Iohexol Plasma Clearance Measurement Protocol Standardization: A Consensus of the European Kidney Function Consortium
Bibliographic record
Abstract
Background: International consensus and the 2024 KDIGO guidelines supports the development of standardized protocols for measured glomerular filtration rate (mGFR) to facilitate the adoption of mGFR in both clinical and research settings. Methods: The European Kidney Function Consortium (EKFC) convened an international group of mGFR experts and performed an extensive literature search to inform the development of recommendations for mGFR determination using one-compartment plasma clearance models and iohexol as the exogenous filtration marker. Iohexol was selected as it is non-radiolabeled, safe, inexpensive, widely available, and can be assayed at a central laboratory. Other commonly used non-radio labeled tracers have been (inulin) or are soon to be (iothalamate) discontinued. A plasma clearance model was selected as it does not require timed urine collections. A one-compartment model was preferred to a two-compartment model as it requires fewer samples. The resulting recommendations were based on published evidence complemented by expert opinion. Results: Recommendations include practical advice for patients and health professionals, preparation, administration and safety aspects of iohexol, laboratory analysis, blood sample collection and sample timing for both multiple and single sample protocols, description of the mGFR mathematical calculations as well as implementation strategies (Figure). The EKFC will provide materials such as patient information sheets, standard operating procedures, a study protocol template, and support for mGFR calculation. Conclusion: Members of the EKFC have evaluated the evidence and formulated recommendations that include all aspects of iohexol plasma clearance measurement using a one-compartment model. Nephrologist education and widespread dissemination is critical to making mGFR available for patient care and research.
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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 | 0.270 | 0.201 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.013 | 0.007 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".