PMID- 36662791
OWN - NLM
STAT- MEDLINE
DCOM- 20230227
LR  - 20231118
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 18
IP  - 1
DP  - 2023
TI  - Longitudinal HbA1c trajectory modelling reveals the association of HbA1c and risk 
      of hospitalization for heart failure for patients with type 2 diabetes mellitus.
PG  - e0275610
LID - 10.1371/journal.pone.0275610 [doi]
LID - e0275610
AB  - BACKGROUND: Inconsistent conclusions in past studies on the association between 
      poor glycaemic control and the risk of hospitalization for heart failure (HHF) 
      have been reported largely due to the analysis of non-trajectory-based HbA1c 
      values. Trajectory analysis can incorporate the effects of HbA1c variability 
      across time, which may better elucidate its association with macrovascular 
      complications. Furthermore, studies analysing the relationship between HbA1c 
      trajectories from diabetes diagnosis and the occurrence of HHF are scarce. 
      METHODS: This is a prospective cohort study of the SingHealth Diabetes Registry 
      (SDR). 17,389 patients diagnosed with type 2 diabetes mellitus (T2DM) from 2013 
      to 2016 with clinical records extending to the end of 2019 were included in the 
      latent class growth analysis to extract longitudinal HbA1c trajectories. 
      Association between HbA1c trajectories and risk of first known HHF is quantified 
      with the Cox Proportional Hazards (PH) model. RESULTS: 5 distinct HbA1c 
      trajectories were identified as 1. low stable (36.1%), 2. elevated stable 
      (40.4%), 3. high decreasing (3.5%), 4. high with a sharp decline (10.8%), and 5. 
      moderate decreasing (9.2%) over the study period of 7 years. Poorly controlled 
      HbA1c trajectories (Classes 3, 4, and 5) are associated with a higher risk of 
      HHF. Using the diabetes diagnosis time instead of a commonly used pre-defined 
      study start time or time from recruitment has an impact on HbA1c clustering 
      results. CONCLUSIONS: Findings suggest that tracking the evolution of HbA1c with 
      time has its importance in assessing the HHF risk of T2DM patients, and T2DM 
      diagnosis time as a baseline is strongly recommended in HbA1c trajectory 
      modelling. To the authors' knowledge, this is the first study to identify an 
      association between HbA1c trajectories and HHF occurrence from diabetes diagnosis 
      time.
CI  - Copyright: (c) 2023 Tee et al. This is an open access article distributed under the 
      terms of the Creative Commons Attribution License, which permits unrestricted 
      use, distribution, and reproduction in any medium, provided the original author 
      and source are credited.
FAU - Tee, Clarence
AU  - Tee C
AUID- ORCID: 0000-0002-2879-9278
AD  - Systems Science Department, Institute of High-Performance Computing, Singapore, 
      Singapore.
FAU - Xu, Haiyan
AU  - Xu H
AUID- ORCID: 0000-0003-4480-402X
AD  - Systems Science Department, Institute of High-Performance Computing, Singapore, 
      Singapore.
FAU - Fu, Xiuju
AU  - Fu X
AD  - Systems Science Department, Institute of High-Performance Computing, Singapore, 
      Singapore.
FAU - Cui, Di
AU  - Cui D
AUID- ORCID: 0000-0002-9355-9991
AD  - Systems Science Department, Institute of High-Performance Computing, Singapore, 
      Singapore.
AD  - Department of Advanced Design and Systmes Engineering, City University of Hong 
      Kong, Kowloon Tong, Hong Kong.
FAU - Jafar, Tazeen H
AU  - Jafar TH
AD  - Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
FAU - Bee, Yong Mong
AU  - Bee YM
AD  - Department of Endocrinology, Singapore General Hospital, Singapore, Singapore.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20230120
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
RN  - 0 (Glycated Hemoglobin)
SB  - IM
MH  - Humans
MH  - *Diabetes Mellitus, Type 2/complications
MH  - *Glycated Hemoglobin/analysis
MH  - *Heart Failure/diagnosis/ethnology
MH  - Hospitalization
MH  - Prospective Studies
MH  - Risk Factors
PMC - PMC9858041
COIS- The authors have declared that no competing interests exist.
EDAT- 2023/01/21 06:00
MHDA- 2023/01/25 06:00
PMCR- 2023/01/20
CRDT- 2023/01/20 13:53
PHST- 2021/12/03 00:00 [received]
PHST- 2022/09/20 00:00 [accepted]
PHST- 2023/01/20 13:53 [entrez]
PHST- 2023/01/21 06:00 [pubmed]
PHST- 2023/01/25 06:00 [medline]
PHST- 2023/01/20 00:00 [pmc-release]
AID - PONE-D-21-37527 [pii]
AID - 10.1371/journal.pone.0275610 [doi]
PST - epublish
SO  - PLoS One. 2023 Jan 20;18(1):e0275610. doi: 10.1371/journal.pone.0275610. 
      eCollection 2023.