Practice variation in urine collection methods among pre-toilet trained children with suspected urinary tract infection: a systematic review.

BACKGROUND: Urinary tract infections (UTIs) are a common cause of acute illness among infants and young children. There are numerous methods for collecting urine in children who are not toilet trained. This review examined practice variation in the urine collection methods for diagnosing UTI in non-toilet-trained children. METHODS: A systematic review was completed by searching MEDLINE (Ovid), Embase (Ovid), CENTRAL (Ovid), PsycInfo (Ovid), CINAHL (EBSCO), and JBI (Ovid) from January 1, 2000 until October 9, 2021 and updated on May 24, 2023. Studies were included if they were conducted in an acute care facility, examined pre-toilet trained children, and compared one urine collection method with another for relevant health care outcomes (such as length of stay in an ED, or re-visits or readmissions to the ED) or provider satisfaction. Two independent reviewers screened the identified articles independently, and those included in the final analysis were assessed for quality and bias using the Newcastle-Ottawa Scale. RESULTS: Overall, 2535 articles were reviewed and 8 studies with a total of 728 children were included in the final analysis. Seven studies investigated the primary outcome of interest, practice variation in urine collection methods to diagnose a UTI. The seven studies that investigated novel methods of urine collection concluded that there were improved health care outcomes compared to conventional methods. Novel methods include emerging methods that are not captured yet captured in clinical practice guidelines including the use of ultrasound guidance to aid existing techniques. Three studies which investigated healthcare provider satisfaction found preference to novel methods of urine collection. CONCLUSIONS: There is significant practice variation in the urine collection methods within and between countries. Further research is needed to better examine practice variation among clinicians and adherence to national organizations and societies guidelines. PROSPERO registration number CRD42021267754.

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Current diagnostic strategies for UTIs, such as urine culture and flow cytometry, require time-consuming protocols and expensive equipment. We present here a machine learning-assisted colorimetric sensor array based on recognition of ligand-functionalized Fe single-atom nanozymes (SANs) for the identification of microorganisms at the order, genus, and species levels. Colorimetric sensor arrays are built from the SAN Fe1-NC functionalized with four types of recognition ligands, generating unique microbial identification fingerprints. By integrating the colorimetric sensor arrays with a trained computational classification model, the platform can identify more than 10 microorganisms in UTI urine samples within 1 h. Diagnostic accuracy of up to 97% was achieved in 60 UTI clinical samples, holding great potential for translation into clinical practice applications.

Florfenicol urinary excretion and its potential for treating canine urinary tract infections.

The canine urinary excretion of florfenicol was evaluated to explore its potential for treating urinary tract infections. Nine healthy male intact purpose-bred Beagles and four healthy client-owned dogs each received a single oral dose of florfenicol 20 mg/kg (300 mg/mL parenteral solution) with food. All voluntary urinations were collected for 12 h. Although florfenicol is reportedly bitter tasting, 7/9 Beagles and 4/4 client-owned dogs completely ingested the florfenicol and were enrolled; salivation (n = 1) and headshaking (n = 3) were observed. The last measured urine florfenicol concentrations were variable: Beagles (0.23-3.19 mcg/mL), Pug (3.01 mcg/mL) English Setter (21.29 mcg/mL), Greyhound (32.68 mcg/mL), and Standard Poodle (13.00 mcg/mL). Urine half-life was similar for the Beagles and the Pug, 0.75-1.39 h, whereas the half-life was 1.70-1.82 h for the English Setter, Greyhound, and Standard Poodle. Larger breed dogs exceeded 8 mcg/mL florfenicol (wild-type cutoff) in their urine at 12 h, whereas the Beagles and Pug had <8 mcg/mL; it is unclear if this is an individual, breed, or size difference. These data suggest oral florfenicol may need to be administered q6-12h for canine urinary tract infections, but further data are needed (more enrolled dogs, multiple-dose regimens) before considering clinical trials or breed-specific differences.

A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.

Urinary tract infection (UTI) is a common disorder. Its diagnosis can be made by microscopic examination of voided urine for markers of infection. This manual technique is technically difficult, time-consuming and prone to inter-observer errors. The application of computer vision to this domain has been slow due to the lack of a clinical image dataset from UTI patients. We present an open dataset containing 300 images and 3,562 manually annotated urinary cells labelled into seven classes of clinically significant cell types. It is an enriched dataset acquired from the unstained and untreated urine of patients with symptomatic UTI using a simple imaging system. We demonstrate that this dataset can be used to train a Patch U-Net, a novel deep learning architecture with a random patch generator to recognise urinary cells. Our hope is, with this dataset, UTI diagnosis will be made possible in nearly all clinical settings by using a simple imaging system which leverages advanced machine learning techniques.

Concentration of novel urinary tract infection biomarkers in neonates.

Urinary tract infections (UTIs) are a common comorbidity in hospitalized neonates. The current UTI diagnostics have several limitations including invasive collection of urinary samples to ensure sterility, risk of contamination and lack of consensus definitions of UTI based on urine culture. Antimicrobial peptides (AMPs) have been recently utilized as novel biomarkers that can efficiently and accurately diagnose pediatric UTI. However, the concentration of AMPs in neonatal urine is not well-defined. Urine from neonates admitted to a single level IV neonatal intensive care unit was obtained to determine baseline concentration of two AMPs, Ribonuclease 7 (RNase 7) and Beta Defensin-1 (BD-1) and to define the relationship between AMP concentration and gestational age (GA). AMP levels were normalized to urine creatinine. RNase 7 and BD-1 were expressed in neonatal urine (n = 66) regardless of GA and as early as 22 weeks gestation. Urinary concentrations of both AMPs decreased as GA and birthweight increased. The overall median urinary RNase 7/UCr and BD-1/UCr values were 271 ng/mg, and 116 ng/mg, respectively. Median urinary concentrations of RNase 7/UCr for infants born at < 27, 27-32, 33-35 and ≥ 36 weeks were 569, 308, 254, and 124 ng/mg respectively. Similarly, the concentrations of BD-1/UCr at these GA were 166, 115, 108, and 14 ng/mg, respectively. Baseline neonatal urinary concentration of two AMPs (RNase 7 and BD-1) and the variation by GA were identified. This is an essential first step toward the potential utilization of AMPs in improving neonatal UTI diagnostics.

Urine soluble TLR4 levels may contribute to predict urinary tract infection in children: the UTILISE Study.

BACKGROUND: One of the most common bacterial infections in childhood is urinary tract infection (UTI). Toll-like receptors (TLRs) contribute to immune response against UTI recognizing specific pathogenic agents. Our aim was to determine whether soluble TLR4 (sTLR4), soluble TLR5 (sTLR5) and interleukin 8 (IL-8) can be used as biomarkers to diagnose UTI. We also aimed to reveal the relationship between urine Heat Shock Protein 70 (uHSP70) and those biomarkers investigated in this study. METHODS: A total of 802 children from 37 centers participated in the study. The participants (n = 282) who did not meet the inclusion criteria were excluded from the study. The remaining 520 children, including 191 patients with UTI, 178 patients with non-UTI infections, 50 children with contaminated urine samples, 26 participants with asymptomatic bacteriuria and 75 healthy controls were included in the study. Urine and serum levels of sTLR4, sTLR5 and IL-8 were measured at presentation in all patients and after antibiotic treatment in patients with UTI. RESULTS: Urine sTLR4 was higher in the UTI group than in the other groups. UTI may be predicted using 1.28 ng/mL as cut-off for urine sTLR4 with 68% sensitivity and 65% specificity (AUC = 0.682). In the UTI group, urine sTLR4 levels were significantly higher in pyelonephritis than in cystitis (p < 0.0001). Post-treatment urine sTLR4 levels in the UTI group were significantly lower than pre-treatment values (p < 0.0001). CONCLUSIONS: Urine sTLR4 may be used as a useful biomarker in predicting UTI and subsequent pyelonephritis in children with UTI. A higher resolution version of the Graphical abstract is available as Supplementary information.

Development and validation of artificial intelligence models to predict urinary tract infections and secondary bloodstream infections in adult patients.

BACKGROUND: Traditional culture methods are time-consuming, making it difficult to utilize the results in the early stage of urinary tract infection (UTI) management, and automated urinalyses alone show insufficient performance for diagnosing UTIs. Several models have been proposed to predict urine culture positivity based on urinalysis. However, most of them have not been externally validated or consisted solely of urinalysis data obtained using one specific commercial analyzer. METHODS: A total of 259,187 patients were enrolled to develop artificial intelligence (AI) models. AI models were developed and validated for the diagnosis of UTI and urinary tract related-bloodstream infection (UT-BSI). The predictive performance of conventional urinalysis and AI algorithms were assessed by the areas under the receiver operating characteristic curve (AUROC). We also visualized feature importance rankings as Shapley additive explanation bar plots. RESULTS: In the two cohorts, the positive rates of urine culture tests were 25.2% and 30.4%, and the proportions of cases classified as UT-BSI were 1.8% and 1.6%. As a result of predicting UTI from the automated urinalysis, the AUROC were 0.745 (0.743-0.746) and 0.740 (0.737-0.743), and most AI algorithms presented excellent discriminant performance (AUROC > 0.9). In the external validation dataset, the XGBoost model achieved the best values in predicting both UTI (AUROC 0.967 [0.966-0.968]) and UT-BSI (AUROC 0.955 [0.951-0.959]). A reduced model using ten parameters was also derived. CONCLUSIONS: We found that AI models can improve the early prediction of urine culture positivity and UT-BSI by combining automated urinalysis with other clinical information. Clinical utilization of the model can reduce the risk of delayed antimicrobial therapy in patients with nonspecific symptoms of UTI and classify patients with UT-BSI who require further treatment and close monitoring.

Point-of-care rapid immunoassay performed on voided urine, refrigerated up to 24 hours, accurately detects bacteriuria.

OBJECTIVE: To collect voided urine from dogs with clinical signs of lower UTI and determine the diagnostic performance of a commercially available rapid immunoassay (RIA) immediately after urine collection and after refrigeration at 4 and 24 hours. ANIMALS: 40 client-owned dogs. METHODS: Aerobic urine culture was performed on urine collected by cystocentesis. Urine samples were collected by voiding, and the RIA performed in triplicate within 30 minutes (time 0) and again in triplicate after 4 and 24 hours of refrigeration. Test precision and agreement between culture results and RIA results at each time point were determined, and factors possibly associated with false results investigated. RESULTS: 14 of 40 dogs (35%) had UTI verified by aerobic urine culture, and all had positive RIA. Three dogs had false positive RIA results. Sensitivity, specificity, positive predictive value, and negative predictive value of the RIA were 100, 88%, 82%, and 100%, respectively, and results were not different after 4 and 24 hours of refrigeration. Precision was excellent. CLINICAL RELEVANCE: This point-of-care RIA, performed on voided urine refrigerated up to 24 hours, rapidly and accurately identifies bacteriuria in dogs with lower urinary tract clinical signs, inexpensively.

A fully interpretable machine learning model for increasing the effectiveness of urine screening.

OBJECTIVES: This article addresses the need for effective screening methods to identify negative urine samples before urine culture, reducing the workload, cost, and release time of results in the microbiology laboratory. We try to overcome the limitations of current solutions, which are either too simple, limiting effectiveness (1 or 2 parameters), or too complex, limiting interpretation, trust, and real-world implementation ("black box" machine learning models). METHODS: The study analyzed 15,312 samples from 10,534 patients with clinical features and the Sysmex Uf-1000i automated analyzer data. Decision tree (DT) models with or without lookahead strategy were used, as they offer a transparent set of logical rules that can be easily understood by medical professionals and implemented into automated analyzers. RESULTS: The best model achieved a sensitivity of 94.5% and classified negative samples based on age, bacteria, mucus, and 2 scattering parameters. The model reduced the workload by an additional 16% compared to the current procedure in the laboratory, with an estimated financial impact of €40,000/y considering 15,000 samples/y. Identified logical rules have a scientific rationale matched to existing knowledge in the literature. CONCLUSIONS: Overall, this study provides an effective and interpretable screening method for urine culture in microbiology laboratories, using data from the Sysmex UF-1000i automated analyzer. Unlike other machine learning models, our model is interpretable, generating trust and enabling real-world implementation.

Evaluation of urine dipstick tests in experimental porcine urinary tract infection with uropathogenic Escherichia coli.

Urinary tract infection is a common disease in pigs and a major reason for sows to be culled. The disease, however, is difficult to diagnose due to lack of distinct clinical signs in the animals. We evaluated the diagnostic value of two commercial urine dipstick tests in 10 pigs using an experimental model of Escherichia coli urinary tract infection. Urine collected at baseline and 48 h after inoculation were analyzed. We show that dipstick tests positive of blood, leucocytes and particularly nitrite are very specific for E. coli UTI with a 100% positive predictive value.

Rapid Screening of Urinary Tract Infection Using Microfluidic Inertial-Impedance Cytometry.

Urinary tract infection (UTI) diagnosis based on urine culture for bacteriuria analysis is time-consuming and often leads to wastage of hospital resources due to false-positive UTI cases. Direct cellular phenotyping (e.g., RBCs, neutrophils, epithelial cells) of urine samples remains a technical challenge as low cell concentrations, and urine characteristics (conductivities, pH, microbes) can affect the accuracy of cell measurements. In this work, we report a microfluidic inertial-impedance cytometry technique for label-free rapid (<5 min) neutrophil sorting and impedance profiling from urine directly. Based on size-based inertial focusing effects, neutrophils are isolated, concentrated, and resuspended in saline (buffer exchange) to improve consistency in impedance-based single-cell analysis. We first observed that both urine pH and the presence of bacteria can affect neutrophil high-frequency impedance measurements possibly due to changes in nucleus morphology as neutrophils undergo NETosis and phagocytosis, respectively. As a proof-of-concept for clinical testing, we report for the first time, rapid UTI testing based on multiparametric impedance profiling of putative neutrophils (electrical size, membrane properties, and distribution) in urine samples from non-UTI (n = 20) and UTI patients (n = 20). A significant increase in cell count was observed in UTI samples, and biophysical parameters were used to develop a UTI classifier with an area under the receiver operating characteristic curve of 0.84. Overall, the developed platform facilitates rapid culture-free urine screening which can be further developed to assess disease severity in UTI and other urologic diseases based on neutrophil electrical signatures.

The diagnostic performances of the Atellica® 1500 automated urinalysis system for ruling out bacterial urinary tract infection.

Urinary tract infection (UTI) is one of the most common diseases occurring in both hospitalized and community subjects. Urine culture is the gold standard test for the diagnosis of UTI, but approximately 80% are negative. The aim of this study was to evaluate the performance of the automated urinalysis system Atellica® 1500 (Siemens Healthineers, Erlangen, Germany) as screening tool for ruling out UTI. A total of 5,490 urine specimens from outpatients, that had simultaneous requests for urinalysis and urine culture, were evaluated. Of the 5,490 samples, 833 (15.2 %) resulted positive for urine culture. Among UTI-related parameters, bacterial count was considered the most apt to be diagnostic of subjects affected by UTI. Using a cutoff value for bacteria count equal to 180 elements/µL, Atellica® 1500 detected bacteriuria with diagnostic sensitivity (Se) of 88.1 %, diagnostic specificity (Sp) of 82.1 %, and negative predictive value (NPV) of 95.2 %. Comparing our results with the literature's data, we observed that our Se and NPV were lower, while our Sp was higher. Our data showed that the Atellica® 1500 system detected bacteria with satisfactory analytical performance, but the results obtained do not make it a reliable tool for excluding UTI with urinalysis.

Nitrofurantoin for the treatment of uncomplicated urinary tract infection in female patients: the impact of dosing regimen, age, and renal function on drug exposure.

PURPOSE: The aim of this study is to determine nitrofurantoin exposure in female patients with different age and renal function with complaints of an uncomplicated UTI. Also the nitrofurantoin exposure in relation to the dosage regimen will be studied. METHODS: Eight general practitioners (GP) participated in the study and included 38 patients with symptoms of an uncomplicated UTI, treated either with a dose of 50 mg q6h or 100 mg q12h, upon the discretion of the GP. Nitrofurantoin exposure was quantified in the patient's 24-h urine samples by UHPLC-UV and the area under the curve was calculated. RESULTS: The 38 patients provided a range of 2-17 urine samples. The urine nitrofurantoin exposure was 1028 mg h/L for the patients receiving 50 mg q6h and 1036 mg h/L for those treated with 100 mg q12h (p = 0.97) and was not affected by age and eGFR (p = 0.64 and p = 0.34, respectively). CONCLUSION: The data obtained do not support the discouragement of nitrofurantoin use in the elderly and in patients with impaired renal function. Since only a small number of patients were included, a larger study with more patients is warranted to evaluate nitrofurantoin exposure and adverse effects.

Urine specific gravity, pyuria, and neutrophil gelatinase-associated lipocalin for identifying urinary tract infection in young children.

BACKGROUND: To determine whether urine neutrophil gelatinase-associated lipocalin (uNGAL) might be superior to pyuria for detecting urinary tract infection (UTI) regardless of urine specific gravity (SG) in young children. METHODS: We conducted a retrospective analysis of children aged < 3 years who were evaluated for UTI with urinalysis, urine culture, and uNGAL measurements during a 5-year period. Sensitivity, specificity, likelihood ratios (LRs), predictive values (PVs), area under the curves (AUCs) of uNGAL cut-off levels, and various microscopic pyuria thresholds for detecting UTI were calculated for dilute (SG < 1.015) and concentrated urine (SG ≥ 1.015). RESULTS: Of 456 children included, 218 had UTI. The diagnostic value of urine white blood cell (WBC) concentration to define UTI changed with urine SG. For detecting UTI, uNGAL cut-off of 68.4 ng/mL had higher AUC values than pyuria ≥ 5 WBCs/high power field (HPF) for dilute and concentrated urine samples (both P < 0.05). Positive LR and PV and specificity of uNGAL were all greater than those of pyuria ≥ 5 WBCs/HPF regardless of urine SG, although the sensitivity of pyuria ≥ 5 WBCs/HPF was higher than that of uNGAL cut-off for dilute urine (93.8% vs. 83.5%) (P < 0.05). At uNGAL ≥ 68.4 ng/mL and ≥ 5 WBCs/HPF, posttest probabilities of UTI were 68.8% and 57.5% for dilute urine and 73.4% and 57.3% for concentrated urine, respectively. CONCLUSIONS: Urine SG can affect the diagnostic performance of pyuria for detecting UTI and uNGAL might be helpful for identifying UTI regardless of urine SG in young children. A higher resolution version of the Graphical abstract is available as Supplementary information.

Susceptibility of urinary Enterobacteriaceae to selected antimicrobials in an out-patient setting in Wallonia-Belgium: retrospective analysis over 5 years period (2018-2022).

OBJECTIVE: Increasing antimicrobial resistance in urinary tract infection is a major healthcare concern. In this study, we evaluate the patterns of resistance exhibited by the most implicated microorganisms in urine infections. This approach is a prerequisite for an appropriate and successful empiric therapy in ambulatory patients. METHODS: A retrospective study was carried out from January 2018 to September 2022 in Synlab-Collard laboratory, Liège, Belgium; a total of 129,939 Enterobacteriaceae isolated from 120,616 positive urine sample were included. RESULTS: Sex ratio is 81.6% female and 18.4% male. E. coli is the most common urinary pathogen (70.4% of cases), followed by Klebsiella spp. (13.5%), Proteus spp. (8.5%), and Citrobacter spp. (2.5%). Ampicillin shows the highest resistance at 56%. Nitrofurantoin, the recommended antimicrobial treatment for cystitis in Belgium, expresses an overall resistance rate of 19% in females and 32% in males peaking at 43% in males over 80 years. Fosfomycin and ciprofloxacin display higher resistance rates in subjects over the age of 80 (18%, 24% in females, and 25%, 35% in males respectively). Trimethoprim shows 24% and 29% resistance rate in females and males over the age of 80 respectively. CONCLUSION: Even if empiric treatment of suspected UTIs may be of benefit in some cases, it is important for healthcare providers to carefully consider its limitations and evaluate its potential failure rate based on the resistance profiles of urinary Enterobacteriaceae. Susceptibility tests should be performed, and treatments adjusted especially in elderly populations.

Accuracy of NGAL as a Biomarker for Urinary Tract Infection in Young Febrile Children: An Individual Patient Data Meta-Analysis.

OBJECTIVE: To compare the accuracy of urine neutrophil gelatinase-associated lipocalin (NGAL) and leukocyte esterase (LE) for the diagnosis of urinary tract infection (UTI) in children. STUDY DESIGN: We performed a systematic review and individual patient data meta-analysis of studies that examined urine NGAL as a marker of UTI in children <18 years of age. We created a standardized definition of UTI and applied it to all included children. We compared sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) of NGAL with LE. RESULTS: We included individual patient data from 3 studies for a total of 845 children. Included children had a mean age of 0.9 years (SD, 0.6 years). Using a cutoff of 32.7 ng/mL, NGAL had a sensitivity of 90.3% (95% CI: 83.2%-95.0%) and specificity of 93.7% (95% CI: 91.7%-95.4%) for the diagnosis of UTI. LE, using a cutoff of ≧ trace had a sensitivity of 81.1% (95% CI: 72.5%-87.9%) and specificity of 97.0% (95% CI: 95.4%-98.1%). The AUC for NGAL was 0.95 (95% CI: 0.92-0.98). The AUC for LE was 0.90 (95% CI: 0.86-0.93). CONCLUSION: In young, febrile children, urinary NGAL is more sensitive for the diagnosis of UTI than LE but is slightly less specific.

Clean-catching urine from pigs: A method for collecting quality specimens for urinalysis and microbiological culturing in a laboratory environment.

Urine is an important biological specimen for assessing various metabolic functions and drug clearance. In urinary tract infection research, urine is particularly important as urinary bacterial titres constitute the main diagnostic outcome for assessing the course of infection. Collecting uncontaminated urine samples from pigs can be done by bladder catheterization or suprapubic bladder aspiration, which are both laborious and invasive procedures that require the need for anaesthesia. To improve animal welfare and optimize urine sampling protocols, we developed a method of clean-catching midstream urine specimens from pigs during spontaneous micturition. The quality of urine specimens collected by clean-catch, bladder catheter and suprapubic bladder aspiration were compared using microbiological culturing. We show that urine specimens collected by clean-catch are only minimally contaminated by skin- and vaginal-commensals with no influence on urinary bacterial titres during ongoing infection. In conclusion, we describe a method in which spontaneous micturition can be prompted in pigs, facilitating fast and reliable collection of quality specimens suitable for microbiological culturing. The method supersedes the need for anaesthesia, which not only represents a considerable refinement in terms of animal welfare but also facilitates more frequent collection of specimens that can enhance the scientific outcome of experimental animal studies in pigs.

Urine collection methods in precontinent children treated at the paediatric emergency department.

AIM: To describe the urine collection methods used in precontinent children presenting at the Paediatric Emergency Department (PED) and compare results and contamination rates. METHODS: Retrospective observational cohort study that included 1678 urine cultures collected in infants <24 months of age between January 2016 and December 2019. Urine cultures were compared based on collection technique, sex and patient age. RESULTS: In total, 60.4% of samples were collected by clean-catch urine collection (CCUC), 26.4% by urethral catheterisation (UC) and 13.2% by urine bag (UB). Contamination rates were 2.9% (95% CI 1.3, 4.4) for UC, 11.3% (95% CI 9.3, 13.2) for CCUC and 23.4% (95% CI 17.8, 29.0) for UB. Significant differences in contamination rates were found between UC and CCUC in the 6-12-month age group (1.9% [95% CI 0.0-4.0] versus 12.0% [95% CI 7.2-16.8] [p < 0.0009]), and between UC and UB for all ages. CONCLUSIONS: CCUC is the most common method for urine culture collection in infants <24 months of age at the PED in our centre. UC has the lowest contamination rates, but significant differences were only observed between CCUC and UC in the 6-12-month age group. CCUC is a non-invasive alternative for urine collection in infants.

Office-Based Urinalysis: A Comprehensive Review.

Comprehensive urinalysis involves inspection of the urine, dipstick chemical analysis, and microscopy and can be performed in the office setting. When testing for urinary tract infection, midstream urine should be collected using the clean-catch technique. A urine collection bag specimen can be used for clinically stable febrile infants with suspected urinary tract infection; however, the presence of leukocyte esterase or nitrites warrants more invasive urine collection. Urine specific gravity shows hydration status. Urinary pH levels can indicate diet, metabolism, or the presence of stones. Bilirubin and urobilinogen may suggest hepatobiliary disease or hemolysis. Glucosuria often indicates uncontrolled diabetes mellitus, and ketones suggest illness and inadequate nutrition. Hematuria on dipstick testing can be confirmed in the office using a spun urine sample. Proteinuria on dipstick testing should be followed by a quantitative test such as a spot urine albumin/creatinine ratio. In patients with symptoms of a urinary tract infection, the presence of nitrites is more specific for bacterial infection, and a positive leukocyte esterase result may occur from inflammation and infection. Asymptomatic bacteriuria is often unnecessarily treated in older patients. Without symptoms of urinary tract infection, urine culture is useful only in pregnancy and preparation for endoscopic urologic procedures.

Women's information needs around urine testing for urinary tract infections: a qualitative study.

BACKGROUND: Urinary tract infection (UTI) is one of the commonest bacterial infections in general practice, with urine testing a frequent feature of its management. Urinary dipsticks are widely used, with urine culture the reference standard test. To avoid contamination, patients are advised to discard the first part of the urine stream, retaining the midstream part for the sample. This process, however, can be challenging both to explain and to perform. There is a lack of literature investigating women's perceptions and understanding of urine sampling. AIM: To explore women's understanding of urine collection, sample contamination, and how information from samples informed UTI management. DESIGN AND SETTING: Qualitative study embedded in a UK randomised controlled trial (RCT) of urinary collection devices (UCDs) among women attending primary care with a suspected UTI. METHOD: Semi-structured telephone interviews were conducted with 29 women participating in the RCT. Interviews were transcribed and thematically analysed. RESULTS: Participants were not always aware about what midstream samples were and why they were preferable. They also lacked understanding about how urine samples may be contaminated, and sources of contamination. Participants experienced variability in the information received following analysis of their sample. CONCLUSION: Provision of clear information could help provide better urine samples, aiding the diagnosis of UTIs, presenting results with greater clarity, and creating less need for repeat samples. Sharing of information derived from uncontaminated samples may also support better UTI management, helping to reduce unnecessary prescribing and antibiotic resistance.