Current Opinion in Urology最新文献

Purpose of review: Bladder stones account for 5% of all urinary tract calculi. Contributing factors include bladder outflow obstruction, infections, foreign bodies, or neurogenic voiding dysfunction. This necessitates an effective treatment modality, and with advances in medical technology, minimally invasive techniques using lasers are being widely adopted. This systematic review aims to assess the efficacy and safety of laser lithotripsy for treating bladder stones.

Recent findings: A thorough literature review (PROSPERO: CRD 42024551910) was conducted using appropriate search terms up to March 2024. Only original studies written in English, with at least 10 patients with bladder stones treated with laser, were considered with inclusion. A total of 8 studies (411 patients) were identified on screening with a mean age of 59.6 ± 8.5 years and a male: female ratio of 326 : 14. These reviews covered a geographical area of Asia, Europe, and the USA. The mean stone size was 3.7 ± 0.7 cm, and an overall stone-free rate (SFR) postlaser lithotripsy was 96%. Mean operation time was calculated to be 76.36 ± 47.10 min and an overall complication rate of 16.5% ( n  = 68), with the most common being haematuria ( n  = 22), followed by UTI ( n  = 18), incontinence ( n  = 8), urosepsis ( n  = 6), clot retention ( n  = 4), mucosal injury ( n  = 3) and urinary retention ( n  = 3). All complications were minor and there were no Clavien >II complications.

Summary: Laser lithotripsy for bladder stone achieves an excellent success rate in the form of SFR, combined with a low risk of major complications, and allows concomitant treatment of enlarged prostate, and should be considered in all patients.

Purpose of review: We aim to review the evolving paradigm in endourology, where technology has led us to manage small stones with ureteroscopy (URS) and large stones with miniaturized percutaneous nephrolithotomy (mPCNL) techniques. We analyse recent literature, their findings, emerging trends and newer technologies that are helping redefine modern day endourology in pushing these boundaries.

Recent findings: A significant trend is the use of smaller devices to treat larger stones via ureteroscopy, and to treat smaller stones via percutaneous nephrolithotomy (PCNL). Improved laser technologies, smaller single use ureteroscopes and nephroscopes, suction access sheaths, all play a key role in this.The use of suction sheaths and vacuum assisted devices allows to control intrarenal pressure and help in reducing infectious and other complications whilst improving the stone-free rate (SFR). The treatment choice often depends on surgical expertise and available resources, guided by anatomical factors, stone composition and patient-specific considerations.

Summary: The management of kidney stone disease has undergone a paradigm shift. While ureteroscopy is being done for larger renal stones, miniaturised PCNL is being done for small stones. This has been driven by a surge in technology, but a tailored and patient-centred approach is needed, and must be helped by guidelines and a multidisciplinary approach.

Purpose of review: The advent of immunotherapy has completely transformed cancer treatment, particularly in genitourinary malignancies, where immune checkpoint inhibitors (ICIs) are now a cornerstone in bladder and kidney cancer management. However, their use introduces a distinct spectrum of immune-related adverse events (irAEs), necessitating a thorough understanding of their incidence, mechanisms, and management. This review explores the safety profile of ICIs in genitourinary cancers, addressing their impact in both localized and metastatic settings.

Recent findings: Recent studies highlight the diverse nature of irAEs, which can affect multiple organ systems with varying severity. While ICIs have demonstrated durable responses, their toxicity profile differs significantly from conventional therapies, requiring vigilant monitoring and prompt intervention. Notably, combination therapies, such as PD-1/PD-L1 inhibitors with CTLA-4 blockade or chemotherapy, may increase the risk of severe irAEs. Emerging data suggest that preexisting autoimmune conditions and specific patient subgroups may be more susceptible to toxicity, emphasizing the need for individualized risk assessment.

Summary: This review highlights the need for continuous monitoring, effective management strategies, and further research to better understand the mechanisms of irAEs and improve the well tolerated use of immunotherapy in genitourinary cancers. Clinicians should be aware of the incidence of immunotherapy-related adverse events in order to early identify them.

Purpose of review: This review focuses on recent advancements in laser technologies used in urology, particularly in enucleation, vaporization, lithotripsy, and focal laser ablation (FLA). The growing use of the thulium fiber laser (TFL) and the development of pulsed thulium lasers (p-Tm:YAG) highlight the relevance of this review, as these innovations aim to improve precision and outcomes in urological procedures.

Recent findings: Recent studies have shown the advantages of TFL in achieving precise tissue ablation, reduced retropulsion offered by the Moses technology in holmium lasers, and the potential of pulsed thulium lasers for more precise control of the effects on tissues. Additionally, FLA is gaining traction for its ability to treat localized prostate cancer with minimal collateral damage. These technologies not only optimize procedural accuracy but also reduce complications, making them safer for high-risk patients, including those receiving anticoagulants.

Summary: The advancements in laser technology, including TFL, Moses technology, and pulsed thulium lasers, are improving outcomes in urological surgeries by increasing precision, reducing operative time, and minimizing complications. FLA represents a promising alternative for minimally invasive cancer treatments. Ongoing research should focus on optimizing laser parameters and exploring broader clinical applications.

Purpose of review: The aim of this study was to outline the role of genetic abnormalities, including chromosomal anomalies, single-gene mutations, epigenetic changes, and mitochondrial DNA (mtDNA) defects, in male factor infertility.

Recent findings: Recent advances in genetic research have brought incredible new perspectives to understanding male infertility, thanks in large part to next-generation sequencing. Chromosomal abnormalities like Klinefelter syndrome and Y chromosome microdeletions remain key contributors, with new insights into their variable presentations and impact on sperm retrieval. Advanced discoveries in genes such as CFTR and ADGRG2 have reframed our approach to conditions like CBAVD, while epigenetic disruptions and mitochondrial DNA mutations are revealing previously unrecognized mechanisms behind impaired spermatogenesis and sperm motility. Rare copy number variations and genetic syndromes like Kallmann and Noonan further underscore the complex interplay between systemic disorders and male fertility.

Summary: The field of genetic infertility is rapidly evolving, offering new insights into the molecular mechanisms behind impaired spermatogenesis and fertility. These findings highlight the importance of integrating genetic testing into infertility evaluations to guide personalized management strategies.

Purpose of review: Prostate cancer remains a leading malignancy among men in the United States. While prostate-specific antigen (PSA) screening improves early detection, it also leads to over-diagnosis and over-treatment. Biomarkers offer a promising solution for risk stratification and guiding treatment decisions. This review examines the cost-effectiveness of serum, urine, and tissue-based biomarkers to assess their impact on healthcare expenditures and clinical decision-making.

Recent findings: Serum-based biomarkers like 4Kscore and PHI reduce unnecessary biopsies and healthcare costs. Urine-based biomarkers, including SelectMDx and ExoDx Prostate IntelliScore (EPI), have shown potential to optimize prostate cancer detection while being more cost-effective than some serum-based alternatives. Tissue-based biomarkers, such as OncotypeDx and Decipher, help in treatment selection, though their economic impact varies. Economic analyses suggest that biomarkers can enhance clinical decision-making while reducing healthcare expenditures, but real-world validation remains limited.

Summary: Prostate cancer biomarkers improve risk stratification and may lower healthcare costs. However, variations in cost-effectiveness, reimbursement policies, and guideline recommendations limit widespread adoption. Prospective studies are needed to validate real-world cost savings and refine biomarker integration into clinical practice. Addressing financial and policy challenges is essential to ensure equitable access and maximize their impact on prostate cancer management.

Purpose of review: The uses of generative artificial intelligence (GAI) technologies in medicine are expanding, with the use of large language models (LLMs) for matching patients to clinical trials of particular interest. This review provides an overview of the current ability of leveraging LLMs for clinical trial matching.

Recent findings: This review article examines recent studies assessing the performance of LLMs in oncologic clinical trial matching. The research in this area has shown promising results when testing these system using artificially created datasets. In general, they looked at how LLMs can be used to match patient health records with clinical trial eligibility criteria. There is still a need for human oversight of the systems in their current state.

Summary: Automated clinical trial matching can improve patient access and autonomy, reduce provider workload, and increase trial enrollment. However, it may potentially create a feeling of "false hope" for patients, can be difficult to navigate, and still requires human oversight. Providers may face a learning curve, while institutions must address data privacy concerns and ensure seamless EMR/EHR integration. Given this, additional studies are needed to ensure safety and efficacy of LLM-based clinical trial matching in oncology.

Purpose of review: There has been an explosion of creative uses of artificial intelligence (AI) in healthcare, with AI being touted as a solution for many problems facing the healthcare system. This review focuses on tools currently available to pediatric urologists, previews up-and-coming technologies, and highlights the latest studies investigating benefits and limitations of AI in practice.

Recent findings: Imaging-driven AI software and clinical prediction tools are two of the more exciting applications of AI for pediatric urologists. As nuanced pattern recognition improves in trained computer models, pediatric urologists will be able to better counsel and risk stratify patients with chronic diseases and surgical needs. AI is also being extensively used in product development for enuresis treatment. Large language models such as ChatGPT continue to be of strong interest as a patient-facing education tool, but it lacks the accuracy needed to serve as a suitable alternative to human response.

Summary: AI is increasingly investigated for use across healthcare fields, including pediatric urology. Use of AI and machine learning (ML) is being explored for patient interface, imaging assessment, outcomes prediction, and product development. Though still in preclinical stages for most systems, ML presents as a promising new clinical tool with potential to shape healthcare systems and medical practice.

Purpose of review: The integration of artificial intelligence in urology presents both transformative opportunities and ethical dilemmas. As artificial intelligence driven tools become more prevalent in diagnostics, robotic-assisted surgeries, and patient monitoring, it is crucial for urologists to understand the ethical implications of these technologies. This review examines key ethical concerns surrounding artificial intelligence in urology, including bias, transparency, accountability, and data privacy.

Recent findings: Recent literature highlights algorithmic bias as a significant challenge, where artificial intelligence models trained on nondiverse datasets may produce inequitable outcomes. The "black-box" nature of artificial intelligence systems complicates transparency and interpretability, raising concerns about clinician and patient trust. Emerging reporting standards, such as STREAM-URO and IDEAL frameworks, and WHO Guidelines provide structured approaches for ethical artificial intelligence integration in urology.

Summary: The ethical deployment of artificial intelligence in urology requires a balanced approach that prioritizes fairness, accountability, and patient autonomy. Clinicians must advocate for explainable artificial intelligence, ensure equitable access, and integrate human oversight into artificial intelligence assisted decision-making. Future research should focus on improving dataset diversity, enhancing artificial intelligence interpretability, and establishing robust ethical guidelines to ensure that artificial intelligence advances align with medical ethics and patient-centered care.

Purpose of review: Prudent integration of artificial intelligence (AI) into outpatient urology has already begun to revolutionize clinical workflows, improve administrative efficiency, and automate mundane and laborious tasks in the clinic setting.

Recent findings: This narrative review explores the current applications of AI in outpatient settings, focusing on previsit, during-visit, and postvisit processes that may improve the experiences of clinicians and patients. We discuss the use of AI in administrative tasks, clinical decision support, documentation, and patient communication. Additionally, we highlight future directions for AI in urology, including integrated solutions that span prediagnosis to posttreatment and disease surveillance. While AI shows promise in reducing physician burden and increasing efficiency, challenges remain.

Summary: Taking lessons from the introduction of the electronic health record (EHR), end-to-end AI integration will require rigorous validation, workflow adaptation, and iterant tailoring to meet the demands of the clinic setting before widespread adoption can occur.