Performance of Estimated Glomerular Filtration Rate Prediction Equations in Preeclamptic Patients
Bibliographic record
Abstract
Accurate estimation of the glomerular filtration rate (GFR) in patients with preeclampsia requires the collection of a 24-hour urine and can have important therapeutic and diagnostic implications. This procedure is often difficult or impossible to accomplish in this patient group. In this study, the Cockcroft-Gault, the Modification of Diet in Renal Disease (MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas were evaluated for their accuracy in determining GFR in the setting of preeclampsia. The estimated GFRs calculated from the above formulas were compared with the creatinine clearance values obtained from a 24-hour urine collections in 543 preeclamptic patients recruited from several large hospitals. Additionally, a set of new equations, preeclampsia GFR (PGFR), based on ethnicity, was created. The Cockcroft-Gault, MDRD, and CKD-EPI formulas were inaccurate in predicting GFR and both were significantly less accurate than PGFR. The latter formula provided an estimated GFR that was much closer to the creatinine clearance. Current GFR estimation equations based on serum creatinine values in nonpregnant patients are not reliable measures of renal function in patients with preeclampsia. The use of a new formula (PGFR) is recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".