Spot Urine Is a Poor Predictor of Dietary Sodium Intake in Individuals
Bibliographic record
Abstract
To the Editor: Sun et al. describe a validation study to develop and test formulae to convert measures from spot urine into an estimate of 24-hour urinary sodium excretion in Chinese patients with hypertension.1 The proposed Sun_C formulae (for men ane women) are similar to an increasing number of published formulae2 which are derived from regression analysis of spot and 24-hour urine results, and include age, weight, and gender as well as urinary parameters. Consistent with other formulae, the Sun_C formulae are very poor at predicting individual sodium excretion, as demonstrated in the Bland–Altman plots (Figures 1 and 3). For example in the testing set (Figure 1a) for 95% of cases, the difference between the paired measures of estimated (spot) and measured 24-hour urinary sodium excretion was between −105 and 105 mmol/day (around −2.4 and 2.4 g), even after 99 outliers (9% of participants) were excluded from the analysis. We suggest that rather than concluding that the Sun_C method “may prove a reasonable method to estimate the daily dietary sodium intakes… in Chinese hypertensive patients,” 1 the authors should conclude that these results show once again that spot urine provides inaccurate estimates of 24-hour urinary sodium excretion in individuals regardless of the forumula used. There is now a large body of evidence to support this conclusion.3 Spot urine sodium reflects very short-term (hours) sodium consumption and urine creatinine also has high variability. Thus, there is a lack of theoretical basis for using spot urine samples to predict ususal sodium intake in individuals, which has been confirmed in meta-analyses of validation studies.2,3 Thus, the International Consortium for Quality Research on Dietary Sodium/Salt (TRUE) position statement recommends that in order to assess an individual’s current usual intake, at least 3 nonconsecutive 24-hour urine collections are collected, and that spot urine collections are not used in this context.4 Rachael M. McLean has no disclosures. Norm Campbell was a paid consultant to the Novartis Foundation (2016–2017) to support their program to improve hypertension control in low- to middle-income countries which includes travel support for site visits and a contract to develop a survey. N.C. has provided paid consultative advice on accurate blood pressure assessment to Midway Corporation (2017) and is an unpaid member of World Action on Salt and Health (WASH).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".