Evidence map›Paper›PMID 37425667›Full record

ArticleHCA healthcare journal of medicine2020

Systematic Survey of Creatinine-Based Versus Cystatin C-based Estimated GFR in People with Diabetes.

Sadik Acaralp, Hossein Akhondi

Open access · diamondAbstract read
In one paragraph

Article in HCA healthcare journal of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 85% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 0 citations in OpenAlex.

  1. Guideline
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

2 authors at 1 institution in 1 country.

Sadik AcaralpDepartment of Internal Medicine and Nephrology, MountainView Hospital-Nevada, Las Vegas, NV.
Hossein AkhondiDepartment of Internal Medicine and Nephrology, MountainView Hospital-Nevada, Las Vegas, NV.
nView Medical (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetes is a common cause of kidney failure, and most anti-diabetic agents are excreted through the kidneys. Therefore, it is critical to adjust medication dosage and anti-diabetic agents based on kidney function. There are different methods to estimate kidney function, but the common practice is to use creatinine to estimate the glomerular filtration rate. Objective: In this systematic review, we identify and review publications in order to assess differences between creatinine-based and cystatin C-based estimated glomerular filtration rates in diabetic patients. Methods: The articles were identified using 3 databases and were assessed for eligibility. A total of 4 articles were included. Comparisons of the 2 patient groups as well as the patient characteristics were compiled into 2 tables. Results: Two studies showed significant differences between creatinine-based and cystatin C-based estimated glomerular filtration rates in patients with type 1 diabetes. There were no significant differences in control or type 2 diabetes groups. Conclusions: Although cystatin C-based estimation of kidney function looks promising, it fails to show superiority over creatinine-based estimation. Most studies included in this systematic review, however, had serious limitations to them. Further research with standardized ways of measuring creatinine and cystatin C is required.

Indexed as

creatinine/bloodcystatin Ccystatins/blooddiabetes mellitus type 1diabetes mellitus type 2diabetic nephropathieseGFRglomerular filtration rate

Identifiers

PMID37425667
PMCPMC10324773
OpenAlexW3081963486

What OpenQuestion holds

Textmetadata
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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.