The Association Between 24-Hour Urine and Stone Recurrence Among High Risk Kidney Stone Formers: A Population Level Assessment

Urology ◽  
2020 ◽  
Vol 144 ◽  
pp. 71-76
Author(s):  
Patrick C. Samson ◽  
Sarah K. Holt ◽  
Ryan S. Hsi ◽  
Mathew D. Sorensen ◽  
Jonathan D. Harper
Keyword(s):  
High Risk ◽  
Kidney Stone ◽  
Population Level ◽  
Stone Recurrence ◽  
Stone Formers

scholarly journals MP08-06 THE ASSOCIATION BETWEEN 24-HOUR URINE COLLECTION USE AND STONE RECURRENCE AMONG HIGH RISK KIDNEY STONE FORMERS

2019 ◽  
Vol 201 (Supplement 4) ◽  
Author(s):  
Patrick Samson* ◽  
Sarah Holt ◽  
Ryan Hsi ◽  
Mathew Sorensen ◽  
Jonathan Harper
Keyword(s):  
High Risk ◽  
Kidney Stone ◽  
Urine Collection ◽  
Stone Recurrence ◽  
Stone Formers

scholarly journals PD35-02 APPLICATION OF ARTIFICIAL INTELLIGENCE TOOL TO IDENTIFY PATIENTS AT HIGH RISK FOR SYMPTOMATIC KIDNEY STONE RECURRENCE

2020 ◽  
Vol 203 ◽  
pp. e717-e718
Author(s):  
Reza Goharderakhshan* ◽  
Drew Clausen ◽  
Oleg Shvarts ◽  
Michelle West ◽  
Ronald Loo
Keyword(s):  
Artificial Intelligence ◽  
High Risk ◽  
Kidney Stone ◽  
Stone Recurrence

scholarly journals P0175DETERMINANTS OF RENAL PAPILLARY APPEARANCE IN RENAL STONE FORMERS: AN IN-DEPTH EXAMINATION

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Matteo Bargagli ◽  
Rossella De Leonardis ◽  
Mauro Ragonese ◽  
Angelo Totaro ◽  
Francesco Pinto ◽  
...  
Keyword(s):  
Kidney Stones ◽  
Kidney Stone ◽  
Medical Condition ◽  
Stone Formation ◽  
Blood Parameters ◽  
Stone Disease ◽  
Stone Composition ◽  
Stone Recurrence ◽  
Stone Formers

Abstract Background and Aims Nephrolithiasis is a medical condition characterized by high prevalence among the general population both in Europe and in the U.S. and it is responsible for high costs reaching up to $10 billion per year. It is associated with specific comorbidities such as obesity, arterial hypertension, diabetes mellitus, metabolic syndrome and chronic kidney disease. Kidney stones development is believed to start either from Randall’s plaques or from stone plugs. Both these lesions can be seen on renal papillary surfaces, but what promotes the formation of plaques and plugs is not entirely understood. The aim of this study is to investigate the association between the urinary metabolic milieu and a published endoscopic papillary evaluation score (PPLA). We also evaluated the correlation of PPLA score with kidney stone recurrence during follow-up. Method We prospectively enrolled 31 stone forming patients who undergone retrograde intrarenal surgery procedures. Visual inspection of the accessible renal papillae was performed in order to calculate the PPLA score based on the appearance of ductal plugging, surface pitting, loss of papillary contour and Randall’s plaque extension. Demographic information, blood samples, 24h urine collections and kidney stone events during follow-up were collected. Stone composition was analyzed using infrared-spectroscopy. Relative urinary supersaturations (RSS) for calcium oxalate (CaOx), calcium phosphate (CaPi) and uric acid (UA) were calculated using the Equil2 software. PPLA score > 3 was defined as high. Results Median follow-up period was 11 (min/max 5, 34) months. PPLA score was inversely correlated with BMI (rho = −0.39, p = 0.035) and history of recurrent kidney stones (median PPLA 5.0 vs 2.5, p = 0.029), these results were confirmed when PPLA was considered as a categorical variable (median BMI 27 vs 24, recurrent stone disease 12 vs 62%, p= 0.006). Furthermore, high PPLA score was associated with lower odds of new kidney stone events during follow-up (OR 0.154, 95% confidence interval 0.024, 0.998, p = 0.05). No significant correlations were found between PPLA score, stone composition, blood parameters, 24h urine solute excretions and RSS for CaOx, CaPi and UA. Conclusion Different papillary abnormalities seem to be linked to specific mechanisms of stone formation. Although data regarding PPLA score are inconsistent, it may be a valid asset for both medical and surgical management of nephrolithiasis. Larger, long-term prospective clinical studies need to be conducted to assess the validity of PPLA score system in evaluating risk of stone recurrence.

Stone recurrence among childhood kidney stone formers: results of a nationwide study in Iceland

Urolithiasis ◽  
2020 ◽  
Vol 48 (5) ◽  
pp. 409-417
Author(s):  
Solborg E. Ingvarsdottir ◽  
Olafur S. Indridason ◽  
Runolfur Palsson ◽  
Vidar O. Edvardsson
Keyword(s):  
Kidney Stone ◽  
Nationwide Study ◽  
Stone Recurrence ◽  
Stone Formers

1844 INNER-CITY KIDNEY STONE FORMERS EXHIBIT PREDOMINATELY HIGH-RISK NEPHROLITHIASIS

2012 ◽  
Vol 187 (4S) ◽  
Author(s):  
Aaron Woodall ◽  
Michael Lasser ◽  
David Hoenig
Keyword(s):  
High Risk ◽  
Inner City ◽  
Kidney Stone ◽  
Stone Formers

Personalized stratification of back to work risk amidst COVID-19: A machine learning approach (Preprint)

2020 ◽  
Author(s):  
Carson Lam ◽  
Jacob Calvert ◽  
Gina Barnes ◽  
Emily Pellegrini ◽  
Anna Lynn-Palevsky ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Learning Algorithm ◽  
Severe Disease ◽  
High Specificity ◽  
Population Level ◽  
The United States ◽  
Health Condition ◽  
Available P ◽  
Severe Illness

BACKGROUND In the wake of COVID-19, the United States has developed a three stage plan to outline the parameters to determine when states may reopen businesses and ease travel restrictions. The guidelines also identify subpopulations of Americans that should continue to stay at home due to being at high risk for severe disease should they contract COVID-19. These guidelines were based on population level demographics, rather than individual-level risk factors. As such, they may misidentify individuals at high risk for severe illness and who should therefore not return to work until vaccination or widespread serological testing is available. OBJECTIVE This study evaluated a machine learning algorithm for the prediction of serious illness due to COVID-19 using inpatient data collected from electronic health records. METHODS The algorithm was trained to identify patients for whom a diagnosis of COVID-19 was likely to result in hospitalization, and compared against four U.S policy-based criteria: age over 65, having a serious underlying health condition, age over 65 or having a serious underlying health condition, and age over 65 and having a serious underlying health condition. RESULTS This algorithm identified 80% of patients at risk for hospitalization due to COVID-19, versus at most 62% that are identified by government guidelines. The algorithm also achieved a high specificity of 95%, outperforming government guidelines. CONCLUSIONS This algorithm may help to enable a broad reopening of the American economy while ensuring that patients at high risk for serious disease remain home until vaccination and testing become available.

scholarly journals Excretion of urine extracellular vesicles bearing markers of activated immune cells and calcium/phosphorus physiology differ between calcium kidney stone formers and non-stone formers

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiqing Zhang ◽  
Sanjay Kumar ◽  
Muthuvel Jayachandran ◽  
Loren P. Herrera Hernandez ◽  
Stanley Wang ◽  
...  
Keyword(s):  
Urinary Excretion ◽  
Calcium Oxalate ◽  
Extracellular Vesicles ◽  
Immune Cells ◽  
Kidney Stone ◽  
Fibroblast Growth Factor 23 ◽  
Pathogenic Mechanisms ◽  
Phosphorus Excretion ◽  
Stone Formers ◽  
Calcium Phosphorus

Abstract Backgrounds: Previous studies have demonstrated that excretion of urinary extracellular vesicles (EVs) from different nephron segments differs between kidney stone formers and non-stone formers (NSFs), and could reflect pathogenic mechanisms of urinary stone disease. In this study we quantified selected populations of specific urinary EVs carrying protein markers of immune cells and calcium/phosphorus physiology in calcium oxalate stone formers (CSFs) compared to non-stone formers (NSFs). Methods Biobanked urine samples from CSFs (n = 24) undergoing stone removal surgery and age- and sex- matched NSFs (n = 21) were studied. Urinary EVs carrying proteins related to renal calcium/phosphorus physiology (phosphorus transporters (PiT1 and PiT2), Klotho, and fibroblast growth factor 23 (FGF23); markers associated with EV generation (anoctamin-4 (ANO4) and Huntington interacting protein 1 (HIP1)), and markers shed from activated immune cells were quantified by standardized and published method of digital flow cytometry. Results Urine excretion of calcium, oxalate, phosphorus, and calcium oxalate supersaturation (SS) were significantly higher in CSFs compared to NSFs (P < 0.05). Urinary excretion of EVs with markers of total leukocytes (CD45), neutrophils (CD15), macrophages (CD68), Klotho, FGF23, PiT1, PiT2, and ANO4 were each markedly lower in CSFs than NSFs (P < 0.05) whereas excretion of those with markers of monocytes (CD14), T-Lymphocytes (CD3), B-Lymphocytes (CD19), plasma cells (CD138 plus CD319 positive) were not different between the groups. Urinary excretion of EVs expressing PiT1 and PiT2 negatively (P < 0.05) correlated with urinary phosphorus excretion, whereas excretion of EVs expressing FGF23 negatively (P < 0.05) correlated with both urinary calcium and phosphorus excretion. Urinary EVs with markers of HIP1 and ANO4 correlated negatively (P < 0.05) with clinical stone events and basement membrane calcifications on papillary tip biopsies. Conclusions Urinary excretion of EVs derived from specific types of activated immune cells and EVs with proteins related to calcium/phosphorus regulation differed between CSFs and NSFs. Further validation of these and other populations of urinary EVs in larger cohort could identify biomarkers that elucidate novel pathogenic mechanisms of calcium stone formation in specific subsets of patients.

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