At-home determination of 24-h urine sodium excretion: Validation of chloride test strips and multiple spot samples
Bibliographic record
Abstract
Sodium intake and compliance with dietary sodium modification are typically assessed using a 24-h urine collection analyzed using flame photometry, but this is inconvenient. Spot urine samples have been investigated as alternatives to 24-h collections, but their accuracy is poor. Since sodium and chloride are present in equal concentrations in dietary salt, chloride test strips may provide a suitable proxy for at-home measurement of urine sodium concentrations. We aimed to determine whether (i) chloride test strips provide a reliable measure of urinary sodium compared to the gold standard flame photometry and (ii) multiple spot samples accurately reflect 24-h urine sodium. We recruited 43 participants (19 males) aged 23.6 ± 0.6 years to complete multiple consecutive spot samples (morning and evening) along with a 24-h urine sodium collection. Urine 24-h sodium estimates using chloride test strips (114.6 ± 7.5 mmol/day) were highly correlated (r = 0.900, p < 0.0001) with flame photometry (121.1 ± 7.7 mmol/day) with a bias of -6.53 ± 22.2 mmol/day. Use of a three-spot sample average (both morning and evening spot samples) with a correction factor applied (122.9 ± 4.1 mmol/day) provided a good approximation of 24-h sodium measured by flame photometry (125.6 ± 9.0 mmol/day), with a bias of -2.55 ± 43.9 mmol/day. Chloride test strips applied to a 24-h urine collection provide a highly accurate measure of urinary sodium excretion, permitting convenient at-home sample collection and analysis. Their application to multiple spot samples provides a reasonable approximation of sodium excretion that can be used to conveniently monitor attempts at dietary sodium manipulation, without the inconvenience of completing a 24-h urine sample.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".