Evidence map›Paper›PMID 40236266›Full record

ArticleThe Lancet regional health. Western Pacific2025

Identifying and visualising temporal trajectories of hospitalisations for traditional and non-traditional complications in people with type 2 diabetes: a population-based study.

Hongjiang Wu, Haobin Zhou, Chuiguo Huang, Aimin Yang, Eric S H Lau, Xinge Zhang, Juliana N M Lui, Baoqi Fan, Mai Shi, Ronald C W Ma and 5 more

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

15 authors.

Hongjiang WuDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Haobin ZhouThe First School of Clinical Medicine, Guangzhou Medical University, People's Republic of China.
Chuiguo HuangDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Aimin YangDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Eric S H LauDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Xinge ZhangDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Juliana N M LuiDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Baoqi FanDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Mai ShiDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Ronald C W MaDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Alice P S KongDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Elaine ChowDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Wing-Yee SoDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Juliana C N ChanDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
Andrea O Y LukDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: People with type 2 diabetes are increasingly susceptible to complications that are not specific to diabetes. We aimed to examine the temporal trajectories of hospitalisations for traditional and non-traditional complications in people with type 2 diabetes. Methods: We included 758,254 people with incident type 2 diabetes between 2002 and 2018 in Hong Kong, followed up until 2019. We included hospitalisations for 72 selected diseases and all-cause deaths. We derived the temporal trajectories of hospitalisations based on pairs of disease associations and identified trajectory clusters using Markov Cluster Algorithm. Findings: During a median follow-up of 7.8 (IQR: 4-12) years, 57.6% of people experienced a hospitalisation for any of the 72 selected diseases and 22.6% of people died. Among the 5184 directional disease pairs, 95 were identified as having a significant and directional association. The three most common disease pairs were hospitalisations for urinary tract infection followed by pneumonia, ischemic heart disease followed by heart failure, and ischemic stroke followed by pneumonia. Cardiovascular and kidney diseases were predominant in the hospitalisation trajectories. However, these traditional complications had complex associations both among themselves and with various non-traditional complications across multiple systems. Three distinct trajectory clusters were identified, with heart failure/chronic kidney disease, pneumonia, and urinary tract infection as central diseases. Interpretation: Cardiovascular and kidney diseases interacted with a broad set of non-traditional complications to influence the overall patterns of hospitalisation progression in people with diabetes, highlighting the need to broaden diabetes care to consider complications beyond the traditional focus. Funding: Direct Grant for Research from The Chinese University of Hong Kong.

Indexed as

HospitalisationTrajectoriesType 2 diabetes

Identifiers

PMID40236266
PMCPMC11999218

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.