Evidence map›Paper›PMID 38308753›Full record

ArticleJournal of nephrology2024

Blood biomarkers improve the prediction of prevalent and incident severe chronic kidney disease.

Simon Nusinovici, Hengtong Li, Crystal Chong, Marco Yu, Ida Maria Hjelm Sørensen, Line Stattau Bisgaard, Christina Christoffersen, Susanne Bro, Sylvia Liu, Jian-Jun Liu and 5 more

Abstract read
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In one paragraph

Article in Journal of nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 5 institutions in 2 countries.

Simon NusinoviciSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore. simon65@nus.edu.sg.ORCID 0000-0002-9599-5818
Hengtong LiSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
Crystal ChongSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
Marco YuSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
Ida Maria Hjelm SørensenDepartment of Nephrology, Rigshospitalet University Hospital, Copenhagen, Denmark.
Line Stattau BisgaardDepartment of Clinical Biochemistry, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
Christina ChristoffersenDepartment of Clinical Biochemistry, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
Susanne BroDepartment of Nephrology, Rigshospitalet University Hospital, Copenhagen, Denmark.
Sylvia LiuClinical Research Unit, Diabetes Centre, Department of Medicine, Khoo Teck Puat Hospital, Singapore, Singapore.
Jian-Jun LiuClinical Research Unit, Diabetes Centre, Department of Medicine, Khoo Teck Puat Hospital, Singapore, Singapore.
Lim Su ChiClinical Research Unit, Diabetes Centre, Department of Medicine, Khoo Teck Puat Hospital, Singapore, Singapore.
Tien-Yin WongSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
Gavin S W TanSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
Ching-Yu ChengSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
Charumathi SabanayagamSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Singapore, 169856, Singapore.
National University of Singapore · SGSingapore National Eye Center · SGKhoo Teck Puat Hospital · SGRigshospitalet · DKUniversity of Copenhagen · DK

Funding

National Medical Research Council (SG) NMRC/CIRG/1371/2013National Medical Research Council (SG) NMRC/CIRG/1488/2018National Medical Research Council (SG) NMRC/MOH-000066National Medical Research Council (SG) NMRC/MOH-0000714National Medical Research Council (SG) NMRC/STaR/016/2013National Medical Research Council (SG) OFLCG/001/2017National Rice Research Institute, Indian Council of Agricultural Research NMRC/OFLCG/001/2017STAR grant 20201
6 · The paper itself

Abstract

backgroundThe prevalence of chronic kidney disease (CKD) is high. Identification of cases with CKD or at high risk of developing it is important to tailor early interventions. The objective of this study was to identify blood metabolites associated with prevalent and incident severe CKD, and to quantify the corresponding improvement in CKD detection and prediction.

methodsData from four cohorts were analyzed: Singapore Epidemiology of Eye Diseases (SEED) (n = 8802), Copenhagen Chronic Kidney Disease (CPH) (n = 916), Singapore Diabetic Nephropathy (n = 714), and UK Biobank (UKBB) (n = 103,051). Prevalent CKD (stages 3-5) was defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m

resultsChronic kidney disease prevalence (stages 3-5) and severe incidence were 11.4% and 2.2% in SEED, and 2.3% and 0.2% in UKBB. Firstly, phenylalanine (Odds Ratio [OR]

conclusionThe performance improvements of CKD detection and prediction achieved by adding metabolites to traditional risk factors are modest and further research is necessary to fully understand the clinical implications of these findings.

Indexed as

BiomarkersGlomerular Filtration RateRenal Insufficiency, ChronicAdultAgedFemaleHumansIncidenceMaleMiddle AgedPredictive Value of TestsPrevalenceRisk AssessmentRisk FactorsSeverity of Illness IndexSingaporeBiomarkersChronic kidney diseaseEnd-stage renal diseaseNuclear magnetic resonance metabolitesPrediction

Identifiers

PMID38308753
OpenAlexW4391515083

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.