Outcomes and Patterns Related to Magnesium in Acute Heart Failure: A Population-Based Study
Bibliographic record
Abstract
Abstract Importance The significance of magnesium as a treatment or prognostic factor is unknown in heart failure despite its frequent use. Objective To assess the frequency and outcomes of magnesium testing, hypomagnesemia and intravenous (IV) replacement in a large population-based cohort. Design, Setting, and Participants Retrospective cohort study using linked administrative data from April 2012 - March 2020. Patients with primary diagnosis of HF in the emergency department or hospital were included and the rates and outcomes of magnesium testing, hypomagnesemia and IV replacement were assessed. Main Outcome(s) and Measure(s) The primary clinical outcomes included all-cause and cause specific death and hospitalization. Secondary outcomes included emergency department visits and physicians claims. Other outcomes included factors and rates of serum magnesium testing and hypomagnesemia. Results Of 78,957 acute heart failure episodes (in 42,763 patients), 58.7% included a serum magnesium measurement. Of the patients who were tested, serum magnesium levels were <0.75 mmol/L in 31.7%, between 0.75 - 0.95 mmol/L in 56.8% and >0.95 mmol/L in 11.5%. Magnesium levels (per 0.02 mmol/L increase) were independently associated with mortality when <0.70 mmol/L [hazard ratio (HR) 0.99 (95% confidence interval (CI) 0.98-0.99); p<0.001] or >0.86 mmol/L [HR 1.04 (95% CI 1.03-1.04); p<0.001]. IV magnesium was given to 13.7% (n=6,333) of those who were tested (29.7% of whom did not have hypomagnesemia); after multivariable adjustment, receiving IV magnesium was associated with a higher short term mortality [HR 1.66 (95% CI 1.4-1.96); p<0.0001] and hospitalization risk [HR 1.36 (95% CI 1.13-1.63); p<0.001]. Conclusions and Relevance Serum magnesium testing is common in patients presenting to the ED or hospital with HF, and low or high magnesium is associated with worse outcomes. Replacement with IV magnesium was associated with worse outcomes even after adjustment, a finding which warrants further study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".