Publications by authors named "Gregory E Tasian"

Background: The prevalence of pediatric urolithiasis has increased rapidly, leading to more emergency department (ED) visits across the United States.

Objective: The purpose of this study was to determine emergency care practices for children and adolescents with urinary stones and characteristics associated with management.

Methods: We performed a cross-sectional study of the 2021 Nationwide Emergency Department Sample to identify pediatric patients (≤21 years) presenting to an ED in the United States with a primary diagnosis of urinary stone disease.

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Purpose: We developed prediction models for severe pain and urinary symptoms after ureteroscopy with ureteral stent placement.

Materials And Methods: The development cohort included 424 adults and adolescents enrolled in the multicenter STENTS prospective cohort study who underwent ureteroscopy with stent placement for urinary stones. The validation cohort was an independent prospective cohort of 115 adults.

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Hyperoxaluria is a condition in which there is a pathologic abundance of oxalate in the urine through either hepatic overproduction (primary hyperoxaluria [PH]) or excessive enteric absorption of dietary oxalate (enteric hyperoxaluria [EH]). Severity can vary with the most severe forms causing kidney failure and extrarenal manifestations. To address the current challenges and innovations in hyperoxaluria, the 14th International Hyperoxaluria Workshop convened in Perugia, Italy, bringing together international experts for focused presentation and discussion.

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Antenatal hydronephrosis (HN) impacts up to 5% of pregnancies and requires close, frequent follow-up monitoring to determine who may benefit from surgical intervention. To create an automated HN Severity Index (HSI) that helps guide clinical decision-making directly from renal ultrasound images. We applied a deep learning model to paediatric renal ultrasound images to predict the need for surgical intervention based on the HSI.

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Purpose: To ensure that research on kidney stones provides meaningful impact for the kidney stone community, patients and caregivers should be engaged as stakeholders in clinical trial design, starting at study inception. This project aimed to elicit, refine, and prioritize research ideas from kidney stone stakeholders to develop a patient-centered research agenda for clinical trials.

Materials And Methods: The Kidney Stone Engagement Core, a group of patients, caregivers, advocates, clinicians, and researchers, executed an iterative process of surveys and focus groups to elicit and refine research themes, which were then translated into research questions.

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Objective: To assess accuracy of self-reported stone events in a large clinical trial by adjudication against the weight of documentation for spontaneous stone passage or surgical intervention.

Methods: Participants in the Prevention of Urinary Stones with Hydration (PUSH) trial were randomized to a multi-component behavioral intervention or control arm to increase and maintain high fluid intake. The primary endpoint was urinary stone events including symptomatic stone passage or procedural intervention.

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Objective: Deep-learning algorithms have been widely applied in the field of automatic kidney ultrasound (US) image segmentation. However, obtaining a large number of accurate kidney labels clinically is very difficult and time-consuming. To solve this problem, we have proposed an efficient cross-modal transfer learning method to improve the performance of the segmentation network on a limited labeled kidney US dataset.

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Purpose: Multiple factors are thought to give rise to common, recurrent kidney stone disease, but for monogenic stone disorders a firm diagnosis is possible through genetic testing. The autosomal recessive primary hyperoxalurias (PH) are rare forms of monogenic kidney stone disease. All 3 types of PH are caused by inborn errors of glyoxylate metabolism in the liver, leading to hepatic oxalate overproduction and excessive renal urinary oxalate excretion.

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Importance: High-risk practices, including dispensing an opioid prescription before surgery when not recommended, remain poorly characterized among US youths and may contribute to new persistent opioid use.

Objective: To characterize changes in preoperative, postoperative, and refill opioid prescriptions up to 180 days after surgery.

Design, Setting, And Participants: This retrospective cohort study was performed using national claims data to determine opioid prescribing practices among a cohort of opioid-naive youths aged 11 to 20 years undergoing 22 inpatient and outpatient surgical procedures between 2015 and 2020.

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Background: Structured Problem Solving (SPS) is a patient-centered approach to promoting behavior change that relies on productive collaboration between coaches and participants and reinforces participant autonomy. We aimed to describe the design, implementation, and assessment of SPS in the multicenter Prevention of Urinary Stones with Hydration (PUSH) randomized trial.

Methods: In the PUSH trial, individuals with a history of urinary stone disease and low urine output were randomized to control versus a multicomponent intervention including SPS that was designed to promote fluid consumption and thereby prevent recurrent stones.

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Objective: To prospectively capture patient-reported outcomes to assess the recovery profile of ureteroscopy (URS).

Materials And Methods: Adults undergoing URS for renal/ureteral stones were eligible for inclusion (11/2020-8/2022). Patients prospectively completed PROMIS - Pain Intensity, - Pain Interference, and - Ability to participate in social roles and activities in-person preoperatively (POD 0) and via email on POD 1, 7, 14, and 30.

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Objective: To reveal barriers and opportunities to implement evidence for the management of pediatric kidney stone disease, we determined surgeon and institutional factors associated with preferences for the type of surgical intervention for kidney and ureteral stones.

Methods: We conducted a cross-sectional study of urologists participating in the Pediatric KIDney Stone Care Improvement Network (PKIDS) trial. Questionnaires ascertained strengths of urologists' preferences for types of surgery as well as characteristics of participating urologists and institutions.

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Introduction: Artificial intelligence (AI) and machine learning (ML) in pediatric urology is gaining increased popularity and credibility. However, the literature lacks standardization in reporting and there are areas for methodological improvement, which incurs difficulty in comparison between studies and may ultimately hurt clinical implementation of these models. The "STandardized REporting of Applications of Machine learning in UROlogy" (STREAM-URO) framework provides methodological instructions to improve transparent reporting in urology and APPRAISE-AI in a critical appraisal tool which provides quantitative measures for the quality of AI studies.

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Objective: To examine the relationships between preoperative hypersensitivity to pain and central sensitization, and postoperative ureteral stent pain after ureteroscopy (URS) for urinary stones.

Methods: Adults enrolled in the STudy to Enhance uNderstanding of sTent-associated Symptoms (STENTS) underwent quantitative sensory testing (QST) prior to URS and stent placement. Hypersensitivity to mechanical pain was assessed using a pressure algometer.

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Background: Primary hyperoxaluria type 1 (PH1) is an autosomal recessive inborn error of metabolism that causes oxalate deposition, leading to recurrent calcium oxalate kidney stones, chronic kidney disease and systemic oxalosis, which produces a broad range of serious life-threatening complications. Patients with PH1 have delayed diagnosis due to the rarity of the disease and the overlap with early-onset kidney stone disease not due to primary hyperoxaluria.

Objective: The objective of this study was to determine the clinical features of individuals <21 years of age with PH1 that precede its diagnosis.

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Kidney stones are rising in incidence and prevalence worldwide. Given the temperature dependence of kidney stone presentations, climate change is projected to further increase the burden of disease for individuals and society. PATIENT SUMMARY: This mini-review reports current knowledge on climate change in relation to kidney stone disease.

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Objective: To review the status of comparative effectiveness studies for kidney stone disease with focus on study outcome, type, population, time trends, and patient-centered approaches.

Methods: A systematic scoping review was performed for articles published between January 1, 2005, and March 30, 2021, using keywords relevant to kidney stone disease. Studies published in English that compared two or more alternative methods for prevention, diagnosis, treatment, monitoring, or care delivery were included.

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The rarity of primary hyperoxaluria (PH) challenges our understanding of the disease. The purpose of our study was to describe the course of clinical care in a United States cohort of PH pediatric patients, highlighting health service utilization. We performed a retrospective cohort study of PH patients < 18 years old in the PEDSnet clinical research network from 2009 to 2021.

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Pediatric nephrolithiasis is less common in children than in adults but the incidence has been rising rapidly, and it is now a public health and economic burden in the United States. There are challenges unique to children that should be taken into consideration when evaluating and managing pediatric stone disease. In this review, we present the current research on risk factors, emerging new technologies for treatment of stones and recent investigations on prevention of stones in this population.

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Article Synopsis
  • This text talks about how doctors use ultrasounds to check for hydronephrosis, a condition where kidneys swell due to urine buildup. Different ways to grade this problem exist but they aren’t always super accurate.
  • Researchers are working on a computer program using machine learning (like artificial intelligence) to help classify the severity of hydronephrosis based on ultrasound images more reliably.
  • In their study, they tested this new computer model against expert doctors and found that the machine was pretty good at predicting the kidney condition correctly, with high accuracy rates!
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