Predicting hepatic encephalopathy in patients with cirrhosis: A UK population-based study and validation of risk scores.

BACKGROUND: HE is a common neurologic complication in cirrhosis associated with substantial disease and economic burden. HE symptoms are nonspecific and there are limited ways of identifying patients with cirrhosis at high risk of later developing HE. A risk score was previously developed to identify patients at risk of developing HE in a predominately male US cohort. Here, we evaluated the performance of the HE risk scores in a UK cohort study. METHODS: Health care records from Clinical Practice Research Datalink and linked Hospital Episode Statistics were used to select patients with cirrhosis who were diagnosed with HE, confirmed by a diagnosis code for HE or a rifaximin-α prescription. The index date was the date of incident cirrhosis. The study period was from January 2003 to June 2019. RESULTS: A total of 40,809 patients with cirrhosis were selected in the UK cohort, of whom 59% were male. A total of 1561 patients were diagnosed with HE. Applying the UK cohort to the baseline sensitivity risk cutoff (≥-11) from the US cohort provided a sensitivity of 92% and a negative predictive value of 99%. Within a longitudinal model, applying a sensitivity cutoff of ≥-3 to this cohort gave a sensitivity of 89% and a negative predictive value of 99%. CONCLUSIONS: Using data from the UK, the previously developed HE risk scores were found to be reliable for selecting those most likely to progress to HE in patients with liver cirrhosis. Despite the HE risk scores originally being estimated using the data from a predominately male US cohort, the scores were validated and found to be generalizable to female patients.

Real-world evidence from the first online healthcare analytics platform-Livingstone. Validation of its descriptive epidemiology module.

Incidence and prevalence are key epidemiological determinants characterizing the quantum of a disease. We compared incidence and prevalence estimates derived automatically from the first ever online, essentially real-time, healthcare analytics platform-Livingstone-against findings from comparable peer-reviewed studies in order to validate the descriptive epidemiology module. The source of routine NHS data for Livingstone was the Clinical Practice Research Datalink (CPRD). After applying a general search strategy looking for any disease or condition, 76 relevant studies were first retrieved, of which 10 met pre-specified inclusion and exclusion criteria. Findings reported in these studies were compared with estimates produced automatically by Livingstone. The published reports described elements of the epidemiology of 14 diseases or conditions. Lin's concordance correlation coefficient (CCC) was used to evaluate the concordance between findings from Livingstone and those detailed in the published studies. The concordance of incidence values in the final year reported by each study versus Livingstone was 0.96 (95% CI: 0.89-0.98), whilst for all annual incidence values the concordance was 0.93 (0.91-0.94). For prevalence, concordance for the final annual prevalence reported in each study versus Livingstone was 1.00 (0.99-1.00) and for all reported annual prevalence values, the concordance was 0.93 (0.90-0.95). The concordance between Livingstone and the latest published findings was near perfect for prevalence and substantial for incidence. For the first time, it is now possible to automatically generate reliable descriptive epidemiology from routine health records, and in near-real time. Livingstone provides the first mechanism to rapidly generate standardised, descriptive epidemiology for all clinical events from real world data.

Comorbid diseases and conditions in people with HIV in the UK.

OBJECTIVES: This study aimed to characterize the risk of people living with HIV (PLHIV) in the UK progressing to pre-specified HIV-associated comorbidities, compared with matched, HIV-negative controls. METHODS: Primary and secondary care records from the Clinical Practice Research Datalink (CPRD) and linked Hospital Episode Statistics (HES) were used to identify PLHIV, and a matched cohort from the HIV-negative population. Kaplan Meier curves and Cox proportional hazard models were used to evaluate the risk of developing comorbidities including central nervous system (CNS) disorders, end-stage renal disease, osteoporosis, diabetes, cardiovascular disease (CVD), hypertension, stroke and cancer. RESULTS: A total of 2945 PLHIV were matched to a cohort of 5890 HIV-negative controls. PLHIV demonstrated an increased hazard ratio (HR) for time to development of incident sleep disorders, depression, osteoporosis, stroke, cancer and renal disease when compared with their matched HIV-negative control. The HRs for anxiety, hypertension, diabetes and CVD were not significantly increased. CONCLUSIONS: PLHIV in the UK were at a higher risk of developing a number of comorbid conditions, highlighting the need for regular attendance of health reviews such as the annual health reviews recommended by the British HIV Associations (BHIVA) quality standard for care, which are currently not uniformly conducted.

Evaluation of the epidemiology of peanut allergy in the United Kingdom.

Aims: To describe the epidemiology of peanut allergy (PA) in the UK over the last three decades.Methods: PA patients were identified from the Clinical Practice Research Datalink between 1987 and 2015. Incidence and prevalence of PA were compared between 2000 and 2015. Prevalence and relative risk (RR) of atopic comorbidities, anaphylaxis, adrenaline prescriptions versus matched controls were calculated.Results: Point prevalence of PA in the entire population and those <18 years increased from 31 to 202 and 116 to 635 per 100,000, respectively, between 2000 and 2015. Incidence increased from 8.6 to 18.2 per 100,000. Incidence in 2015 was 105 cases per 100,000 aged 0-4 years versus 13.4 per 100,000 aged 5+ years. Anaphylactic events affected 1.2% of the cases and 0.007% of the controls. The rate of adrenaline prescriptions was 5,910 per 100,000 person-years for PA patients. RRs for asthma, eczema and allergic rhinitis in PA patients versus controls were 4.5 (95% CI 4.2-4.8), 3.2 (3.1-3.4) and 2.6 (2.4-3.0), respectively.Conclusions: The prevalence and incidence of PA increased markedly over the study period. PA was associated with atopic conditions and anaphylaxis. PA patients had increased adrenaline prescriptions.

The Model of Mortality with Incident Cirrhosis (MoMIC) and the model of Long-term Outlook of Mortality in Cirrhosis (LOMiC).

The purpose of this study was to produce two statistical survival models in those with cirrhosis utilising only routine parameters, including non-liver-related clinical factors that influence survival. The first model identified and utilised factors impacting short-term survival to 90-days post incident diagnosis, and a further model characterised factors that impacted survival following this acute phase. Data were from the Clinical Practice Research Datalink linked with Hospital Episode Statistics. Incident cases in patients ≥18 years were identified between 1998 and 2014. Patients that had prior history of cancer or had received liver transplants prior were excluded. Model-1 used a logistic regression model to predict mortality. Model-2 used data from those patients who survived 90 days, and used an extension of the Cox regression model, adjusting for time-dependent covariables. At 90 days, 23% of patients had died. Overall median survival was 3.7 years. Model-1: numerous predictors, prior comorbidities and decompensating events were incorporated. All comorbidities contributed to increased odds of death, with renal disease having the largest adjusted odds ratio (OR = 3.35, 95%CI 2.97-3.77). Model-2: covariables included cumulative admissions for liver disease-related events and admissions for infections. Significant covariates were renal disease (adjusted hazard ratio (HR = 2.89, 2.47-3.38)), elevated bilirubin levels (aHR = 1.38, 1.26-1.51) and low sodium levels (aHR = 2.26, 1.84-2.78). An internal validation demonstrated reliability of both models. In conclusion: two survival models that included parameters commonly recorded in routine clinical practice were generated that reliably forecast the risk of death in patients with cirrhosis: in the acute, post diagnosis phase, and following this critical, 90 day phase. This has implications for practice and helps better forecast the risk of mortality from cirrhosis using routinely recorded parameters without inputs from specialists.