Evidence map›Paper›PMID 34666746›Full record

ArticleCardiovascular diabetology2021

Optimal glucose, HbA1c, glucose-HbA1c ratio and stress-hyperglycaemia ratio cut-off values for predicting 1-year mortality in diabetic and non-diabetic acute myocardial infarction patients.

Ching-Hui Sia, Mervyn Huan-Hao Chan, Huili Zheng, Junsuk Ko, Andrew Fu-Wah Ho, Jun Chong, David Foo, Ling-Li Foo, Patrick Zhan-Yun Lim, Boon Wah Liew and 8 more

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 4 pooled it
12.8field-weighted citation impact, top 1% 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

57 citing papers in PubMed, 4 syntheses or guidelines pooled it, 113 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

18 authors at 10 institutions in 3 countries.

Ching-Hui Sia *Department of Cardiology, National University Heart Centre Singapore, Singapore, Singapore.
Mervyn Huan-Hao Chan *Cardiovascular & Metabolic Disorders Program, Duke-NUS Medical School, 8 College Road, Level 8, Singapore, 169857, Singapore.
Huili ZhengHealth Promotion Board, National Registry of Diseases Office, Singapore, Singapore.
Junsuk KoMD Program, Duke-NUS Medical School, Singapore, Singapore.
Andrew Fu-Wah HoSingHealth Duke-NUS Emergency Medicine Academic Clinical Programme, Singapore, Singapore.
Jun ChongNational Heart Research Institute Singapore, National Heart Centre Singapore, Singapore, Singapore.
David FooTan Tock Seng Hospital, Singapore, Singapore.
Ling-Li FooHealth Promotion Board, National Registry of Diseases Office, Singapore, Singapore.
Patrick Zhan-Yun LimKhoo Teck Puat Hospital, Singapore, Singapore.
Boon Wah LiewChangi General Hospital, Singapore, Singapore.
Ping ChaiDepartment of Cardiology, National University Heart Centre Singapore, Singapore, Singapore.
Tiong-Cheng YeoDepartment of Cardiology, National University Heart Centre Singapore, Singapore, Singapore.
Huay-Cheem TanDepartment of Cardiology, National University Heart Centre Singapore, Singapore, Singapore.
Terrance ChuaDepartment of Cardiology, National Heart Centre Singapore, Singapore, Singapore.
Mark Yan-Yee ChanDepartment of Cardiology, National University Heart Centre Singapore, Singapore, Singapore.
Jack Wei Chieh TanPre-Hospital and Emergency Care Research Centre, Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
Heerajnarain Bulluck *Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Derek J Hausenloy *Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. derek.hausenloy@duke-nus.edu.sg.ORCID 0000-0003-0729-4956
National University of Singapore · SGDuke-NUS Medical School · SGHealth Promotion Board · SGNational Heart Centre Singapore · SGAsia University · TWChangi General Hospital · SGKhoo Teck Puat Hospital · SGLeeds General Infirmary · GBSingHealth Duke-NUS Academic Medical Centre · SGTan Tock Seng Hospital · SG

Funding

duke-nus medical school and national medical research council KP/2019/0034European Cooperation in Science and Technology CA16225national medical research council NMRC/CGAug16C006national medical research council NMRC/CSA-SI/0011/2017
6 · The paper itself

Abstract

backgroundStress-induced hyperglycaemia at time of hospital admission has been linked to worse prognosis following acute myocardial infarction (AMI). In addition to glucose, other glucose-related indices, such as HbA1c, glucose-HbA1c ratio (GHR), and stress-hyperglycaemia ratio (SHR) are potential predictors of clinical outcomes following AMI. However, the optimal blood glucose, HbA1c, GHR, and SHR cut-off values for predicting adverse outcomes post-AMI are unknown. As such, we determined the optimal blood glucose, HbA1c, GHR, and SHR cut-off values for predicting 1-year all cause mortality in diabetic and non-diabetic ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) patients.

methodsWe undertook a national, registry-based study of patients with AMI from January 2008 to December 2015. We determined the optimal blood glucose, HbA1c, GHR, and SHR cut-off values using the Youden's formula for 1-year all-cause mortality. We subsequently analyzed the sensitivity, specificity, positive and negative predictive values of the cut-off values in the diabetic and non-diabetic subgroups, stratified by the type of AMI.

resultsThere were 5841 STEMI and 4105 NSTEMI in the study. In STEMI patients, glucose, GHR, and SHR were independent predictors of 1-year all-cause mortality [glucose: OR 2.19 (95% CI 1.74-2.76); GHR: OR 2.28 (95% CI 1.80-2.89); SHR: OR 2.20 (95% CI 1.73-2.79)]. However, in NSTEMI patients, glucose and HbA1c were independently associated with 1-year all-cause mortality [glucose: OR 1.38 (95% CI 1.01-1.90); HbA1c: OR 2.11 (95% CI 1.15-3.88)]. In diabetic STEMI patients, SHR performed the best in terms of area-under-the-curve (AUC) analysis (glucose: AUC 63.3%, 95% CI 59.5-67.2; GHR 68.8% 95% CI 64.8-72.8; SHR: AUC 69.3%, 95% CI 65.4-73.2). However, in non-diabetic STEMI patients, glucose, GHR, and SHR performed equally well (glucose: AUC 72.0%, 95% CI 67.7-76.3; GHR 71.9% 95% CI 67.7-76.2; SHR: AUC 71.7%, 95% CI 67.4-76.0). In NSTEMI patients, glucose performed better than HbA1c for both diabetic and non-diabetic patients in AUC analysis (For diabetic, glucose: AUC 52.8%, 95% CI 48.1-57.6; HbA1c: AUC 42.5%, 95% CI 37.6-47. For non-diabetic, glucose: AUC 62.0%, 95% CI 54.1-70.0; HbA1c: AUC 51.1%, 95% CI 43.3-58.9). The optimal cut-off values for glucose, GHR, and SHR in STEMI patients were 15.0 mmol/L, 2.11, and 1.68 for diabetic and 10.6 mmol/L, 1.72, and 1.51 for non-diabetic patients respectively. For NSTEMI patients, the optimal glucose values were 10.7 mmol/L for diabetic and 8.1 mmol/L for non-diabetic patients.

conclusionsSHR was the most consistent independent predictor of 1-year all-cause mortality in both diabetic and non-diabetic STEMI, whereas glucose was the best predictor in NSTEMI patients.

Indexed as

AgedBiomarkersBlood GlucoseDiabetes MellitusFemaleGlycated HemoglobinHumansMaleMiddle AgedNon-ST Elevated Myocardial InfarctionPatient AdmissionPredictive Value of TestsPrognosisRegistriesRetrospective StudiesRisk AssessmentBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID34666746
PMCPMC8524932
OpenAlexW3205751778

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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.