Evidence map›Paper›PMID 39515855›Full record

ArticleBMJ open2024

Cohort profile: the Nanjing Diabetes Cohort database - a population-based surveillance cohort.

Wei Feng, Yuechuchu Yin, Chunyan Gu, Yuan Mu, Duxiao Zhang, Zhenhuan Tao, Weidong Yin, Xin Zhang, Yun Yu, Jie Hu and 2 more

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Wei Feng *Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China.ORCID http://orcid.org/0000-0002-6843-2067
Yuechuchu Yin *Department of Information, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China.
Chunyan GuDepartment of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China.
Yuan MuDepartment of Laboratory Medicine, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China.
Duxiao ZhangDepartment of Pharmacy, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China.
Zhenhuan TaoNanjing Health Information Center, Nanjing, China.
Weidong YinNanjing Health Information Center, Nanjing, China.
Xin ZhangDepartment of Information, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China.
Yun YuDepartment of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China.
Jie HuDepartment of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China.
Cheng WanDepartment of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China yun_liu@njmu.edu.cn chengwan@njmu.edu.cn.
Yun LiuDepartment of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China yun_liu@njmu.edu.cn chengwan@njmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo study epidemiology, complications, risk factors, clinical course and treatment patterns of diabetes, the Nanjing Diabetes Cohort (NDC) was established using anonymised electronic health records from 650 hospitals and primary care since 2020. This cohort provides valuable data for researchers and policy-makers focused on diabetes management and public health strategies.

participantsDiabetes was defined as having inpatient or outpatient encounters with a diagnosis of diabetes International Classification of Diseases-9/10 codes, any use of insulin or oral hypoglycaemic drugs, or one encounter with haemoglobin A1C >4.8 mmol/mol or 6.5%. Patients with diabetes have been continuously enrolled on hospitals and primary care in Nanjing since 2020. Demographic, medications and comorbidities data were extracted from clinical notes, diagnostic codes, labs, prescriptions and vital signs among different types of diabetes. FINDINGS TO DATE: The NDC consisted of 1 033 904 patients from 1 January 2020 to 31 December 2022, the majority were male (50.62%) and from the Gulou district (30.79%). The clinical characteristics and medication usage of patients with type 1 diabetes, type 2 diabetes, gestational diabetes and other diabetes were assessed. The prevalences of hypertension, ischemic heart disease, and cerebrovascular disease were 49.72%, 17.85% and 24.90%, respectively. FUTURE PLANS: NDC will annually enrol eligible patients and include socioeconomic data in future updates. The data of NDC are maintained by the Department of Medical Informatics at Nanjing Medical University.

Indexed as

Diabetes Mellitus, Type 2AdolescentAdultAgedCerebrovascular DisordersChildChild, PreschoolChinaCohort StudiesComorbidityDatabases, FactualDiabetes, GestationalDiabetes MellitusDiabetes Mellitus, Type 1Electronic Health RecordsFemaleGlycated HemoglobinHypoglycemic AgentsDIABETES & ENDOCRINOLOGYElectronic Health RecordsPUBLIC HEALTH

Identifiers

PMID39515855
PMCPMC11660322

What OpenQuestion holds

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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.