Further evidence that methods based on spot urine samples should not be used to examine sodium‐disease relationships from the Science of Salt: A regularly updated systematic review of salt and health outcomes (November 2018 to August 2019)
Bibliographic record
Abstract
The aim of this eighth Science of Salt outcomes review is to identify, summarize, and critically appraise studies on dietary sodium and health outcomes published between November 1, 2018, and August 31, 2019, to extend this series published in the Journal since 2016. The standardized Science of Salt search strategy was conducted. Studies were screened based on a priori defined criteria to identify publications eligible for detailed critical appraisal. The search strategy resulted in 2621 citations with 27 studies on dietary sodium and health outcomes identified. Two studies met the criteria for detailed critical appraisal and commentary. We report more evidence that high sodium intake has detrimental health effects. A post hoc analysis of the Dietary Approaches to Stop Hypertension (DASH) sodium trial showed that lightheadedness occurred at a greater frequency with a high sodium DASH diet compared to a low sodium DASH diet. In addition, evidence from a post-trial analysis of the Trials of Hypertension (TOHP) I and II cohorts showed that estimates of sodium intake from methods based on spot urine samples are inaccurate and this method alters the linearity of the sodium-mortality association. Compared to measurement of 24-hour sodium excretion using three to seven 24-hour urine collections, estimation of average 24-hour sodium excretion with the Kawasaki equation appeared to change the mortality association from linear to J-shaped. Only two high-quality studies were identified during the review period, both were secondary analyses of previously conducted trials, highlighting the lack of new methodologically sound studies examining sodium and health outcomes.
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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 | 0.114 | 0.376 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".