Abstract P227: The Feasibility of Interventions to Increase Potassium Intake for Hypertension: A Systematic Review of the Evidence
Bibliographic record
Abstract
Background: Increased potassium (K) intake has been reported to decrease blood pressure (BP) in animal studies as well as clinical trials. On this basis, major organizations including the American Heart Association recommend increasing K intake, preferably by diet, as a non pharmacological mean of reducing BP. However, it is not clear if the interventions for efficaciously increasing K intake are reproducible or feasible for translation into public health. Hence, we conducted a systematic review of the evidence to review this from randomized controlled trials (RCTs). Methods: We conducted a literature search using an information specialist of MEDLINE, EMBASE and Cochrane CENTRAL till November 2017. Two reviewers selected RCTs that were in adults, with an intervention aimed at increasing K intake, with blood pressure as an outcome. From RCTs which reported both a significant change in BP and K using 24 hour urine K, we evaluated the interventions for ease of reproducibility and feasibility based on prespecified criteria. Results: The initial search retrieved 1199 non-duplicate citations. After applying eligibility criteria, 90 studies were selected for inclusion. In 31 studies, the change in BP or K was not significant. Of the remaining 59 studies which reported a significant change in K and BP, 47 reported a change in K based on 24 hour urinary K measurement. 32/47 studies used a K supplement, with details provided on dose and administration to make it both reproducible and feasible. 15/47 studies used a dietary intervention, of which in 4, the intervention was not described in sufficient detail to be reproducible.The remaining 11 studies were feeding trials, with intervention consisting of provision of prepared meals, or of food items on a daily basis to make them unfeasible for routine clinical practice. Conclusions: Dietary potassium interventions from trials in which there was a significant change in K based on 24 hour urine and a significant change in BP are not reproducible or feasible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".