| Title: | Multimorbidity trajectories and their sex-specific impacts on risk of mortality and re-hospitalisation |
| Journal: | Scientific Reports |
| Published: | 7 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41794875/ |
| DOI: | https://doi.org/10.1038/s41598-026-41806-7 |
| URL: | http://dx.doi.org/10.1038/s41598-026-41806-7 |
Publication 17456
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Abstract
The clinical presentation of disease is complicated by multimorbidity, underscoring the need to clarify its effects and identify intervention targets. Using whole UK Biobank hospital inpatient data, we performed the first comprehensive, sex-stratified analysis of age- and morbidity-adjusted mortality and re-hospitalisation outcomes of multimorbidity accrual, both total and specific historical diagnoses, for a range of presenting diagnoses. One-year mortality and re-hospitalisation risks associated with the presenting total accrued multimorbidity of an individual varied markedly with the presenting diagnosis, ranging from no effect to a 1.58-fold increase per diagnosis, highlighting strong context-dependent risks of multimorbidity accrual. Sex disparities in these context-dependent effects were greater for re-hospitalisation than mortality risk. Identification and risk-modelling of non-random trajectories of specific diagnoses revealed especially high-risk multimorbidity (1.16-16.18 fold resultant increases in 1-year mortality/re-hospitalisation) with predictable orders of presentation, suggesting potential points of focused intervention. Notably, a history of diagnosed substance use in males markedly amplified mortality and re-hospitalisation rates, particularly in presentations of anaemias and infections, as did cardiometabolic histories in men presenting with certain digestive diseases.</p>
6 Authors
- Matthew Ennis
- Paula L. McClean
- Priyank Shukla
- Joanna L. Sharman
- Ramneek Gupta
- Steven Watterson
1 Application
| Application ID | Title |
|---|---|
| 48433 | Computational analyses of genotypic and phenotypic data with treatment response from patients with multimorbidity and the role of inflammation as a driver of multimorbidity. |
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