Evidence of multiple species of Chilodonella (Protozoa, Ciliophora) infecting Australian farmed freshwater fishes

Parasitic Chilodonella species, Chilodonella piscicola and Chilodonella hexasticha, cause considerable economic losses globally to freshwater farmed fish production. Some genetic studies of Chilodonella spp. have indicated that many species within the genus may form cryptic species complexes. To understand the diversity of Chilodonella spp. infecting Australian freshwater farmed fish, specimens were isolated from infected barramundi (Lates calcarifer) and Murray cod (Maccullochella peelii) from fish farms in tropical north Queensland (QLD), temperate Victoria (Vic) and New South Wales (NSW) for genetic and morphological analysis. Parasites were stained and measured for morphological description and comparative phylogenetic analyses were performed using the mitochondrial small subunit (mtSSU) rDNA marker. Morphological analyses revealed four distinct morphotypes of Chilodonella infecting farmed barramundi and Murray Cod. Three putative species were isolated from barramundi (Chilodonella hexasticha, C. acuta and C. uncinata) and one from Murray cod (C. piscicola). However, phylogenetic analyses detected only three distinct genotypes, with the putative C. hexasticha and C. piscicola sharing 100% sequence identity. This suggests that Australian isolates of C. hexasticha and C. piscicola could represent the same species and may exhibit phenotypic plasticity. Further molecular analysis, including isolates from the type localities, should be performed to support or refute the synonymy of these species

Anticholinergic medicines in an older primary care population: A cross-sectional analysis of medicines' levels of anticholinergic activity and clinical indications

WHAT IS KNOWN AND OBJECTIVES: Adverse clinical outcomes have been associated with cumulative anticholinergic burden (to which low-potency as well as high-potency anticholinergic medicines contribute). The clinical indications for which anticholinergic medicines are prescribed (and thus the 'phenotype' of patients with anticholinergic burden) have not been established. We sought to establish the overall prevalence of prescribing of anticholinergic medicines, the prevalence of prescribing of low-, medium- and high-potency anticholinergic medicines, and the clinical indications for which the medicines were prescribed in an older primary care population. METHODS: This was a cross-sectional analysis of a cohort study of Australian early-career general practitioners' (GPs') clinical consultations - the Registrar Clinical Encounters in Training (ReCEnT) study. In ReCEnT, GPs collect detailed data (including medicines prescribed and their clinical indication) for 60 consecutive patients, on up to three occasions 6 months apart. Anticholinergic medicines were categorized as levels 1 (low-potency) to 3 (high-potency) using the Anticholinergic Drug Scale (ADS). RESULTS: During 2010-2014, 879 early-career GPs (across five of Australia's six states) conducted 20 555 consultations with patients aged 65 years or older, representing 35 506 problems/diagnoses. Anticholinergic medicines were prescribed in 10·4% [95% CIs 9·5-10·5] of consultations. Of the total anticholinergic load of prescribed medicines ('community anticholinergic load') 72·7% [95% CIs 71·0-74·3] was contributed by Level 1 medicines, 0·8% [95% CIs 0·5-1·3] by Level 2 medicines and 26·5% [95% CIs 24·8-28·1] by Level 3 medicines. Cardiac (40·0%), Musculoskeletal (16·9%) and Respiratory (10·6%) were the most common indications associated with Level 1 anticholinergic prescription. For Level 2 and 3 medicines (combined data), Psychological (16·1%), Neurological (16·1%), Musculoskeletal (15·7%) and Urological (11·1%) indications were most common. WHAT IS NEW AND CONCLUSION: Anticholinergic medicines are frequently prescribed in Australian general practice, and the majority of the 'community' anticholinergic burden is contributed by 'low'-anticholinergic potency medicines whose anticholinergic effects may be largely 'invisible' to prescribing GPs. Furthermore, the clinical 'phenotype' of the patient with high anticholinergic burden may be very different to common stereotypes (patients with urological, psychological or neurological problems), potentially making recognition of risk of anticholinergic adverse effects additionally problematic for GPs

Protocol for the development of the Wales Multimorbidity e-Cohort (WMC): Data sources and methods to construct a population-based research platform to investigate multimorbidity

Introduction Multimorbidity is widely recognised as the presence of two or more concurrent long-term conditions, yet remains a poorly understood global issue despite increasing in prevalence. We have created the Wales Multimorbidity e-Cohort (WMC) to provide an accessible research ready data asset to further the understanding of multimorbidity. Our objectives are to create a platform to support research which would help to understand prevalence, trajectories and determinants in multimorbidity, characterise clusters that lead to highest burden on individuals and healthcare services, and evaluate and provide new multimorbidity phenotypes and algorithms to the National Health Service and research communities to support prevention, healthcare planning and the management of individuals with multimorbidity. Methods and analysis The WMC has been created and derived from multisourced demographic, administrative and electronic health record data relating to the Welsh population in the Secure Anonymised Information Linkage (SAIL) Databank. The WMC consists of 2.9 million people alive and living in Wales on the 1 January 2000 with follow-up until 31 December 2019, Welsh residency break or death. Published comorbidity indices and phenotype code lists will be used to measure and conceptualise multimorbidity. Study outcomes will include: (1) a description of multimorbidity using published data phenotype algorithms/ontologies, (2) investigation of the associations between baseline demographic factors and multimorbidity, (3) identification of temporal trajectories of clusters of conditions and multimorbidity and (4) investigation of multimorbidity clusters with poor outcomes such as mortality and high healthcare service utilisation. Ethics and dissemination The SAIL Databank independent Information Governance Review Panel has approved this study (SAIL Project: 0911). Study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals