BACKGROUND: Spot urine collection offers a convenient alternative to the more cumbersome 24-hour urine collection. However, the widely recognized estimation models, such as Tanaka and INTERSALT, have not been adequately adapted for widespread use in the general Chinese population.
OBJECTIVE: This study was designed to evaluate the precision of the Tanaka and INTERSALT calibration models, alongside a locally-Zhejiang Province formulated model, in predicting 24-hour urinary sodium (24-hUNa) excretion among the Chinese population.
METHODS: The study comprised 1,424 participants, aged 18 to 69 years, who provided both comprehensive 24-hour urine and fasting morning urine samples. The researchers assessed the accuracy of the measured 24-hUNa against the estimates obtained from the Tanaka, INTERSALT, and Zhejiang models. This evaluation was conducted at both population and individual levels, employing a range of statistical techniques, including bias analysis, correlation coefficients, intraclass correlation coefficients (ICC), receiver operating characteristic (ROC) curves, Bland-Altman plots, as well as relative and absolute difference calculations, and misclassification rates.
RESULTS: The measured average 24-hUNa excretion was found to be 165.7 ± 71.5 mmol/24-hour. Notably, there was a significant deviation between the estimated and measured values for the Tanaka-adjusted model (-11.7 mmol, 95% Confidence Interval (CI): -16.7, -6.7 mmol/24-hour), indicating a statistically significant difference. In contrast, the deviations for the INTERSALT-adjusted model (0.6 mmol, 95% CI: -4.2, 5.4 mmol/24-hour) and the Zhejiang model (0.2 mmol, 95% CI: -4.6, 5.0 mmol/24-hour) were not significant. The correlation coefficients for the models were 0.303, 0.398, and 0.391, respectively, with the INTERSALT-adjusted and Zhejiang models showing superior performance at the population level.
CONCLUSIONS: The three evaluation models may serve as effective, low-burden alternatives for assessing urinary sodium levels in the population. However, to enhance the accuracy and reliability of predictions at the individual level, further repeated measurements are necessary to minimize measurement errors and augment the validity of the estimations.

Objectives: The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of stone events is also a significant limitation for clinical trials, where many patients must be enrolled to obtain sufficient stone events for analysis. In this study, we sought to use machine learning methods to identify a novel algorithm to predict stone recurrence. Subjects/Patients and Methods: Patients enrolled in the Registry for Stones of the Kidney and Ureter (ReSKU), a registry of nephrolithiasis patients collected between 2015-2020, with at least one prospectively collected 24-hour urine test (Litholink 24-hour urine test; Labcorp) were included in the training set. A validation set was obtained from chart review of stone patients not enrolled in ReSKU with 24-hour urine data. Stone events were defined as either an office visit where a patient reports symptomatic passage of stones or a surgical procedure for stone removal. Seven prediction classification methods were evaluated. Predictive analyses and receiver operator characteristics (ROC) curve generation were performed in R. Results: A training set of 423 kidney stone patients with stone event data and 24-hour urine samples were trained using the prediction classification methods. The highest performing prediction model was a Logistic Regression with ElasticNet machine learning model (area under curve [AUC] = 0.65). Restricting analysis to high confidence predictions significantly improved model accuracy (AUC = 0.82). The prediction model was validated on a validation set of 172 stone patients with stone event data and 24-hour urine samples. Prediction accuracy in the validation set demonstrated moderate discriminative ability (AUC = 0.64). Repeat modeling was performed with four of the highest scoring features, and ROC analyses demonstrated minimal loss in accuracy (AUC = 0.63). Conclusion: Machine-learning models based on 24-hour urine data can predict stone recurrences with a moderate degree of accuracy.

24-hour urinary free cortisol (UFC) is considered as the first-line test for screening and diagnosis of Cushing\'s syndrome. Although 24-hour UFC assay has been extensively studied by liquid chromatography-tandem mass spectrometry (LC-MS/MS), an accurate assay coupled with a reliable sample preparation procedure and a method-specific reference interval would be very important for reasonable diagnosis. In this study, a simple dilute and shoot method has been proposed for UFC determination by LC-MS/MS. Namely, 50 µL of urine sample was mixed with 200 µL of a 50 % methanol/water solution containing the internal standard cortisol-13C3. The mixture was centrifuged and the supernatant was used for direct analysis by LC-MS/MS. This method was validated with wide linear range from 0.625 to 500 ng/ml with coefficients of variation (CVs) ≤ 3.64 %, excellent precision (intra-day CVs ≤ 5.70 % and inter-day CVs ≤ 5.33 %) and good recovery in the range of 93.3-109 %. The preservatives were further evaluated for urine storage. It was recommended that no preservatives could be used in collection of 24-hour urine for good detecting peaks. The investigation of reference interval and diagnostic performance finally confirmed the potential usage of this LC-MS/MS assay in routing clinical testing.

Monitoring salt consumption in children is essential for informing and implementing public health interventions to reduce children\'s salt intake. However, collection of 24-hour urines, considered as the most reliable approach, can be especially challenging to school children. This study aimed to assess the agreement between 24-hour urine (24hrU) and 24-hour food recall (24hrFR) in: (1) estimating salt intake in children; (2) classifying salt intakes above the recommended upper level set for children, and; (3) estimating change in mean salt intake over time.
This study utilised data from two cross-sectional surveys of school children aged 8 to 12 years living in the state of Victoria, Australia. A single 24hrU and 24hrFR were collected from each participant. Suspected inaccurate urine collections and implausible energy intakes were excluded based on pre-defined criteria. The agreement between the two methods was assessed using Bland-Altman methodology, the intraclass correlation coefficient (ICC), and the kappa statistic. The difference between the measured change in salt intake over time using 24hrU and 24hrFR was derived using mixed effects linear regression analysis.
A total of 588 participants provided a 24hrU and 24hrFR. Overall, there was no meaningful difference in mean estimated salt intake between the two methods (- 0.2 g/day, 95% CI - 0.5 to 0.1). The Bland-Altman plot showed wide 95% limits of agreement (- 7.2 to 6.8). The ICC between the two methods was 0.13 (95% CI 0.05 to 0.21). There was poor interrater reliability in terms of classifying salt intake above the recommended upper level for children, with an observed agreement of 63% and kappa statistic of 0.11. The change in mean salt intake over time was 0.2 g/day (- 0.4 to 0.7) based on 24hrU, and 0.5 g/day (- 0.0 to 1.1) based on 24hrFR, with a difference-in-differences of 0.4 g/day (- 0.3 to 1.1).
24hrFR appears to provide a reasonable estimate of mean salt intake as measured by 24hrU in Australian school children. However, similar to previous observations in adults, and of studies exploring other alternative methods for estimating salt intake, 24hrFR is a poor predictor of individual-level salt intake in children.

Proteinuria is one of the diagnostic criteria of preeclampsia (PE). Measurement of 24-hour urine protein is the gold standard method for detection of proteinuria in PE. The 24-hour urine sampling is time-consuming, and inconvenient. To evaluate the accuracy of protein/creatinine (P/C) ratio in detection of significant proteinuria (> 1 g/24-hours urine) in PE.
One hundred and ten (110) preeclamptic women were included in this study and admitted for blood pressure monitoring, 24-hour urine collection, fetal well-being assessment and spot urine sample for measuring of P/C ratio. After thorough history and clinical examination, routine antenatal investigations were done for the women included in the study according to the hospital`s protocol, and to exclude pre-existing chronic renal disease. Twenty-four-hour urine collection started on the morning following hospital admission. Spot urine samples were obtained shortly before the 24-hour urine collection for measuring of P/C ratio. Collected data statistically analyzed to evaluate the accuracy of P/C ratio in detection of significant proteinuria in PE.
The P/C ratio of 1.35 ± 2.54 had 94.4% sensitivity, 94.9% specificity, 97.1% positive predictive value (PPV), 90.2% negative predictive value (NPV), and 94.5% overall accuracy in detection of significant proteinuria (> 1 g/24-hour urine) in PE.
The P/C ratio of 1.35 ± 2.54 had 94.4% sensitivity, 94.9% specificity, 97.1% PPV, 90.2% NPV, and 94.5% overall accuracy in detection of significant proteinuria (> 1 g/24-hour urine) in PE. This study suggests the use of P/C ratio as an alternative to 24-hour urine protein to detect significant proteinuria in PE.

BACKGROUND: Assessing estimated sodium (Na) and potassium (K) intakes derived from 24-h urinary excretions compared with a spot urine sample, if comparable, could reduce participant burden in epidemiologic and clinical studies.
OBJECTIVE: In a 2-week controlled-feeding study, Na and K excretions from a 24-h urine collection were compared with a first-void spot urine sample, applying established algorithms and enhanced models to estimate 24-h excretion. Actual and estimated 24-h excretions were evaluated relative to mean daily Na and K intakes in the feeding study.
METHODS: A total of 153 older postmenopausal women ages 75.4 ± 3.5 y participated in a 2-wk controlled-feeding study with a 4-d repeating menu cycle based on their usual intake (ClinicalTrials.gov Identifier: NCT00000611). Of the 150 participants who provided both a first-void spot urine sample and a 24-h urine collection on the penultimate study day, statistical methods included Pearson correlations for Na and K between intake, 24-h collections, and the 24-h estimated excretions using 4 established algorithms: enhanced biomarker models by regressing ln-transformed intakes on ln-transformed 24-h excretions or ln-transformed 24-h estimated excretions plus participant characteristics and sensitivity analyses for factors potentially influencing Na or K excretion (e.g., possible kidney disease estimated glomerular filtration rate <60 mL/min/1.73 m2 ).
RESULTS: Pearson correlation coefficients between Na and K intakes and actual 24-h excretions were 0.57 and 0.38-0.44 for estimated 24-h excretions, depending on electrolyte and algorithm used. Enhanced biomarker model cross-validated R 2 (CVR2) for 24-h excretions were 38.5% (Na), 40.2% (K), and 42.0% (Na/K). After excluding participants with possible kidney disease, the CVR2 values were 43.2% (Na), 40.2% (K), and 38.1% (Na/K).
CONCLUSIONS: Twenty-four-hour urine excretion measurement performs better than estimated 24-h excretion from a spot urine as a biomarker for Na and K intake among a sample of primarily White postmenopausal women.

Background: There are multiple stone types, with each forming under different urinary conditions. We compared clinical and metabolic findings in pure stone formers (SFs) to understand whether there are consistent factors that differentiate these groups in terms of underlying etiology and potential for empiric treatment. Materials and Methods: Pure SFs based on infrared spectroscopic analysis of stones obtained at our institution between January 2002 and July 2018 with a corresponding 24-hour urinalysis were retrospectively evaluated. Results: One hundred twenty-one apatite (AP), 54 brushite (BRU), 50 calcium oxalate (CaOx) dihydrate, 104 CaOx monohydrate, and 82 uric acid (UA) patients were analyzed. AP, BRU, and CaOx dihydrate patients were younger than CaOx monohydrate and UA patients. The UA patients had the highest male predominance (76.8%), whereas AP patients were predominantly female (80.2%). UA was most associated with diabetes mellitus (45.3%), and CaOx monohydrate with cardiovascular disease (27.2%) and malabsorptive gastrointestinal conditions (19.2%). BRU patients had the highest prevalence of primary hyperparathyroidism (17%). AP, BRU, and CaOx dihydrate patients demonstrated high rates of hypercalciuria (66.1%, 79.6%, 82%). AP and BRU patients had the highest urinary pH. AP patients exhibited the highest rate of hypocitraturia, whereas CaOx dihydrate patients exhibited the lowest (55.4%, 30%). CaOx monohydrate patients had the highest rate of hyperoxaluria (51.9%). UA patients had the lowest urinary pH. There were no observable differences in the rates of hyperuricosuria or hypernatriuria. Conclusions: These results demonstrate that pure stone composition correlates with certain urinary and clinical characteristics. These data can help guide empiric clinical decision making.

Intakes of excess Na and insufficient K are two major contributors of heart diseases and stroke development. However, no precise study has previously been carried out on Na and K intakes among Indonesian adults. The present study aimed to estimate the Na and K intakes using two consecutive 24-h urine collections. Participants were community-dwelling adults aged between 20 and 96 years, randomly selected from a pool of resident registration numbers. Of the 506 participants, 479 (240 men and 239 women) completed urine collections. The mean Na excretion was 102·8 and 100·6 mmol/d, while the mean K excretion was 25·0 and 23·4 mmol/d for men and women, respectively. Na and K excretions were higher in participants with a higher BMI. A higher K excretion was associated only with younger age. More than 80 % of the participants consumed more than 5 g/d of salt (the upper limit recommended by the Indonesian government), whereas none of them consumed more than 3510 mg/d of K (the lower limit). The high Na and low K intakes, especially high Na among participants with high BMI, should be considered when future intervention programmes are planned in this country.

UNASSIGNED: The primary aim of this study was to determine the utility of dried urine sampling in obtaining measures of cortisol and cortisol metabolites. Additional aims were to evaluate if a 4-spot dried urine collection is representative of a 24-hour urine collection and if expected diurnal cortisol patterns can be observed in samples from both urine and saliva.
UNASSIGNED: Data from individuals with cortisol measures available from both a 4-spot dried urine collection and a 24-hour urine collection (n = 28) were evaluated. Of these 28, 20 also had concurrent liquid and dried 24-hour urine measures. Consistency between these methods was evaluated using paired t-tests and intraclass correlation coefficients (ICCs). In addition, data from individuals with concurrent measures of both urinary and salivary cortisol (n = 68) were assessed for consistency in the diurnal pattern of change in cortisol.
UNASSIGNED: Near ideal consistency was observed between liquid and dried urine for measures of total urine free cortisol, total urine cortisone, and total cortisol metabolites (n = 20; ICCs = 0.99, 0.97 and 0.96, respectively). Good to excellent consistency was observed between the 4-spot method and the 24-hour collection (n = 28; ICCs = 0.89, 0.95 and 0.92, respectively). In mixed model analysis, no difference was seen in the diurnal pattern of cortisol between salivary and urinary free cortisol (n = 68; P = 0.83).
UNASSIGNED: Dried urine is a viable alternative to liquid urine for the measurement of cortisol and cortisol metabolites. Additionally, if the 4 measures are added together, 4-spot urine collections can be representative of diurnal cortisol patterns commonly assessed using saliva and 24-hour urine collections.

In this study, we hypothesized that spot urine can be used to predict protein intake at both group and individual levels. Participants (n = 369) of this study were recruited from all 47 prefectures in Japan. Sex-specific formulas were developed based on the ratio of urea nitrogen to creatinine concentration obtained from 3 spot urine samples. Validity of the formulas was examined against two 24-hour urine collections for 7 combinations of spot urine (single and means of 2 or 3 samples) using t test (mean estimation), Spearman correlation, and Bland-Altman plot (individual bias). Means of measured protein intake based on 24-hour urinary excretions were 87.3 g/d (standard deviation 19.7) for men and 70.5 g/d (standard deviation 14.7) for women. Irrespective of sex, the predicted intakes were not significantly different (within 2.7% of differences) from those measured by urinary excretions. Predicted intakes were moderately correlated with measured intakes (men, 0.45-0.60; women, 0.35-0.53). Even after using the mean of 3 samples, Bland-Altman plots showed a considerably wide limit of agreement (men, -30 to 33 g/d; women, -27 to 24 g/d). Except for using single spot urine samples in women, the formula tended to overestimate intake at a lower and underestimate at a higher level of protein intake (slope: men, -0.47 [P < .0001]; women, -0.38 [P = .002]). In conclusion, predictive formulas developed in this study can be used to predict protein intake at group level or to rank individuals\' intake but not to predict absolute intake at individual level.