Metaepidemiological Inventory of Diagnostic Studies on Urodynamics

An automatic diagnostic system for the urodynamic study applying in lower urinary tract dysfunction

OBJECTIVE

To establish an automatic diagnostic system based on machine learning for preliminarily analysis of urodynamic study applying in lower urinary tract dysfunction (LUTD).

METHODS

The eight most common conditions of LUTDs were included in the present study. A total of 527 eligible patients with complete data, from the year of 2015 to 2020, were enrolled in this study. In total, two global parameters (patients' age and sex) and 13 urodynamic parameters were considered to be the input for machine learning algorithms. Three machine learning approaches were applied and evaluated in this study, including Decision Tree (DT), Logistic Regression (LR), and Support Vector Machine (SVM).

RESULTS

By applying machine learning algorithms into the 8 common LUTDs, the DT models achieved the AUC of 0.63-0.98, the LR models achieved the AUC of 0.73-0.99, and the SVM models achieved the AUC of 0.64-1.00. For mutually exclusive diagnoses of underactive detrusor and acontractile detrusor, we developed a classification model that classifies the patients into either of these two diseases or double-negative class. For this classification method, the DT models achieved the AUC of 0.82-0.85 and the SVM models achieved the AUC of 0.86-0.90. Among all these models, the LR and the SVM models showed better performance. The best model of these diagnostic tasks achieved an average AUC of 0.90 (0.90 ± 0.08).

CONCLUSIONS

An automatic diagnostic system was developed using three machine learning models in urodynamic studies. This automated machine learning process could lead to promising assistance and enhancements of diagnosis and provide more useful reference for LUTD treatment.

Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective

According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.

Neuro-Urology and Biobanking: An Integrated Approach for Advancing Research and Improving Patient Care

Understanding the molecular mechanisms underlying neuro-urological disorders is crucial for the development of targeted therapeutic interventions. Through the establishment of comprehensive biobanks, researchers can collect and store various biological specimens, including urine, blood, tissue, and DNA samples, to study these mechanisms. In the context of neuro-urology, biobanking facilitates the identification of genetic variations, epigenetic modifications, and gene expression patterns associated with neurogenic lower urinary tract dysfunction. These conditions often present as symptoms of neurological diseases such as Alzheimer's disease, multiple sclerosis, Parkinson's disease, spinal cord injury, and many others. Biobanking of tissue specimens from such patients is essential to understand why these diseases cause the respective symptoms and what can be done to alleviate them. The utilization of high-throughput technologies, such as next-generation sequencing and gene expression profiling, enables researchers to explore the molecular landscape of these conditions in an unprecedented manner. The development of specific and reliable biomarkers resulting from these efforts may help in early detection, accurate diagnosis, and effective monitoring of neuro-urological conditions, leading to improved patient care and management. Furthermore, these biomarkers could potentially facilitate the monitoring of novel therapies currently under investigation in neuro-urological clinical trials. This comprehensive review explores the synergistic integration of neuro-urology and biobanking, with particular emphasis on the translation of biobanking approaches in molecular research in neuro-urology. We discuss the advantages of biobanking in neuro-urological studies, the types of specimens collected and their applications in translational research. Furthermore, we highlight the importance of standardization and quality assurance when collecting samples and discuss challenges that may compromise sample quality and impose limitations on their subsequent utilization. Finally, we give recommendations for sampling in multicenter studies, examine sustainability issues associated with biobanking, and provide future directions for this dynamic field.

Rosier P, Serati M, Solomon E, van Koeveringe G, Bachmann LM, Kessler TM. Randomised Controlled Trials Assessing the Clinical Value of Urodynamic Studies: A Systematic Review and Meta-analysis

Context

The role of urodynamic studies (UDSs) in the diagnosis of lower urinary tract symptoms (LUTS) is crucial. Although expert statements and guidelines underline their value for clinical decision-making in various clinical settings, the academic debate as to their impact on patient outcomes continues.

Objective

To summarise the evidence from all randomised controlled trials assessing the clinical usefulness of UDS in the management of LUTS.

Evidence acquisition

For this systematic review, searches were performed without language restrictions in three electronic databases until November 18, 2020. The inclusion criteria were randomised controlled study design and allocation to receive UDS or not prior to any clinical management. Quality assessment was performed by two reviewers independently, using the Cochrane Collaboration’s tool for assessing the risk of bias. A random-effect meta-analysis was performed on the uniformly reported outcome parameters.

Evidence synthesis

Eight trials were included, and all but two focused on women with pure or predominant stress urinary incontinence (SUI). A meta-analysis of six studies including 942 female patients was possible for treatment success, as defined by the authors (relative risk 1.00, 95% confidence interval: 0.93–1.07), indicating no difference in efficacy when managing women with UDS.

Conclusions

Although UDSs are not replaceable in diagnostics, since there is no other equivalent method to find out exactly what the lower urinary tract problem is, there are little data supporting its impact on outcomes. Randomised controlled trials have focussed on a small group of women with uncomplicated SUI and showed no added value, but these findings cannot be extrapolated to the overall patient population with LUTS, warranting further well-designed trials.

Patient summary

Despite urodynamics being the gold standard to assess lower urinary tract symptoms (LUTS), as it is the only method that can specify lower urinary tract dysfunction, more studies assessing the clinical usefulness of urodynamic studies (UDSs) in the management of LUTS are needed. UDS investigation is not increasing the probability of success in the treatment of stress urinary incontinence.