Palmaria palmata (Dulse) as an unusual maritime aetiology of hyperkalemia in a patient with chronic renal failure: a case report
Bibliographic record
Abstract
INTRODUCTION: Hyperkalemia is rare in individuals with normal renal function, regardless of dietary intake. This is due to the ability of the kidneys to adapt to increasing serum potassium concentrations. In patients with renal compromise, potassium homeostasis can become impaired. Palmaria palmata (dulse) is an edible seaweed known to be very rich in potassium. We report a case of hyperkalemia precipitated by the consumption of dulse by a patient with known renal disease. CASE PRESENTATION: A 66-year-old Caucasian woman with diabetes and chronic renal disease presented to our emergency department with nausea, vomiting, and worsening malaise, which had been present for less than a day. She had undergone electrocardiogram monitoring, which showed bradycardia, and periods of asystole. Our patient denied any other symptoms. Laboratory analysis revealed a serum potassium level of 8.6 mmol/L (normal range 3.5 to 4.9 mmol/L). Although our patient was taking some medications known to influence renal function, the only recent change that she could recount was that she had consumed approximately 200 g of dulse within the preceding 24 hours. A diagnosis of hyperkalemia was made, and the patient was treated successfully, and discharged home in her pre-morbid state. CONCLUSION: To the best of our knowledge, this is the first published report of hyperkalemia due to dulse consumption. Dulse is high in potassium, with concentrations upwards of 34 times greater than that found in bananas. Caution should be taken in prescribing medications with potential adverse renal effects for patients with known renal impairment. In such instances, renal function should be monitored closely. Patients should be counseled to avoid dietary sources high in potassium, with particular attention paid to unusual geographical dietary variations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 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".