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Record W2110777344 · doi:10.1681/asn.2012020144

Improvement in Kidney Function

2012· letter· en· W2110777344 on OpenAlexafffundabout
Tanvir Chowdhury Turin, Brenda R. Hemmelgarn

Bibliographic record

VenueJournal of the American Society of Nephrology · 2012
Typeletter
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsFoothills Medical CentreUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsRenal functionMedicineFunction (biology)KidneyUrologyInternal medicineBiologyCell biology

Abstract

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CKD is thought traditionally to follow an unremittingly progressive decline over time. Because of this, guidelines and public health campaigns have focused on early detection and treatments directed to slow the progression of CKD and delay the onset of ESRD. Progression of kidney disease has been studied in both observational and clinical trial settings.1–7 However, there has been considerable variability in progression reported, ranging from rapid progression to nonprogressive stable kidney function to an improvement in kidney function over time.2,6–8 Recent studies that attempted to characterize patients who experience an improvement in kidney function were plagued by the variability inherent in serum creatinine measurements used to estimate GFR. In this issue of JASN, Hu et al.9 report improvement in kidney function among a subset of patients with hypertensive CKD. The authors use data from the AASK (The African-American Study of Kidney Disease and Hypertension) trial,3,10 which was designed to evaluate the effect of BP and antihypertensive drug therapy on the rate of decline of renal function in participants with mild-to-moderate chronic renal insufficiency caused by hypertension. The participants were 1094 African Americans 18–70 years of age, with GFRs between 20 and 65 ml/min per 1.73 m2 at enrollment. Kidney function was determined by direct measurement of GFR from 125I-iothalamate clearances for the trial phase of the study. An equation was derived from this measured GFR data to estimate GFR (eGFR) using serum creatinine. This eGFR was used for the longitudinal assessment of kidney function. To avoid the acute hemodynamic changes in eGFR related to drug interventions, the authors focused on chronic eGFR slopes among the 949 participants with three or more eGFR measurements (61% male) with a baseline mean age of 55 (SD:11) years. During the 8.8 years of follow-up, the median number of eGFR measurements was 16. Bayesian linear mixed effects models were applied to derive the probability that each patient's true underlying slope was greater than zero and could not be explained by random measurement variation; clear improvers were defined as patients with a probability of at least 0.95 of having positive eGFR slopes. Among the participants, 3.3% (n=31) demonstrated clear positive eGFR slopes—that is an improvement in kidney function over time. The mean slope of these patients was +1.06 (SD: 0.12) ml/min per 1.73 m2 per year, compared with −2.45 (SD: 0.07) ml/min per 1.73 m2 per year among remaining patients. Relative to nonimprovers, improvers were more likely to be younger, have low baseline proteinuria, and lower BP goal assignment at randomization. Younger age and lower levels of proteinuria were associated with improvement in kidney function in the multivariate model. Methodological and analytical differences across studies make it difficult to directly compare results from prior studies to those reported by Hu et al. However, several prior studies have also reported improvements in kidney function in a subset of patients over time. As many as 19% patients with a GFR between 25 and 55 ml/min per 1.73 m2 in the Modification of Diet in Renal Disease study had stabilization or improvement of their renal function during the 2-year follow-up. Eriksen and Ingebretsen,2 examining 3047 Norwegian clinical practice patients with stage 3 CKD, reported that 27% did not experience a decline in GFR during the mean observation period of 4 years. In a recent study, Al-Aly et al,8 studying the Veteran Affairs cohort of 4171 patients with early CKD (eGFR between 59 and 45 ml/min per 1.73 m2), reported that after a median observation period of 2.6 years, 38% patients with stage 3 CKD maintained stable kidney function. Similarly, Perkins et al.,6 studying 15,465 patients receiving primary care through a large integrated health care system, reported that approximately one-third of patients had an increase in eGFR over the follow-up period. In the study by Hu et al.,9 baseline proteinuria was lower among improvers than nonimprovers, and in multivariate analysis, the authors demonstrate that reduction in proteinuria was associated with improvement in eGFR. These results add to prior studies demonstrating the importance of proteinuria as a prognostic marker and specifically that the prognosis associated with a given level of kidney function varies significantly based on the presence and severity of proteinuria.11–14 Although the paper of Hu et al.9 is interesting because it demonstrates that true improvement in eGFR (confirmed by direct measurement of kidney function) can occur over time, it also raises some important questions. In particular, the prognostic implications of an improvement in kidney function over time are not addressed in this study. An improvement in kidney function in general is expected to be associated with a more favorable health status; however, recent studies5,6,8 report that improvement in eGFR over time is associated with adverse outcomes. Perkins et al.6 demonstrated that both declining and increasing eGFR over time associates with an increased risk of death compared with stable kidney function. Similarly, Al-Aly et al.8 reported that, compared with the patients with mild CKD progression, patients with nondeclining kidney function (rate of eGFR change >0 ml/min per 1.73 m2 per year) exhibited a trend toward increased risk of death. Similarly, Matsushita et al.,5 studying the Atherosclerosis Risk in Communities cohort, also reported that increasing eGFR is associated with increased risk of adverse outcomes. The study by Hu et al.9 was rigorously conducted and sheds light on this important issue of the dynamics of change in renal function. The completeness of the baseline clinical data, by the virtue of the initial well designed clinical trial, enabled an accurate assessment of factors associated with improvement in kidney function. Robust statistical analysis methods also allowed the authors to account for the common biases encountered in slope analysis. There are, however, a few limitations, appropriately acknowledged by the authors, which should be kept in mind while interpreting the study results. The study population was very selective; thus, the generalizability of the results is limited. Although the authors used robust statistical methods, the phenomenon of regression to the mean cannot be excluded. Finally, the study sample was small and points toward the necessity to explore this issue in a larger cohort. Despite these limitations, the study by Hu et al. highlights the potential that eGFR may improve over time among a subset of patients. Further studies in this area are required to characterize the improvers, as well as to determine the prognostic implications of an improvement in eGFR. Disclosures None. T.C.T. is supported by Fellowship Awards from the Canadian Institutes of Health Research (CIHR), Canadian Diabetes Association (CDA), and the Interdisciplinary Chronic Disease Collaboration (ICDC) team grant funded by Alberta Innovates–Health Solutions (AI-HS). B.R.H. is supported by an AI-HS Salary Award and by the Roy and Vi Baay Chair in Kidney Research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.005

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.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2012
Admission routes3
Has abstractyes

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Same venueJournal of the American Society of NephrologySame topicChronic Kidney Disease and DiabetesFrench-language works237,207