A Cohort Study of Urinary Tract Infections in People Living with Dementia: Epidemiology and Diagnostic Challenges

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Crone, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7185812/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Urinary tract infections (UTIs) are a leading cause of hospitalisation in people living with dementia (PLWD), making accurate detection and prompt treatment essential in this vulnerable population. Methods This retrospective longitudinal cohort study assessed the concordance between self-reported symptoms, urine colony counts > 10⁵ CFU/mL, dipstick results positive for leukocytes and/or nitrites, and urinary IL-8 levels in identifying UTIs among PLWD. The study included 78 community-dwelling individuals aged over 50 with a confirmed dementia diagnosis, recruited from cohorts established by the Surrey and Borders Partnership NHS Foundation Trust and the Hammersmith & Fulham Partnership Primary Care Network between late 2019 and 2023. Results UTI frequency among PLWD was highly variable, with some individuals experiencing recurrent infections whilst others had none throughout the study period. The microbial taxa identified were consistent with those seen in other populations. There was no clear concordance between self-reported symptoms and laboratory indicators of UTI. However, dipstick-positive results correlated with urine samples showing > 10⁵ CFU/mL of a single colony morphology growth and elevated IL-8 concentrations. Conclusions Urinary dipstick tests for nitrites and leukocytes may serve as a practical screening tool for UTIs in PLWD, particularly in individuals unable to reliably report symptoms. However, future research is needed to evaluate the clinical impact of this diagnostic approach on outcomes such as hospitalisation rates, delirium incidence, and antibiotic resistance and stewardship in this vulnerable population. Urinary Tract Infection Dementia Neurodegenerative Disease Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background At any given time, one in four hospital beds in the United Kingdom is occupied by people living with dementia (PLWD). Around 20% of these admissions result from acute conditions, such as infections, where timely intervention could prevent serious outcomes [ 1 , 2 ]. Among these, urinary tract infections (UTIs) are especially common, accounting for approximately 9% of hospital admissions in this population [ 2 – 4 ]. Beyond hospitalisation risk, delayed UTI diagnosis in PLWD can lead to increased confusion, delirium, sepsis, faster clinical deterioration [ 5 – 7 ], and potentially worsened neurodegeneration [ 8 , 9 ]. A major barrier to timely UTI detection in PLWD is symptom presentation. Current UK and European guidelines recommend diagnosing and treating UTIs only when localised signs or symptoms are evident [ 10 , 11 ]. However, infection symptoms are often atypical or absent in older adults, particularly for UTIs [ 12 , 13 ] and PLWD may struggle to recognise or communicate symptoms due to cognitive impairment [ 14 ]. Reliable biomarkers for diagnosing UTIs in the absence of symptoms are currently lacking. Moreover, the presence of bacteria in urine (asymptomatic bacteriuria) is common among the elderly [ 15 ], and treating it has not shown clinical benefit [ 16 – 18 ]. While UTIs have been studied extensively across various populations, little is known about which uropathogens affect PLWD specifically. Given both the impact on individual well-being and the broader public health burden, there is a clear need to better understand UTIs in this group. In this study, we conducted a longitudinal analysis of urinary pathogens in people with Alzheimer’s disease, the most prevalent form of dementia, who were still living at home. By combining molecular, microbiological, and clinical data, we aimed to characterise bacterial colonisation and infection in this understudied, community-dwelling population, filling a gap in a field that has focused largely on institutionalised cohorts. Methods Study Cohort This study involves a cohort established by the Surrey and Borders Partnership NHS Foundation Trust (SABP) and the Hammersmith & Fulham Partnership Primary Care Network (HFP PCN) between late 2019 and the end of 2023. Participants with a confirmed dementia diagnosis (any type) were recruited via health and social care partners, including NHS Community Mental Health Teams for older adults (CMHT-OP) and specialist memory services at SABP and in North West London. The study was also advertised on the national ‘Join Dementia Research’ website https://www.joindementiaresearch.nihr.ac.uk/ . Inclusion Criteria : Aged 50 or older at baseline Confirmed dementia diagnosis by specialist assessment Able and willing to provide informed consent Standardised Mini-Mental State Examination (SMMSE) score at baseline interview over 12 Living in the community Sufficient functional English to complete assessments Exclusion Criteria : Living in a residential care home Unstable mental state (e.g., severe depression, psychosis, agitation, anxiety, or suicidal ideation) Severe sensory impairment SMMSE score < 12 Unable to communicate verbally Under treatment for a terminal illness Urine Collection Urine samples were collected every 4–6 weeks using sterile containers or, for those with fine motor difficulties, via a sterile kidney dish. Samples were transported on ice for analysis. Dipstick Analysis Dipstick testing was performed on the Clinitek Status analyser (Siemens Healthcare Diagnostics) using Siemens Multistix 10SG strips, following the manufacturer’s protocol. Chromogenic Agar Plates To quantify bacterial colonies, 1 µL of urine mixed with 99 µL 1× sterile PBS was cultured on Brilliance UTI Clarity Agar (Oxoid Ltd) and incubated at 37°C for 18–24 hours. Colony counts were recorded as CFU/mL, capped at 100,000 + CFU/mL. Overnight Cultures of Bacterial Strains Selected colonies were cultured overnight in Tryptone Soy Broth (Oxoid Ltd) at 37°C with shaking at 200 rpm. Subsequently, a 400 µL aliquot of culture was mixed with 400 µL of sterile 50% glycerol in 2D barcoded matrix tubes (Nunc™) and stored at -80°C. 16S rRNA Gene Amplification, Sequencing, and Classification To confirm bacterial identity, 1 µL of overnight culture was mixed with 99 µL 1× sterile PBS and heated at 95°C for 30 minutes, after which the V3-V4 regions of the 16S rRNA gene were amplified using: Forward primer : AGGGTTTTCCCAGTCACGACGTTCCTACGGGNGGCWGCA Reverse primer : GACTACHVGGGTATCTAATCC PCR conditions: 1 cycle of 95°C for 5 min; 30 cycles of 95°C for 30 s, 50°C for 30 s, 1 cycle of 72°C for 30 s; final extension at 72°C for 5 min. Amplicons (5 µL) were treated with 2 µL ExoSAP-IT™ at 37°C for 4 min, then 80°C for 1 min. Products were sent to Eurofins Genomics for Sanger sequencing using the M13 uni (-43) primer (AGGGTTTTCCCAGTCACGACGTT). Sequences were quality-filtered (QV30) and classified via the SILVA ACT tool using default settings. Interleukin 8 (IL-8) Concentration in Urine Urine samples were centrifuged at > 500 × g for 10 minutes at 4°C to remove insoluble material. Supernatants were diluted 1:4 with Olink® Focus Sample Diluent to a final volume of 50 µL and stored at -80°C until shipment. Samples were submitted to the UKDRI Fluid Biomarker Laboratory and Biomarker Factory for cytokine quantification using the Olink® Target 48 inflammation panel on the Olink® Signature Q100 instrument. This panel employs Olink’s Proximity Extension Assay (PEA) technology, in which matched antibody pairs conjugated to DNA oligonucleotides bind to the target protein, allowing hybridisation and extension by polymerase. This enables highly sensitive and specific protein quantification via qPCR. Data Pre-Processing and Classification Symptom Reporting Participants completed a UTI symptom questionnaire (Supplementary Table 1) on the day of sample collection. Their symptom responses were manually reviewed and recoded as follows: Responses with a clear yes/no intent, including synonyms or elaborations, were coded accordingly. Non-responses, unrelated causes, or expressions of uncertainty were coded as "Other". Supplementary Table 1 provides details of the original and recoded responses. UTI Classification For this study, UTIs were defined as bacterial growth with a single colony morphology > 10⁵ CFU/mL, alongside detection of leukocytes and/or nitrites [ 19 , 20 ]. Symptomatic status was based on an adapted questionnaire per NICE guidelines [ 19 ]. Data Analysis All analyses were conducted in R. Descriptive statistics summarised cohort demographics and UTI frequency. Associations between laboratory indicators, bacterial taxa, symptoms, and UTI frequency were assessed using generalized linear mixed-effects models (GLMMs) with a logit link, with separate models applied for distinct analyses. Repeated measures were included as random effects. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported. False discovery rate (FDR) correction adjusted for multiple comparisons models. Bias-reduced binomial GLMMs explored associations with participants with High Frequency of UTI. Linear mixed-effects models (LMMs) quantified relationships between IL-8 levels, bacterial growth, dipstick results, and symptoms. Sensitivity and specificity calculations were performed at both the participant and sample levels to evaluate the diagnostic performance of symptom reporting, dipstick testing, and bacterial counts. UTI frequency was categorised per 6-week windows into: "No UTI," "Low-Frequency," "Mid- Frequency," or "High- Frequency”. Analysis code and outputs are available in the supplementary materials. Results Cohort characteristic Over the four-year study period, 602 urine samples were collected approximately every six weeks from 86 participants (Figure 1). All participants were living at home, and 55% lived with a carer. The cohort was nearly gender-balanced (45% female), with Alzheimer’s disease being the most common diagnosis (66%). The median age at enrolment was 82 years (interquartile range [IQR]: 77–88). Due to rolling recruitment, participants contributed varying numbers of samples, with a mean of seven samples per person (IQR: 3–10). Clinicians classified 512 samples as non-UTI and 90 as UTI. Of the UTI-positive samples, 65% were from females and 35% from males. Overall, 33% of participants submitted at least one UTI-positive sample (Figure 1). Variable UTI frequency among PLWD To assess how often participants experienced UTIs, we grouped individuals based on the occurrence of UTI events within six-week intervals—the approximate time between sample collections (Figure 2). A window was marked “positive” if a UTI was recorded during that period. We focused this analysis on 58 participants who were enrolled for at least six months; the remaining 28 participants were classified as “Short-Term” and excluded from frequency-based categorisation. Participants with no positive windows were classified as "No UTI". Those with fewer than 20% of their windows marked positive were labelled "Low-frequency", those with 20–50% as "mid-frequency", and those with more than 50% as "high-frequency". In total, we identified 4 high-frequency, 13 mid-frequency, 22 low-frequency, and 19 no-UTI participants . Microbiological Characteristics of Collected Samples To characterise the chemical and microbial composition of each urine sample, we performed urinary dipstick testing and bacterial culturing on chromogenic agar—both standard clinical methods for detecting UTIs [19, 20]. For the dipstick analysis, we focused exclusively on the presence of leukocytes and nitrites, excluding other markers from consideration (Figure 3A)[21]. Of the 602 samples collected, 597 underwent dipstick testing. Among these, 26% were positive for leukocytes and 8% for nitrites. As not all bacteria produce nitrites, their absence does not exclude infection. Bacterial growth was detected in 362 samples, with one excluded due to excessive mixed growth, leaving 361 for colony counting (Figure 3B). Using the UK NICE threshold of ≥10⁵ CFU/mL for a single colony morphology to define UTIs [19], 19% of samples met this criterion. A generalised linear mixed model (GLMM) revealed a strong association between a positive dipstick result and culture positivity above this threshold OR = 18.1, p < 0.001). The dipstick test sensitivity —defined as a positive dipstick result in the presence of a single colony morphology ≥10⁵ CFU/mL— was 82% per participant and 70% per sample. Dipstick test specificity—defined as a negative dipstick result in the absence of a single colony morphology ≥10⁵ CFU/mL—was 73% per participant and 84% per sample. This indicates that while a positive dipstick result substantially increases the likelihood of a culture-confirmed UTI, dipstick tests are slightly more effective at ruling out samples without high bacterial loads than they are at reliably identifying those with high bacterial loads — particularly when assessed at the sample level. Common Uropathogens Detected in PLWD and Their Association with Laboratory Markers To determine whether cultured bacteria from urine samples were known uropathogens, we performed 16S rRNA gene Sanger sequencing on a subset of 330 isolates out of 771 from the 362 samples with bacterial growth. We then compared the taxonomic profiles of isolates from dipstick-positive samples (leukocytes and/or nitrites) that exceeded the ≥10⁵ CFU/mL threshold with those that did not meet these criteria. Given known sex-related differences in urinary tract colonisation, participant sex was included as a variable but was insignificant (p = 0.5) in our analysis (Figure S1) [22, 23]. Escherichia was the most frequently identified genus, consistent with previous studies, and was strongly associated with both dipstick positivity and high colony counts (OR = 16.4, p < 0.001, FDR-adjusted p < 0.001) [24]. Klebsiella (OR = 75.4, p < 0.001, FDR-adjusted p < 0.001) and Streptococcus (OR = 9.6, p = 0.003, FDR-adjusted p = 0.004) also showed strong associations, supporting their roles as common uropathogens [24]. Although Enterococcus and Staphylococcus were not significantly associated in our model, they were frequently detected in dipstick-negative samples. As members of the gut and skin microbiota, their presence may reflect low-level contamination during sampling, increased susceptibility to colonisation in this cohort, or both. Nonetheless, since these genera can cause UTIs and were observed in participants classified as UTI-positive, their potential clinical relevance should not be overlooked. To prevent complete separation when modelling dipstick results—in which samples with multiple organisms have the same outcome—we restricted the analysis to the dominant taxon per sample. Klebsiella was excluded from this primary analysis, as all dominant Klebsiella samples tested dipstick-positive. In this context, both Escherichia (OR = 12.06, p < 0.001, FDR-adjusted p < 0.001) and Streptococcus (OR = 9.7, p = 0.008, FDR-adjusted p = 0.014) were significantly associated with dipstick positivity. When Klebsiella and multiple taxa per sample were included and focusing on samples with ≥10⁵ CFU/mL of a single colony type, Escherichia (OR = 5.9, p < 0.001, FDR-adjusted p < 0.001) and Klebsiella (OR = 19.0, p < 0.001, FDR-adjusted p < 0.001) remained significant. These results suggest that dipstick tests reliably detect samples dominated by potentially pathogenic taxa, particularly Escherichia and Klebsiella, when present at ≥10⁵ CFU/mL. No Association Between Bacterial Taxa and UTI Frequency in PLWD To explore potential microbial drivers of recurrent infection, we examined whether specific bacterial taxa were associated with differing frequencies of presumed UTIs across participants (Figure S2). While we hypothesised that certain species might underlie high -frequency of infections, our logistic model found no clear associations—likely due to limited statistical power, as only four participants met the criteria for high-frequency of UTI. Additionally, participants with more frequent infections were not consistently colonised by a single bacterial genus. For example, some individuals (e.g., P061 and P004) were predominantly infected by a single genus across timepoints, whereas others (e.g., P054) exhibited greater variability, with different dominant isolates detected in different samples. Symptom Reporting Does Not Predict Laboratory Evidence of UTI Given that self-reported symptoms form the primary basis for diagnosing UTIs in individuals over 65 according to NICE guidelines, we assessed the relationship between reported symptoms and laboratory indicators of infection (Figure 4) [19]. At each visit, participants answered seven questions addressing common UTI symptoms, including increased urgency, frequency, dysuria, urinary retention, changes in urine smell or colour, localised pain, and general malaise. A "yes" response to any question classified the individual as symptomatic. Most participants reported no symptoms across all categories. There was no significant association between symptom presence and dipstick positivity (p = 0.2). Sensitivity—defined as the proportion of symptomatic participants with a positive laboratory test—was 45% per participant and 29% per sample, while specificity—defined as the proportion of asymptomatic participants with a negative laboratory test—was 46% per participant and 76% per sample. High bacterial counts (>10⁵ CFU/mL) likewise showed no significant link to symptoms (p = 0.7), with the same sensitivity (45% per participant; 29% per sample) and specificity (46% per participant; 76% per sample). Combining dipstick positivity and high colony counts also failed to reveal a relationship with symptoms (p = 0.4), producing a sensitivity of 30% per participant and 29% per sample, and a specificity of 73% per participant and 76% per sample. These results indicate that self-reported symptoms alone lack the sensitivity required to detect laboratory-confirmed infection, so relying solely on symptom reports would miss a substantial number of cases. Dipstick Results Correlate with Inflammatory Marker IL-8 To evaluate the biological relevance of laboratory-defined UTIs, we examined a subset of data from 31 participants (107 samples) using a linear mixed model (LMM). This analysis assessed associations between urinary IL-8—a validated biomarker of inflammation in UTIs[25]—and bacterial colony counts for different taxon. A second, separate LMM of IL‑8 on dipstick results and self‑reported symptoms was employed to avoid over‑adjustment and collider bias with bacterial counts, reduce multicollinearity, isolate the clinical proxy evaluation from the mechanistic model, and maximise statistical power. IL-8 levels were significantly associated with log-transformed colony counts of Escherichia (coefficient = 0.12, p = 0.005, FDR-adjusted p = 0.01), Klebsiella (coefficient = 0.19, p = 0.011, FDR-adjusted p = 0.016), Staphylococcus (coefficient = 0.15, raw p < 0.001, FDR-adjusted p < 0.001), and Enterococcus (coefficient = 0.13, p = 0.015, FDR-adjusted p = 0.018). Dipstick positivity (leukocytes and/or nitrites) was also strongly linked to elevated IL-8 levels (coefficient = 2.2, p < 0.001, FDR-adjusted p < 0.001). In contrast, self-reported symptoms showed no significant association with IL-8 concentrations (Figure 5). These findings suggest that dipstick positivity and high colony counts of known uropathogens, particularly Escherichia and Klebsiella , are markers of biologically relevant inflammation in PLWD. Observed association with Staphylococcus and Enterococcus warrants caution, given these genera include both low-virulence skin and gastrointestinal commensals, respectively, and, less frequently, established urinary pathogens [26–28]. Discussion In this study, we characterised the nature and frequency of UTIs in PLWD using a longitudinal routine sampling method. This is the first study to do so in a cohort of PLWD living at home, a demographic less often studied due to the logistical challenges of working with dispersed populations outside care facilities. We found UTIs to be more common in this group than in the general population, consistent with previous findings [ 29 ]. Notably, there was considerable variation in infection frequency: some individuals experienced persistent UTIs despite treatment, while others remained infection-free. This disparity may reflect differences in comorbidities such as diabetes, incontinence, or immunosuppressive therapy [ 30 , 31 ]. The most frequently isolated bacteria—especially Escherichia —were consistent with known UTI pathogens [ 19 ]. Although diagnoses were primarily based on laboratory criteria, our analysis revealed that self-reported symptoms in PLWD showed poor correlation with both microbiological evidence (> 10⁵ CFU/mL) and the presence of known uropathogens. In the general population, symptoms such as dysuria, urgency, and frequency are moderately predictive [ 32 , 33 ], but cognitive impairments in PLWD likely impair symptom recognition and reporting [ 34 ]. This raises concerns that strict symptom-based guidelines, such as those from NICE, may lead to missed infections or inappropriate treatment of asymptomatic bacteriuria (ASB), contributing to antimicrobial resistance [ 19 ]. While dipstick testing has limited diagnostic reliability [ 35 , 36 ], its rapidity and low cost make it a potentially useful initial screen when paired with confirmatory cultures. This contrasts with Public Health England’s recommendation against dipstick use in adults over 65 due to ASB prevalence [ 37 ]. However, our data suggest dipstick results in PLWD correlate more closely with both high bacterial loads and the inflammatory marker IL-8 than with reported symptoms. A two-step protocol, where a positive dipstick prompts culture testing, may help identify true infections while reducing unnecessary antibiotic use. This approach supports the need for dementia-specific diagnostic frameworks that balance sensitivity with the risk of overtreatment. Implications and Future Directions Our findings underscore the need to refine UTI diagnostics for PLWD while cautioning against interventions lacking proven clinical benefit. Although dipsticks may help identify high bacterial loads, their impact on outcomes such as hospitalisation or delirium remains uncertain. Future studies should assess the effectiveness of dipstick-guided multi-step protocols in this regard. Crucially, biomarker discovery is needed to differentiate true UTIs from ASB, as prior attempts to treat ASB based solely on bacterial persistence have not improved outcomes [ 18 ]. Biomarkers linked to host immune response (e.g IL-8 and C-reactive protein) offer more promise than bacterial presence alone. Although resource-intensive, such research could reduce diagnostic uncertainty and support better antibiotic stewardship. Abbreviations ASB : Asymptomatic Bacteriuria CFU/mL : Colony-Forming Units per Millilitre CI : Confidence Interval CMHT-OP : Community Mental Health Teams for older adults FDR : False Discovery Rate GLMM : Generalized Linear Mixed-Effects Model HFP PCN : Hammersmith & Fulham Partnership Primary Care Network IL-8 : Interleukin 8 IQR : Interquartile Range LMM : Linear Mixed-Effects Model SMMSE : Standardised Mini-Mental State Examination NICE : National Institute for Health and Care Excellence OR : Odds Ratio PEA : Proximity Extension Assay PLWD : People Living with Dementia SABP : Surrey and Borders Partnership NHS Foundation Trust UKDRI : UK Dementia Research Institute UTI : Urinary Tract Infection Declarations Ethics approval and consent to participate This study was submitted to, and approved by, the Surrey and Borders NHS Trust Research Ethics Committee (reference number: 19/LO/0102) and registered via the Integrated Research Application System (IRAS project ID: 257561). The research was conducted in accordance with the ethical principles set out in the Declaration of Helsinki. Informed consent was obtained from all participants prior to enrolment. Individuals unable to provide informed consent were excluded from participation. Clinical Trial Clinical trial number: not applicable. Consent for publication Not applicable. Availability of data and materials The data collected during the current study and the code used to analyse the data are available from a Zenodo public repository at (10.5281/zenodo.15720387). Competing interests The authors declare that they have no competing interests. Funding sources This work is supported by the UK Dementia Research Institute [award number UKI DRI- WBCN_PA5470], through UK DRI Ltd, principally funded by the Medical Research Council, and additional funding partners Alzheimer’s Society. Authors' contributions R.J. and R.C. are joint first authors, having both contributed equally to writing the main manuscript text, conducting the data analysis, and developing the R code. M.T., K.J., A.J.W., L.P.C., and M.A.C. provided laboratory support, including sample collection and processing for culture growth assays, dipstick tests, 16S Sanger sequencing, and Olink analyses. R.N. and D.W. provided clinical guidance and were responsible for diagnosing patients. D.J.W. and P.S.F. contributed by securing funding for the research. All authors reviewed the manuscript. Acknowledgements We thank the patients and study partners who took part in the study. We also thank all members of the UK Dementia Research Institute Care Research & Technology Centre who contributed in some way to this work; a full list of members can be found in the supplementary file “Centre Members” . We are grateful to the Surrey and Borders Partnership, the sponsors of this study. 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Giesen LG, Cousins G, Dimitrov BD, van de Laar FA, Fahey T. Predicting acute uncomplicated urinary tract infection in women: a systematic review of the diagnostic accuracy of symptoms and signs. BMC Fam Pract. 2010;11:78. Hodgson N, Gitlin LN, Winter L, Czekanski K. Undiagnosed Illness and Neuropsychiatric Behaviors In Community-residing Older Adults with Dementia. Alzheimer Dis Assoc Disord. 2011;25:109–15. Mambatta AK, Jayarajan J, Rashme VL, Harini S, Menon S, Kuppusamy J. Reliability of dipstick assay in predicting urinary tract infection. J Fam Med Prim Care. 2015;4:265–8. Kristensen LH, Winther R, Colding-Jørgensen JT, Pottegård A, Nielsen H, Bodilsen J. Diagnostic accuracy of dipsticks for urinary tract infections in acutely hospitalised patients: a prospective population-based observational cohort study. BMJ Evid-Based Med. 2025;30:36–44. Joseph A. The Diagnosis and Management of UTI in >65s: To Dipstick or Not? The Argument Against Dipsticks. Infect Prev Pract. 2020;2:100063. Additional Declarations No competing interests reported. Supplementary Files Supplementryfigure.docx SupplementaryTable1.csv Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7185812","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":506041763,"identity":"7993cd68-af27-4170-a6a7-dbb6bb86efce","order_by":0,"name":"Raphaella Jackson","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Raphaella","middleName":"","lastName":"Jackson","suffix":""},{"id":506041764,"identity":"62c495cb-54fb-423a-8763-38d45836b88d","order_by":1,"name":"Rory Cave","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Rory","middleName":"","lastName":"Cave","suffix":""},{"id":506041765,"identity":"b77644a4-2c54-4870-8bc0-db4c15fc3c4d","order_by":2,"name":"Martin Tran","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Tran","suffix":""},{"id":506041766,"identity":"30680020-3c2d-4743-9867-6156d4d8b444","order_by":3,"name":"Kirsten Jensen","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Kirsten","middleName":"","lastName":"Jensen","suffix":""},{"id":506041767,"identity":"2c0b367d-64b0-4419-aab6-f7d46c0bacaa","order_by":4,"name":"Michael A. Crone","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"A.","lastName":"Crone","suffix":""},{"id":506041768,"identity":"e2d20fb0-d098-4834-8e41-9aaf4fda72a4","order_by":5,"name":"Alexander J. Webb","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"J.","lastName":"Webb","suffix":""},{"id":506041769,"identity":"d9905960-b95d-4040-bc95-b365e3607d62","order_by":6,"name":"Loren P. Cameron","email":"","orcid":"","institution":"Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Loren","middleName":"P.","lastName":"Cameron","suffix":""},{"id":506041770,"identity":"3e0f99bf-fe41-4813-8f19-940b087f3876","order_by":7,"name":"Ramin Nilforooshan","email":"","orcid":"","institution":"UK Dementia Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Ramin","middleName":"","lastName":"Nilforooshan","suffix":""},{"id":506041771,"identity":"6076dff3-7691-4fdd-8659-802e33272ba3","order_by":8,"name":"David Wingfield","email":"","orcid":"","institution":"UK Dementia Research Institute","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Wingfield","suffix":""},{"id":506041772,"identity":"ff943526-96a5-4f3e-ad28-150e40c3bb70","order_by":9,"name":"David J. Sharp","email":"","orcid":"","institution":"UK Dementia Research Institute","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"J.","lastName":"Sharp","suffix":""},{"id":506041773,"identity":"53441688-fd87-489a-bdeb-9ba60bf3594f","order_by":10,"name":"Paul S. Freemont","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIie2RsWoCQRCGZxlYm7vYXpHoKwxccRxIniWLYCdpU1gMCFcdpFWEPINVsFyzcJUvEK7xSJvCkCaNSfb0BANZk9Jiv2b2Lz5mZgfA4zlLxLp5oNZ1kYC8y5FTQdpXKW8aRfxbCejQ97SSAMrN5u6xk3Tzt6fnRe/2orVk+BiBmvLvSsqI08mqjNMsnJvhapBmgWKRF6Bmji6k2wbDrFTzolYyQxIUQ8igHpwKIm4/ayVYW+WLZLtisf1LEbxTwCqaZKQY6y6uwdKxNfKijKkYkN2lb5WKzWURxa71k9YY7f+UHTLm5X24uKbufX9ZvY56VxPtGAyPU3MR0KcOST/SQfF4PB7PMd+iPVwLqzr35gAAAABJRU5ErkJggg==","orcid":"","institution":"Imperial College London","correspondingAuthor":true,"prefix":"","firstName":"Paul","middleName":"S.","lastName":"Freemont","suffix":""}],"badges":[],"createdAt":"2025-07-22 10:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7185812/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7185812/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90111185,"identity":"fa9ab6d4-5bbf-4c80-bb51-430e97e7211c","added_by":"auto","created_at":"2025-08-28 15:09:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":257802,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eParticipant Demographics and Samples Collected. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eA Sankey plot showing the study cohort’s living situation, gender, diagnosis, number of samples collected per participant, and whether they submitted at least one UTI sample.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/293dc405b26c64823904be26.png"},{"id":90111168,"identity":"0dc833b5-912b-435a-805a-53292e97ccd6","added_by":"auto","created_at":"2025-08-28 15:09:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":375481,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eUTI Frequency in Cohort\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e. A plot showing UTI occurrence in each 6-week window following a participant’s first sample. Participants are grouped by UTI Frequency Type. Those with less than 6 months of study participation are labelled “Short-Term” and not further classified. The X-axis represents sequential 6-week intervals since each participant’s first sample, with each unit indicating whether a UTI event occurred within that window. The Y-axis represents individual participants. The figure demonstrates substantial variability in UTI frequency between participants.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/ce0c6b820636624a383c3810.png"},{"id":90111180,"identity":"5fde1c7e-4739-4f61-bded-9f22695f68f6","added_by":"auto","created_at":"2025-08-28 15:09:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":101183,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDipstick Test Results and Dominant Colony Morphology Count\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e. (A) Bar plot displaying leukocyte and nitrite results from dipstick tests across all analysable urine samples.\u003cbr\u003e\n(B) Bar plot showing the colony-forming unit (CFU/mL) count of the most dominant colony morphology observed on chromogenic agar following culture of each sample.\u003cbr\u003e\nThe figure indicates that the majority of samples do not exhibit strong evidence of urinary tract infection, as reflected by negative dipstick results for leukocytes and nitrite, alongside culture growth below the diagnostic threshold of 10⁵ CFU/mL.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/9517c5f3848a2732bee2230b.png"},{"id":90111181,"identity":"83921148-8ebf-4b5c-978c-e9da09b514ed","added_by":"auto","created_at":"2025-08-28 15:09:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":264608,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSymptom Reporting by Dipstick Result and Colony Count\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e.(A) Proportion of reported symptoms stratified by dipstick result type. (B) Proportion of reported symptoms stratified by colony count.(C) Proportion of reported symptoms based on the combination of a dipstick-positive result and ≥100,000 CFU/mL culture growth. The figure shows no clear association between symptom questionnaire responses and either dipstick test results or culture findings.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/f5799766d9ba5d315c117d1f.png"},{"id":90111165,"identity":"ff5fee00-de3e-426f-813d-464187823c17","added_by":"auto","created_at":"2025-08-28 15:09:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":54865,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation of urinary inflammatory marker IL-8 with dipstick result and symptoms.\u003c/strong\u003e The figure shows that higher urinary IL-8 levels are associated with an increased likelihood of a dipstick-positive result (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). In contrast, no clear difference in IL-8 levels is observed between participants who self-report as asymptomatic and those reporting symptoms (\u003cem\u003esymptomatic p\u003c/em\u003e = 0.6; \u003cem\u003euncertain p\u003c/em\u003e = 0.3, with asymptomatic as the reference category).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/de59eb03fec0dbf5f6539057.png"},{"id":94016673,"identity":"10f6453f-edde-4428-b2d3-f651468b1612","added_by":"auto","created_at":"2025-10-21 11:23:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1944380,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/da394971-c849-401b-8d5a-85da387a27b2.pdf"},{"id":90111517,"identity":"f3efab01-bf95-4f60-b0f2-15a4e903bb88","added_by":"auto","created_at":"2025-08-28 15:17:16","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":609846,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementryfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/55a648b9ceb61b2137ccf32e.docx"},{"id":90111173,"identity":"a622d354-7b0e-473f-b9ac-c66f844411e6","added_by":"auto","created_at":"2025-08-28 15:09:16","extension":"csv","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":64099,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.csv","url":"https://assets-eu.researchsquare.com/files/rs-7185812/v1/85283ae9b54deefc60efd799.csv"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Cohort Study of Urinary Tract Infections in People Living with Dementia: Epidemiology and Diagnostic Challenges","fulltext":[{"header":"Background","content":"\u003cp\u003eAt any given time, one in four hospital beds in the United Kingdom is occupied by people living with dementia (PLWD). Around 20% of these admissions result from acute conditions, such as infections, where timely intervention could prevent serious outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Among these, urinary tract infections (UTIs) are especially common, accounting for approximately 9% of hospital admissions in this population [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Beyond hospitalisation risk, delayed UTI diagnosis in PLWD can lead to increased confusion, delirium, sepsis, faster clinical deterioration [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e–\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and potentially worsened neurodegeneration [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA major barrier to timely UTI detection in PLWD is symptom presentation. Current UK and European guidelines recommend diagnosing and treating UTIs only when localised signs or symptoms are evident [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, infection symptoms are often atypical or absent in older adults, particularly for UTIs [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and PLWD may struggle to recognise or communicate symptoms due to cognitive impairment [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Reliable biomarkers for diagnosing UTIs in the absence of symptoms are currently lacking. Moreover, the presence of bacteria in urine (asymptomatic bacteriuria) is common among the elderly [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and treating it has not shown clinical benefit [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e–\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile UTIs have been studied extensively across various populations, little is known about which uropathogens affect PLWD specifically. Given both the impact on individual well-being and the broader public health burden, there is a clear need to better understand UTIs in this group. In this study, we conducted a longitudinal analysis of urinary pathogens in people with Alzheimer’s disease, the most prevalent form of dementia, who were still living at home. By combining molecular, microbiological, and clinical data, we aimed to characterise bacterial colonisation and infection in this understudied, community-dwelling population, filling a gap in a field that has focused largely on institutionalised cohorts.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Cohort\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study involves a cohort established by the Surrey and Borders Partnership NHS Foundation Trust (SABP) and the Hammersmith \u0026amp; Fulham Partnership Primary Care Network (HFP PCN) between late 2019 and the end of 2023. Participants with a confirmed dementia diagnosis (any type) were recruited via health and social care partners, including NHS Community Mental Health Teams for older adults (CMHT-OP) and specialist memory services at SABP and in North West London. The study was also advertised on the national ‘Join Dementia Research’ website \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.joindementiaresearch.nihr.ac.uk/\u003c/span\u003e\u003cspan address=\"https://www.joindementiaresearch.nihr.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion Criteria\u003c/b\u003e:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eAged 50 or older at baseline\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eConfirmed dementia diagnosis by specialist assessment\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAble and willing to provide informed consent\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStandardised Mini-Mental State Examination (SMMSE) score at baseline interview over 12\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLiving in the community\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSufficient functional English to complete assessments\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003cb\u003eExclusion Criteria\u003c/b\u003e:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eLiving in a residential care home\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eUnstable mental state (e.g., severe depression, psychosis, agitation, anxiety, or suicidal ideation)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSevere sensory impairment\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSMMSE score \u0026lt; 12\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eUnable to communicate verbally\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eUnder treatment for a terminal illness\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eUrine Collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUrine samples were collected every 4–6 weeks using sterile containers or, for those with fine motor difficulties, via a sterile kidney dish. Samples were transported on ice for analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDipstick Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDipstick testing was performed on the Clinitek Status analyser (Siemens Healthcare Diagnostics) using Siemens Multistix 10SG strips, following the manufacturer’s protocol.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChromogenic Agar Plates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo quantify bacterial colonies, 1 µL of urine mixed with 99 µL 1× sterile PBS was cultured on Brilliance UTI Clarity Agar (Oxoid Ltd) and incubated at 37°C for 18–24 hours. Colony counts were recorded as CFU/mL, capped at 100,000 + CFU/mL.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOvernight Cultures of Bacterial Strains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSelected colonies were cultured overnight in Tryptone Soy Broth (Oxoid Ltd) at 37°C with shaking at 200 rpm. Subsequently, a 400 µL aliquot of culture was mixed with 400 µL of sterile 50% glycerol in 2D barcoded matrix tubes (Nunc™) and stored at -80°C.\u003c/p\u003e\u003cp\u003e\u003cb\u003e16S rRNA Gene Amplification, Sequencing, and Classification\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo confirm bacterial identity, 1 µL of overnight culture was mixed with 99 µL 1× sterile PBS and heated at 95°C for 30 minutes, after which the V3-V4 regions of the 16S rRNA gene were amplified using:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eForward primer\u003c/b\u003e: AGGGTTTTCCCAGTCACGACGTTCCTACGGGNGGCWGCA\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eReverse primer\u003c/b\u003e: GACTACHVGGGTATCTAATCC\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003ePCR conditions: 1 cycle of 95°C for 5 min; 30 cycles of 95°C for 30 s, 50°C for 30 s, 1 cycle of 72°C for 30 s; final extension at 72°C for 5 min.\u003c/p\u003e\u003cp\u003eAmplicons (5 µL) were treated with 2 µL ExoSAP-IT™ at 37°C for 4 min, then 80°C for 1 min. Products were sent to Eurofins Genomics for Sanger sequencing using the M13 uni (-43) primer (AGGGTTTTCCCAGTCACGACGTT). Sequences were quality-filtered (QV30) and classified via the SILVA ACT tool using default settings.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInterleukin 8 (IL-8) Concentration in Urine\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUrine samples were centrifuged at \u0026gt; 500 × \u003cem\u003eg\u003c/em\u003e for 10 minutes at 4°C to remove insoluble material. Supernatants were diluted 1:4 with Olink® Focus Sample Diluent to a final volume of 50 µL and stored at -80°C until shipment. Samples were submitted to the UKDRI Fluid Biomarker Laboratory and Biomarker Factory for cytokine quantification using the Olink® Target 48 inflammation panel on the Olink® Signature Q100 instrument. This panel employs Olink’s Proximity Extension Assay (PEA) technology, in which matched antibody pairs conjugated to DNA oligonucleotides bind to the target protein, allowing hybridisation and extension by polymerase. This enables highly sensitive and specific protein quantification via qPCR.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Pre-Processing and Classification\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSymptom Reporting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eParticipants completed a UTI symptom questionnaire (Supplementary Table\u0026nbsp;1) on the day of sample collection. Their symptom responses were manually reviewed and recoded as follows:\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e Responses with a clear yes/no intent, including synonyms or elaborations, were coded accordingly.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eNon-responses, unrelated causes, or expressions of uncertainty were coded as \"Other\".\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003eSupplementary Table\u0026nbsp;1 provides details of the original and recoded responses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eUTI Classification\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor this study, UTIs were defined as bacterial growth with a single colony morphology \u0026gt; 10⁵ CFU/mL, alongside detection of leukocytes and/or nitrites [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Symptomatic status was based on an adapted questionnaire per NICE guidelines [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eAll analyses were conducted in R. Descriptive statistics summarised cohort demographics and UTI frequency. Associations between laboratory indicators, bacterial taxa, symptoms, and UTI frequency were assessed using generalized linear mixed-effects models (GLMMs) with a logit link, with separate models applied for distinct analyses. Repeated measures were included as random effects. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported. False discovery rate (FDR) correction adjusted for multiple comparisons models. Bias-reduced binomial GLMMs explored associations with participants with High Frequency of UTI. Linear mixed-effects models (LMMs) quantified relationships between IL-8 levels, bacterial growth, dipstick results, and symptoms. Sensitivity and specificity calculations were performed at both the participant and sample levels to evaluate the diagnostic performance of symptom reporting, dipstick testing, and bacterial counts. UTI frequency was categorised per 6-week windows into: \"No UTI,\" \"Low-Frequency,\" \"Mid- Frequency,\" or \"High- Frequency”. Analysis code and outputs are available in the supplementary materials.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eCohort characteristic\u003c/h2\u003e\n\u003cp\u003eOver the four-year study period, 602 urine samples were collected approximately every six weeks from 86 participants (Figure 1). All participants were living at home, and 55% lived with a carer. The cohort was nearly gender-balanced (45% female), with Alzheimer\u0026rsquo;s disease being the most common diagnosis (66%). The median age at enrolment was 82 years (interquartile range [IQR]: 77\u0026ndash;88). Due to rolling recruitment, participants contributed varying numbers of samples, with a mean of seven samples per person (IQR: 3\u0026ndash;10).\u003c/p\u003e\n\u003cp\u003eClinicians classified 512 samples as non-UTI and 90 as UTI. Of the UTI-positive samples, 65% were from females and 35% from males. Overall, 33% of participants submitted at least one UTI-positive sample (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariable UTI frequency among PLWD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess how often participants experienced UTIs, we grouped individuals based on the occurrence of UTI events within six-week intervals\u0026mdash;the approximate time between sample collections (Figure 2). A window was marked \u0026ldquo;positive\u0026rdquo; if a UTI was recorded during that period. We focused this analysis on 58 participants who were enrolled for at least six months; the remaining 28 participants were classified as \u0026ldquo;Short-Term\u0026rdquo; and excluded from frequency-based categorisation.\u003c/p\u003e\n\u003cp\u003eParticipants with no positive windows were classified as \u0026quot;No UTI\u0026quot;. Those with fewer than 20% of their windows marked positive were labelled \u0026quot;Low-frequency\u0026quot;, those with 20\u0026ndash;50% as \u0026quot;mid-frequency\u0026quot;, and those with more than 50% as \u0026quot;high-frequency\u0026quot;. In total, we identified \u003cstrong\u003e4 high-frequency, 13 mid-frequency, 22 low-frequency, and 19 no-UTI participants\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicrobiological Characteristics of Collected Samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo characterise the chemical and microbial composition of each urine sample, we performed urinary dipstick testing and bacterial culturing on chromogenic agar\u0026mdash;both standard clinical methods for detecting UTIs [19, 20]. For the dipstick analysis, we focused exclusively on the presence of leukocytes and nitrites, excluding other markers from consideration (Figure 3A)[21]. Of the 602 samples collected, 597 underwent dipstick testing. Among these, 26% were positive for leukocytes and 8% for nitrites. As not all bacteria produce nitrites, their absence does not exclude infection.\u003c/p\u003e\n\u003cp\u003eBacterial growth was detected in 362 samples, with one excluded due to excessive mixed growth, leaving 361 for colony counting (Figure 3B). Using the UK NICE threshold of \u0026ge;10⁵ CFU/mL for a single colony morphology to define UTIs [19], 19% of samples met this criterion. A generalised linear mixed model (GLMM) revealed a strong association between a positive dipstick result and culture positivity above this threshold OR = 18.1, p \u0026lt; 0.001). The dipstick test sensitivity \u0026mdash;defined as a positive dipstick result in the presence of a single colony morphology \u0026ge;10⁵ CFU/mL\u0026mdash; was 82% per participant and 70% per sample. Dipstick test specificity\u0026mdash;defined as a negative dipstick result in the absence of a single colony morphology \u0026ge;10⁵ CFU/mL\u0026mdash;was 73% per participant and 84% per sample. This indicates that while a positive dipstick result substantially increases the likelihood of a culture-confirmed UTI, dipstick tests are slightly more effective at ruling out samples without high bacterial loads than they are at reliably identifying those with high bacterial loads \u0026mdash; particularly when assessed at the sample level.\u003c/p\u003e\n\u003ch2\u003eCommon Uropathogens Detected in PLWD and Their Association with Laboratory\u003c/h2\u003e\n\u003ch2\u003eMarkers\u003c/h2\u003e\n\u003cp\u003eTo determine whether cultured bacteria from urine samples were known uropathogens, we performed 16S rRNA gene Sanger sequencing on a subset of 330 isolates out of 771 from the 362 samples with bacterial growth. We then compared the taxonomic profiles of isolates from dipstick-positive samples (leukocytes and/or nitrites) that exceeded the \u0026ge;10⁵ CFU/mL threshold with those that did not meet these criteria. Given known sex-related differences in urinary tract colonisation, participant sex was included as a variable but was insignificant (p = 0.5) in our analysis (Figure S1) [22, 23].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEscherichia\u003c/em\u003e was the most frequently identified genus, consistent with previous studies, and was strongly associated with both dipstick positivity and high colony counts (OR = 16.4, p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001) [24]. \u003cem\u003eKlebsiella\u003c/em\u003e (OR = 75.4, p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001) and \u003cem\u003eStreptococcus\u003c/em\u003e (OR = 9.6, p = 0.003, FDR-adjusted p = 0.004) also showed strong associations, supporting their roles as common uropathogens \u0026nbsp;[24].\u003c/p\u003e\n\u003cp\u003eAlthough \u003cem\u003eEnterococcus\u003c/em\u003e and \u003cem\u003eStaphylococcus\u003c/em\u003e were not significantly associated in our model, they were frequently detected in dipstick-negative samples. As members of the gut and skin microbiota, their presence may reflect low-level contamination during sampling, increased susceptibility to colonisation in this cohort, or both. Nonetheless, since these genera can cause UTIs and were observed in participants classified as UTI-positive, their potential clinical relevance should not be overlooked.\u003c/p\u003e\n\u003cp\u003eTo prevent complete separation when modelling dipstick results\u0026mdash;in which samples with multiple organisms have the same outcome\u0026mdash;we restricted the analysis to the dominant taxon per sample. Klebsiella was excluded from this primary analysis, as all dominant Klebsiella samples tested dipstick-positive. In this context, both Escherichia (OR = 12.06, p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001) and Streptococcus (OR = 9.7, p = 0.008, FDR-adjusted p = 0.014) were significantly associated with dipstick positivity. When Klebsiella and multiple taxa per sample were included and focusing on samples with \u0026ge;10⁵ CFU/mL of a single colony type, Escherichia (OR = 5.9, p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001) and Klebsiella (OR = 19.0, p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001) remained significant. These results suggest that dipstick tests reliably detect samples dominated by potentially pathogenic taxa, particularly Escherichia and Klebsiella, when present at \u0026ge;10⁵ CFU/mL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo Association Between Bacterial Taxa and UTI Frequency in PLWD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore potential microbial drivers of recurrent infection, we examined whether specific bacterial taxa were associated with differing frequencies of presumed UTIs across participants (Figure S2). While we hypothesised that certain species might underlie high -frequency of infections, our\u0026nbsp;logistic\u0026nbsp;model found no clear associations\u0026mdash;likely due to limited statistical power, as only four participants met the criteria for high-frequency of UTI. Additionally, participants with more frequent infections were not consistently colonised by a single bacterial genus. For example, some individuals (e.g., P061 and P004) were predominantly infected by a single genus across timepoints, whereas others (e.g., P054) exhibited greater variability, with different dominant isolates detected in different samples.\u003c/p\u003e\n\u003ch2\u003eSymptom Reporting Does Not Predict Laboratory Evidence of UTI\u003c/h2\u003e\n\u003cp\u003eGiven that self-reported symptoms form the primary basis for diagnosing UTIs in individuals over 65 according to NICE guidelines, we assessed the relationship between reported symptoms and laboratory indicators of infection (Figure 4) [19].\u003c/p\u003e\n\u003cp\u003eAt each visit, participants answered seven questions addressing common UTI symptoms, including increased urgency, frequency, dysuria, urinary retention, changes in urine smell or colour, localised pain, and general malaise. A \u0026quot;yes\u0026quot; response to any question classified the individual as symptomatic.\u003c/p\u003e\n\u003cp\u003eMost participants reported no symptoms across all categories. There was no significant association between symptom presence and dipstick positivity (p = 0.2). Sensitivity\u0026mdash;defined as the proportion of symptomatic participants with a positive laboratory test\u0026mdash;was 45% per participant and 29% per sample, while specificity\u0026mdash;defined as the proportion of asymptomatic participants with a negative laboratory test\u0026mdash;was 46% per participant and 76% per sample. High bacterial counts (\u0026gt;10⁵ CFU/mL) likewise showed no significant link to symptoms (p = 0.7), with the same sensitivity (45% per participant; 29% per sample) and specificity (46% per participant; 76% per sample). Combining dipstick positivity and high colony counts also failed to reveal a relationship with symptoms (p = 0.4), producing a sensitivity of 30% per participant and 29% per sample, and a specificity of 73% per participant and 76% per sample. These results indicate that self-reported symptoms alone lack the sensitivity required to detect laboratory-confirmed infection, so relying solely on symptom reports would miss a substantial number of cases.\u003c/p\u003e\n\u003ch2\u003eDipstick Results Correlate with Inflammatory Marker IL-8\u003c/h2\u003e\n\u003cp\u003eTo evaluate the biological relevance of laboratory-defined UTIs, we examined a subset of data from 31 participants (107 samples) using a linear mixed model (LMM). This analysis assessed associations between urinary IL-8\u0026mdash;a validated biomarker of inflammation in UTIs[25]\u0026mdash;and bacterial colony counts for different taxon.\u0026nbsp;A second, separate LMM of IL‑8 on dipstick results and self‑reported symptoms was employed to avoid over‑adjustment and collider bias with bacterial counts, reduce multicollinearity, isolate the clinical proxy evaluation from the mechanistic model, and maximise statistical power.\u003c/p\u003e\n\u003cp\u003eIL-8 levels were significantly associated with log-transformed colony counts of \u003cem\u003eEscherichia\u003c/em\u003e (coefficient = 0.12, p = 0.005, FDR-adjusted p = 0.01), \u003cem\u003eKlebsiella\u003c/em\u003e (coefficient = 0.19, p = 0.011, FDR-adjusted p = 0.016), \u003cem\u003eStaphylococcus\u003c/em\u003e (coefficient = 0.15, raw p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001), and \u003cem\u003eEnterococcus\u003c/em\u003e (coefficient = 0.13, p = 0.015, FDR-adjusted p = 0.018). \u0026nbsp;Dipstick positivity (leukocytes and/or nitrites) was also strongly linked to elevated IL-8 levels (coefficient = 2.2, p \u0026lt; 0.001, FDR-adjusted p \u0026lt; 0.001). In contrast, self-reported symptoms showed no significant association with IL-8 concentrations (Figure 5).\u003c/p\u003e\n\u003cp\u003eThese findings suggest that dipstick positivity and high colony counts of known uropathogens, particularly \u003cem\u003eEscherichia\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e, are markers of biologically relevant inflammation in PLWD.\u0026nbsp;Observed association with \u003cem\u003eStaphylococcus\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e warrants caution, given these genera include both low-virulence skin and gastrointestinal commensals, respectively, and, less frequently, established urinary pathogens [26\u0026ndash;28].\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we characterised the nature and frequency of UTIs in PLWD using a longitudinal routine sampling method. This is the first study to do so in a cohort of PLWD living at home, a demographic less often studied due to the logistical challenges of working with dispersed populations outside care facilities.\u003c/p\u003e\u003cp\u003eWe found UTIs to be more common in this group than in the general population, consistent with previous findings [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Notably, there was considerable variation in infection frequency: some individuals experienced persistent UTIs despite treatment, while others remained infection-free. This disparity may reflect differences in comorbidities such as diabetes, incontinence, or immunosuppressive therapy [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The most frequently isolated bacteria\u0026mdash;especially \u003cem\u003eEscherichia\u003c/em\u003e\u0026mdash;were consistent with known UTI pathogens [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough diagnoses were primarily based on laboratory criteria, our analysis revealed that self-reported symptoms in PLWD showed poor correlation with both microbiological evidence (\u0026gt;\u0026thinsp;10⁵ CFU/mL) and the presence of known uropathogens. In the general population, symptoms such as dysuria, urgency, and frequency are moderately predictive [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], but cognitive impairments in PLWD likely impair symptom recognition and reporting [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This raises concerns that strict symptom-based guidelines, such as those from NICE, may lead to missed infections or inappropriate treatment of asymptomatic bacteriuria (ASB), contributing to antimicrobial resistance [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile dipstick testing has limited diagnostic reliability [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], its rapidity and low cost make it a potentially useful initial screen when paired with confirmatory cultures. This contrasts with Public Health England\u0026rsquo;s recommendation against dipstick use in adults over 65 due to ASB prevalence [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, our data suggest dipstick results in PLWD correlate more closely with both high bacterial loads and the inflammatory marker IL-8 than with reported symptoms. A two-step protocol, where a positive dipstick prompts culture testing, may help identify true infections while reducing unnecessary antibiotic use. This approach supports the need for dementia-specific diagnostic frameworks that balance sensitivity with the risk of overtreatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplications and Future Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur findings underscore the need to refine UTI diagnostics for PLWD while cautioning against interventions lacking proven clinical benefit. Although dipsticks may help identify high bacterial loads, their impact on outcomes such as hospitalisation or delirium remains uncertain. Future studies should assess the effectiveness of dipstick-guided multi-step protocols in this regard.\u003c/p\u003e\u003cp\u003eCrucially, biomarker discovery is needed to differentiate true UTIs from ASB, as prior attempts to treat ASB based solely on bacterial persistence have not improved outcomes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Biomarkers linked to host immune response (e.g IL-8 and C-reactive protein) offer more promise than bacterial presence alone. Although resource-intensive, such research could reduce diagnostic uncertainty and support better antibiotic stewardship.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eASB\u003c/strong\u003e: Asymptomatic Bacteriuria\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCFU/mL\u003c/strong\u003e: Colony-Forming Units per Millilitre\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e: Confidence Interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCMHT-OP\u003c/strong\u003e: Community Mental Health Teams for older adults\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFDR\u003c/strong\u003e: False Discovery Rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGLMM\u003c/strong\u003e: Generalized Linear Mixed-Effects Model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHFP PCN\u003c/strong\u003e: Hammersmith \u0026amp; Fulham Partnership Primary Care Network\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-8\u003c/strong\u003e: Interleukin 8\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIQR\u003c/strong\u003e: Interquartile Range\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLMM\u003c/strong\u003e: Linear Mixed-Effects Model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSMMSE\u003c/strong\u003e: Standardised Mini-Mental State Examination\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNICE\u003c/strong\u003e: National Institute for Health and Care Excellence\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e: Odds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePEA\u003c/strong\u003e: Proximity Extension Assay\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePLWD\u003c/strong\u003e: People Living with Dementia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSABP\u003c/strong\u003e: Surrey and Borders Partnership NHS Foundation Trust\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUKDRI\u003c/strong\u003e: UK Dementia Research Institute\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUTI\u003c/strong\u003e: Urinary Tract Infection\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was submitted to, and approved by, the Surrey and Borders NHS Trust Research Ethics Committee (reference number: 19/LO/0102) and registered via the Integrated Research Application System (IRAS project ID: 257561). The research was conducted in accordance with the ethical principles set out in the Declaration of Helsinki. Informed consent was obtained from all participants prior to enrolment. Individuals unable to provide informed consent were excluded from participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collected during the current study and the code used to analyse the data are available from a Zenodo public repository at (10.5281/zenodo.15720387).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is supported by the UK Dementia Research Institute [award number UKI DRI-\u0026nbsp;WBCN_PA5470], through UK DRI Ltd, principally funded by the Medical Research Council, and additional funding partners Alzheimer\u0026rsquo;s Society.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.J. and R.C. are joint first authors, having both contributed equally to writing the main manuscript text, conducting the data analysis, and developing the R code. M.T., K.J., A.J.W., L.P.C., and M.A.C. provided laboratory support, including sample collection and processing for culture growth assays, dipstick tests, 16S Sanger sequencing, and Olink analyses. R.N. and D.W. provided clinical guidance and were responsible for diagnosing patients. D.J.W. and P.S.F. contributed by securing funding for the research. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the patients and study partners who took part in the study. We also thank all members of the UK Dementia Research Institute Care Research \u0026amp; Technology Centre who contributed in some way to this work; a full list of members can be found in the supplementary file \u003cem\u003e\u0026ldquo;Centre Members\u0026rdquo;\u003c/em\u003e. We are grateful to the Surrey and Borders Partnership, the sponsors of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ehttps://www.alzheimers.org.uk/sites/default/files/2018-05/Counting_the_cost_report.pdf. https://www.alzheimers.org.uk/sites/default/files/2018-05/Counting_the_cost_report.pdf. Accessed 23 Jun 2025.\u003c/li\u003e\n\u003cli\u003eNational Mental Health D and NIN. Reasons why people with dementia are admitted to a general hospital in an emergency. 2015. https://webarchive.nationalarchives.gov.uk/ukgwa/20170302124526mp_/http://www.yhpho.org.uk/default.aspx?RID=207311. Accessed 23 Jun 2025.\u003c/li\u003e\n\u003cli\u003eCounting_the_cost_report.pdf.\u003c/li\u003e\n\u003cli\u003eCorrado O, Swanson B, Hood C, Morris A, Ofili S, Capistrano J, et al. 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Int Psychogeriatr. 2011;23:496\u0026ndash;502.\u003c/li\u003e\n\u003cli\u003ePerry VH, Cunningham C, Holmes C. Systemic infections and inflammation affect chronic neurodegeneration. Nat Rev Immunol. 2007;7:161\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eDunn N, Mullee M, Perry VH, Holmes C. Association between Dementia and Infectious Disease: Evidence from a Case-Control Study. Alzheimer Dis Assoc Disord. 2005;19:91.\u003c/li\u003e\n\u003cli\u003eEAU Guidelines on Urological Infections - Uroweb. https://uroweb.org/guidelines/urological-infections. Accessed 16 Apr 2025.\u003c/li\u003e\n\u003cli\u003eUrinary tract infection: diagnostic tools for primary care. GOV.UK. 2024. https://www.gov.uk/government/publications/urinary-tract-infection-diagnosis. Accessed 16 Apr 2025.\u003c/li\u003e\n\u003cli\u003eBerman P, Hogan DB, Fox RA. The atypical presentation of infection in old age. Age Ageing. 1987;16:201\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eBai AD, Bonares MJ, Thrall S, Bell CM, Morris AM. Presence of urinary symptoms in bacteremic urinary tract infection: a retrospective cohort study of Escherichia coli bacteremia. BMC Infect Dis. 2020;20:781.\u003c/li\u003e\n\u003cli\u003eCerejeira J, Lagarto L, Mukaetova-Ladinska EB. Behavioral and Psychological Symptoms of Dementia. Front Neurol. 2012;3:73.\u003c/li\u003e\n\u003cli\u003eBoscia JA, Kobasa WD, Knight RA, Abrutyn E, Levison ME, Kaye D. Epidemiology of bacteriuria in an elderly ambulatory population. Am J Med. 1986;80:208\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eNicolle LE. Asymptomatic bacteriuria in the elderly. Infect Dis Clin North Am. 1997;11:647\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eAbrutyn E, Mossey J, Berlin JA, Boscia J, Levison M, Pitsakis P, et al. Does asymptomatic bacteriuria predict mortality and does antimicrobial treatment reduce mortality in elderly ambulatory women? Ann Intern Med. 1994;120:827\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eNicolle LE, Mayhew WJ, Bryan L. Prospective randomized comparison of therapy and no therapy for asymptomatic bacteriuria in institutionalized elderly women. Am J Med. 1987;83:27\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eDiagnosis of urinary tract infections: quick reference tools for primary care. GOV.UK. https://www.gov.uk/government/consultations/urinary-tract-infection-diagnostic-tools-for-primary-care/diagnosis-of-urinary-tract-infections-quick-reference-tools-for-primary-care. Accessed 16 Apr 2025.\u003c/li\u003e\n\u003cli\u003eRoberts KB, Wald ER. The Diagnosis of UTI: Colony Count Criteria Revisited. Pediatrics. 2018;141:e20173239.\u003c/li\u003e\n\u003cli\u003eBarratt J. What to do with patients with abnormal dipstick urinalysis. Medicine (Baltimore). 2007;35:365\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eGu J, Chen X, Yang Z, Bai Y, Zhang X. Gender differences in the microbial spectrum and antibiotic sensitivity of uropathogens isolated from patients with urinary stones. J Clin Lab Anal. 2021;36:e24155.\u003c/li\u003e\n\u003cli\u003eMagliano E, Grazioli V, Deflorio L, Leuci AI, Mattina R, Romano P, et al. Gender and Age-Dependent Etiology of Community-Acquired Urinary Tract Infections. Sci World J. 2012;2012:349597.\u003c/li\u003e\n\u003cli\u003eFlores-Mireles AL, Walker JN, Caparon M, Hultgren SJ. Urinary tract infections: epidemiology, mechanisms of infection and treatment options. Nat Rev Microbiol. 2015;13:269\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eKo YC, Mukaida N, Ishiyama S, Tokue A, Kawai T, Matsushima K, et al. Elevated interleukin-8 levels in the urine of patients with urinary tract infections. Infect Immun. 1993;61:1307\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eBecker K, Heilmann C, Peters G. Coagulase-negative staphylococci. Clin Microbiol Rev. 2014;27:870\u0026ndash;926.\u003c/li\u003e\n\u003cli\u003eEhlers S, Merrill SA. Staphylococcus saprophyticus Infection. In: StatPearls. Treasure Island (FL): StatPearls Publishing; 2025.\u003c/li\u003e\n\u003cli\u003eCodelia-Anjum A, Lerner LB, Elterman D, Zorn KC, Bhojani N, Chughtai B. Enterococcal Urinary Tract Infections: A Review of the Pathogenicity, Epidemiology, and Treatment. Antibiotics. 2023;12:778.\u003c/li\u003e\n\u003cli\u003eRodriguez-Ma\u0026ntilde;as L. Urinary tract infections in the elderly: a review of disease characteristics and current treatment options. Drugs Context. 2020;9:2020-4\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eGeerlings SE. Urinary tract infections in patients with diabetes mellitus: epidemiology, pathogenesis and treatment. Int J Antimicrob Agents. 2008;31 Suppl 1:S54-57.\u003c/li\u003e\n\u003cli\u003eTandogdu Z, Cai T, Koves B, Wagenlehner F, Bjerklund-Johansen TE. Urinary Tract Infections in Immunocompromised Patients with Diabetes, Chronic Kidney Disease, and Kidney Transplant. Eur Urol Focus. 2016;2:394\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eG\u0026aacute;gyor I, Rentzsch K, Strube-Plaschke S, Himmel W. Psychometric properties of a self-assessment questionnaire concerning symptoms and impairment in urinary tract infections: the UTI-SIQ-8. BMJ Open. 2021;11:e043328.\u003c/li\u003e\n\u003cli\u003eGiesen LG, Cousins G, Dimitrov BD, van de Laar FA, Fahey T. Predicting acute uncomplicated urinary tract infection in women: a systematic review of the diagnostic accuracy of symptoms and signs. BMC Fam Pract. 2010;11:78.\u003c/li\u003e\n\u003cli\u003eHodgson N, Gitlin LN, Winter L, Czekanski K. Undiagnosed Illness and Neuropsychiatric Behaviors In Community-residing Older Adults with Dementia. Alzheimer Dis Assoc Disord. 2011;25:109\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eMambatta AK, Jayarajan J, Rashme VL, Harini S, Menon S, Kuppusamy J. Reliability of dipstick assay in predicting urinary tract infection. J Fam Med Prim Care. 2015;4:265\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eKristensen LH, Winther R, Colding-J\u0026oslash;rgensen JT, Potteg\u0026aring;rd A, Nielsen H, Bodilsen J. Diagnostic accuracy of dipsticks for urinary tract infections in acutely hospitalised patients: a prospective population-based observational cohort study. BMJ Evid-Based Med. 2025;30:36\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eJoseph A. The Diagnosis and Management of UTI in \u0026gt;65s: To Dipstick or Not? The Argument Against Dipsticks. Infect Prev Pract. 2020;2:100063.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Urinary Tract Infection, Dementia, Neurodegenerative Disease","lastPublishedDoi":"10.21203/rs.3.rs-7185812/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7185812/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eUrinary tract infections (UTIs) are a leading cause of hospitalisation in people living with dementia (PLWD), making accurate detection and prompt treatment essential in this vulnerable population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective longitudinal cohort study assessed the concordance between self-reported symptoms, urine colony counts\u0026thinsp;\u0026gt;\u0026thinsp;10⁵ CFU/mL, dipstick results positive for leukocytes and/or nitrites, and urinary IL-8 levels in identifying UTIs among PLWD. The study included 78 community-dwelling individuals aged over 50 with a confirmed dementia diagnosis, recruited from cohorts established by the Surrey and Borders Partnership NHS Foundation Trust and the Hammersmith \u0026amp; Fulham Partnership Primary Care Network between late 2019 and 2023.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eUTI frequency among PLWD was highly variable, with some individuals experiencing recurrent infections whilst others had none throughout the study period. The microbial taxa identified were consistent with those seen in other populations. There was no clear concordance between self-reported symptoms and laboratory indicators of UTI. However, dipstick-positive results correlated with urine samples showing\u0026thinsp;\u0026gt;\u0026thinsp;10⁵ CFU/mL of a single colony morphology growth and elevated IL-8 concentrations.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eUrinary dipstick tests for nitrites and leukocytes may serve as a practical screening tool for UTIs in PLWD, particularly in individuals unable to reliably report symptoms. However, future research is needed to evaluate the clinical impact of this diagnostic approach on outcomes such as hospitalisation rates, delirium incidence, and antibiotic resistance and stewardship in this vulnerable population.\u003c/p\u003e","manuscriptTitle":"A Cohort Study of Urinary Tract Infections in People Living with Dementia: Epidemiology and Diagnostic Challenges","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-28 15:09:01","doi":"10.21203/rs.3.rs-7185812/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"25fc7e90-0cb6-45ec-a8d7-8efb43a59290","owner":[],"postedDate":"August 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-21T11:23:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-28 15:09:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7185812","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7185812","identity":"rs-7185812","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}