Tenapanor: A new treatment option for hyperphosphatemia in end stage kidney disease
Bibliographic record
Abstract
PURPOSE: This narrative review explores the currently published studies that have evaluated tenapanor for the treatment of hyperphosphatemia in end-stage kidney disease (ESKD) patients on hemodialysis. This medication's new phosphate lowering mechanism of action reduces intestinal phosphate absorption predominantly through reduction of passive paracellular phosphate flux by inhibition of the sodium/hydrogen exporter isoform 3 (NHE3). Tenapanor additionally prevents active transcellular phosphate absorption compensation by decreasing the expression of sodium phosphorus 2b transport protein (NaPi2b). METHODS: A comprehensive search of the literature was conducted using PubMed and ClinicalTrials.gov search engines. The search term "tenapanor hyperphosphatemia" was used for study retrieval. Results were limited to studies published in the English language and excluded review articles. Human, animal, and in vitro studies were included. No date range was specified. RESULTS: A total of 11 primary studies were identified and included in this review, the largest human study of which enrolled 236 patients. Each study is presented in table format along with measured end points. CONCLUSIONS: Tenapanor is the first drug in its class that lowers hyperphosphatemia in ESKD patients through a novel mechanism of action involving paracellular inactive transport. Although more studies are needed, early results indicate that tenapanor may have a place in managing hyperphosphatemia in ESKD patients both as monotherapy and as an adjunct to existing phosphate binder 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.005 | 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".