Comparison of Chronic Kidney Disease (CKD) Epidemiology Formula with Other Calculated Creatinine Formulas for the Determination of CKD in Cognitively Intact and Impaired Elderly Outpatients
Bibliographic record
Abstract
Chronic kidney disease (CKD) is defined as a glomerular filtration rate (GFR) less than 60 mL/min per 1.73 m2 for three or more months. The prevalence of CKD increases with advancing age.1 Because serum creatinine is not an accurate measure for estimating renal function in elderly adults, creatinine clearance or GFR is used to assess CKD. The criterion standard methods for measuring GFR are based upon injection of a radioactive contrast agent such as iodothalamate or using a substance such as inulin. This method is impractical in regular clinical practice and is not cost effective, so calculated creatinine formulas are used instead. Various formulas for estimating the GFR such as the Cockroft-Gault adjusted for body surface area (CG/BSA), Modified Diet in Renal Disease (MDRD), Wright, and Mayo Clinic formulas have been suggested for calculating GFR from serum creatinine concentration.2-5 A new formula to estimate GFR from serum creatinine called the chronic kidney disease epidemiology (CKD-EPI) equation was recently developed and validated in some studies.6 CKD is associated with outcomes such as development of cardiovascular disease, progression to end-stage renal disease, hospitalization, and death in community-based populations.7, 8 Clinicians need a quick and reliable method to estimate renal function before determining proper doses of renally excreted medications. A recent study indicated that CKD-EPI estimated GFR (eGFR) is an independent predictor of incident adverse drug reactions in elderly adults.9 Little is known about the extent of the discrepancy between the CKD-EPI formulas and other calculated creatinine clearance formulas. The aim of this retrospective study was to compare a recently introduced CKD-EPI formula with other calculated creatinine clearance formulas in determining CKD in elderly outpatients. A chart review was conducted on consecutive adults aged 65 and older over a 9-month period. Data regarding age, sex, cognitive status, clock drawing, weight, height, and serum creatinine were collected. Serum creatinine was estimated using the isotope dilution mass spectrometry method. Pearson correlation coefficients, Bland-Altman plots, and kappa statistics were used for statistical analysis. Of 197 participants, 72% had mild cognitive impairment or dementia. Thirty-five percent of participants had Stage 3 renal disease according to the CKD-EPI formula, 36% according to the MDRD formula, 48% according to the CG/BSA formula, 48% according to the Wright formula, and 18% according to the Mayo clinic formula There was a high correlation between CKD-EPI and the MDRD (Pearson correlation coefficient (r) = 0.97, P < .001), CKD-EPI and the CG/BSA formulas (r = 0.91, P < .001), CKD-EPI and the Wright formula (r = 0.84, P < .001), and CKD-EPI and the Mayo Clinic formula (r = 0.84, P < .001). As shown in Bland-Altman plots (Figure 1), agreement between CKD-EPI and MDRD was better than agreement between CKD-EPI and the other formulas. In determining Stage 3 CKD, the kappa statistic was 0.91 between CKD-EPI and MDRD, 0.49 between CKD-EPI and the CG/BSA formula, 0.42 between CKD-EPI and the Mayo formula, 0.29 between CKD-EPI and the Wright formula, indicating low agreement between these last three formulas. The diagnosis of Stage 3 CKD in elderly adults with and without cognitive impairment depended on the formula used. Discordance of 1 mL/min was seen between CKD-EPI and MDRD, −9 mL/min between CKD-EPI and the CG/BSA, −12 mL/min between CKD-EPI and the Wright formulas, and 13 mL/min between CKD-EPI and the Mayo formulas for eGFR. The difference between CKD-EPI and MDRD was small, but the difference between CKD-EPI and the other formulas was significant. Similar differences were seen in the subgroup analysis comparing elderly adults with and without cognitive impairment. Even though there was strong correlation between the CKD-EPI and all four formulas studied, there was a clear discrepancy indicated by poor agreement between the CKD-EPI and the CG/BSA, Wright, and Mayo formulas. A limitation of the study was its cross-sectional nature and that eGFR was not correlated with definite or criterion standard measures of GFR, such as inulin clearance. In CKD screening, testing for proteinuria is also recommended in addition to eGFR. This was also a limitation, because this study did not have information on proteinuria. In conclusion, significant differences in eGFR were observed between the CKD-EPI equation and other calculated formulas in individuals with and without cognitive impairment. The most accurate method of estimating GFR and creatinine clearance in elderly adults is a topic of ongoing debate, and more research is needed to find an acceptable, validated formula. Conflict of Interest: None. Author Contributions: Dr. Alagiakrishnan: Study concept and design, acquisition of data, preparation of manuscript. Dr. Senthilselvan: Study design, analysis and interpretation of data, preparation of manuscript. Sponsor's Role: None.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".