Evidence mapPaperPMID 33925666Full record

ArticleDiagnostics (Basel, Switzerland)2021

Correlation of Kidney Size on Computed Tomography with GFR, Creatinine and HbA1C for an Accurate Diagnosis of Patients with Diabetes and/or Chronic Kidney Disease.

Nashaat Ghaith, Bassem Malaeb, Rasha Itani, Mohammed Alnafea, Achraf Al Faraj

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Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Nashaat GhaithDepartment of Radiologic Sciences, Faculty of Health Sciences, American University of Science and Technology (AUST), Beirut 1100, Lebanon.
Bassem MalaebDepartment of Radiology, Ain Wazein Medical Village, Chouf 5841, Lebanon.
Rasha ItaniDepartment of Radiologic Sciences, Faculty of Health Sciences, American University of Science and Technology (AUST), Beirut 1100, Lebanon.
Mohammed AlnafeaDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.ORCID 0000-0003-3512-6220
Achraf Al FarajDepartment of Radiologic Sciences, Faculty of Health Sciences, American University of Science and Technology (AUST), Beirut 1100, Lebanon.ORCID 0000-0002-8943-1354

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes is considered one of the major causes of chronic kidney disease (CKD), affecting renal blood vessels and nerves. Diagnosis of CKD by traditional biochemical serum and blood analyses is insufficient and insensitive, thus requiring the development of a more robust technique. This novel study aims to propose a new method for the accurate diagnosis of CKD, quantification of kidney damage, and its prognosis by physicians by measuring the kidney volume on computed tomography (CT). In total, 251 patients were enrolled in this retrospective study. They were divided into four groups: control, patients having diabetes, patients having CKD, and patients having both diabetes and CKD. Results showed that kidney volume correlated negatively with both GFR and HbA1C on CT images, in addition to decreasing faster in males than females. Moreover, HbA1C was shown to correlate positively with creatinine and negatively with GFR. Finally, GFR was more robust than creatinine when correlated with age. The association between kidney volume with GFR and HbA1c can be used to accurately anticipate kidney volume in established CKD on CT scan, especially in resource-poor settings. Furthermore, HbA1C can serve as a powerful biomarker for studying renal function in diabetic CKD patients as it correlates with creatinine and GFR.

Indexed as

albumin creatinine ratechronic kidney diseasecomputed tomographydiabetesglomerular filtration rateHbA1ckidney volume

Identifiers

PMID33925666
PMCPMC8145367

What Socratic holds

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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 Socratic graph.