Biomedical subjects

Bruce Guthrie

Publications and source records attributed to Bruce Guthrie.

3 recordsLinked to original sources

PubMed2026

Eligibility of real-world patients for aspirin primary prevention trials in cardiovascular disease.

BACKGROUND: Evidence for the net benefit of aspirin for primary prevention of cardiovascular disease (CVD) is finely balanced, leading to variation in guideline recommendations internationally. External validity of randomised clinical trial (RCT) evidence may therefore be of particular importance. The aim of this study is to characterise real-world patients according to their eligibility for guideline-cited aspirin RCTs for primary CVD prevention. METHODS: Eligibility criteria from 14 RCTs were applied to a linked primary care/hospital discharge dataset of people ≥ 40 years without CVD. Proportions eligible for each trial were calculated, and characteristics of eligible and ineligible patients compared for each trial, including Cox regression analysis of event rates for major adverse cardiovascular events (MACE), major bleeding events, and non-cardiovascular mortality. RESULTS: Of 570,211 included patients (300,500 [52.7%] women, 336,877 [59%] < 60 years), the median proportion ineligible for 14 RCTs was 90.7% (range 42.5-99.4%) and 24.0% of patients were ineligible for all RCTs. On average, trial-ineligible populations were younger (median age trial-ineligible 57.8 vs trial-eligible 62.6 years, p = 0.008) and a lower proportion had hypertension (23.9% vs 50.9%, p = 0.004), diabetes (6.4% vs 11.5%, p = 0.015), or a regular statin prescription (11.8% vs 26.7%, p = 0.001). Trial-ineligible populations had a higher hazard of MACE compared to trial-eligible in four RCTs and lower in ten (hazard ratio [HR] range across all RCTs 0.45 [95%CI 0.40-0.51] to 2.78 [95%CI 2.61-2.96]). Hazards of bleeding events in the trial-ineligible were lower than the trial-eligible in eight RCTs and higher in four (HR range across all RCTs 0.63 [95%CI, 0.59-0.66] to 1.69 [95%CI, 1.53-1.86]), and time-varying hazards of non-CVD death were consistently lower in four RCTs and higher in five (HR range across all RCTs and time points 0.29 [95%CI 0.24-0.36] to 11.42 [95%CI 9.91-13.17]). CONCLUSIONS: Compared with trial-ineligible populations within the same age and sex strata, RCTs recruited people of varying CVD risk but often excluded people at high risk of bleeding or non-CVD death, highlighting that many trials may overestimate the net benefit of aspirin for primary prevention.

Humans↗

PubMed2025

Health conditions in adults with atrial fibrillation compared with the general population: a population-based cross-sectional analysis.

BACKGROUND: Atrial fibrillation (AF) prevalence is rising due to population ageing and comorbidity is an increasing problem. The aim of this study was to examine the prevalence and association of coexisting health conditions among adults with AF in the general population. METHODS: Cross-sectional analysis of Clinical Practice Research Datalink (CPRD) primary care electronic medical records in England linked to hospital admissions as of 30 November 2015. CPRD is broadly representative of the UK general population in terms of age, sex and ethnicity. We estimated prevalence and used logistic regression examining risk factors of age, sex and socioeconomic status (SES) to compare prevalence of 252 physical and mental health conditions and 23 higher level health condition groups in adults with AF compared with adults without AF. RESULTS: 34 338 adults with AF (57% male; 83% ≥65 years) and 907 739 without AF (49% male; 23% ≥65 years) were identified. Adjusted for age and sex, adults with AF were significantly more likely to have 20/23 (87%) health condition groups than adults without AF. The most prevalent health condition groups in adults with AF were cardiovascular (prevalence of 89% in adults with AF vs 26% in adults without AF, adjusted OR (aOR) 5.82, 95% CI 5.60 to 6.05), gastrointestinal (62% vs 37%, aOR 1.34, 95% CI 1.31 to 1.38) and orthopaedic (58% vs 24%, aOR 1.32, 95% CI 1.29 to 1.35). 151/252 individual conditions were significantly more common in adults with AF including cardiovascular conditions such as cardiomyopathy (4.5% vs 0.3%, aOR 9.58, 95% CI 8.88 to 10.35) and heart failure (18% vs 0.7%, aOR 9.07, 95% CI 8.70 to 9.46), and non-cardiovascular conditions such as pleural effusion (16% vs 1.8%, aOR 3.55, 95% CI 3.42 to 3.67) and oesophageal malignancy (0.3% vs 0.0%, aOR 2.14, 95% CI 1.69 to 2.70). Associations were similar after SES adjustment. CONCLUSIONS: While cardiovascular conditions are highly prevalent and strongly associated with AF, a wide spectrum of non-cardiovascular conditions were also strongly associated, requiring a greater understanding of managing comorbid conditions with management principles contradictory to AF.

Humans↗

PubMed2025

A Digital Tool for Clinical Evidence-Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study.

BACKGROUND: Clinical guideline development preferentially relies on evidence from randomized controlled trials (RCTs). RCTs are gold-standard methods to evaluate the efficacy of treatments with the highest internal validity but limited external validity, in the sense that their findings may not always be applicable to or generalizable to clinical populations or population characteristics. The external validity of RCTs for the clinical population is constrained by the lack of tailored epidemiological data analysis designed for this purpose due to data governance, consistency of disease or condition definitions, and reduplicated effort in analysis code. OBJECTIVE: This study aims to develop a digital tool that characterizes the overall population and differences between clinical trial eligible and ineligible populations from the clinical populations of a disease or condition regarding demography (eg, age, gender, ethnicity), comorbidity, coprescription, hospitalization, and mortality. Currently, the process is complex, onerous, and time-consuming, whereas a real-time tool may be used to rapidly inform a guideline developer's judgment about the applicability of evidence. METHODS: The National Institute for Health and Care Excellence-particularly the gout guideline development group-and the Scottish Intercollegiate Guidelines Network guideline developers were consulted to gather their requirements and evidential data needs when developing guidelines. An R Shiny (R Foundation for Statistical Computing) tool was designed and developed using electronic primary health care data linked with hospitalization and mortality data built upon an optimized data architecture. Disclosure control mechanisms were built into the tool to ensure data confidentiality. The tool was deployed within a Trusted Research Environment, allowing only trusted preapproved researchers to conduct analysis. RESULTS: The tool supports 128 chronic health conditions as index conditions and 161 conditions as comorbidities (33 in addition to the 128 index conditions). It enables 2 types of analyses via the graphic interface: overall population and stratified by user-defined eligibility criteria. The analyses produce an overview of statistical tables (eg, age, gender) of the index condition population and, within the overview groupings, produce details on, for example, electronic frailty index, comorbidities, and coprescriptions. The disclosure control mechanism is integral to the tool, limiting tabular counts to meet local governance needs. An exemplary result for gout as an index condition is presented to demonstrate the tool's functionality. Guideline developers from the National Institute for Health and Care Excellence and the Scottish Intercollegiate Guidelines Network provided positive feedback on the tool. CONCLUSIONS: The tool is a proof-of-concept, and the user feedback has demonstrated that this is a step toward computer-interpretable guideline development. Using the digital tool can potentially improve evidence-driven guideline development through the availability of real-world data in real time.

Humans↗