Severe hyperkalemia following adrenalectomy for aldosteronoma: prediction, pathogenesis and approach to clinical management- a case series
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Bibliographic record
Abstract
BACKGROUND: As the field of Primary Aldosteronism (PA) becomes ever expanded, diagnosis of PA is increasingly diagnosed by endocrinologists. With increased PA screening, many of the cases are now found in patients with complex co-morbidities in addition to their hypertension. Post adrenalectomy renal impairment with hyperkalemia is now increasingly seen in these complex patients, as evidenced by the numerous reports on this issue that have appeared within the past 3 years. We present a small case series to illustrate the breadth of the problem, along with a discussion about how such CKD/hyperkalemic events may be predicted. CASE PRESENTATION: We present three cases of primary aldosteronism with long standing hypertension (more than 10 years) hypokalemia (2.0-3.0 mmol/l). Serum aldosterone was high with low renin activity leading to high aldosterone to renin ratio (ARR). They underwent abdominal CT scan revealing adrenal mass and adrenal vein sample confirmed lateralization. None of the patients had evidence of renal disease before surgery (as evident by normal eGFR and serum creatinine). Post adrenalectomy they had reduction in the blood pressure and became eukalemic. Serum aldosterone and renin activity were low leading to a low ARR. Case 1 developed hyperkalemia and increased serum creatinine 6 weeks post operatively which resolved with initiation of fludrocortisone and every attempt to discontinue fludrocortisone resulted in hyperkalemia and rising creatinine. Her hyperkalemia is under control with oral sodium bicarbonate. Case 2 developed hyperkalemia and increasing creatinine 2 months post operatively transiently requiring fludrocortisone and later on managed with furosemide for hyperkalemia. Case 3 developed renal impairment and hyperkalemia 2 weeks post operatively requiring fludrocortisone. CONCLUSION: Post APA resection severe hyperkalemia may be a common entity and screening should be actively considered in high risk patients. Older age, longer duration of hypertension, impaired pre-op and post-op GFR and higher levels of pre-op aldosterone and are all risk factors which predict the likelihood of developing post-operative hyperkalemia. Fludrocortisone, sodium bicarbonate, loop diuretics and potassium binders can be used for treatment. Treatment choice should be tailored to patient characteristics including fluid status, blood pressure and serum creatinine. Potassium binders should be avoided in patients with history of recent abdominal surgery, opioid use and constipation. Serum electrolytes and creatinine should be monitored every 1-2 weeks after starting treatment to ensure an adequate response. Prolonged management may be necessary in some cases and at-risk patients should be counselled as to the meaning and importance of post-operative changes in measured renal function and potassium.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it