Does knowledge of liver fibrosis affect high-risk drinking behaviour (KLIFAD): an open-label pragmatic feasibility randomised controlled trial

Background

Early identification followed by effective behaviour interventions is pivotal to changing the natural history of alcohol-related liver disease. We examined the feasibility of using transient elastography based advice and alcohol recovery video stories (ARVS) to change drinking behaviour in community alcohol services.

Methods

A feasibility randomised control trial (RCT) was conducted in three community alcohol services. Adults 18+ years presenting with a primary alcohol problem were randomised (1:1) to receive either usual care (control group) or usual care and the KLIFAD Intervention, consisting of advice tailored to liver stiffness measure and access to ARVS (intervention group). Data were collected at baseline and six months. To establish definitive trial feasibility, recruitment and retention rates, study procedure safety and extent of effectiveness were measured (Start date: 02.10.2019, End date: 30.11.2022, ISRCTN.com: 16922410).

Findings

382 service users were screened, 184 were randomised (intervention: 93, control: 91), and baseline data were collected for 128 (intervention: 71, control: 59). Six months follow-up data were available in 87 (intervention: 53, control: 34). Intervention compared to the control group had a longer duration of engagement with services (mean difference 8.6 days SD = 18.4), was more likely to complete the allocated treatment program and reduced or stop drinking (54.9% vs 43.9%) and reduce AUDIT category (71.7% vs 61.8%). There were no reported serious adverse reactions, one intervention group participant reported an increase in AUDIT category.

Interpretation

Integration of transient elastography in community alcohol services is feasible. It may improve engagement with services, retention in clinical trials and supplement the reduction in self-reported alcohol consumption. A definitive RCT is supported.

Funding

National Institute for Health and Care Research (NIHR201146).

Does knowledge of liver fibrosis affect high-risk drinking behaviour (KLIFAD)? protocol for a feasibility randomised controlled trial

INTRODUCTION

Heavy drinkers in contact with alcohol services do not routinely have access to testing to establish the severity of potential liver disease. Transient elastography by FibroScan can provide this information. A recent systematic review suggested providing feedback to patients based on markers of liver injury can be an effective way to reduce harmful alcohol intake. This randomised control trial (RCT) aims to establish the feasibility of conducting a larger national trial to test the effectiveness of FibroScan advice and Alcohol Recovery Video Stories (ARVS) in changing high-risk drinking behaviour in community alcohol services common to UK practice.

METHODS AND ANALYSIS

This feasibility trial consists of three work packages (WP). WP1: To draft a standardised script for FibroScan operators to deliver liver disease-specific advice to eligible participants having FibroScan. WP2: To create a video library of ARVS for use in the feasibility RCT (WP3). WP3: To test the feasibility of the trial design, including the FibroScan script and video stories developed in WP1 and WP2 in a one-to-one individual randomised trial in community alcohol services. Semi-structured interviews will be conducted at 6 months follow-up for qualitative evaluation. Outcomes will be measures of the feasibility of conducting a larger RCT. These outcomes will relate to: participant recruitment and follow-up, intervention delivery, including the use of the Knowledge of LIver Fibrosis Affects Drinking trial FibroScan scripts and videos, clinical outcomes, and the acceptability and experience of the intervention and trial-related procedures. Data analysis will primarily be descriptive to address the feasibility aims of the trial. All proposed analyses will be documented in a Statistical Analysis Plan.

ETHICS AND DISSEMINATION

This trial received favourable ethical approval from the West of Scotland Research Ethics Service (WoSRES) on 20 January 2021, REC reference: 20/WS/0179. Results will be submitted for publication to a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ISRCTN16922410.

Younger people with rheumatoid arthritis are at increased risk of fracture even before age 50 years: a population-based cohort study

Less is known about the risk of fracture in people with rheumatoid arthritis aged under 50 than those in older age groups. The study shows that the risk of fracture before age 50 remains significantly higher in those with rheumatoid arthritis than matched controls. This has implications for fracture risk management.

INTRODUCTION

To determine the risk of first and subsequent fracture occurring before age 50 in people diagnosed with rheumatoid arthritis (RA) before age 50.

METHODS

A retrospective observational cohort study of RA cases with matched controls using data from Clinical Practice Research Datalink (CPRD) of adults ≥ 18 years with diagnosis of RA recorded from 1992 to 2016 in the UK. Patients were followed from index date to the first fracture and subsequent fracture. A total of 36,858 cases were each matched to 3 controls. Incidence rates (IR) and incidence rate ratios (IRR) of first and subsequent fractures were calculated. A multivariate Cox's proportional hazards model was used to calculate the risk of first fracture and of subsequent fracture in the presence of different risk factors.

RESULTS

The IR of first and subsequent fractures at any age is significantly higher in cases than controls for patients with onset of RA at any age. This includes first fractures occurring before age 50 for those diagnosed with RA before this age. In women, the rate of first fracture before age 50 are significantly higher than matched controls (IRR 1.29 CI 1.12-1.49), the IRR for subsequent fracture is higher but not significantly so. For men, the IRRs of first and subsequent fractures below age 50 are also higher but not significantly so. Gender, previous fracture, glucocorticoid prescription, osteoporosis diagnosis, alcohol, smoking, and bisphosphonate prescription have a significant effect on the risk of first fracture at any age for RA patients; all these variables except osteoporosis diagnosis and alcohol have a significant effect on the risk of subsequent fracture and first fractures before age 50.

CONCLUSIONS

These results indicate an increased risk of first fracture before age 50 in people with RA diagnosed before this age. It is important that patients with RA of all ages are given timely support from the time of diagnosis to protect their bone health.

Systematic review with meta-analysis: high mortality in patients with non-severe alcoholic hepatitis

BACKGROUND

Alcoholic hepatitis is a serious complication of alcohol misuse. Severe alcoholic hepatitis with its high mortality, has been investigated in detail but 'nonsevere alcoholic hepatitis' is poorly characterised. Survival of this group of patients is unknown.

AIM

To conduct a systematic review and meta-analysis to determine 28-day, 90-day and 1-year mortality of patients with nonsevere alcoholic hepatitis.

METHODS

The protocol was registered on the PROSPERO database (CRD42018107451). Embase, Medline and Cochrane Central databases were searched until July 2018. All study designs reporting mortality rates in patients with nonsevere alcoholic hepatitis were eligible. Mortality data were extracted and meta-analysis performed using a random effects model. Risk of bias was assessed by Cochrane risk of bias or National Institutes of Health quality assessment tool for case series studies.

RESULTS

Twenty-five studies (n = 1372 patients; 12 prospective) met criteria. Nonsevere was variably defined based on bilirubin, prothrombin time, and creatinine. Twenty-eight day mortality (17 studies; n = 993) was 6% (95% CI 3%-9%; I2  = 67.3%; P < 0.001), 90-day mortality (15 studies; n = 755) was 7% (4%-11%, I2  = 64.2%; P < 0.001) and 1-year mortality (five studies; n = 234) was 13% (4%-24%; I2  = 72%; P = 0.006). Subgroup analyses by method of diagnosis (histological vs clinical) or study design (prospective vs retrospective) did not reveal differences in mortality.

CONCLUSION

Nonsevere alcoholic hepatitis is not benign with 6% and 13% 28-day and 1-year mortality, respectively. This systematic review demonstrates the paucity of high quality studies in patients with nonsevere alcoholic hepatitis. Our analysis suggests that patients who do not meet criteria for severe alcoholic hepatitis are an important and hitherto overlooked clinical group. Full characterisation of clinical outcome and development of treatment strategies to reduce mortality in this group is a priority.

Paediatric traumatic cardiac arrest: a Delphi study to establish consensus on definition and management

AIMS

Paediatric traumatic cardiac arrest (TCA) is associated with low survival and poor outcomes. The mechanisms that underlie TCA are different from medical cardiac arrest; the approach to treatment of TCA may therefore also need to differ to optimise outcomes. The aim of this study was to explore the opinion of subject matter experts regarding the diagnosis and treatment of paediatric TCA, and to reach consensus on how best to manage this group of patients.

METHODS

An online Delphi study was conducted over three rounds, with the aim of achieving consensus (defined as 70% agreement) on statements related to the diagnosis and management of paediatric TCA. Participants were invited from paediatric and adult emergency medicine, paediatric anaesthetics, paediatric ICU and paediatric surgery, as well as Paediatric Major Trauma Centre leads and representatives from the Resuscitation Council UK. Statements were informed by literature reviews and were based on elements of APLS resuscitation algorithms as well as some concepts used in the management of adult TCA; they ranged from confirmation of cardiac arrest to the indications for thoracotomy.

RESULTS

73 experts completed all three rounds between June and November 2016. Consensus was reached on 14 statements regarding the diagnosis and management of paediatric TCA; oxygenation and ventilatory support, along with rapid volume replacement with warmed blood, improve survival. The duration of cardiac arrest and the lack of a response to intervention, along with cardiac standstill on ultrasound, help to guide the decision to terminate resuscitation.

CONCLUSION

This study has given a consensus-based framework to guide protocol development in the management of paediatric TCA, though further work is required in other key areas including its acceptability to clinicians.

A pre-post intervention study of pulmonary rehabilitation for adults with post-tuberculosis lung disease in Uganda

Setting

The study was conducted at Mulago Hospital, Kampala, Uganda.

Objective

As chronic respiratory disease (CRD) is a huge, growing burden in Africa, with few available treatments, we aimed to design and evaluate a culturally appropriate pulmonary rehabilitation (PR) program in Uganda for people with post-tuberculosis lung disorder (p-TBLD).

Design

In a pre–post intervention study, a 6-week, twice-weekly PR program was designed for people with p-TBLD. Outcome measures included recruitment, retention, the Clinical COPD Questionnaire (CCQ), tests of exercise capacity, and biometrics. Given this was a developmental study, no formal statistical significance testing was undertaken.

Results

In all, 34 participants started PR and 29 (85%) completed all data collection. The mean age of the 29 participants was 45 years, and 52% were female. The mean (95% confidence interval) CCQ score at baseline was 1.8 (1.5, 2.0), at the end of PR was 1.0 (0.8, 1.2), and at 6 weeks after the end of PR was 0.8 (0.7, 1.0). The Incremental Shuttle Walking Test (ISWT) was 299 m (268.5, 329.4) at baseline, 377 (339.6, 413.8) at the end of PR, and 374 (334.2, 413.5) at 6 weeks after the end of PR. Improvements were seen in measures of chest pain; 13/29 (45%) participants reported chest pain at baseline but only 7/29 (24%) at the end of PR, and in those with persistent pain, the mean pain scores decreased. Mild hemoptysis was reported in 4/29 (17%) participants at baseline and in 2/29 (7%) at the end of PR.

Conclusion

PR for people with p-TBLD in Uganda was feasible and associated with clinically important improvements in quality of life, exercise capacity, and respiratory outcomes. PR uses local resources, requires little investment, and offers a new, sustainable therapy for p-TBLD in resource-limited settings. With the rising global burden of CRD, further studies are needed to assess the value of PR in p-TBLD and other prevalent forms of CRD.

Development and validation of a novel bioassay to determine glucocorticoid sensitivity

Background

Glucocorticoids (GCs) remain the first line treatment for almost all non-infectious inflammatory diseases, ranging from acute asthma to rheumatoid arthritis. However, across all conditions, patients have a variable response to GCs with approximately 30% being non-responders. This group of GC resistant patients is typically exposed to high-dose GCs and their side-effects before more appropriate immunotherapy is instituted. Hence, there is a pressing clinical need for a predictive biomarker of GC responsiveness. The availability of such a tool would also enable patient stratification for the conduct of smart clinical trials in GC resistance. Lymphocyte GC sensitivity has been shown to be closely associated with clinical GC sensitivity in a number of inflammatory diseases. However, the method for determining in vitro GC response is not standardized and requires the use of specialist equipment, including a radioisotope to quantify cellular proliferation, making it challenging to translate into clinical practice.

Results

Here we describe the optimization and validation of a novel non-radioactive in vitro bioassay based on measuring cellular proliferation by incorporation of bromodeoxyuridine (BrdU), termed the BrdU incorporation in lymphocyte steroid sensitivity assay (BLISS). In comparison to the current gold standard lymphocyte GC sensitivity assay in 101 healthy control samples, BLISS has an area under receiver operating characteristic of 0.82 and a sensitivity of 83% for correctly identifying GC resistant subjects.

Conclusions

The performance of the novel BLISS bioassay makes it a strong candidate biomarker for clinical application. It now requires validation in a prospective patient cohort.

Electronic supplementary material

The online version of this article (doi:10.1186/s40364-016-0079-y) contains supplementary material, which is available to authorized users.

Comparison of Statistical Algorithms for the Detection of Infectious Disease Outbreaks in Large Multiple Surveillance Systems

A large-scale multiple surveillance system for infectious disease outbreaks has been in operation in England and Wales since the early 1990s. Changes to the statistical algorithm at the heart of the system were proposed and the purpose of this paper is to compare two new algorithms with the original algorithm. Test data to evaluate performance are created from weekly counts of the number of cases of each of more than 2000 diseases over a twenty-year period. The time series of each disease is separated into one series giving the baseline (background) disease incidence and a second series giving disease outbreaks. One series is shifted forward by twelve months and the two are then recombined, giving a realistic series in which it is known where outbreaks have been added. The metrics used to evaluate performance include a scoring rule that appropriately balances sensitivity against specificity and is sensitive to variation in probabilities near 1. In the context of disease surveillance, a scoring rule can be adapted to reflect the size of outbreaks and this was done. Results indicate that the two new algorithms are comparable to each other and better than the algorithm they were designed to replace.

Statistical Models for Biosurveillance of Multiple Organisms

Objective

To look at the diversity of the patterns displayed by a range of organisms, and to seek a simple family of models that adequately describes all organisms, rather than a well-fitting model for any particular organism.

Introduction

There has been much research on statistical methods of prospective outbreak detection that are aimed at identifying unusual clusters of one syndrome or disease, and some work on multivariate surveillance methods (1). In England and Wales, automated laboratory surveillance of infectious diseases has been undertaken since the early 1990’s. The statistical methodology of this automated system is described in (2). However, there has been little research on outbreak detection methods that are suited to large, multiple surveillance systems involving thousands of different organisms.

Methods

We obtained twenty years’ data on weekly counts of all infectious disease organisms reported to the UK’s Health Protection Agency. We summarized the mean frequencies, trends and seasonality of each organism using log-linear models. To identify a simple family of models which adequately represents all organisms, the Poisson model, the quasi-Poisson model and the negative binomial model were investigated (3,4). Formal goodness-of-fit tests were not used as they can be unreliable with sparse data. Adequacy of the models was empirically studied using the relationships between the mean, variance and skewness. For this purpose, each data series was first subdivided into 41 half-years and de-seasonalized.

Results

Trends and seasonality were summarized by plotting the distribution of estimated linear trend parameters for 2250 organisms, and modal seasonal period for 2254 organisms, including those organisms for which the seasonal effect is statistically significant.

Relationships between mean and variance were summarized as given in Figure 1.

Similar plots were used to summarize the relationships between mean and skewness.

Conclusions

Statistical outbreak detection models must be able to cope with seasonality and trends. The data analyses suggest that the great majority of organisms can adequately – though far from perfectly – be represented by a statistical model in which the variance is proportional to the mean, such as the quasi-Poisson or negative binomial models.

Automated biosurveillance data from England and Wales, 1991-2011

Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we analyzed 20 years of data (1991-2011) from a large laboratory surveillance database used for outbreak detection in England and Wales. The data relate to 3,303 distinct types of infectious pathogens, with a frequency range spanning 6 orders of magnitude. Several hundred organism types were reported each week. We describe the diversity of seasonal patterns, trends, artifacts, and extra-Poisson variability to which an effective multiple laboratory-based outbreak detection system must adjust. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms, in the light of the key requirements of such outbreak detection systems, namely, robustness, flexibility, and sensitivity.

An improved algorithm for outbreak detection in multiple surveillance systems

In England and Wales, a large-scale multiple statistical surveillance system for infectious disease outbreaks has been in operation for nearly two decades. This system uses a robust quasi-Poisson regression algorithm to identify abberrances in weekly counts of isolates reported to the Health Protection Agency. In this paper, we review the performance of the system with a view to reducing the number of false reports, while retaining good power to detect genuine outbreaks. We undertook extensive simulations to evaluate the existing system in a range of contrasting scenarios. We suggest several improvements relating to the treatment of trends, seasonality, re-weighting of baselines and error structure. We validate these results by running the existing and proposed new systems in parallel on real data. We find that the new system greatly reduces the number of alarms while maintaining good overall performance and in some instances increasing the sensitivity.