Dataset Information

Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms.

ABSTRACT: Women with uncomplicated urinary tract infection (UTI) symptoms are commonly treated with empirical antibiotics, resulting in overuse of antibiotics, which promotes antimicrobial resistance. Available diagnostic tools are either not cost-effective or diagnostically sub-optimal. Here, we identified clinical and urinary immunological predictors for UTI diagnosis. We explored 17 clinical and 42 immunological potential predictors for bacterial culture among women with uncomplicated UTI symptoms using random forest or support vector machine coupled with recursive feature elimination. Urine cloudiness was the best performing clinical predictor to rule out (negative likelihood ratio [LR-]?=?0.4) and rule in (LR+?=?2.6) UTI. Using a more discriminatory scale to assess cloudiness (turbidity) increased the accuracy of UTI prediction further (LR+?=?4.4). Urinary levels of MMP9, NGAL, CXCL8 and IL-1? together had a higher LR+ (6.1) and similar LR- (0.4), compared to cloudiness. Varying the bacterial count thresholds for urine culture positivity did not alter best clinical predictor selection, but did affect the number of immunological predictors required for reaching an optimal prediction. We conclude that urine cloudiness is particularly helpful in ruling out negative UTI cases. The identified urinary biomarkers could be used to develop a point of care test for UTI but require further validation.

SUBMITTER: Gadalla AAH

PROVIDER: S-EPMC6928162 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms.

Gadalla Amal A H AAH Friberg Ida M IM Kift-Morgan Ann A Zhang Jingjing J Eberl Matthias M Topley Nicholas N Weeks Ian I Cuff Simone S Wootton Mandy M Gal Micaela M Parekh Gita G Davis Paul P Gregory Clive C Hood Kerenza K Hughes Kathryn K Butler Christopher C Francis Nick A NA

Scientific reports 20191223 1

Women with uncomplicated urinary tract infection (UTI) symptoms are commonly treated with empirical antibiotics, resulting in overuse of antibiotics, which promotes antimicrobial resistance. Available diagnostic tools are either not cost-effective or diagnostically sub-optimal. Here, we identified clinical and urinary immunological predictors for UTI diagnosis. We explored 17 clinical and 42 immunological potential predictors for bacterial culture among women with uncomplicated UTI symptoms usin ...[more]

PMID: 31873085

Similar Datasets

Project description:Background Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in adults. Thus, novel reliable biomarkers need to be further explored to increase diagnostic, therapeutic, and prognostic effectiveness. Methods Six datasets containing CLL and control samples were downloaded from the Gene Expression Omnibus database. Differential gene expression analysis, weighted gene coexpression network analysis (WGCNA), and the least absolute shrinkage and selection operator (LASSO) regression were applied to identify potential diagnostic biomarkers for CLL using R software. The diagnostic performance of the hub genes was then measured by the receiver operating characteristic (ROC) curve analysis. Functional analysis was implemented to uncover the underlying mechanisms. Additionally, correlation analysis was performed to assess the relationship between the hub genes and immunity characteristics. Results A total number of 47 differentially expressed genes (DEGs) and 25 candidate hub genes were extracted through differential gene expression analysis and WGCNA, respectively. Based on the 14 overlapped genes between the DEGs and the candidate hub genes, LASSO regression analysis was used, which identified a final number of six hub genes as potential biomarkers for CLL: ABCA6, CCDC88A, PMEPA1, EBF1, FILIP1L, and TEAD2. The ROC curves of the six genes showed reliable predictive ability in the training and validation cohorts, with all area under the curve (AUC) values over 0.80. Functional analysis revealed an abnormal immune status in the CLL patients. A significant correlation was found between the hub genes and the immune-related pathways, indicating a possible tight connection between the hub genes and tumor immunity in CLL. Conclusion This study was based on machine learning algorithms, and we identified six genes that could be possible CLL markers, which may be involved in CLL pathogenesis and progression through immune-related signal pathways.

Project description:BackgroundEffective alternatives to antibiotics for alleviating symptoms of acute infections may be appealing to patients and enhance antimicrobial stewardship. Cranberry-based products are already in wide use for symptoms of acute urinary tract infection (UTI). The aim of this review was to identify and critically appraise the supporting evidence.MethodsThe protocol was registered on PROSPERO. Searches were conducted of Medline, Embase, Amed, Cinahl, The Cochrane library, Clinicaltrials.gov and WHO International Clinical Trials Registry Platform. We included randomised clinical trials (RCTs) and non-randomised studies evaluating the effect of cranberry extract in the management of acute, uncomplicated UTI on symptoms, antibiotic use, microbiological assessment, biochemical assessment and adverse events. Study risk of bias assessments were made using Cochrane criteria.ResultsWe included three RCTs (n = 688) judged to be at moderate risk of bias. One RCT (n = 309) found that advice to consume cranberry juice had no statistically significant effect on UTI frequency symptoms (mean difference (MD) -0.01 (95% CI: -0.37 to 0.34), p = 0.94)), on UTI symptoms of feeling unwell (MD 0.02 (95% CI: -0.36 to 0.39), p = 0.93)) or on antibiotic use (odds ratio 1.27 (95% CI: 0.47 to 3.43), p = 0.64), when compared with promoting drinking water. One RCT (n = 319) found no symptomatic benefit from combining cranberry juice with immediate antibiotics for an acute UTI, compared with placebo juice combined with immediate antibiotics. In one RCT (n = 60), consumption of cranberry extract capsules was associated with a within-group improvement in urinary symptoms and Escherichia coli load at day 10 compared with baseline (p < 0.01), which was not found in untreated controls (p = 0.72). Two RCTs were under-powered to detect differences between groups for outcomes of interest. There were no serious adverse effects associated with cranberry consumption.ConclusionThe current evidence base for or against the use of cranberry extract in the management of acute, uncomplicated UTIs is inadequate; rigorous trials are needed.

Project description:Study questionCan treatment of the symptoms of uncomplicated urinary tract infection (UTI) with ibuprofen reduce the rate of antibiotic prescriptions without a significant increase in symptoms, recurrences, or complications?MethodsWomen aged 18-65 with typical symptoms of UTI and without risk factors or complications were recruited in 42 German general practices and randomly assigned to treatment with a single dose of fosfomycin 3 g (n=246; 243 analysed) or ibuprofen 3 × 400 mg (n=248; 241 analysed) for three days (and the respective placebo dummies in both groups). In both groups additional antibiotic treatment was subsequently prescribed as necessary for persistent, worsening, or recurrent symptoms. The primary endpoints were the number of all courses of antibiotic treatment on days 0-28 (for UTI or other conditions) and burden of symptoms on days 0-7. The symptom score included dysuria, frequency/urgency, and low abdominal pain.Study answer and limitationsThe 248 women in the ibuprofen group received significantly fewer course of antibiotics, had a significantly higher total burden of symptoms, and more had pyelonephritis. Four serious adverse events occurred that lead to hospital referrals; one of these was potentially related to the trial drug. Results have to be interpreted carefully as they might apply to women with mild to moderate symptoms rather than to all those with an uncomplicated UTI.What this paper addsTwo thirds of women with uncomplicated UTI treated symptomatically with ibuprofen recovered without any antibiotics. Initial symptomatic treatment is a possible approach to be discussed with women willing to avoid immediate antibiotics and to accept a somewhat higher burden of symptoms.Funding, competing interests, data sharingGerman Federal Ministry of Education and Research (BMBF) No 01KG1105. Patient level data are available from the corresponding author. Patient consent was not obtained but the data are anonymised and risk of identification is low.Trial registration No ClinicalTrialGov Identifier NCT01488955.

Dataset Information

Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms.

Publications

Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets