Evidence map›Paper›PMID 35576113›Full record

ArticleZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2022

Design and development of a Wechat applet for intelligent health management of metabolic syndrome.

Leiwen Tang, Dandan Chen, Jing Shao, Hui Zhang, Jingjie Wu, Zhihong Ye

Open access · greenAbstract read
In one paragraph

Article in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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.

Leiwen Tang1. Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Dandan Chen2. Institute of Nursing Research, Zhejiang University School of Medicine, Hangzhou 310058, China.
Jing Shao2. Institute of Nursing Research, Zhejiang University School of Medicine, Hangzhou 310058, China.
Hui Zhang2. Institute of Nursing Research, Zhejiang University School of Medicine, Hangzhou 310058, China.
Jingjie Wu2. Institute of Nursing Research, Zhejiang University School of Medicine, Hangzhou 310058, China.
Zhihong Ye1. Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Zhejiang Institute of Mechanical and Electrical Engineering · CNSir Run Run Shaw Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

: To design and develop a Wechat applet for intelligent health management of metabolic syndrome. Based on the needs and requirements of individuals undergoing health check-up, patients with metabolic syndrome and medical workers, a Wechat applet for metabolic syndrome management was designed and developed, which involving health data collection, health risk prediction, health management knowledge base fusion and intelligent recommendation, data privacy and security. The platform consists of three user ports: individuals undergoing health check and patients with metabolic syndrome, the medical workers and the system administrators. The main functions of the platform included metabolic syndrome risk prediction, intelligent recommendation of health management strategies, health behavior record and supervision, experts' consultation and health knowledge guide. The Wechat applet developed in this study can be used for metabolic syndrome risk prediction for general population, and health management for patients with metabolic syndrome, which helps them to enhance health management awareness and health behavior adherence.

Indexed as

Metabolic SyndromeHumansSoftwareHealth managementMetabolic syndromeRisk forecastingWechat applet

Identifiers

PMID35576113
PMCPMC9109770
OpenAlexW4224137409

What OpenQuestion holds

Textmetadata
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.