Evidence map›Paper›PMID 34574911›Full record

ArticleHealthcare (Basel, Switzerland)2021

Development and Validation of an Undiagnosed Diabetes Screening Tool: Based on the Korean National Health and Nutrition Examination Survey (2010-2016).

Eunhee Cho, Deulle Min, Hye Sun Lee

Open access · goldAbstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2021. 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
0.3field-weighted citation impact, top 40% 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, 3 citations in OpenAlex.

  1. Review
  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

3 authors at 2 institutions in 1 country.

Eunhee ChoMo-Im Kim Nursing Research Institute, Yonsei University College of Nursing, Seoul 03722, Korea.ORCID 0000-0002-7871-6848
Deulle MinDepartment of Nursing, College of Medicine, Wonkwang University, Iksan 54538, Korea.ORCID 0000-0002-7305-5059
Hye Sun LeeBiostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul 06229, Korea.ORCID 0000-0001-6328-6948
Yonsei University · KRWonkwang University · KR

Funding

Yonsei University 2018 Faculty Research Grant
6 · The paper itself

Abstract

Approximately half of the population worldwide suffers from under/undiagnosed diabetes. In South Korea, 27.7% of people aged over 30 years have type 2 diabetes and are unaware of their condition because they have not been diagnosed. Optimal tools for identifying risk factors of undiagnosed diabetes, which is associated with multiple complications, are currently lacking. Secondary data analysis was conducted using the 2010-2016 Korean National Health and Nutrition Examination Survey. This study aimed to identify the risk factors in individuals not diagnosed with type 2 diabetes, using glycated hemoglobin as the diagnostic standard. Furthermore, we aimed to develop an accurate screening tool for diabetes using HbA1c values by analyzing the data of 12,843 adults (aged ≥20 years) not diagnosed with type 2 diabetes. Age, gender, family history of diabetes, hypertension diagnosis, waist-to-height ratio, smoking, and health check-ups were identified as significant risk factors for undiagnosed type 2 diabetes. A screening tool with total and cutoff scores of 13 and 7 points was developed, and it had a sensitivity of 82.7% and specificity of 58.2%. The developed screening tool appears to be a simple and cost-effective method for detecting undiagnosed type 2 diabetes.

Indexed as

diabetes early diagnosishealth check-upsscreening toolsmoking cessationundiagnosed diabetes

Identifiers

PMID34574911
PMCPMC8467253
OpenAlexW3197084445

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.