Browsing by Subject "Urinalysis"

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    Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data
    (Oxford University Press, 2022) Moledina, Dennis G.; Eadon, Michael T.; Calderon, Frida; Yamamoto, Yu; Shaw, Melissa; Perazella, Mark A.; Simonov, Michael; Luciano, Randy; Schwantes-An, Tae-Hwi; Moeckel, Gilbert; Kashgarian, Michael; Kuperman, Michael; Obeid, Wassim; Cantley, Lloyd G.; Parikh, Chirag R.; Wilson, F. Perry; Medicine, School of Medicine
    Background: Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. Methods: In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. Results: We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. Conclusions: We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.
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    Spot Urine Samples to Estimate Na and K Intake in Patients With Chronic Kidney Disease and Healthy Adults: A Secondary Analysis From a Controlled Feeding Study
    (Elsevier, 2021) Lobene, Andrea J.; Stremke, Elizabeth R.; McCabe, George P.; Moe, Sharon M.; Moorthi, Ranjani N.; Hill Gallant, Kathleen M.; Medicine, School of Medicine
    Objective: The objective of this study was to assess the agreement between estimated 24-hour urinary sodium excretion (e24hUNa) and estimated 24-hour urinary potassium excretion (e24hUK), calculated from a spot urine sample using several available equations and actual sodium and potassium intake from a controlled diet in both healthy participants and those with chronic kidney disease (CKD). Design and methods: This study is a secondary analysis of a controlled feeding study in CKD patients matched to healthy controls. Participants (n = 16) consumed the controlled diet, which provided ∼2400 mg Na/day and ∼3000 mg K/day, for 8 days. On days 7 and 8, participants consumed all meals and collected all urine in an inpatient research setting, and they were discharged on day 9. The day 7 morning spot urine sample was used to calculate e24hUNa and e24hUK, which was compared with known sodium and potassium intake, respectively. Results: Average e24hUNa from the INTERSALT and Tanaka-Na equations were higher than actual sodium intake by 373 mg and 559 mg, respectively, though the differences were not significant. e24hUNa from the Nerbass-SALTED equation in CKD participants was significantly higher than actual sodium intake by ∼2000 mg (P < .001), though e24hUNa from the Nerbass-RRID equation was not different from intake. e24hUK from the Tanaka-K equation was significantly lower than actual potassium intake (P < .001). For both e24hUNa and e24hUK for all participants, agreement with actual intake was poor, and e24hUNa and e24hUK were not correlated with actual sodium or potassium intake, respectively. Conclusion: e24hUNa and e24hUK are poor indicators of true sodium and potassium intake, respectively, in both healthy and CKD participants. Findings should be confirmed in larger sample sizes with varying levels of dietary sodium and potassium.