Hyperkalemia and its Association With Mortality, Cardiovascular Events, Hospitalizations, and Intensive Care Unit Admissions in a Population-Based Retrospective Cohort
Bibliographic record
Abstract
Introduction Hyperkalemia is a common, potentially life-threatening condition in patients with chronic kidney disease (CKD). We studied the association between hyperkalemia and mortality, cardiovascular events, hospitalizations, and intensive care unit (ICU) admissions. Methods We performed a retrospective cohort study using administrative databases in Manitoba, Canada. All adults (≥18 years of age) with potassium tests between January 2007 and December 2016 were included, with follow-up until March 31, 2017. Propensity score matching was performed among patients with de novo hyperkalemia (serum potassium ≥ 5.0 mmol/l) and patients who were nonhyperkalemic. The association between hyperkalemia and normokalemia and mortality was assessed using multivariate Cox proportional hazards regression models, adjusting for patient characteristics in a 1:1 propensity score–matched sample. Secondary outcomes included cardiovascular events, hospitalizations, and ICU admissions. A sensitivity analysis was performed with hyperkalemia defined as serum potassium ≥ 5.5 mmol/l. Results Of 93,667 patients with de novo hyperkalemia, 36% had diabetes mellitus (DM), 28% had CKD, and 21% had heart failure (HF). In the propensity score–matched sample of 177,082 individuals, hyperkalemia was associated with an increased risk for all-cause mortality (hazard ratio [HR] 1.15 [95% confidence interval {CI} 1.13–1.18], P < 0.001), cardiovascular events (HR 1.20 [95% CI 1.14–1.26], P < 0.001), short-term mortality (odds ratio [OR] 1.29 [95% CI 1.24–1.34], P < 0.001), hospitalizations (OR 1.71 [95% CI 1.68–1.74]), and ICU admissions (OR 3.48 [95% CI 3.34–3.62], P < 0.001). Findings were unchanged when a threshold of serum potassium ≥ 5.5 mmol/l was used. Conclusion Hyperkalemia was an independent risk factor for all-cause mortality, cardiovascular events, hospitalizations, and ICU admissions. This finding expands our understanding of important clinical outcomes associated with hyperkalemia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".