Potassium levels and the risk of all-cause and cardiovascular mortality among patients with cardiovascular diseases: a meta-analysis of cohort studies
Bibliographic record
Abstract
BACKGROUND: Abnormal blood potassium levels are associated with an increased risk of cardiometabolic diseases and mortality in the general population; however, evidence regarding the association between dyskalemia and mortality among patients with cardiovascular disease (CVD) remains inconclusive. This study aimed to evaluate the association of potassium levels with all-cause and cardiovascular mortality among patients with CVD. METHODS: PubMed, Embase, Web of Science, and Cochrane Library databases were searched up to August 2023 to identify relevant cohort studies among patients with CVD, such as myocardial infarction, stroke, and heart failure. Abnormal potassium levels were considered as hypokalemia or hyperkalemia. The primary outcomes were all-cause mortality based on follow-up length (including in-hospital, short-term and long-term mortality) and cardiovascular mortality. The methodological quality of included studies was assessed by using the Newcastle-Ottawa Scale. The pooled relative risks (RRs) and 95% confidence intervals (CIs) were calculated using random-effects models. Restricted cubic splines were applied to explore the dose-response relationship. RESULTS: Thirty-one cohort studies involving 227,645 participants with an average age of 68.3 years were included in the meta-analysis, all of which achieved moderate to high quality. Hyperkalemia was significantly associated with an approximately 3.0-fold increased risk of all-cause in-hospital mortality (RR:2.78,95CI%:1.92,4.03), 1.8-fold of all-cause short-term mortality (RR:1.80, 95CI%:1.44,2.27), 1.3-fold of all-cause long-term mortality (RR:1.33, 95CI%:1.19,1.48) and 1.2-fold of cardiovascular mortality (RR:1.19, 95CI%:1.04,1.36). Similar positive associations were also observed between hypokalemia and risk of all-cause mortality and cardiovascular mortality. The RRs of all-cause in-hospital, short-term, long-term mortality and cardiovascular mortality with hyperkalemia were attenuated to 2.21 (95CI%:1.60,3.06), 1.46(95CI%:1.25,1.71), 1.23 (95CI%:1.09,1.39) and 1.13 (95CI%:1.00,1.27) when treating hypokalemia together with normokalemia as the reference group. A U-shaped association was observed between potassium levels and mortality, with the lowest risk at around 4.2 mmol/L. CONCLUSIONS: Both hypokalemia and hyperkalemia were positively associated with the risk of mortality in patients with CVD. Our results support the importance of potassium homeostasis for improving the CVD management. REGISTRATION: PROSPERO, CRD42022324337.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.062 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".