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Record W7008089254

Asprosin Levels in Adults with Type 2 Diabetes Mellitus and Diabetic Kidney Disease: A Systematic Review and Meta-Analysis

2025· article· en· W7008089254 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsType 2 Diabetes MellitusDiabetes mellitusDiseaseConfidence intervalBiomarkerType 2 diabetesKidney diseaseMeta-analysisHealth care
DOInot available

Abstract

fetched live from OpenAlex

Jovana Ristic,1 Sena Kodalak,2 Gonzalo Alberto Peralta-Jiménez,3 Maria Fernanda Moura de Lima,4 Marijana Kovacevic,5 Srdjan Masic,6 Tatjana Nikolic1,7 1Faculty of Medicine, University of Belgrade, Belgrade, Serbia; 2Department of Internal Medicine, Faculty of Medicine, Hacettepe University, Ankara, Turkey; 3Arica and Parinacota Health Service, Subdirectorate of Healthcare Management, Arica, Chile; 4Federal University of Campina Grande, Paraiba, Brazil; 5Department of Internal Medicine, Faculty of Medicine Foca, University of East Sarajevo, Foca, Bosnia and Herzegovina; 6Department of Primary Health Care and Public Health, Faculty of Medicine, University of East Sarajevo, Foca, Bosnia and Herzegovina; 7Institute of Medical and Clinical Biochemistry “Ljubiša Rakić”, Faculty of Medicine, University of Belgrade, Belgrade, SerbiaCorrespondence: Marijana Kovacevic, Email kovacevicvmarijana@gmail.com Tatjana Nikolic, Email tatjana.nikolic@med.bg.ac.rsPurpose: Diabetic kidney disease (DKD) significantly affects health and healthcare costs due to chronic kidney disease complications. Given asprosin’s potential as a biomarker for disease progression, we conducted the first systematic review and meta-analysis on its relationship with DKD in adults with type 2 diabetes mellitus (T2DM).Methods: PubMed, Embase, Cochrane, and Web of Science were systematically searched. Standard mean differences (SMD) with 95% confidence intervals (CI) and Fisher’s Z transformation were used to examine the relationship between asprosin and DKD. The risk of bias was evaluated using the Newcastle-Ottawa Scale (NOS) and its version for cross-sectional studies. Heterogeneity (I² > 50%) was analyzed with a random-effects model.Results: Six studies (n = 1340) were included. Meta-analysis results indicated that T2DM patients with DKD (micro/macroalbuminuria) had significantly higher circulating asprosin levels than normoalbuminuric T2DM patients (SMD: 1.5, 95% CI: 0.69– 2.32, p = 0.0003). Meta-analysis of correlation revealed a positive association of asprosin with urinary albumin excretion ratio (UACR) (Fisher’s Z = 0.4; 95% CI: 0.240– 0.554, p < 0.001) and body mass index (BMI) (Fisher’s Z = 0.17; 95% CI: 0.036– 0.301, p = 0.013), and a negative association with estimated glomerular filtration rate (eGFR) (Fisher’s Z = − 0.35; 95% CI: − 0.471 to − 0.239, p < 0.001).Conclusion: Asprosin is elevated in T2DM patients with pre-DKD (early stage DKD) and DKD and correlates with key markers of disease severity. Additional research is required to better understand the pathophysiological mechanisms of asprosin and its role in DKD.Keywords: asprosin, diabetic kidney disease, diabetes mellitus, adipokine, eGFR, albuminuria

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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.020
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.153
GPT teacher head0.495
Teacher spread0.342 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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