The Role of Anterior Vaginal Prolapse in Co-Existent Underactive Overactive Bladder Syndrome-A Retrospective Cohort Study.

CUOB (co-existent underactive overactive bladder) syndrome is a clinical entity that embraces storage and emptying symptoms, not strictly correlated with urodynamic findings. We assessed the differences between patients diagnosed with CUOB with/without cystocele. The study group was allocated from 2000 women who underwent urodynamic studies between 2008 and 2016.

National Survey on the Management of Genital Prolapse in Italy.

Purpose: Surgical repair is considered the mainstay of genital prolapse management. Several procedures are available both by vaginal and abdominal route, with and without mesh augmentation. The Italian UroGynecology Association (AIUG) promoted this survey with the aim of evaluating current variations in the surgical management of various types of prolapse in different clinical settings and to compare practice amongst practitioners working in high- and medium/low-volume centers.

The Evil Twins of Chronic Pelvic Pain Syndrome: A Systematic Review and Meta-Analysis on Interstitial Cystitis/Painful Bladder Syndrome and Endometriosis.

Background: Chronic pelvic pain is a debilitating condition affecting quality of life. Endometriosis is one of the leading causes of CPP, but recent studies highlighted the role of interstitial cystitis/bladder pain syndrome (IC/PBS) in causing CPP. Only some studies addressed the coexistence of these two conditions, which seems more frequent than what is supposed, leading to diagnostic delays and unnecessary surgeries.

External validation of SpineNetV2 on a comprehensive set of radiological features for grading lumbosacral disc pathologies.

Background: In recent years, the integration of Artificial Intelligence (AI) models has revolutionized the diagnosis of Low Back Pain (LBP) and associated disc pathologies. Among these, SpineNetV2 stands out as a state-of-the-art, open-access model for detecting and grading various intervertebral disc pathologies. However, ensuring the reliability and applicability of AI models like SpineNetV2 is paramount.