Ashley Akbari

Bio: Ashley Akbari is an academic researcher from Swansea University. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 18, co-authored 112 publications receiving 1233 citations. Previous affiliations of Ashley Akbari include National Institute for Health Research.

First-dose ChAdOx1 and BNT162b2 COVID-19 vaccines and thrombocytopenic, thromboembolic and hemorrhagic events in Scotland.

Abstract: Reports of ChAdOx1 vaccine–associated thrombocytopenia and vascular adverse events have led to some countries restricting its use. Using a national prospective cohort, we estimated associations between exposure to first-dose ChAdOx1 or BNT162b2 vaccination and hematological and vascular adverse events using a nested incident-matched case-control study and a confirmatory self-controlled case series (SCCS) analysis. An association was found between ChAdOx1 vaccination and idiopathic thrombocytopenic purpura (ITP) (0–27 d after vaccination; adjusted rate ratio (aRR) = 5.77, 95% confidence interval (CI), 2.41–13.83), with an estimated incidence of 1.13 (0.62–1.63) cases per 100,000 doses. An SCCS analysis confirmed that this was unlikely due to bias (RR = 1.98 (1.29–3.02)). There was also an increased risk for arterial thromboembolic events (aRR = 1.22, 1.12–1.34) 0–27 d after vaccination, with an SCCS RR of 0.97 (0.93–1.02). For hemorrhagic events 0–27 d after vaccination, the aRR was 1.48 (1.12–1.96), with an SCCS RR of 0.95 (0.82–1.11). A first dose of ChAdOx1 was found to be associated with small increased risks of ITP, with suggestive evidence of an increased risk of arterial thromboembolic and hemorrhagic events. The attenuation of effect found in the SCCS analysis means that there is the potential for overestimation of the reported results, which might indicate the presence of some residual confounding or confounding by indication. Public health authorities should inform their jurisdictions of these relatively small increased risks associated with ChAdOx1. No positive associations were seen between BNT162b2 and thrombocytopenic, thromboembolic and hemorrhagic events. New data from the EAVE II cohort in Scotland suggests that a first dose of the ChAdOx1 nCoV-19 vaccine might be associated with a small increase in the risk of idiopathic thrombocytopenic purpura between 0 and 27 d after vaccination.

The incidence of acute pancreatitis: impact of social deprivation, alcohol consumption, seasonal and demographic factors.

Abstract: Background The incidence of acute pancreatitis has increased sharply in many European countries and the USA in recent years.

Hospitalized incidence and case fatality for upper gastrointestinal bleeding from 1999 to 2007: a record linkage study

Abstract: Aliment Pharmacol Ther 2011; 33: 64–76 Summary Background Upper gastrointestinal (GI) bleeding is the most common emergency managed by gastroenterologists. Aim To establish the hospitalized incidence and case fatality for upper GI bleeding, and to determine how they are associated with factors including day of admission, hospital size, social deprivation and distance from hospital. Methods Systematic record linkage of hospital in-patient and mortality data for 24 421 admissions for upper GI bleeding among 22 299 people in Wales from 1999 to 2007. Results The hospitalized incidence of upper GI bleeding was 134 per 100 000. Case fatality was 10.0%. Incidence was stable from 1999 to 2007; case fatality fell from 11.4% in 1999–2000 to 8.6% in 2006–7. Incidence was associated significantly with social deprivation. Compared with weekday admissions, case fatality was 13% higher for weekend admissions and 41% higher for admissions on public holidays. There was little variation in case fatality according to social deprivation, hospital size or distance from hospital. Conclusions Incidence, but not case fatality, was associated significantly with social deprivation. The higher mortality for weekend and public holiday admissions could not be explained by measures of case mix and may indicate a possible impact of reduced staffing levels and delays to endoscopy at weekends in some hospitals.

Review article: the prevalence of Helicobacter pylori and the incidence of gastric cancer across Europe

Abstract: Summary Background There is little up-to-date review evidence on the prevalence of Helicobacter pylori across Europe. Aim To establish regional and national patterns in H. pylori prevalence across Europe. Secondly, to establish trends over time in H. pylori prevalence and gastric cancer incidence and, thirdly, to report on the relationship between H. pylori prevalence and age group across Europe. Methods A review of H. pylori prevalence from unselected surveys of adult or general populations across 35 European countries and four European regions since 1990. Secondly, an analysis of trends over time in H. pylori prevalence and in gastric cancer incidence from cancer registry data. Results Helicobacter pylori prevalence was lower in northern and western Europe than in eastern and southern Europe (P < 0.001). In 11 of 12 European studies that reported on trends, there were sharp reductions in H. pylori prevalence (mean annual reduction = 3.1%). The mean annual reduction in the incidence of gastric cancer across Europe from 1993 to 2007 was 2.1% with little variation regionally across Europe (north 2.2%, west 2.3%, east 1.9% and south 2.0%). Sharp increases in age-related prevalence of H. pylori often levelled off for middle age groups of about 50 years onwards, especially in areas with high prevalence. Conclusions This review shows that H. pylori prevalence is much higher in less affluent regions of Europe and that age-related increases in prevalence are confined to younger age groups in some areas. There were sharp reductions in both H. pylori prevalence and gastric cancer incidence throughout Europe.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Abstract: Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Correlates of protection against symptomatic and asymptomatic SARS-CoV-2 infection.

Abstract: The global supply of COVID-19 vaccines remains limited. An understanding of the immune response that is predictive of protection could facilitate rapid licensure of new vaccines. Data from a randomized efficacy trial of the ChAdOx1 nCoV-19 (AZD1222) vaccine in the United Kingdom was analyzed to determine the antibody levels associated with protection against SARS-CoV-2. Binding and neutralizing antibodies at 28 days after the second dose were measured in infected and noninfected vaccine recipients. Higher levels of all immune markers were correlated with a reduced risk of symptomatic infection. A vaccine efficacy of 80% against symptomatic infection with majority Alpha (B.1.1.7) variant of SARS-CoV-2 was achieved with 264 (95% CI: 108, 806) binding antibody units (BAU)/ml: and 506 (95% CI: 135, not computed (beyond data range) (NC)) BAU/ml for anti-spike and anti-RBD antibodies, and 26 (95% CI: NC, NC) international unit (IU)/ml and 247 (95% CI: 101, NC) normalized neutralization titers (NF50) for pseudovirus and live-virus neutralization, respectively. Immune markers were not correlated with asymptomatic infections at the 5% significance level. These data can be used to bridge to new populations using validated assays, and allow extrapolation of efficacy estimates to new COVID-19 vaccines.