The Leicester, Leicestershire and Rutland quality improvement project and integrated chronic kidney disease system: implementation within a primary care network.

BACKGROUND: The optimisation of patients in primary care is a prime opportunity to manage patient care within the community and reduce the burden of referrals on secondary care. This paper presents a quality improvement clinical programme taking place within an NHS Primary Care Network as part of the wider Leicester Leicestershire Rutland integrated chronic kidney disease programme. METHOD: Patients are optimised to guidelines from the National Institute for Health and Care Excellence, by a primary care clinical team who are supported by nephrology consultants and nephrology pharmacists. Multidisciplinary team meetings take place with secondary care specialists and primary care staff. Learning is passed to the community clinicians for better patient treatment locally. RESULTS: A total of 526 patients were reviewed under this project.The total number of referrals to secondary care which were discharged following first outpatient appointment, reduced from 42.9% to 10%. This reduction of 32.9% represents the optimisation of patient cases through this quality improvement project. Patients can be optimised and managed within the community, reducing the number of unnecessary referrals to secondary care. CONCLUSION: This programme has the potential to offer significant improvement in patient outcomes when expanded to a larger patient base. Medicine management and the use of clinical staff are optimised in both primary and secondary care.

Glitches in Rotating Supersolids.

Glitches, spin-up events in neutron stars, are of prime interest, as they reveal properties of nuclear matter at subnuclear densities. We numerically investigate the glitch mechanism due to vortex unpinning using analogies between neutron stars and dipolar supersolids. We explore the vortex and crystal dynamics during a glitch and its dependence on the supersolid quality, providing a tool to study glitches from different radial depths of a neutron star. Benchmarking our theory against neutron-star observations, our work will open a new avenue for the quantum simulation of stellar objects from Earth.

Genomic characterisation of bioaerosols within livestock facilities: A systematic review.

Livestock facilities are widely regarded as reservoirs of infectious disease, owing to their abundance in particulate matter (PM) and microbial bioaerosols. Over the past decade, bioaerosol studies have increasingly utilised high throughput sequencing (HTS) to achieve superior throughput, taxonomic resolution, and the detection of unculturable organisms. However, the prevailing focus on amplicon sequencing has limited the identification of viruses and microbial taxa at the species-level. Herein, a literature search was conducted to identify methods capable of overcoming the aforementioned limitations. Screening 1531 international publications resulted in 29 eligible for review. Metagenomics capable of providing rich insights were identified in only three instances. Notably, long-read sequencing was not utilised for metagenomics. This review also identified that sample collection methods lack a uniform approach, highlighted by the differences in sampling equipment, flow rates and durations. Further heterogeneity was introduced by the unique sampling conditions, which makes it challenging to ground new findings within the established literature. For instance, winter was associated with increased microbial abundance and antimicrobial resistance, yet less alpha diversity. Researchers implementing metagenomics into the livestock environment should consider season, the microclimate, and livestock growth stage as influential upon their findings. Considering the increasing accessibility of long-read sequencing, future research should explore its viability within a novel uniform testing protocol for bioaerosol emissions.

Heterogeneity in Systematic Reviews of Medical Imaging Diagnostic Test Accuracy Studies: A Systematic Review.

Importance: Systematic reviews of medical imaging diagnostic test accuracy (DTA) studies are affected by between-study heterogeneity due to a range of factors. Failure to appropriately assess the extent and causes of heterogeneity compromises the interpretability of systematic review findings. Objective: To assess how heterogeneity has been examined in medical imaging DTA studies. Evidence Review: The PubMed database was searched for systematic reviews of medical imaging DTA studies that performed a meta-analysis. The search was limited to the 40 journals with highest impact factor in the radiology, nuclear medicine, and medical imaging category in the InCites Journal Citation Reports of 2021 to reach a sample size of 200 to 300 included studies. Descriptive analysis was performed to characterize the imaging modality, target condition, type of meta-analysis model used, strategies for evaluating heterogeneity, and sources of heterogeneity identified. Multivariable logistic regression was performed to assess whether any factors were associated with at least 1 source of heterogeneity being identified in the included meta-analyses. Methodological quality evaluation was not performed. Data analysis occurred from October to December 2022. Findings: A total of 242 meta-analyses involving a median (range) of 987 (119-441 510) patients across a diverse range of disease categories and imaging modalities were included. The extent of heterogeneity was adequately described (ie, whether it was absent, low, moderate, or high) in 220 studies (91%) and was most commonly assessed using the I2 statistic (185 studies [76%]) and forest plots (181 studies [75%]). Heterogeneity was rated as moderate to high in 191 studies (79%). Of all included meta-analyses, 122 (50%) performed subgroup analysis and 87 (36%) performed meta-regression. Of the 242 studies assessed, 189 (78%) included 10 or more primary studies. Of these 189 studies, 60 (32%) did not perform meta-regression or subgroup analysis. Reasons for being unable to investigate sources of heterogeneity included inadequate reporting of primary study characteristics and a low number of included primary studies. Use of meta-regression was associated with identification of at least 1 source of variability (odds ratio, 1.90; 95% CI, 1.11-3.23; P = .02). Conclusions and Relevance: In this systematic review of assessment of heterogeneity in medical imaging DTA meta-analyses, most meta-analyses were impacted by a moderate to high level of heterogeneity, presenting interpretive challenges. These findings suggest that, despite the development and availability of more rigorous statistical models, heterogeneity appeared to be incomplete, inconsistently evaluated, or methodologically questionable in many cases, which lessened the interpretability of the analyses performed; comprehensive heterogeneity assessment should be addressed at the author level by improving personal familiarity with appropriate statistical methodology for assessing heterogeneity and involving biostatisticians and epidemiologists in study design, as well as at the editorial level, by mandating adherence to methodologic standards in primary DTA studies and DTA meta-analyses.

Prevalence of Falciparum and non-Falciparum Malaria in the 2014-15 Rwanda Demographic Health Survey.

Background: Malaria remains a major cause of morbidity in sub-Saharan Africa. Undetected asymptomatic falciparum malaria results in a large transmission reservoir and there is evidence of increasing non-falciparum malaria as malaria is controlled in Africa, both resulting in challenges for malaria control programs. Methods: We performed quantitative real time PCR for 4 malaria species in 4,596 individuals from the 2014-2015 Rwanda Demographic Health Survey. Bivariate models were used to determine species-specific associations with risk factors. Results: Asymptomatic falciparum malaria, P. ovale spp., and P. malariae infection had broad spatial distribution across Rwanda. P. vivax infection was rare. Overall infection prevalence was 23.6% (95%CI [21.7%, 26.0%]), with falciparum and non-falciparum at 17.6% [15.9%, 19.0%] and 8.3% [7.0%, 10.0%], respectively. Parasitemias tended to be low and mixed species infections were common, especially where malaria transmission was the highest. Falciparum infection was associated with socio-econiomic status, rural residence and low altitude. Few risk factors were associated with non-falciparum malaria. Conclusions: Asymptomatic falciparum malaria and non-falciparum malaria are common and widely distributed across Rwanda. Continued molecular monitoring of Plasmodium spp. is needed to monitor these threats to malaria control in Africa.