A Comparison of the Predictive Performance of Different Methods of Kidney Function Estimation in a Well-Characterized HIV-Infected Population
Bibliographic record
Abstract
BACKGROUND: Glomerular filtration rate (GFR) estimation equations have never been validated in the HIV population. This pilot study aimed to compare all currently available methods of kidney function assessment with nuclear GFR in HIV-infected adults. METHODS: Patients underwent GFR measurement with (99m)Tc-diethylenetriaminepentaacetic acid (Tc-99m Pentetate), and measured values were compared with results of creatinine-based estimation equations [abbreviated 4-variable Modification of Diet in Renal Disease (MDRD) formula and Cockcroft-Gault (CG) formulae], 24-hour urine creatinine clearance and estimated cystatin C GFR. RESULTS: Twenty-seven HIV-infected adults were studied. Most were male and Caucasian, with a mean age of 52 years. Median CD4 was 290 cells/mm(3), 70% of patients had HIV RNA <50 copies/ml and all were receiving highly active antiretroviral therapy (median 5 drugs). Median Tc-99m Pentetate-GFR was 91 ml/min/1.73 m(2). Despite greater bias and similar accuracy, the MDRD formula was more precise than the CG formula, regardless of whether CG estimations were corrected for ideal body weight or body surface area. Relative accuracy within 30% of nuclear GFR was greater for the MDRD formula than for all other methods. The performance of 24-hour urine creatinine clearance was similar to that of the MDRD formula for patients with GFR <90 ml/min/1.73 m(2), although it performed less well at higher GFR. The performance of cystatin C GFR was inferior to that of all the creatinine-based methods. CONCLUSIONS: While no method of kidney function estimation performed highly, both 24-hour urine creatinine clearance and the MDRD formula performed with a level of precision and accuracy sufficient for clinical decision making. Our findings support the preferential use of the MDRD formula in the treated HIV population and suggest that there are no HIV-specific factors that limit equation applicability. Larger validation studies are needed to confirm our findings and allow generalization to the HIV population at large.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".