Evidence map›Paper›PMID 40791893›Full record

ArticleEClinicalMedicine2025

Estimated glomerular filtration rate, albuminuria, and risk of infection: a collaborative meta-analysis of individual participant data.

Junichi Ishigami, Aditya Surapaneni, Kunihiro Matsushita, Josef Coresh, Morgan E Grams, Shoshana H Ballew, Yingying Sang, Benedicte Stengel, Johan Ärnlöv, Samira Bell and 13 more

Abstract read
In one paragraph

Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

23 authors.

Junichi IshigamiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Aditya SurapaneniDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA.
Kunihiro MatsushitaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Josef CoreshOptimal Aging Institute, New York University Grossman School of Medicine, New York, NY, USA.
Morgan E GramsDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA.
Shoshana H BallewOptimal Aging Institute, New York University Grossman School of Medicine, New York, NY, USA.
Yingying SangOptimal Aging Institute, New York University Grossman School of Medicine, New York, NY, USA.
Benedicte StengelCentre for Research in Epidemiology and Population Health (CESP), Paris-Saclay University, Inserm U1018, Versailles Saint-Quentin University, Clinical Epidemiology Team, Villejuif, France.
Johan ÄrnlövSchool of Health and Social Studies, Dalarna University, Falun, Sweden and Department of Neurobiology, Care Sciences and Society, Family Medicine and Primary Care Unit, Karolinska Institutet, Huddinge, Sweden.
Samira BellDivision of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, United Kingdom.
Juan-Jesus CarreroDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Huddinge, Sweden.
Alexander R ChangDepartment of Population of Health Sciences, Center for Kidney Health Research, and Department of Nephrology, Geisinger, Danville, PA, USA.
Elizabeth L CieminsAMGA (American Medical Group Association), Alexandria, VA, USA.
Richard HaynesClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Joachim IxDivision of Nephrology-Hypertension, Department of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
Fruzsina KotsisInstitute of Genetic Epidemiology, Faculty of Medicine and Medical Center and Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
Jennifer S LeesSchool of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, United Kingdom.
Krutika PanditDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA.
Panduranga RaoDivision of Nephrology, Department of Medicine, University of Michigan, Ann Arbor, MI, USA.
Cassianne Robinson-CohenDivision of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Natalia Alencar de PinhoCentre for Research in Epidemiology and Population Health (CESP), Paris-Saclay University, Inserm U1018, Versailles Saint-Quentin University, Clinical Epidemiology Team, Villejuif, France.
Keiichi SumidaDivision of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA.
CKD Prognosis Consortium

Funding

Chronic Kidney Disease Prognosis Consortium (CKD-PC)R01DK100446 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI JOSEF CORESH, Morgan Erika Grams · 2014 to 2026
$10.7M
NIDDK NIH HHS R01 DK100446
6 · The paper itself

Abstract

Background: Infections are a major cause of hospitalization in people with chronic kidney disease (CKD), with incidence similar to cardiovascular disease, yet the risk of infection has not been systematically studied across stages of CKD. Methods: We conducted a meta-analysis of individual participant data including 1,246,912 individuals across 47 cohorts in the CKD Prognosis Consortium, with information on estimated glomerular filtration rate based on serum creatinine (eGFRcr) and urinary albuminuria (ACR) (or proteinuria converted to ACR), to examine the association of eGFR and ACR with the risk of hospitalization with infection. Outcomes were ascertained through diagnostic codes on hospital discharge records relevant to acute infections (i.e., upper and lower respiratory tract, urinary tract, skin and soft tissue, musculoskeletal, gastrointestinal tract, genital, nervous system, and cardiovascular system infections, and sepsis). Follow-up was censored on December 31, 2019 or on the last date of cohort follow-up, whichever was earlier. Multivariable Cox models were used to estimate hazard ratios (HRs). Findings: During follow-up, 170,864 (13.7%) individuals had a hospitalization with infection (IR, 22.0 [IQI, 16.2-31.0] per 1000 person-yrs). In Cox models, compared to eGFRcr 90-104 ml/min/1.73 m Interpretation: Lower kidney function and higher albuminuria were independently associated with higher risk of infection. The risk was elevated even in mild to moderate CKD, with the highest risk seen in the most advanced stage of CKD. Infection prevention measures should target individuals across all CKD stages. Funding: US National Kidney Foundation and the National Institute of Diabetes and Digestive and Kidney Diseases.

Indexed as

AlbuminuriaChronic kidney diseaseEstimated glomerular filtration rateInfectionRisk

Identifiers

PMID40791893
PMCPMC12337016

What OpenQuestion holds

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Registered trials

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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.