Amoebiasis is the third-most common cause of mortality worldwide from a parasitic disease. Although the primary etiological agent of amoebiasis is the obligate human parasite Entamoeba histolytica, other members of the genus Entamoeba can infect humans and may be pathogenic. Here, we present the first annotated reference genome for Entamoeba moshkovskii, a species that has been associated with human infections, and compare the genomes of E. moshkovskii, E. histolytica, the human commensal Entamoeba dispar, and the nonhuman pathogen Entamoeba invadens. Gene clustering and phylogenetic analyses show differences in expansion and contraction of families of proteins associated with host or bacterial interactions. They intimate the importance to parasitic Entamoeba species of surface-bound proteins involved in adhesion to extracellular membranes, such as the Gal/GalNAc lectin and members of the BspA and Ariel1 families. Furthermore, E. dispar is the only one of the four species to lack a functional copy of the key virulence factor cysteine protease CP-A5, whereas the gene’s presence in E. moshkovskii is consistent with the species’ potentially pathogenic nature. Entamoeba moshkovskii was found to be more diverse than E. histolytica across all sequence classes. The former is ∼200 times more diverse than latter, with the four E. moshkovskii strains tested having a most recent common ancestor nearly 500 times more ancient than the tested E. histolytica strains. A four-haplotype test indicates that these E. moshkovskii strains are not the same species and should be regarded as a species complex.

ObjectiveTo investigate the frequency of diagnoses seen among new referrals to neurology outpatient services; to understand how these services are used through exploratory analysis of diagnostic tests and follow-up appointments; and to examine the waiting times between referral and appointment.MethodsRoutine data from new National Health Service appointments at a single consultant-delivered clinic between September 2016 and January 2019 were collected. These clinical data were then linked to hospital administrative data. The combined data were assigned diagnostic categories based on working diagnoses to allow further analysis using descriptive statistics.ResultsFive diagnostic categories accounted for 62% of all patients seen within the study period, the most common of which was headache disorders. Following a first appointment, 50% of all patients were offered at least one diagnostic test, and 35% were offered a follow-up appointment, with variation in both measures by diagnostic category. Waiting times from referral to appointment also varied by diagnostic category. 65% of patients with a seizure/epilepsy disorder were seen within the 18-week referral to treatment target, compared with 38% of patients with a movement disorder.ConclusionsA small number of diagnostic categories account for a large proportion of new patients. This information could be used in policy decision-making to describe a minimum subset of categories for diagnostic coding. We found significant differences in waiting times by diagnostic category, as well as tests ordered, and follow-up offered; further investigation could address causes of variation.

Objective: This study provides a framework methodology for identifying GP surgeries with unexpected rates of referral to specialist services, using headache referrals to outpatient neurology as an example. Design: This is a retrospective observational study using routinely collected and open-source data. Setting and participants: Data was collected from a single consultant outpatient neurology clinic and 202 GP surgeries across seven CCGs in the Northwest of England. Primary Outcome: The number of headache referrals from each GP surgery during the study period of three and a quarter years was used as the primary outcome in a generalised linear model. The standardised residuals from this model were then used to identify GP surgeries that were likely to have referred unexpected patient numbers for headaches to an outpatient neurology clinic during the study period. Results: In the model using data from the CCG in which the outpatient neurology clinic is located we identified one GP surgery referring more headache patients than expected. The model showed that the clearest predictor of headache referrals was the number of referrals for other types of neurological disorders. In the model using data from all seven CCGs we identified four GP surgeries with unexpected numbers of referrals. This model showed that there were two predictors of headache referral, namely other neurology referrals and the distance from the clinic. Conclusion: We have developed a flexible methodology for identifying GP surgeries with unexpected numbers of referrals to specialist services. This methodology was demonstrated using headache referrals but could be adapted to any type of referral or geographical area.

ObjectiveTo investigate the frequency of diagnoses seen among new referrals to neurology outpatient services; to understand how these services are used through exploratory analysis of diagnostic tests and follow-up appointments; and to examine the waiting times between referral and appointment.MethodsRoutine data from new NHS appointments at a single consultant-delivered clinic between Sept 2016 and January 2019 were collected. These clinical data were then linked to hospital administrative data. The combined data were assigned diagnostic categories based on working diagnoses to allow further analysis using descriptive statistics.ResultsFive diagnostic categories accounted for 62% of all patients seen within the study period, the most common of which was headache disorders. Following a first appointment, 50% of all patients were offered at least one diagnostic test, and 35% were offered a follow-up appointment, with variation in both measures by diagnostic category. Waiting times from referral to appointment also varied by diagnostic category. 65% of patients with a seizure/epilepsy disorder were seen within the 18 week referral to treatment target, compared to 38% of patients with a movement disorder.ConclusionsA small number of diagnostic categories account for a large proportion of new patients. This information could be used in policy decision making to describe a minimum subset of categories for diagnostic coding. We found significant differences in waiting times by diagnostic category, as well as tests ordered, and follow-up offered; further investigation could address causes of variation.