Evidence map›Paper›PMID 32753935›Full record

ArticleInternational journal of general medicine2020

Study on Risk Factors of Diabetic Nephropathy in Obese Patients with Type 2 Diabetes Mellitus.

Fan Hu, Taotao Zhang

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

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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

15 citing papers in PubMed, 26 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

2 authors at 1 institution in 1 country.

Fan Hu *School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.ORCID 0000-0002-7929-6953
Taotao Zhang *School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
Shanghai University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this study was to identify diabetic nephropathy risk factors in type 2 diabetes mellitus obese people based on community type 2 diabetes mellitus patients. PATIENTS AND

methodsIn the community in Shanghai, we conduct a questionnaire, physical examination, and biochemical examination. The 406 patients included in the analysis were divided into two groups based on whether or not they had diabetic nephropathy. The influencing factors of type 2 diabetes mellitus obese patients were screened by the least absolute shrinkage and selection operator method, and then the influencing factors detected by the least absolute shrinkage and selection operator method were included in the binary logistic regression analysis, and the risk factors for diabetic nephropathy in obese people with type 2 diabetes mellitus were obtained. Finally, the nomogram and forest plot are used to visualize the binary logistic regression results, and the calibration plot and receiver-operating characteristic curve are used to verify the result.

resultsThe results showed that family history of diabetes (OR= 2.091, P= 0.002), disease course (OR=1.050, P= 0.007). hypertension (OR=1.768, P=0.042), hyperuricemia (OR=2.263, P=0.003), systolic blood pressure (OR=1.027, P<0.001), and glycosylated haemoglobin A1c (OR=1.358, P<0.001) were risk factors for diabetic nephropathy.

conclusionFor obese patients with type 2 diabetes mellitus, they should pay attention to family history of diabetes, disease course and hyperuricemia. Hypertension should be concerned and strictly controlled. Systolic blood pressure and glycosylated haemoglobin A1c will help prolong the survival of diabetic nephropathy patients.

Indexed as

diabetic nephropathyobesityrisk factorstype 2 diabetes mellitus

Identifiers

PMID32753935
PMCPMC7352450
OpenAlexW3040303049

What OpenQuestion 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 OpenQuestion graph.