Abstract

Urinary tract infection (UTI) is frequently invoked to explain delirium, confusion, and functional decline in persons with dementia. Yet urine positivity in this population often reflects asymptomatic bacteriuria, colonization, chronic pyuria, contamination, or sampling noise rather than clinically attributable infection. For biomedical informatics and computational diagnostics readers, this narrative review contributes an integrative conceptual bioinformatics framework for probabilistic clinical attribution of suspected UTI in dementia under uncertainty. We formalizes the attribution problem by distinguishing organism detection from a clinically plausible infection-related contribution to neurocognitive decline. The framework integrates clinical, laboratory, biological, and longitudinal data to clarify whether urinary findings are clinically attributable, potentially contributory, incidental, or misleading. As a secondary contribution, we propose a five-layer implementation blueprint comprising clinical phenotype capture, conventional laboratory data, host-response and omics data, computational inference, and decision-support outputs. This architecture is offered as a translational scaffold for future development and validation, not as an established diagnostic platform. The review also outlines a research agenda for future framework validation and refinement.

Description

Authors retain the copyright of their articles published in the journal. However, authors agree that their articles remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License (http://creativecommons.org/licenses/by/4.0/deed.en_US).

Publisher

Wireilla Scientific Publications

Date of publication

Summer 7-1-2026

Language

english

Persistent identifier

http://hdl.handle.net/10950/5086

Document Type

Article

Publisher Citation

Carpenter, R. E., & Krouse, A. (2026). UTI, delirium, and dementia: A conceptual bioinformatics framework for clinical attribution. International Journal on Bioinformatics & Biosciences, 16(2).

Share

COinS