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Record W4380264534 · doi:10.34067/kid.0000000000000183

Associations of Biomarkers of Kidney Tubule Health, Injury, and Inflammation with Left Ventricular Hypertrophy in Children with CKD

2023· article· en· W4380264534 on OpenAlexaboutno aff
Kuan Jiang, Jason H. Greenberg, Alison G. Abraham, Yunwen Xu, Jeffrey R. Schelling, Harold I. Feldman, Sarah J. Schrauben, Sushrut S. Waikar, Michael G. Shlipak, Nicholas Wettersten, Steven G. Coca, Ramachandran S. Vasan, Orlando M. Gutiérrez, Joachim H. Ix, Bradley A. Warady, Paul L. Kimmel, Joseph V. Bonventre, Chirag R. Parikh, Mark Mitsnefes, Michelle Denburg, Susan L. Furth

Bibliographic record

VenueKidney360 · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteU.S. Department of Veterans Affairs
KeywordsMedicineLeft ventricular hypertrophyInternal medicineKidney diseaseSuPARBiomarkerBody mass indexEndocrinologyGastroenterologyCardiologyPlasminogen activatorBlood pressureBiology

Abstract

fetched live from OpenAlex

Key Points Higher plasma and urine kidney injury molecule-1, urine monocyte chemoattractant protein-1, and lower urine alpha-1-microglobulin were associated with left ventricular hypertrophy, even after adjustment for confounders. Biomarkers of tubular injury, dysfunction, and inflammation may indicate the severity of kidney pathology and are associated with left ventricular hypertrophy. Background Left ventricular hypertrophy (LVH) is common in children with CKD and is associated with an increased risk of cardiovascular disease and mortality. We have shown that several plasma and urine biomarkers are associated with increased risk of CKD progression. As CKD is associated with LVH, we sought to investigate the association between the biomarkers and LVH. Methods In the CKD in Children Cohort Study, children aged 6 months to 16 years with an eGFR of 30–90 ml/min per 1.73 m 2 were enrolled at 54 centers in the United States and Canada. We measured plasma biomarkers kidney injury molecule-1 (KIM-1), tumor necrosis factor receptor-1, tumor necrosis factor receptor-2, soluble urokinase-type plasminogen activator receptor and urine KIM-1, monocyte chemoattractant protein-1 (MCP-1), YKL-40, alpha-1-microglobulin (alpha-1m), and epidermal growth factor in stored plasma and urine collected 5 months after enrollment. Echocardiograms were performed 1 year after enrollment. We assessed the cross-sectional association between the log 2 biomarker levels and LVH (left ventricular mass index greater than or equal to the 95th percentile) using a Poisson regression model, adjusted for age, sex, race, body mass index, hypertension, glomerular diagnosis, urine protein-to-creatinine ratio, and eGFR at study entry. Results Among the 504 children, LVH prevalence was 12% ( n =59) 1 year after enrollment. In a multivariable-adjusted model, higher plasma and urine KIM-1 and urine MCP-1 concentrations were associated with a higher prevalence of LVH (plasma KIM-1 prevalence ratio [PR] per log 2 : 1.27, 95% confidence interval [CI], 1.02 to 1.58; urine KIM-1 PR: 1.21, 95% CI, 1.11 to 1.48; and urine MCP-1 PR: 1.18, 95% CI, 1.04 to 1.34). After multivariable adjustment for covariates, lower urine alpha-1m was also associated with a higher prevalence of LVH (PR: 0.90, 95% CI, 0.82 to 0.99). Conclusions Higher plasma and urine KIM-1, urine MCP-1, and lower urine alpha-1m were each associated with LVH prevalence in children with CKD. These biomarkers may better inform risk and help elucidate the pathophysiology of LVH in pediatric CKD.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.244
Teacher spread0.236 · 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 teacher head, 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".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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