of an analytical quality control procedure for the Trophic Diatom Index (TDI) is explained, highlighting some of the statistical and taxonomic problems encountered, and going on to demonstrate how the system works in practice. Most diatom-based pollution indices, including the TDI, use changes in the relative proportions of different taxa to indicate changing environmental conditions. The techniques involved are therefore much simpler than those involved in many studies of phytoplankton, for example, where absolute numbers are required

IMPaCT Back study protocol. Implementation of subgrouping for targeted treatment systems for low back pain patients in primary care: a prospective population-based sequential comparison.

BACKGROUND: Prognostic assessment tools to identify subgroups of patients at risk of persistent low back pain who may benefit from targeted treatments have been developed and validated in primary care. The IMPaCT Back study is investigating the effects of introducing and supporting a subgrouping for targeted treatment system in primary care. METHODS/DESIGN: A prospective, population-based, quality improvement study in one Primary Care Trust in England with a before and after design. Phases 1 and 3 collect data on current practice, attitudes and behaviour of health care practitioners, patients' outcomes and health care costs. Phase 2 introduces and supports the subgrouping for targeted treatment system, via a multi-component, quality improvement intervention that includes educational courses and outreach visits led by opinion leaders, audit/feedback, mentoring and organisational support to embed the subgrouping tools within IT and clinical management systems.We aim to recruit 1000 low back pain patients aged 18 years and over consulting 7 GP practices within one Primary Care Trust in England, UK. The study includes GPs in participating practices and physiotherapists in associated services. The primary objective is to determine the effect of the subgrouping for targeted treatment system on back pain related disability and catastrophising at 2 and 6 months, comparing data from phase 1 with phase 3. Key secondary objectives are to determine the impact on: a) GPs' and physiotherapists' attitudes and behaviour regarding low back pain; b) The process of care that patients receive; c) The cost-effectiveness and sustainability of the new clinical system. DISCUSSION: This paper details the rationale, design, methods, planned analysis and operational aspects of the IMPaCT Back study. We aim to determine whether the new subgrouping for targeted treatment system is implemented and sustained in primary care, and evaluate its impact on clinical decision-making, patient outcomes and costs. STUDY REGISTRATION: International Standard Randomised Controlled Trial Number Register ISRCTN55174281.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Matching the outcomes to treatment targets of exercise for low back pain: does it make a difference? Results of secondary analyses from individual patient data of randomised controlled trials and pooling of results across trials in comparative meta-analyses.

OBJECTIVE: To explore whether using a single matched or composite outcome might impact the results of previous randomised controlled trials (RCTs) testing exercise for non-specific low back pain (NSLBP). The first objective was to explore whether a single matched outcome generated a greater standardised mean differences (SMD) when compared to the original unmatched primary outcome SMD. The second objective was to explore whether a composite measure, comprised of matched outcomes, generated a greater SMD when compared to the original primary outcome SMD. DESIGN: We conducted exploratory secondary analyses of data. SETTING: Seven RCTs were included, of which two were based in the USA (University research clinic, Veterans Affairs medical centre) and the UK (primary care clinics, nonmedical centres). One each were based in Norway (clinics), Brazil (primary care), and Japan (outpatient clinics). PARTICIPANTS: The first analysis comprised 1) five RCTs (n=1,033) that used an unmatched primary outcome but included (some) matched outcomes as secondary outcomes, and the second analysis comprised 2) four RCTs (n=864) that included multiple matched outcomes by developing composite outcomes. INTERVENTION: Exercise compared to no exercise. MAIN OUTCOME MEASURES: The composite consisted of standardised averaged matched outcomes. All analyses replicated the RCTs' primary outcome analyses. RESULTS: Of five RCTs, three had greater SMDs with matched outcomes (pooled effect SMD 0.30 (95% CI 0.04, 0.56), p=0.02) compared to an unmatched primary outcome (pooled effect SMD 0.19 (95% CI -0.03, 0.40) p=0.09). Of four composite outcome analyses, three RCTs had greater SMDs in the composite outcome (pooled effect SMD 0.28 (95%CI 0.05, 0.51) p=0.02) compared to the primary outcome (pooled effect SMD 0.24 (95%CI -0.04, 0.53) p=0.10). CONCLUSIONS: These exploratory analyses suggest that using an outcome matched to exercise treatment targets in NSLBP RCTs may produce greater SMDs than an unmatched primary outcome. Composite outcomes could offer a meaningful way of investigating superiority of exercise than single domain outcomes

Models used for case-mix adjustment of patient reported outcome measures (PROMs) in musculoskeletal healthcare: A systematic review of the literature.

BACKGROUND: Case-mix adjustment is an established method to take account of variations across cohorts in baseline patient factors, when comparing health outcomes. Although commonplace, there is a lack of evidence as to the most appropriate case-mix adjustment model to use to enable fair comparisons of PROM data in musculoskeletal services. OBJECTIVES: To conduct a systematic review summarising evidence of the development, validation, and performance of musculoskeletal case-mix adjustment models, and to make recommendations for future methods. DATA SOURCES: Searches included; AMED, CINAHL, EMBASE, HMIC, MEDLINE, and grey literature. ELIGIBILITY CRITERIA: Studies; from January 1992-May 2017, English language, musculoskeletal adult population, developing or validating a case-mix adjustment model, using a relevant PROM, and using patient factors feasible for clinical collection. DATA SYNTHESIS: Two reviewers evaluated selected papers. The CASP Cohort Tool was used to assess quality. RESULTS: Fourteen studies were included; eight US studies on the Focus on Therapeutic Outcomes model (pooled n=546,726 patients (with pre/post treatment data)) and six UK studies related to the UK National PROMs Programme model (pooled n=282,424 patients (with pre/post treatment data)). The majority used retrospective data, restricted to complete datasets. Both US and UK models showed good predictive ability (R2 18-42%). Common model variables were; baseline PROM score, age, sex, comorbidities, symptom duration, and surgical history. Reduced quality scores were mainly due to acceptability of patient recruitment, and completeness and length of patient follow up. CONCLUSION: Significant methodological crossover was found. Further studies are however needed to externally validate and develop models across musculoskeletal settings

Origin of the thiopyrone CTP-431 “unexpectedly” isolated from the marine sponge Cacospongia mycofijiensis

An intriguing hypothesis that latrunculin A, a well-known natural product, might have undergone transformation into the unprecedented thiopyrone CTP-431 upon long-term storage in methanol is advanced. Thus opening of the hemiacetal of latrunculin A, followed by E1CB elimination, and dehydration would give a polyene that could undergo intramolecular Diels-Alder reaction, followed by methanolysis of the thiazolidinone ring and ring closure by intramolecular thiol addition to an enone. Experimental evidence that the novel thiazolidinone to thiopyrone rearrangement can occur is presented.The marine sponge Cacospongia mycofijiensis, found in the ocean surrounding Fiji, is a source of several polyketide natural products with interesting biological properties,1 including the tubulin binding macrolide fijianolide B (also known as laulimalide),2,3 the HIF1 signal inhibitor mycothiazole,4,5 and the macrolide latrunculins (Figure 1).6 The thiazolidinone-containing latruculins are of mixed polyketide synthesis (PKS) and non-ribosomal peptide synthesis (NRPS) origin, and latrunculin A 1 disrupts microfilament assembly to such an extent that it is the most widely used chemical tool to study actin binding

Rationale, design and methods of the Study of Work and Pain (SWAP): a cluster randomised controlled trial testing the addition of a vocational advice service to best current primary care for patients with musculoskeletal pain (ISRCTN 52269669)

Background Musculoskeletal pain is a major contributor to short and long term work absence. Patients seek care from their general practitioner (GP) and yet GPs often feel ill-equipped to deal with work issues. Providing a vocational case management service in primary care, to support patients with musculoskeletal problems to remain at or return to work, is one potential solution but requires robust evaluation to test clinical and cost-effectiveness. Methods/Design This protocol describes a cluster randomised controlled trial, with linked qualitative interviews, to investigate the effect of introducing a vocational advice service into general practice, to provide a structured approach to managing work related issues in primary care patients with musculoskeletal pain who are absent from work or struggling to remain in work. General practices (n = 6) will be randomised to offer best current care or best current care plus a vocational advice service. Adults of working age who are absent from or struggling to remain in work due to a musculoskeletal pain problem will be invited to participate and 330 participants will be recruited. Data collection will be through patient completed questionnaires at baseline, 4 and 12 months. The primary outcome is self-reported work absence at 4 months. Incremental cost-utility analysis will be undertaken to calculate the cost per additional QALY gained and incremental net benefits. A linked interview study will explore the experiences of the vocational advice service from the perspectives of GPs, nurse practitioners (NPs), patients and vocational advisors. Discussion This paper presents the rationale, design, and methods of the Study of Work And Pain (SWAP) trial. The results of this trial will provide evidence to inform primary care practice and guide the development of services to provide support for musculoskeletal pain patients with work-related issues. Trial registration Current Controlled Trials ISRCTN52269669

Prognosis of sciatica and back-related leg pain in primary care: the ATLAS cohort

BACKGROUND CONTEXT: Evidence is lacking on the prognosis and prognostic factors of back-related leg pain and sciatica in patients seeing their primary care physicians. This evidence could guide timely appropriate treatment and referral decisions. PURPOSE: The present study aims to describe the prognosis and prognostic factors in primary care patients with low back-related leg pain and sciatica. STUDY DESIGN: This is a prospective cohort study. PATIENT SAMPLE: The present study included adults visiting their family doctor with back-related leg pain in the United Kingdom. OUTCOME MEASURES: Information about pain, function, psychological, and clinical variables, was collected. Good outcome was defined as 30% or more reduction in disability (Roland-Morris Disability Questionnaire). METHODS: Participants completed the questionnaires, underwent clinical assessments, received a magnetic resonance imaging scan, and were followed-up 12 months later. Mixed-effects logistic regression evaluated the prognostic value of six a priori defined variable sets (leg pain duration, pain intensity, neuropathic pain, psychological factors, clinical examination, and imaging variables). A combined model, including variables from all models, examined independent effects. The National Institute for Health Research funded the study. There are no conflicts of interest. RESULTS: A total of 609 patients were included. At 12 months, 55% of patients improved in both the total sample and the sciatica group. For the whole cohort, longer leg pain duration (odds ratio [OR] 0.41; confidence interval [CI] 0.19-0.90), higher identity score (OR 0.70; CI 0.53-0.93), and patient's belief that the problem will last a long time (OR 0.27; CI 0.13-0.57) were the strongest independent prognostic factors negatively associated with improvement. These last two factors were similarly negatively associated with improvement in the sciatica subgroup. CONCLUSIONS: The present study provides new evidence on the prognosis and prognostic factors of back-related leg pain and sciatica in primary care. Just over half of patients improved at 12 months. Patient's belief of recovery timescale and number of other symptoms attributed to the pain are independent prognostic factors. These factors can be used to inform and direct decisions about timing and intensity of available therapeutic options

Assessing the quality of water quality assessments: an analytical quality control protocol for benthic diatoms

Analytical Quality Control (AQC) is becoming increasingly recognised as anessential guarantee of the quality of environmental data. Techniques forassessing the quality of chemical data and some biological data (such aschlorophyll concentration) are well developed and, conceptually, quitestraightforward. Depending upon the system, either a proportion of thesamples are subjected to independent analysis, or samples with knownconcentrations of a determinand are inserted into routine analytical runs.Matching the "observed" and "expected" values is then a relativelystraightforward statistical exercise

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models