Evidence map›Paper›PMID 29330426›Full record

ArticleScientific reports2018

Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus.

Min-Ho Jun, Soochan Kim, Boncho Ku, JungHee Cho, Kahye Kim, Ho-Ryong Yoo, Jaeuk U Kim

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 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

7 authors at 3 institutions in 1 country.

Min-Ho JunKM Fundamental Research Division, Korea Institute of Oriental Medicine (KIOM), 1672 Yuseongdaero, Yuseong-gu, Daejeon, Republic of Korea.
Soochan KimDepartment of Electrical and Electronic Engineering & Institute for IT Convergence, Hankyong National University, 327 Jungang-no, Anseong-si, Gyeonggi-do, Republic of Korea.
Boncho KuKM Fundamental Research Division, Korea Institute of Oriental Medicine (KIOM), 1672 Yuseongdaero, Yuseong-gu, Daejeon, Republic of Korea.
JungHee ChoKM Fundamental Research Division, Korea Institute of Oriental Medicine (KIOM), 1672 Yuseongdaero, Yuseong-gu, Daejeon, Republic of Korea.
Kahye KimKM Fundamental Research Division, Korea Institute of Oriental Medicine (KIOM), 1672 Yuseongdaero, Yuseong-gu, Daejeon, Republic of Korea.
Ho-Ryong YooInternal Medicine of Cardiovascular, Daejeon Oriental Hospital of Oriental Medical College of Daejeon University, 22-5 Daehung-dong, Jung-gu, Daejeon, 301-724, Republic of Korea.
Jaeuk U KimKM Fundamental Research Division, Korea Institute of Oriental Medicine (KIOM), 1672 Yuseongdaero, Yuseong-gu, Daejeon, Republic of Korea. jaeukkim@kiom.re.kr.ORCID http://orcid.org/0000-0003-0408-5569
Korea Institute of Oriental Medicine · KRDaejeon University · KRHankyong National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated segmental phase angles (PAs) in the four limbs using a multi-frequency bioimpedance analysis (MF-BIA) technique for noninvasively diagnosing diabetes mellitus. We conducted a meal tolerance test (MTT) for 45 diabetic and 45 control subjects stratified by age, sex and body mass index (BMI). HbA1c and the waist-to-hip-circumference ratio (WHR) were measured before meal intake, and we measured the glucose levels and MF-BIA PAs 5 times for 2 hours after meal intake. We employed a t-test to examine the statistical significance and the area under the curve (AUC) of the receiver operating characteristics (ROC) to test the classification accuracy using segmental PAs at 5, 50, and 250 kHz. Segmental PAs were independent of the HbA1c or glucose levels, or their changes caused by the MTT. However, the segmental PAs were good indicators for noninvasively screening diabetes In particular, leg PAs in females and arm PAs in males showed best classification accuracy (AUC = 0.827 for males, AUC = 0.845 for females). Lastly, we introduced the PA at maximum reactance (PAmax), which is independent of measurement frequencies and can be obtained from any MF-BIA device using a Cole-Cole model, thus showing potential as a useful biomarker for diabetes.

Indexed as

AgedArea Under CurveBody CompositionCross-Sectional StudiesDiabetes Mellitus, Type 2Electric ImpedanceFemaleGlucoseGlycated HemoglobinHumansMaleMiddle AgedObesityROC CurveSex CharacteristicsWaist-Hip RatioGlucoseGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID29330426
PMCPMC5766497
OpenAlexW2782756786

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Registered trials

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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.