Evaluating and communicating hepatitis C cascades of care data in Tayside, Scotland: A journey towards elimination.

Chronic hepatitis C virus (HCV) is one of the leading causes of liver cirrhosis and hepatocellular carcinoma. The WHO 2030 Elimination Goals require each country to evaluate their response to their epidemics. This can be achieved by visualization of cascades of care, depicting how infected cases move through disease control stages. However, methods of displaying data are debated and lack practical application. This project proposes a new way of codifying and displaying HCV data using Tayside as a case study. 1464 cases of active HCV infections in Tayside from 2015 to 2019 were analysed from NHS Tayside's HCV Database. Variables were evaluated to create a systematic coding framework that was then used to code each patient's diagnosis, treatment and cure status each year from 2015 to 2019. Graphical representation of the data in the form of a stacked clustered bar chart demonstrates general trends and conversion rates. For example, Tayside has seen an increase in diagnosis-to-cure rates from 18% to 49% (2015-2019). This method also demonstrates the portion of newly and previously diagnosed people accessing treatment, those with unsuccessful or incomplete treatments, completed treatments with unconfirmed cure, and the number of deaths and relocations. In conclusion, this project proposes a novel way of displaying cascades of care data that relays yearly snapshots of an epidemic, cumulative progression over time, nuanced information of each stage and progression towards elimination targets. This method can be meaningfully used to improve local service planning, knowledge exchange across health systems and reporting to bodies like the WHO.

Hepatitis C reinfection by treatment pathway among people who inject drugs in Tayside, Scotland.

The efficacy of direct-acting antivirals (DAA) provides an excellent opportunity to scale up HCV diagnosis and treatment, achieving the WHO target of HCV elimination by 2030. However, HCV reinfection among people who inject drugs (PWID) remains a concern and may impede elimination efforts. We assessed reinfection rates among PWID across six specialized treatment pathways, following DAA-based and interferon-based therapies in Tayside, Scotland. Data were collected retrospectively for every treatment episode that resulted in a sustained viral response (SVR) after undergoing treatment. Reinfection rates were calculated for each treatment pathway: hospital outpatient clinic; community pharmacy; drug treatment outreach; prison clinic; nurse-led outreach clinic; and injection equipment provision site. Reinfection is defined as a positive RNA test result after SVR. Incidences of reinfection are expressed in 100 person-years (PYs). In total, 916 treatment episodes met selection criteria. Of these, 100 reinfections were identified, generating an overall reinfection rate of 5.27 per 100 PYs (95%CI: 4.36-6.38). The hospital outpatient clinic had the lowest reinfection incidence (1.81 per 100 PYs, 95%CI: 1.11-2.93), with the injection equipment provision site treatment pathway having the highest reinfection incidence (19.89 per 100 PYs, 95%CI: 14.91-26.54). The incidence of reinfection among those treated with interferon-based therapies and those treated with DAA-based therapies was 4.93 per 100 PYs (95%CI: 3.97-6.11) and 7.17 per 100 PYs (95%CI: 4.75-10.82), respectively. Specialized treatment pathways in Tayside yield varying reinfection incidence rates, with different subpopulations of patients at varying risk of reinfection post-SVR. Results suggest that resources should be targeted at the injection equipment provision site pathway in order to reduce the incidence of reinfection and achieve elimination targets. The study found comparable rates of reinfection following interferon-based and DAA-based therapies, providing support for widening access to treatment services.

Hepatitis C diagnosis and treatment, impact on engagement and behaviour of people who inject drugs, a service evaluation, the hooked C project.

There is emerging evidence that Hepatitis C (HCV) treatment engagement is associated with change in drug behaviours and reduced drug-related death rates among people who inject drugs (PWID). The project aims to investigate whether HCV diagnosis and treatment engagement reduces all-cause mortality and drug-related death, and whether any effect is dependent on treatment regimen and intensity of engagement with staff. Case-control studies comparing: PWID with active HCV infection (PCR positive) to PWID HCV infected but spontaneously resolved (PCR negative); PCR-positive patients who engaged with treatment services to nonengagers; and patients who received interferon vs direct-acting antiviral (DAA) based treatment. No differences in risk of all-cause mortality or drug-related death between PCR-negative controls and PCR-positive cases were detected. The odds of all-cause mortality was 12.2 times higher in nonengaging persons compared to treatment engaging cases (aOR 12.15, 95% CI 7.03-20.99, P < .001). The odds of a drug-related death were 5.5 times higher in nonengaging persons compared with treatment engaging cases (aOR 5.52, 95% CI 2.67- 11.44, P < .001). No differences in risk of all-cause mortality or drug-related death between interferon-treated cases and DAA-treated controls were detected. HCV treatment engagement is significantly protective against all-cause mortality and drug-related death. This engagement effect is independent of treatment regimen, with the introduction of DAA therapies not increasing risk of drug-related death, suggesting intensity of HCV therapy provider interaction is not an important factor.

Intelligent liver function testing (iLFT): A trial of automated diagnosis and staging of liver disease in primary care.

BACKGROUND & AIMS: Liver function tests (LFTs) are frequently requested blood tests which may indicate liver disease. LFTs are commonly abnormal, the causes of which can be complex and are frequently under investigated. This can lead to missed opportunities to diagnose and treat liver disease at an early stage. We developed an automated investigation algorithm, intelligent liver function testing (iLFT), with the aim of increasing the early diagnosis of liver disease in a cost-effective manner. METHODS: We developed an automated system that further investigated abnormal LFTs on initial testing samples to generate a probable diagnosis and management plan. We integrated this automated investigation algorithm into the laboratory management system, based on minimal diagnostic criteria, liver fibrosis estimation, and reflex testing for causes of liver disease. This algorithm then generated a diagnosis and/or management plan. A stepped-wedged trial design was utilised to compare LFT outcomes in general practices in the 6 months before and after introduction of the iLFT system. Diagnostic outcomes were collated and compared. RESULTS: Of eligible patients with abnormal LFTs, 490 were recruited to the control group and 64 were recruited to the intervention group. The primary diagnostic outcome was based on the general practitioner diagnosis, which agreed with the iLFT diagnosis in 67% of cases. In the iLFT group, the diagnosis of liver disease was increased by 43%. Additionally, there were significant increases in the rates of GP visits after diagnosis and the number of referrals to secondary care in the iLFT group. iLFT was cost-effective with a low initial incremental cost-effectiveness ratio of £284 per correct diagnosis, and a saving to the NHS of £3,216 per patient lifetime. CONCLUSIONS: iLFT increases liver disease diagnoses, improves quality of care, and is highly cost-effective. This can be achieved with minor changes to working practices and exploitation of functionality existing within modern laboratory diagnostics systems. LAY SUMMARY: There is a growing epidemic of advanced liver disease, this could be offset by early detection and management. Checking liver blood tests (LFTs) should be an opportunity to diagnose liver problems, but abnormal results are often incompletely investigated. In this study we were able to substantially increase the diagnostic yield of the abnormal LFTs using the automated intelligent LFT system. With the addition of referral recommendations and management plans, this strategy provides optimum investigation and management of LFTs and is cost saving to the NHS.

Characterizing the structure of mouse behavior using Motion Sequencing.

Spontaneous mouse behavior is composed from repeatedly used modules of movement (e.g., rearing, running or grooming) that are flexibly placed into sequences whose content evolves over time. By identifying behavioral modules and the order in which they are expressed, researchers can gain insight into the effect of drugs, genes, context, sensory stimuli and neural activity on natural behavior. Here we present a protocol for performing Motion Sequencing (MoSeq), an ethologically inspired method that uses three-dimensional machine vision and unsupervised machine learning to decompose spontaneous mouse behavior into a series of elemental modules called 'syllables'. This protocol is based upon a MoSeq pipeline that includes modules for depth video acquisition, data preprocessing and modeling, as well as a standardized set of visualization tools. Users are provided with instructions and code for building a MoSeq imaging rig and acquiring three-dimensional video of spontaneous mouse behavior for submission to the modeling framework; the outputs of this protocol include syllable labels for each frame of the video data as well as summary plots describing how often each syllable was used and how syllables transitioned from one to the other. In addition, we provide instructions for analyzing and visualizing the outputs of keypoint-MoSeq, a recently developed variant of MoSeq that can identify behavioral motifs from keypoints identified from standard (rather than depth) video. This protocol and the accompanying pipeline significantly lower the bar for users without extensive computational ethology experience to adopt this unsupervised, data-driven approach to characterize mouse behavior.

Intelligent Liver Function Testing: Working Smarter to Improve Patient Outcomes in Liver Disease.

Chronic liver disease (CLD) is a significant health problem affecting millions of people worldwide. In Scotland, CLD is a major cause of premature mortality. Liver function tests (LFTs) are a panel of frequently requested blood tests which may indicate liver disease. However, LFTs commonly contain at least one abnormal result, and abnormalities are rarely investigated to the extent recommended by national guidelines. The intelligent Liver Function Testing (iLFT) pathway is a novel, automated system designed to improve early diagnosis of liver disease. Initial abnormal LFT results trigger a cascade of reflexive testing to help identify the cause of any liver dysfunction. Algorithms combine these results with demographic and clinical data (such as patient age, body mass index, and alcohol intake) and fibrosis estimates to produce an electronic diagnosis and management plan. The pilot trial demonstrated that iLFT increased diagnosis of liver disease whilst remaining cost-effective. As such, iLFT has been fully operational across our region (NHS Tayside, Scotland) since August 2018. In the first year, iLFT generated over 2000 diagnoses from 1824 patient samples with an abnormality in the initial LFTs. The majority of these patients could be safely managed in primary care. iLFT allows maximal value to be obtained from liver blood tests across biochemistry, virology, immunology, and hematology with only minor changes to working practices. 'Intelligent', algorithm-led testing pathways break down the barrier between clinical and laboratory medicine and offer solutions to many of the challenges experienced in modern healthcare systems.

Are patients in the IBD clinic at risk of proctitis secondary to sexually transmitted infections?

OBJECTIVE: To gauge the potential risk of sexually transmitted infection (STI) as a cause of proctitis in a cohort of patients with inflammatory bowel disease (IBD) and to gauge whether this cohort could benefit from STI testing in the future. DESIGN: Patients attending the IBD clinic were given an anonymous questionnaire recording demographics, sexual behaviour, rectal symptoms, history of receptive anal intercourse (RAI), STIs and attitudes towards sexual health screening. SETTING: A gastroenterology teaching hospital IBD clinic. PATIENTS: 280 consecutive patients attending a teaching hospital IBD clinic over a consecutive 6-week period. All patients had an endoscopic, radiological and/or histological diagnosis of IBD. RESULTS: 280 questionnaires were distributed and 274 analysed (3 incomplete, 2 not returned, 1 no sexual activity). 167 female (median: 46 years, range 17-81 years) and 107 males. Two males disclosed RAI and were used as a control. Of the 167 females, 96% were heterosexual, 2.4% were same-sex partners and 1.2% were bisexual. 14% had a history of RAI-this group had more previous STIs (40%) versus those with no history RAI (5%) (p<0.0001; relative risk (RR) 13.41). Chronic rectal pain was more frequent in women with RAI (RR 2.4; p≤0.03). No difference in rectal discharge (RR 1.75; p=0.72) or bleeding (p=0.3). CONCLUSIONS: This is the first report of sexual behaviours in a non-genitourinary medicine clinic; giving a unique insight into sexual practices in a cohort of patients with IBD. A past history of STI and RAI can identify risk and we propose testing for those with a history of STI, RAI, men who have sex with men and women aged under 25 years.