Diagnosis of urinary tract infections in the pediatric population - current practices, advances and progress
Maria Bitsori1, Roza-Ioanna Poulaki1, Emmanouil Galanakis1,2
1Department of Paediatrics, University Hospital of Heraklion, Heraklion, Greece.
Insights
Diagnosing pediatric urinary tract infections (UTIs) is challenging. Novel diagnostics like biosensors and AI prediction models offer faster, more accurate results, improving treatment strategies for children.
Area of Science:
- Pediatric infectious diseases
- Diagnostic technologies
- Medical informatics
Background:
- Pediatric urinary tract infection (UTI) diagnosis is complex due to non-specific symptoms and delayed results from current urine culture methods.
- Accurate and timely diagnosis is crucial for effective treatment and management of pediatric UTIs.
- Existing diagnostic strategies lack specificity and efficiency, highlighting the need for advanced approaches.
Purpose of the Study:
- To review current diagnostic methods for pediatric UTIs.
- To explore emerging technologies and future perspectives in UTI diagnostics for children.
- To assess the potential of novel host-based, pathogen-directed methods, and AI prediction models.
Main Methods:
- Narrative review of recent literature on UTI diagnostics in children.
- Literature search conducted using PubMed, focusing on novel technologies and prediction models.
- Analysis of advancements in point-of-care, laboratory-based, and host-response diagnostic approaches.
Main Results:
- Novel diagnostics, including biosensors and molecular techniques, provide rapid pathogen identification and antibiotic susceptibility testing within hours.
- Host-response diagnostics using urine biomarkers show promise but require further development.
- Artificial intelligence (AI)-based prediction models are advancing rapidly for personalized UTI risk assessment.
Conclusions:
- Emerging diagnostic technologies significantly improve the speed and accuracy of pediatric UTI detection.
- Future UTI management in children may involve integrated approaches combining rapid diagnostics and AI-driven predictions.
- Continued research into host-response biomarkers and AI integration is essential for optimizing pediatric UTI care.
Introduction:
One of the most controversial issues surrounding the management of urinary tract infection (UTI) in children remains that of diagnosis, which is paramount for successful therapeutics and overall management, due to lack of specific symptoms, sampling difficulties and debatable diagnostic criteria, all characteristics that differentiate pediatric from adult UTI. The current diagnostic strategy, based on urine culture, lacks specificity and entails considerable delay until the availability of the results.
Areas Covered:
This narrative review includes current diagnostics and their future perspectives with the integration of new technologies, novel host-based and pathogen-directed diagnostic methods and prediction models. Literature search was performed using Pubmed, focusing on recent publications about diagnostics of UTI and their use in children.
Expert Opinion:
Novel diagnostics include ultra-sensitive biosensors at point-of-care level and light-scattering, advanced microscopy and molecular techniques at laboratory level and have achieved reliable pathogen identification and provision of antibiotic susceptibility testing within hours instead of days. Less progress has been made in host-response approaches, based mostly on urine biomarkers, which nevertheless remain a promising field. Prediction models based on artificial intelligence (AI) methods are developing fast and with the combination of all information relevant to UTI can significantly contribute to individualized patient-tailored predictions.
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