Impact of sodium intake on blood pressure, mortality and major cardiovascular events: an umbrella review of systematic reviews and meta-analyses
Bibliographic record
Abstract
A plethora of systematic reviews with meta-analyses (SRMAs) evaluating sodium intake on cardiovascular health have been published. However, the quality of the SRMAs, that report absolute estimates of effect for major cardiovascular events and the corresponding certainty of the evidence has not been explicitly summarized. We conducted an umbrella review to assess the strength and validity of associations between lower sodium intake and cardiovascular outcomes. We used a modified, more stringent, version of the AMSTAR 2 instrument and the GRADE approach to assess SRMA methodological quality and evidence certainty, respectively. Across three cardiovascular risk strata, we computed the absolute risk reduction (ARR) for binary outcomes. We included 56 SRMAs. In various cardiovascular risk populations, moderate to high certainty evidence suggested that lower sodium intake reduced systolic blood pressure (BP) by -8.69 to -2.00 mmHg, and had concordant but smaller effects on diastolic BP. Salt substitutes conferred a small but important reduction in all-cause and cardiovascular mortality [ARR 12 fewer per 1000; 9 fewer per 1000; respectively], and had little to no effect on the risk of stroke [ARR 1 fewer per 1000]. Moderate to high certainty evidence suggested that lower sodium intake is probably beneficial for the prevention of major cardiovascular events, especially in low cardiovascular risk populations.
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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 | 0.024 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.018 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".