DIAB-6258; No. of Pages 12 diabetes research and clinical practice xxx (2015) xxx–xxx
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Prediction of heart failure in patients with type 2 diabetes mellitus—A systematic review and meta-analysis Ying Wang, Tomoko Negishi, Kazuaki Negishi, Thomas H. Marwick * Menzies Research Institute Tasmania, 17 Liverpool Street, Hobart, TAS, Australia
article info
abstract
Article history:
Background: Heart failure (HF) is a major cause of mortality and disability in type 2 diabetes
Received 16 October 2014
mellitus (T2DM). This study sought to improve the assessment of HF risk in patients with
Received in revised form
T2DM—a step that would be critical for effective HF screening.
25 November 2014
Methods: A systematic literature search was performed on electronic databases including
Accepted 14 January 2015
MEDLINE and EMBASE, using MeSH terms ‘heart failure’, ‘risk factor’, ‘T2DM’, ‘cardiac
Available online xxx
dysfunction’, ‘stage B heart failure’, ‘incident heart failure’, ‘risk assessment’, ‘risk impact’,
Keywords:
human studies in full-length publications in English language journal from 1946 to 2014.
Type 2 diabetes mellitus
Univariable and multivariable relative risk (RR) and hazard ratio (HR) were obtained from
‘risk score’, ‘predictor’, ‘prediction’ and related free text terms. The search was limited to
Heart failure
each study.
Predictor
Results: Twenty-one studies (n = 1111,569, including 507,637 subjects with T2DM) were
Risk factors
included in this analysis with a follow-up ranging from 1 to 12 years. Associations between incident HF and risk variables described in 3 studies were reported. This association was greatest for insulin use (HR 2.48; 1.24–4.99), HbA1c 7.0–8.0% (2.41; 1.62–3.59), 5 years increase in age (1.47; 1.25–1.73), fasting glucose (1.28; 1.10–1.51 per standard deviation) and HbA1c (1.18; 1.14–1.23 each 1% increase). After adjustment for confounders, there were strong associations with coronary artery disease (1.77; 1.31, 2.39), HbA1c 10% (1.66; 1.45–1.89), insulin use (1.43; 1.14–1.79), HbA1c 9.0–10.0% (1.31; 1.14–1.50), fasting glucose (1.27; 1.10–1.47 per standard deviation) and 5 years increase in age (1.26; 1.13–1.40). Conclusion: Among patients with T2DM, five common clinical variables are associated with significantly increased risk of incident HF. # 2015 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
Heart failure (HF) is a common end stage of heart disease and affects up to 26 million people worldwide [1], and the prevalence of heart failure in diabetic patients is also
increasing rapidly each year [2–5]. Results from a health maintenance organization show that about 12% of 10,000 patients with diabetes had heart failure at baseline, and 3.3% of the rest developed heart failure during each year of followup [6]. The 5-year survival rate of heart failure is analogous to that of malignancy, and the morbidity and mortality rates of
* Corresponding author. Tel.: +61 36226 7703; fax: +61 36226 7704. E-mail address: [email protected] (T.H. Marwick). http://dx.doi.org/10.1016/j.diabres.2015.01.011 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Wang Y, et al. Prediction of heart failure in patients with type 2 diabetes mellitus—A systematic review and meta-analysis. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.011
DIAB-6258; No. of Pages 12
2
diabetes research and clinical practice xxx (2015) xxx–xxx
diabetic heart failure are 4–8 fold higher than in the nondiabetic population [7]. The mortality ratio is approximately 9 fold higher in elderly patients [7]. In addition to its association with ischaemic heart disease, diabetes confers a demonstrably higher risk of developing cardiomyopathy [8]. Subclinical dysfunction may be a precursor to the development of subsequent symptomatic heart failure in patients with diabetes mellitus. However, at least 50% of those patients with asymptomatic left ventricular (LV) dysfunction are still unidentified [8]. The underlying metabolic disturbance of both pre-diabetes and diabetes leads to hyperinsulinemia, inflammation and oxidative stress. Multiple pathophysiological changes at the microscopic level culminate in abnormal cardiac function. Examples include impaired myocardial relaxation and cardiomyocyte resting tension giving rise to increased LV stiffness and diabetic autonomic neuropathy leading to sympathetic imbalance, which in turn drives increased fatty acid metabolism and foetal gene expression. Activation of the renin-angiotensin system is linked to increased deposition of myocardial collagen, advanced glycation and products (AGEs), and cardiac remodelling [8]. Diabetic microangiopathy, vascular endothelial dysfunction and coronary flow reserve impairment may arise from small vessel disease [9]. Although the epidemiology and mechanisms of the association of diabetes mellitus with heart failure are understood, an effective strategy for early diagnosis and effective intervention has not yet been demonstrated. Fundamental to this is the fact that not all patients are at equal risk, and a screening and intervention approach would be most effective if it involved the highest risk patients. The purpose of this study was to better quantify heart failure risk in subjects with diabetes mellitus.
2.
Methods
2.1.
Search strategy
This approach followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline[10]. A systematic literature search was performed on MEDLINE and EMBASE using the medical subject heading (MeSH) terms ‘heart failure’, ‘risk factor’, ‘type 2 diabetes mellitus’ ‘LV dysfunction’, ‘cardiac dysfunction’, ‘stage B heart failure’ ‘incident heart failure’, ‘risk assessment’, ‘risk impact’, ‘risk score’, ‘predictor’, ‘prediction’ and related free text terms. The search was limited to human epidemiological and clinical studies in English language (updated on February 2014). The search strategy, study selection, and analysis followed the recommendations in the Cochrane Handbook [11]. No previous reports of this nature have been identified. The review was registered with the Prospective Registration Of Systematic Reviews (http://www.crd.york.ac.uk/PROSPERO/display_record. asp?ID=CRD42014008821), as PROSPERO 2014:CRD42014008821. None of the authors have employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and grants or other funding that would constitute a conflict of interest in relation to this document.
2.2.
Study inclusion
Inclusion criteria for the review were: (1) full-length publication of original data in a peer-reviewed English language journal; (2) human adults >18 years of age with T2DM; (3) reported incident HF in subjects with T2DM; (4) analysis of risk factors relating to incident heart failure in T2DM, reporting effect sizes as relative risk (RR), odds ratio (OR) or hazard ratio (HR) with 95% confidence intervals (CIs). Exclusion criteria were (1) review articles, editorial comments, and letters to the editor, practice guidelines and articles without full text; (2) studies included T2DM patients had heart failure at baseline or used an inappropriate comparison group (the comparison was not between diabetic incident HF group non-HF groups). Two independent investigators (YW and TN) assessed the eligibility of the studies. Titles, abstracts and keywords, information of identified studies were assessed for the first screening. The second screening was based on the full texts review. The information of included studies was entered into an inclusion/exclusion form. Full texts were further assessed when the collected information of a primary study indicated that it was eligible to be included in this review. The references in the identified articles were also reviewed for possible inclusion.
2.3.
Data extraction
Data were carefully extracted from all eligible studies independently by two reviewers (YW and TN). A third reviewer (TM) was included for unresolved discrepancies, all discrepancies were reviewed and resolved by consensus. The recorded study characteristics included first author’s name, publication information, study design, time frame of study, age, sex distribution, follow-up time, number of participants, number of incident HF cases, method of assessment of HF, numbers of T2DM subjects with different risk factors of incident HF, and covariates included in the adjusted models. Outcome measures (RR, OR, HR) and their associated 95% confidence intervals (CIs) were extracted from included studies or calculated from available data. Only the largest dataset was included in the analysis when multiple articles represented data from the same dataset, except when different variables were reported in each article. The outcome was defined as new onset heart failure and the study was excluded if participants had a heart failure history. The definition of an incident heart failure event varied somewhat from different studies, but in general it was defined as a physician diagnosis of heart failure or a hospital discharge diagnosis coded as heart failure (ICD-9, code 428 or 518.4).
2.4.
Assessment of methodological quality
Two investigators (YW and TN) independently assessed the quality of included studies. The assessment of methodological quality was based on the Newcastle-Ottawa Quality Assessment Scale (NOS) for cohort studies with slight modifications to accommodate the topic of this review (Appendix 1).
Please cite this article in press as: Wang Y, et al. Prediction of heart failure in patients with type 2 diabetes mellitus—A systematic review and meta-analysis. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.011
DIAB-6258; No. of Pages 12 diabetes research and clinical practice xxx (2015) xxx–xxx
2.5.
Assessment of heterogeneity
Heterogeneity across included studies was tested using the Cochran Q and I2 tests. A chi-square >25% and P < 0.10 was defined as evidence of significant heterogeneity across studies. The I2 test was used to estimate the extent of heterogeneity that is attributable to inter-study variation [12,13]; a value >30% represents moderate heterogeneity and a value >50% represents substantial heterogeneity. Possible sources of heterogeneity were explored by subsequent meta-regression and sensitivity analyses. Meta-regression models were established to screen the affected factors resulting in heterogeneity using Comprehensive Metaanalysis software (version 2.0, Biostat, Englewood, NJ). For sensitivity analyses, data was extracted from relevant articles individually for pooled RRs to test the results of HRs.
3
Oxford, UK) with random effect-models weighted by inverse variance. Two-tailed p values
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Prediction of heart failure in patients with type 2 diabetes mellitus—A systematic review and meta-analysis Ying Wang, Tomoko Negishi, Kazuaki Negishi, Thomas H. Marwick * Menzies Research Institute Tasmania, 17 Liverpool Street, Hobart, TAS, Australia
article info
abstract
Article history:
Background: Heart failure (HF) is a major cause of mortality and disability in type 2 diabetes
Received 16 October 2014
mellitus (T2DM). This study sought to improve the assessment of HF risk in patients with
Received in revised form
T2DM—a step that would be critical for effective HF screening.
25 November 2014
Methods: A systematic literature search was performed on electronic databases including
Accepted 14 January 2015
MEDLINE and EMBASE, using MeSH terms ‘heart failure’, ‘risk factor’, ‘T2DM’, ‘cardiac
Available online xxx
dysfunction’, ‘stage B heart failure’, ‘incident heart failure’, ‘risk assessment’, ‘risk impact’,
Keywords:
human studies in full-length publications in English language journal from 1946 to 2014.
Type 2 diabetes mellitus
Univariable and multivariable relative risk (RR) and hazard ratio (HR) were obtained from
‘risk score’, ‘predictor’, ‘prediction’ and related free text terms. The search was limited to
Heart failure
each study.
Predictor
Results: Twenty-one studies (n = 1111,569, including 507,637 subjects with T2DM) were
Risk factors
included in this analysis with a follow-up ranging from 1 to 12 years. Associations between incident HF and risk variables described in 3 studies were reported. This association was greatest for insulin use (HR 2.48; 1.24–4.99), HbA1c 7.0–8.0% (2.41; 1.62–3.59), 5 years increase in age (1.47; 1.25–1.73), fasting glucose (1.28; 1.10–1.51 per standard deviation) and HbA1c (1.18; 1.14–1.23 each 1% increase). After adjustment for confounders, there were strong associations with coronary artery disease (1.77; 1.31, 2.39), HbA1c 10% (1.66; 1.45–1.89), insulin use (1.43; 1.14–1.79), HbA1c 9.0–10.0% (1.31; 1.14–1.50), fasting glucose (1.27; 1.10–1.47 per standard deviation) and 5 years increase in age (1.26; 1.13–1.40). Conclusion: Among patients with T2DM, five common clinical variables are associated with significantly increased risk of incident HF. # 2015 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
Heart failure (HF) is a common end stage of heart disease and affects up to 26 million people worldwide [1], and the prevalence of heart failure in diabetic patients is also
increasing rapidly each year [2–5]. Results from a health maintenance organization show that about 12% of 10,000 patients with diabetes had heart failure at baseline, and 3.3% of the rest developed heart failure during each year of followup [6]. The 5-year survival rate of heart failure is analogous to that of malignancy, and the morbidity and mortality rates of
* Corresponding author. Tel.: +61 36226 7703; fax: +61 36226 7704. E-mail address: [email protected] (T.H. Marwick). http://dx.doi.org/10.1016/j.diabres.2015.01.011 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Wang Y, et al. Prediction of heart failure in patients with type 2 diabetes mellitus—A systematic review and meta-analysis. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.011
DIAB-6258; No. of Pages 12
2
diabetes research and clinical practice xxx (2015) xxx–xxx
diabetic heart failure are 4–8 fold higher than in the nondiabetic population [7]. The mortality ratio is approximately 9 fold higher in elderly patients [7]. In addition to its association with ischaemic heart disease, diabetes confers a demonstrably higher risk of developing cardiomyopathy [8]. Subclinical dysfunction may be a precursor to the development of subsequent symptomatic heart failure in patients with diabetes mellitus. However, at least 50% of those patients with asymptomatic left ventricular (LV) dysfunction are still unidentified [8]. The underlying metabolic disturbance of both pre-diabetes and diabetes leads to hyperinsulinemia, inflammation and oxidative stress. Multiple pathophysiological changes at the microscopic level culminate in abnormal cardiac function. Examples include impaired myocardial relaxation and cardiomyocyte resting tension giving rise to increased LV stiffness and diabetic autonomic neuropathy leading to sympathetic imbalance, which in turn drives increased fatty acid metabolism and foetal gene expression. Activation of the renin-angiotensin system is linked to increased deposition of myocardial collagen, advanced glycation and products (AGEs), and cardiac remodelling [8]. Diabetic microangiopathy, vascular endothelial dysfunction and coronary flow reserve impairment may arise from small vessel disease [9]. Although the epidemiology and mechanisms of the association of diabetes mellitus with heart failure are understood, an effective strategy for early diagnosis and effective intervention has not yet been demonstrated. Fundamental to this is the fact that not all patients are at equal risk, and a screening and intervention approach would be most effective if it involved the highest risk patients. The purpose of this study was to better quantify heart failure risk in subjects with diabetes mellitus.
2.
Methods
2.1.
Search strategy
This approach followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline[10]. A systematic literature search was performed on MEDLINE and EMBASE using the medical subject heading (MeSH) terms ‘heart failure’, ‘risk factor’, ‘type 2 diabetes mellitus’ ‘LV dysfunction’, ‘cardiac dysfunction’, ‘stage B heart failure’ ‘incident heart failure’, ‘risk assessment’, ‘risk impact’, ‘risk score’, ‘predictor’, ‘prediction’ and related free text terms. The search was limited to human epidemiological and clinical studies in English language (updated on February 2014). The search strategy, study selection, and analysis followed the recommendations in the Cochrane Handbook [11]. No previous reports of this nature have been identified. The review was registered with the Prospective Registration Of Systematic Reviews (http://www.crd.york.ac.uk/PROSPERO/display_record. asp?ID=CRD42014008821), as PROSPERO 2014:CRD42014008821. None of the authors have employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and grants or other funding that would constitute a conflict of interest in relation to this document.
2.2.
Study inclusion
Inclusion criteria for the review were: (1) full-length publication of original data in a peer-reviewed English language journal; (2) human adults >18 years of age with T2DM; (3) reported incident HF in subjects with T2DM; (4) analysis of risk factors relating to incident heart failure in T2DM, reporting effect sizes as relative risk (RR), odds ratio (OR) or hazard ratio (HR) with 95% confidence intervals (CIs). Exclusion criteria were (1) review articles, editorial comments, and letters to the editor, practice guidelines and articles without full text; (2) studies included T2DM patients had heart failure at baseline or used an inappropriate comparison group (the comparison was not between diabetic incident HF group non-HF groups). Two independent investigators (YW and TN) assessed the eligibility of the studies. Titles, abstracts and keywords, information of identified studies were assessed for the first screening. The second screening was based on the full texts review. The information of included studies was entered into an inclusion/exclusion form. Full texts were further assessed when the collected information of a primary study indicated that it was eligible to be included in this review. The references in the identified articles were also reviewed for possible inclusion.
2.3.
Data extraction
Data were carefully extracted from all eligible studies independently by two reviewers (YW and TN). A third reviewer (TM) was included for unresolved discrepancies, all discrepancies were reviewed and resolved by consensus. The recorded study characteristics included first author’s name, publication information, study design, time frame of study, age, sex distribution, follow-up time, number of participants, number of incident HF cases, method of assessment of HF, numbers of T2DM subjects with different risk factors of incident HF, and covariates included in the adjusted models. Outcome measures (RR, OR, HR) and their associated 95% confidence intervals (CIs) were extracted from included studies or calculated from available data. Only the largest dataset was included in the analysis when multiple articles represented data from the same dataset, except when different variables were reported in each article. The outcome was defined as new onset heart failure and the study was excluded if participants had a heart failure history. The definition of an incident heart failure event varied somewhat from different studies, but in general it was defined as a physician diagnosis of heart failure or a hospital discharge diagnosis coded as heart failure (ICD-9, code 428 or 518.4).
2.4.
Assessment of methodological quality
Two investigators (YW and TN) independently assessed the quality of included studies. The assessment of methodological quality was based on the Newcastle-Ottawa Quality Assessment Scale (NOS) for cohort studies with slight modifications to accommodate the topic of this review (Appendix 1).
Please cite this article in press as: Wang Y, et al. Prediction of heart failure in patients with type 2 diabetes mellitus—A systematic review and meta-analysis. Diabetes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.diabres.2015.01.011
DIAB-6258; No. of Pages 12 diabetes research and clinical practice xxx (2015) xxx–xxx
2.5.
Assessment of heterogeneity
Heterogeneity across included studies was tested using the Cochran Q and I2 tests. A chi-square >25% and P < 0.10 was defined as evidence of significant heterogeneity across studies. The I2 test was used to estimate the extent of heterogeneity that is attributable to inter-study variation [12,13]; a value >30% represents moderate heterogeneity and a value >50% represents substantial heterogeneity. Possible sources of heterogeneity were explored by subsequent meta-regression and sensitivity analyses. Meta-regression models were established to screen the affected factors resulting in heterogeneity using Comprehensive Metaanalysis software (version 2.0, Biostat, Englewood, NJ). For sensitivity analyses, data was extracted from relevant articles individually for pooled RRs to test the results of HRs.
3
Oxford, UK) with random effect-models weighted by inverse variance. Two-tailed p values
