Can methods based on spot urine samples be used to estimate average population 24 h sodium excretion? Results from the Isfahan Salt Study
Bibliographic record
Abstract
OBJECTIVE: To assess agreement between established methods of estimating salt intake from spot urine collections and 24 h urinary Na (24hUNa) and then to develop a valid formula that can be used in the Iranian population to estimate salt intake from spot urine samples. DESIGN: A validation study. Three spot urine samples were collected (fasting second-void morning; afternoon; evening) on the same day as a 24 h urine collection. We estimated 24hUNa from spot specimens using the Kawasaki, Tanaka and INTERSALT equations. Two new formulas were developed, the Iran formula 1 (Iran 1) and Iran formula 2 (Iran 2), based on our population characteristics. SETTING: Iranian adults recruited in 2014-2015. PARTICIPANTS: Healthy volunteer adults aged ≥18 years. RESULTS: With all three spot urine specimens, predicted population 24hUNa was underestimated based on the INTERSALT equation (-469 to -708 mg/d; all P < 0·05) and conversely overestimation occurred with the Kawasaki equation (926 to 1080 mg/d; all P < 0·01). The Tanaka equation produced comparable estimates to measured 24hUNa (-151 to 86 mg/d; all P > 0·49). The newly derived formulas, Iran 1 and Iran 2, showed less mean bias than the established equations (Iran 1: 43 to 80 mg/d, all P > 0·55; Iran 2: 22 to 90 mg/d, all P > 0·50). CONCLUSIONS: In this Iranian sample, the Tanaka equation and newly derived formulas produced group-level estimates comparable to measured 24hUNa. The newly developed formulas showed less mean bias than established equations; however, they need to be tested for generalization in a larger sample.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".