Evidence map›Paper›PMID 35794676›Full record

ArticleDiabetology & metabolic syndrome2022

Assessment of sublingual microcirculation for the screening of diabetic nephropathy.

Qiang Li, XiaoXiao Liu, Mengxiao Jia, Fang Sun, Yingsha Li, Hexuan Zhang, Xiaoli Liu, Hongbo He, Zhigang Zhao, Zhencheng Yan and 1 more

Open access · goldAbstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Observational
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  4. Observational
  5. Review
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  7. 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

11 authors at 2 institutions in 1 country.

Qiang Li *Center for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
XiaoXiao Liu *Center for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Mengxiao JiaCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Fang SunCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Yingsha LiCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Hexuan ZhangCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Xiaoli LiuCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Hongbo HeCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Zhigang ZhaoCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Zhencheng YanCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
Zhiming ZhuCenter for Hypertension and Metabolic Diseases, Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, 400042, China. hbpcms@sina.com.
Daping Hospital · CNArmy Medical University · CN

Funding

National Key Research and Development Project 2018YFA0800601National Natural Science Foundation of China 32171152National Natural Science Foundation of China 81721001
6 · The paper itself

Abstract

objectiveTo investigate the potential of employing sublingual microcirculation as an early noninvasive screening technique for diabetic nephropathy (DN). RESEARCH DESIGN AND

methodsWe recruited 89 patients with type 2 diabetes mellitus (T2DM) and 41 healthy subjects in this cross-sectional observational study. All participants underwent fluorescein fundus angiography, vibration perception testing, 10 g (Semmes-Weinstein) monofilament examination, nerve conduction velocity, and 24-h urine microalbumin determination. HbA1c, fasting plasma glucose, blood lipid, and estimated glomerular filtration rate(eGFR) were measured. Sublingual microcirculatory images were captured using side-stream dark-field (SDF) microcirculation microscopy, and total and perfused vascular density (TVD and PVD) were calculated.

resultsThe sublingual microcirculatory parameters denoting microvascular density and perfusion were negatively correlated with both fasting plasma glucose (TVD, r =  - 0.316, P < 0.001; PVD, r =  - 0.350, P < 0.001; PPV, r =  - 0.279, P = 0.001) and HbA1c (TVD, r =  - 0.367, P < 0.001; PVD, r =  - 0.423, P < 0.001; PPV, r =  - 0.399, P < 0.001). Diabetes patients already had a reduction in sublingual microcirculation compared with healthy control, and more severe reductions in TVD (7.07 ± 1.64 vs. 9.67 ± 1.94 mm/mm

conclusionsDiabetes patients experienced impaired sublingual microcirculation, which was closely correlated with UACR. Sublingual microcirculation monitoring could be used for the noninvasive early detection of DN.

Indexed as

Diabetic nephropathySublingual microcirculationType 2 diabetes mellitusUrinary albumin creatinine ratio

Identifiers

PMID35794676
PMCPMC9258215
OpenAlexW4283834420

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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.