Evidence map›Paper›PMID 35360475›Full record

ArticleJournal of healthcare engineering2022

Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection.

Jing Wang, Yang Wang, Ping Pang, Xiaomeng Jia, Xu Yan, Zhaohui Lv

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 41% 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, 3 citations in OpenAlex.

  1. Article
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

6 authors at 2 institutions in 1 country.

Jing WangDepartment of Clinical Nutrition, The 8th Medical Center of Chinese PLA General Hospital, Beijing 100091, China.
Yang WangDepartment of Nephrology, The 8th Medical Center of Chinese PLA General Hospital, Beijing 100091, China.
Ping PangDepartment of Endocrinology, Hainan Branch of Chinese PLA General Hospital, Sanya 572013, China.
Xiaomeng JiaCenter for Endocrine Metabolism and Immune Disease, Beijing Luhe Hospital, Capital Medical University, Beijing 101149, China.
Xu YanDepartment of Clinical Nutrition, The 8th Medical Center of Chinese PLA General Hospital, Beijing 100091, China.
Zhaohui LvDepartment of Endocrinology, The 1st Medical Center of Chinese PLA General Hospital, Beijing 100853, China.ORCID 0000-0002-1414-5599
Chinese PLA General Hospital · CNBeijing Luhe Hospital Affiliated to Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of IoT technology, it is a new trend to combine edge computing with smart medicine in order to better develop modern medicine, avoid the crisis of information "sibling," and meet the requirements of timeliness and computational performance of the massive data generated by edge devices. However, edge computing is somewhat open and prone to security risks, so the security and privacy protection of edge computing systems for smart healthcare is receiving increasing attention. The two groups were compared before and after treatment for blood glucose, blood lipids, blood pressure, renal function, serum advanced glycosylation end products (AGEs) and cyclic adenosine monophosphate (cAMP), serum oxidative stress indicators, and levels of cAMP/PKA signalling pathway-related proteins in peripheral blood mononuclear cells. The results of this study show that the reduction of AGEs, the improvement of oxidative stress, and the regulation of the cAMP/PKA signalling pathway may be associated with a protective effect against early DKD. By introducing the edge computing system and its architecture for smart healthcare, we describe the security risks encountered by smart healthcare in edge computing, introduce the solutions proposed by some scholars to address the security risks, and finally summarize the security protection framework and discuss the specific solutions for security and privacy protection under this framework, which will provide some help for the credible research of smart healthcare edge computing.

Indexed as

Diabetes MellitusGlucagon-Like Peptide 1Delivery of Health CareHumansKidneyLeukocytes, MononuclearGlucagon-Like Peptide 1

Identifiers

PMID35360475
PMCPMC8964200
OpenAlexW4221079640

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.