Evidence map›Paper›PMID 38938187›Full record

SynthesisRenal failure2024

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis.

Shanshan Wan, Shiping Wang, Xinyu He, Chao Song, Jiaping Wang

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Current Progress in the CT- and MRI-Based Detection and Evaluation of Acute Pancreatitis Complications.Medical science monitor : international medical journal of experimental and clinical research · 2025
    Review
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

5 authors.

Shanshan WanDepartment of Radiology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Shiping WangDepartment of Radiology, The Affiliated Anning First People's Hospital of Kunming University of Science and Technology, Kunming, China.
Xinyu HeDepartment of Radiology, The Affiliated Anning First People's Hospital of Kunming University of Science and Technology, Kunming, China.
Chao SongDepartment of Radiology, The Affiliated Anning First People's Hospital of Kunming University of Science and Technology, Kunming, China.
Jiaping WangDepartment of Radiology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RATIONALE AND

objectivesResearchers have delved into noninvasive diagnostic methods of renal fibrosis (RF) in chronic kidney disease, including ultrasound (US), magnetic resonance imaging (MRI), and radiomics. However, the value of these diagnostic methods in the noninvasive diagnosis of RF remains contentious. Consequently, the present study aimed to systematically delineate the accuracy of the noninvasive diagnosis of RF. MATERIALS AND

methodsA systematic search covering PubMed, Embase, Cochrane Library, and Web of Science databases for all data available up to 28 July 2023 was conducted for eligible studies.

resultsWe included 21 studies covering 4885 participants. Among them, nine studies utilized US as a noninvasive diagnostic method, eight studies used MRI, and four articles employed radiomics. The sensitivity and specificity of US for detecting RF were 0.81 (95% CI: 0.76-0.86) and 0.79 (95% CI: 0.72-0.84). The sensitivity and specificity of MRI were 0.77 (95% CI: 0.70-0.83) and 0.92 (95% CI: 0.85-0.96). The sensitivity and specificity of radiomics were 0.69 (95% CI: 0.59-0.77) and 0.78 (95% CI: 0.68-0.85).

conclusionsThe current early noninvasive diagnostic methods for RF include US, MRI, and radiomics. However, this study demonstrates that US has a higher sensitivity for the detection of RF compared to MRI. Compared to US, radiomics studies based on US did not show superior advantages. Therefore, challenges still exist in the current radiomics approaches for diagnosing RF, and further exploration of optimized artificial intelligence (AI) algorithms and technologies is needed.

Indexed as

FibrosisMagnetic Resonance ImagingRenal Insufficiency, ChronicUltrasonographyHumansKidneySensitivity and Specificitychronic kidney disease (CKD)meta-analysisNoninvasive diagnosisrenal fibrosis

Identifiers

PMID38938187
PMCPMC11216256

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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.