Evidence map›Paper›PMID 37794456›Full record

ArticleCardiovascular diabetology2023

Association between estimated glomerular filtration rate slope and cardiovascular disease among individuals with and without diabetes: a prospective cohort study.

Azra Ramezankhani, Fereidoun Azizi, Farzad Hadaegh

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Azra RamezankhaniPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Fereidoun AziziEndocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farzad HadaeghPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. fzhadaegh@endocrine.ac.ir.
Research Institute for Endocrine Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies have reported an association between a significant decline in estimated glomerular filtration rate (eGFR) over time and an increased risk of cardiovascular disease (CVD). This study aimed to investigate the association between the eGFR slope and CVD among individuals with and without diabetes.

methodsThis prospective cohort study was conducted within the Tehran Lipid and Glucose Study (TLGS) framework. We studied 6919 adults aged 20-70 years, including 985 with diabetes and 5934 without diabetes. The eGFR slope was determined based on repeated measurements of eGFR through linear mixed-effects models. A multivariable Cox proportional hazard model was employed to evaluate the association between eGFR slope, both in continuous and categorical form, and the risk of CVD.

resultsThe slopes of eGFR exhibited a bell-shaped distribution, with a mean (standard deviation (SD)) of -0.63 (0.13) and - 0.70 (0.14) ml/min per 1.73 m

conclusionMonitoring the eGFR slope may serve as a potential predictor of CVD risk in individuals with diabetes.

Indexed as

Cardiovascular DiseasesDiabetes MellitusRenal Insufficiency, ChronicAdultGlomerular Filtration RateHumansIranProspective StudiesRisk FactorsCardiovascular diseaseDiabetesGlomerular filtration rateSlop

Identifiers

PMID37794456
PMCPMC10552420
OpenAlexW4387330101

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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.