Evidence map›Paper›PMID 31485449›Full record

ArticleJournal of diabetes research2019

Clinical Implications of Urinary C-Peptide Creatinine Ratio in Patients with Different Types of Diabetes.

Yanai Wang, Ying Gao, Xiaoling Cai, Ling Chen, Lingli Zhou, Yumin Ma, Siqian Gong, Xueyao Han, Linong Ji

Abstract read
In one paragraph

Article in Journal of diabetes research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
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  4. Review
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  7. Maturity Onset Diabetes of the Young-New Approaches for Disease Modelling.International journal of molecular sciences · 2021
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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

9 authors.

Yanai WangDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.ORCID https://orcid.org/0000-0002-8190-0152
Ying GaoDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.
Xiaoling CaiDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.ORCID https://orcid.org/0000-0002-7881-0543
Ling ChenDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.
Lingli ZhouDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.ORCID https://orcid.org/0000-0002-3227-2778
Yumin MaDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.
Siqian GongDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.
Xueyao HanDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.ORCID https://orcid.org/0000-0002-2387-4937
Linong JiDepartments of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing 100044, China.ORCID https://orcid.org/0000-0002-3262-2168

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUrinary C-peptide creatinine ratio (UCPCR) is used as a marker of endogenous insulin secretion. This study aims to assess the effectiveness of UCPCR for distinguishing between type 1 diabetes (T1DM) and non-T1DM (monogenic diabetes and T2DM) and predicting therapeutic choices in type 2 diabetes (T2DM) patients.

methodsTwenty-three patients with genetically confirmed monogenic diabetes (median age 35.0 years (interquartile range 30.0-47.0), 13 (56.5%) men), 56 patients with T1DM (median age 46.0 years (interquartile range 26.5-59.5), 28 (50.0%) men), 136 patients with T2DM (median age 53.0 years (interquartile range 42.0-60.0), 87 (64.0%) men), and 59 healthy subjects (median age 36.0 years (30.0-42.0), 26 (44.1%) men) were included. UCPCR was collected in the morning. Receiver operating characteristic (ROC) curves were used to identify optimal UCPCR cut-off values to differentiate T1DM from non-T1DM. This UCPCR cut-off was used to divide T2DM patients into two groups, and the two groups were compared.

resultsThe UCPCR was lower in patients with T1DM compared with T2DM, monogenic diabetes, and healthy subjects, while the UCPCR was similar in T2DM and monogenic diabetes. A UCPCR cut-off of ≥0.21 nmol/mmol distinguished between monogenic diabetes and T1DM (area under the curve [AUC], 0.949) with 87% sensitivity and 93% specificity. UCPCR ≥ 0.20 nmol/mmol had 82% sensitivity and 93% specificity for distinguishing between T2DM and T1DM, with an AUC of 0.932. UCPCR was not reliable for distinguishing between monogenic diabetes and T2DM (AUC, 0.605). Twenty-five of 136 (18.4%) T2DM patients had UCPCR ≤ 0.20 nmol/mmol. Compared with T2DM patients with a UCPCR > 0.20 nmol/mmol, T2DM patients with UCPCR ≤ 0.20 nmol/mmol had a lower serum C-peptide (fasting C-peptide, 0.39 nmol/L vs. 0.66 nmol/L,

conclusionsUCPCR is a practical and noninvasive marker that can distinguish between TIDM and T2DM or monogenic diabetes. UCPCR ≤ 0.20 nmol/mmol reflects severe impaired beta cell function and the need for insulin or secretagogue therapy in T2DM patients.

Indexed as

AdultBiomarkersCase-Control StudiesC-PeptideCreatinineDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Diagnosis, DifferentialFemaleHumansMaleMiddle AgedPrognosisUrinalysisBiomarkersC-PeptideCreatinine

Identifiers

PMID31485449
PMCPMC6702841

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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.