ArticleScientific reports2021
Characterisation, identification, clustering, and classification of disease.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- A systematic review and meta-analysis of disease clusters in multimorbidity.Nature communications · 2025Pooled it
- Two Blood-based Endotypes Reveal Divergent Clinical Outcomes of Fibrotic Hypersensitivity Pneumonitis.medRxiv : the preprint server for health sciences · 2026Article
- Multimorbidity trajectories and their sex-specific impacts on risk of mortality and re-hospitalisation.Scientific reports · 2026Article
- Tracking Animal Health in Zoos Using Blockchain Technology.Blockchain in healthcare today · 2026Article
- Multimorbidity as a multistage disease process.PNAS nexus · 2026Article
- Differential Distributions: A refined methodology to indirect reference interval estimation by including Patient's health status according to associated ICD-10 codes.Practical laboratory medicine · 2025Article
- Distinct clinical trajectories of gastrointestinal progression among patients with systemic sclerosis.Rheumatology (Oxford, England) · 2025Article
- Revealing Patient Dissatisfaction With Health Care Resource Allocation in Multiple Dimensions Using Large Language Models and the International Classification of Diseases 11th Revision: Aspect-Based Sentiment Analysis.Journal of medical Internet research · 2025Article
- Patient-Specific Variability in Interleukin-6 and Myeloperoxidase Responses in Osteoarthritis: Insights from Synthetic Data and Clustering Analysis.Journal of personalized medicine · 2025Article
- Patients with Non-Specific Complaints in Emergency Departments: A Growing Patient Safety Concern in an Aging Population with Multimorbidity.Healthcare (Basel, Switzerland) · 2024Article
- Recent advances and evolving concepts in Still's disease.Nature reviews. Rheumatology · 2024Review
- Factors influencing vitamin B6 status in domestic cats: age, disease, and body condition score.Scientific reports · 2024Article
- Observational
- A Novel Classification of Endometriosis Based on Clusters of Comorbidities.Biomedicines · 2023Article
- Article
- Epidemiology and risk factors for ovarian cancer.Przeglad menopauzalny = Menopause review · 2023Review
- Gender-specific disease trajectories prior to the onset of COPD allow individualized screening and early intervention.PloS one · 2023Article
- Causal attribution fractions, and the attribution of smoking and BMI to the landscape of disease incidence in UK Biobank.Scientific reports · 2022Article
- Sporadic, late-onset, and multistage diseases.PNAS nexus · 2022Article
- Cross-sectional metabolic subgroups and 10-year follow-up of cardiometabolic multimorbidity in the UK Biobank.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
The importance of quantifying the distribution and determinants of multimorbidity has prompted novel data-driven classifications of disease. Applications have included improved statistical power and refined prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases, with studies using molecular information, age of disease incidence, and sequences of disease onset ("disease trajectories") to classify disease clusters. Here we consider whether easily measured risk factors such as height and BMI can effectively characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for analysis using clinical and epidemiological criteria, and conventional proportional hazards models were used to estimate associations with 12 established risk factors. Several diseases had strongly sex-dependent associations of disease risk with BMI. Importantly, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. These included 10 diseases presently classified as "Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified". Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.