Type II Renal Tubular Acidosis Secondary to Topiramate: A Review
Bibliographic record
Abstract
Topiramate (TMP) is a broad-spectrum anticonvulsant drug used to treat a wide variety of seizure disorders, for migraine prophylaxis, and for many other indications. An important side effect of TMP is metabolic acidosis, which is mediated by renal tubular defects. TMP inhibits carbonic anhydrase, an enzyme that is necessary for acid handling in the proximal renal tubule. Patients can present with asymptomatic serum electrolyte derangements, acute change in mental status, hyperventilation, cardiac arrhythmias, or other sequelae of metabolic acidosis and associated respiratory compensation. If taken chronically, TMP can cause renal stone formation, bone mineralization defects, and several other effects secondary to changes in serum and urine pH and electrolytes. There is no well-studied way to prevent metabolic acidosis in patients taking TMP, but physicians should be vigilant when prescribing this drug to patients with the history of renal diseases and other comorbidities, and aware of this potential etiology of metabolic acidosis. We present a literature review of the underlying mechanisms involved in the development of renal tubular acidosis secondary to TMP and its clinical consequences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".