Background: Urinary tract infection (UTI) affects half of women at least once in their lifetime. Current diagnosis involves urinary dipstick and urine culture, yet both methods have modest diagnostic accuracy, and cannot support decision-making in patient populations with high prevalence of asymptomatic bacteriuria, such as older adults. Detecting biomarkers of host response in the urine of hosts has the potential to improve diagnosis.
Objectives: To synthesise the evidence of the diagnostic accuracy of novel biomarkers for UTI, and of their ability to differentiate UTI from asymptomatic bacteriuria.
Design: A systematic review.
Data Sources And Methods: We searched MEDLINE, EMBASE, CINAHL and Web of Science for studies of novel biomarkers for the diagnosis of UTI. We excluded studies assessing biomarkers included in urine dipsticks as these have been well described previously. We included studies of adult patients (≥16 years) with a suspected or confirmed urinary tract infection using microscopy and culture as the reference standard. We excluded studies using clinical signs and symptoms, or urine dipstick only as a reference standard. Quality appraisal was performed using QUADAS-2. We summarised our data using point estimates and data accuracy statistics.
Results: We included 37 studies on 4009 adults measuring 66 biomarkers. Study quality was limited by case-control design and study size; only 4 included studies had a prospective cohort design. IL-6 and IL-8 were the most studied biomarkers. We found plausible evidence to suggest that IL-8, IL-6, GRO-a, sTNF-1, sTNF-2 and MCR may benefit from more rigorous evaluation of their potential diagnostic value for UTI.
Conclusions: There is insufficient evidence to recommend the use of any novel biomarker for UTI diagnosis at present. Further evaluation of the more promising candidates, is needed before they can be recommended for clinical use.
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http://dx.doi.org/10.1177/11772719221144459 | DOI Listing |
J Am Med Inform Assoc
January 2025
Kennewick, WA 99338, United States.
Objective: This study evaluates the utility of word embeddings, generated by large language models (LLMs), for medical diagnosis by comparing the semantic proximity of symptoms to their eponymic disease embedding ("eponymic condition") and the mean of all symptom embeddings associated with a disease ("ensemble mean").
Materials And Methods: Symptom data for 5 diagnostically challenging pediatric diseases-CHARGE syndrome, Cowden disease, POEMS syndrome, Rheumatic fever, and Tuberous sclerosis-were collected from PubMed. Using the Ada-002 embedding model, disease names and symptoms were translated into vector representations in a high-dimensional space.
Allergol Immunopathol (Madr)
January 2025
Faculty of Medicine, Department of Pediatric Allergy and Immunology, Ondokuz Mayıs University, Samsun, Turkey.
Background: Egg allergy is among the most common food allergies in children, significantly affecting the dietary habits and quality of life of both the affected children and their families. This study aims to assess the clinical role of the Basophil Activation Test (BAT) in children with egg allergy and to evaluate its diagnostic accuracy in comparison to other tests.
Methods: The study included 46 children with egg allergy.
JAMA Netw Open
January 2025
Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania.
Importance: Recently, the US Food and Drug Administration gave premarketing approval to an algorithm based on its purported ability to identify individuals at genetic risk for opioid use disorder (OUD). However, the clinical utility of the candidate genetic variants included in the algorithm has not been independently demonstrated.
Objective: To assess the utility of 15 genetic variants from an algorithm intended to predict OUD risk.
Hum Genet
January 2025
Department of Biomedical Sciences, University of Padova, Padova, Italy.
The Genetics of Neurodevelopmental Disorders Lab in Padua provided a new intellectual disability (ID) Panel challenge for computational methods to predict patient phenotypes and their causal variants in the context of the Critical Assessment of the Genome Interpretation, 6th edition (CAGI6). Eight research teams submitted a total of 30 models to predict phenotypes based on the sequences of 74 genes (VCF format) in 415 pediatric patients affected by Neurodevelopmental Disorders (NDDs). NDDs are clinically and genetically heterogeneous conditions, with onset in infant age.
View Article and Find Full Text PDFClin Chem
December 2024
Department of Clinical Biochemistry (Synnovis), King's College Hospital NHS Foundation Trust, Denmark Hill, London SE5 9RS, United Kingdom.
Background: Noninvasive tests (NITs) to monitor metabolic dysfunction-associated steatohepatitis (MASH) progression and response to interventions are needed because of the risks of liver biopsy. A monocytes-based diagnostic test using perilipin-2 (PLIN2) and Ras-related protein-14 (RAB14) predict the severity of MASH and fibrosis. Here we compared the performances of PLIN2 and RAB14 with cytokeratin-18 (CK18) assessed by Ella™ or M65 ELISA in predicting MASH and fibrosis resolution following bariatric surgery in a longitudinal and histologically characterized cohort of individuals with obesity.
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