Severe Hyperkalemia: Electrocardiographic Tips for Early Recognition Based on a Case Report
Bibliographic record
Abstract
Background: Rapid correction of severe hyperkalemia is mandatory to survival due to its induction of fatal cardiac arrhythmias. The electrocardiogram serves as the diagnostic tool that can provide insight into such fatal arrhythmias. We present two relevant alterations seen in an 84-year-old female patient with previous anterior myocardial infarction, angioplasty of the circumflex coronary artery, left ventricular ejection fraction of 35%, hypertension, dyslipidemia, paroxysmal atrial fibrillation, and diabetes. The Case: The patient had 4-days with asthenia, adynamia and dyspnea. Lung auscultation showed bilateral base rales with cardiomegaly and interstitial edema identified on chest x-ray. Lab work revealed severe metabolic acidosis, increased plasma urea, creatinine, and severe hyperkalemia (7.9 mEq/liter) considered secondary to acute renal failure. Treatment was initiated with 0.9% sodium chloride, bicarbonate, ASA diuretics and polarizing solution (insulin), resulting in a reduction of hyperkalemia to 6.1 mEq/liter. The patient suffered a cardiorespiratory arrest with recovery and needed intubation and dopamine for hemodynamic support but died 15 hours after admission. Conclusion: The electrocardiographic findings characteristic of severe hyperkalemia were: (i) regular rhythm (cycle length 920-950 ms) without discernible P-waves, which may have a junctional or ventricular origin and less probably could be a manifestation of sinoventricular conduction (preferential conduction from the sinus node to the AV node through specialized tracts without activation of the atrial cardiomyocytes), and (ii) sine wave morphology (markedly wide QRS, absence of ST-segment and broadly based T-waves). These electrocardiographic features, typical of hyperkalemia exceeding 7.0 mEq/liter, are harbingers of malignant arrhythmias and should prompt immediate therapy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".