Evidence map›Paper›PMID 39239111›Full record

ArticleThe EPMA journal2024

Eyecare-cloud: an innovative electronic medical record cloud platform for pediatric research and clinical care.

Xinyu Zhao, Zhenquan Wu, Yaling Liu, Honglang Zhang, Yarou Hu, Duo Yuan, Xiayuan Luo, Mianying Zheng, Zhen Yu, Dahui Ma and 1 more

Abstract read
In one paragraph

Article in The EPMA journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

11 authors.

Xinyu ZhaoShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Zhenquan WuShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Yaling LiuShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Honglang ZhangShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Yarou HuShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Duo YuanShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Xiayuan LuoShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Mianying ZhengShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Zhen YuShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Dahui MaShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
Guoming ZhangShenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: Clinical data are essential for developing cloud platforms for intelligent diagnosis and treatment decision of diseases. However, cloud platforms for data sharing and exchange with clinicians are poorly suited. We aim to establish Eyecare-cloud, a platform which provide a novel method for clinical data and medical image sharing, to provide a convenient tool for clinicians. Methods: In this study, we displayed the main functions of Eyecare-cloud that we established. Based on clinical data from the cloud platform, we analyzed the incidence trend of the most common infantile retinal diseases, such as retinopathy of prematurity (ROP), over the past 20 years, as well as the associated risk factors for ROP occurrence. Statistical analyses were performed using GraphPad Prism (V.8.0) and SPSS software (V.26.0). Results: The Eyecare-cloud offers numerous advantages, including systematic archiving of patient information, one-click export data, simplifying data collection and management, eliminating the need for manual input of clinical information, reducing clinical data migration time, and lowering data management costs significantly. A total of 22,913 premature infants from Eyecare-cloud were included in the data analysis. Based on 20 years of premature infant screening data analysis, we found that the ROP incidence began to slowly decline starting in 2003 but showed a gradual increase trend again in 2016. The incidence of severe ROP remained relatively stable at a low level since 2010. The number of premature infants increased steadily before 2016 but decreased since then. ROP occurrence was significantly associated with male sex, lower gestational age, and lower birth weight ( Conclusion: Eyecare-cloud provides clinicians and researchers with convenient tools for big data analysis, which helps alleviate clinical workloads and integrate research data. This cloud platform supports the principles of predictive, preventive, and personalized medicine (PPPM/3PM), empowering clinicians and researchers to deliver more precise, proactive, and patient-centered eye care.

Indexed as

Artificial intelligenceBig dataCloud platformPredictive Preventive Personalised Medicine (PPPM / 3PM)Retinopathy of prematurity

Identifiers

PMID39239111
PMCPMC11372004

What Socratic 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 Socratic graph.