The WATCH-DM Risk Score Estimates Clinical Outcomes in Type 2 Diabetic Patients with Heart Failure with Preserved Ejection Fraction

doi:10.21203/rs.3.rs-3124111/v1

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Research Article

The WATCH-DM Risk Score Estimates Clinical Outcomes in Type 2 Diabetic Patients with Heart Failure with Preserved Ejection Fraction

https://doi.org/10.21203/rs.3.rs-3124111/v1

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Background: The coexistence of heart failure is frequent and associated with higher mortality in patients with type 2 diabetes (T2DM), and its management is a critical issue. The WATCH-DM risk score is a tool to predict heart failure in patients with type 2 diabetes mellitus (T2DM). We investigated whether it could estimate outcomes in T2DM patients with heart failure with preserved ejection fraction (HFpEF).

Methods:The WATCH-DM risk score was calculated in 418 patients with T2DM hospitalized for HFpEF (male 49.5%, age 80±9 years, HbA1c 6.8±1.0%), and they were divided into the “average or lower” (≤10 points), “high” (11-13 points) and “very high” (≥14 points) risk groups. We followed patients to observe all-cause death for 386 days (median). We compared the area under the curve (AUC) of the WATCH-DM score for predicting 1-year mortality with that of the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score and of the Barcelona Bio-Heart Failure Risk (BCN Bio-HF).

Results: Among the study patients, 108 patients (25.8%) had average or lower risk scores, 147 patients (35.2%) had high risk scores, and 163 patients (39.0%) had very high risk scores. The Cox proportional hazard model selected the WATCH-DM score as an independent predictor of all-cause death (HR per unit 1.10, 95% CI 1.03 to 1.19), and the “average or lower” risk group had lower mortality than the other groups (p=0.047 by log-rank test). The AUC of the WATCH-DM for 1-year mortality was 0.64 (95% CI; 0.45 to 0.74), which was not different from that of the MAGGIC score (0.72, 95% CI 0.63 to 0.80, p=0.08) or that of BCN Bio-HF (0.70, 0.61 to 0.80, p=0.25).

Conclusion: The WATCH-DM risk score can estimate prognosis in T2DM patients with HFpEF and can identify patients at higher risk of mortality. It can be a useful tool for heart failure management in T2DM patients.

heart failure with preserved ejection fraction

diabetes

risk score

mortality

Heart failure (HF) is one of the major complications of diabetes mellitus (DM) and is strongly associated with the prognosis of diabetic patients. HF is observed in up to 22% of diabetic patients, and patients with DM or prediabetes have a two to four times higher risk of developing HF than those without them[1–4]. HF is also the strongest risk factor for death among cardiovascular or renal complications in patients with newly diagnosed type 2 diabetes mellitus (T2DM)[1, 3, 5]. On the other hand, DM is present in 20 to 40% of HF patients[4], and concomitant DM increases mortality and hospitalization in patients with HF[1–4, 6]. HF with preserved ejection fraction (HFpEF) is as common as HF with reduced ejection fraction (HFrEF) in T2DM patients, and the impact of DM on cardiovascular death or HF hospitalization is greater in HFpEF than in HFrEF[6].

For the risk stratification of patients with T2DM and HF, prediction of functional and clinical outcomes is as important as prediction of HF development. The WATCH-DM risk score is a novel risk score for predicting incident HF hospitalization in T2DM patients without baseline HF, using readily available clinical, laboratory, and electrocardiographic (ECG) variables[7]. We investigated whether the WATCH-DM score can predict prognosis in T2DM patients hospitalized with acutely decompensated HFpEF. We also compared its ability to predict all-cause mortality with other established risk scores for morality in patients with HFpEF.

Study Population: We retrospectively analyzed the data from the Prospective Multicenter Observational Study of Patients with Heart Failure with Preserved Ejection Fraction (PURSUIT-HFpEF), a multicenter, observational study enrolling consecutive patients hospitalized with acute decompensated HFpEF (left ventricular ejection fraction (LVEF) ≥ 50%) in 31 collaborating hospitals [UMIN-CTR ID: UMIN000021831][8]. Details of the entry criteria and data collection have been described elsewhere. Briefly, patients admitted with acutely decompensated HFpEF were registered, and their clinical data, including medications, laboratory tests, and ECG, were collected on admission, at discharge, and 1 year after discharge. Acutely decompensated HFpEF was diagnosed based on the following criteria: (1) clinical symptoms and signs according to the Framingham Heart Study criteria, (2) LVEF on admission ≥ 50%, and (3) serum N-terminal pro-B type natriuretic peptide (NT-proBNP) ≥ 400 pg/mL or brain natriuretic peptide ≥ 100 pg/mL. T2DM was diagnosed based on clinical history or on fasting plasma glucose and/or hemoglobin A1c (HbA1c) during hospitalization based on the Japanese Clinical Practice Guideline for Diabetes 2019[9]. Oral glucose tolerance testing was not mandatory for the present study.

This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by each corresponding hospital’s Ethics Committee. Informed consent was obtained from each patient by one of the investigators before the study.

Data Collection

We collected patient data, including risk factors and history of major comorbidities such as DM, hypertension, dyslipidemia, smoking, chronic kidney disease (CKD), history of HF hospitalization, prior myocardial infarction, prior stroke and malignancy, and history of percutaneous coronary intervention or coronary artery bypass graft (CABG). Blood tests, standard 12-lead ECG recording, chest radiography, and echocardiography were performed immediately after admission, before discharge, and 1 year after discharge. LVEF was determined by either the Teichholz method or the modified Simpson’s technique on admission but only by Simpson’s technique at discharge and 1 year after discharge. Study patients were followed up by direct contact or telephone interview with patients to observe all-cause death, which was a primary endpoint of the PURSUIT-HFpEF registry[8]. For patients whose survival information could not be determined by these means, the data from National Vital Statistics of Japan, which includes all death records in Japan reported by prefectural public health centers, were used with the permission of the Ministry of Health, Labor and Welfare in accordance with the Statistics Act in Japan.

The WATCH-DM risk score and other heart failure risk scores: We calculated the WATCH-DM score as the sum of the scores obtained from the following factors[7]: age (0 to 6 points), body mass index (BMI, 0 to 5 points), systolic (0 to 3 points) and diastolic (0 to 2 points) blood pressure (BP), fasting plasma glucose (0 to 3 points), serum creatinine (0 to 5 points), high density lipoprotein cholesterol (HDL-c, 0 to 2 points), QRS width on ECG (0 or 3 points) and history of myocardial infarction (0 or 3 points) or CABG (0 or 2 points), all of which were measured or obtained at hospital discharge. The risk of HF in each patient was estimated as very low (≤ 7 points), low (8–9 points), average (10 points), high (11–13 points) and very high (≥ 14 points) (Table 1). Due to the limited number of patients, we combined patients with very low to average risk as the “average or lower” risk group.

Table 1

The WATCH-DM risk score.
Age (years)	< 50	50–54	55–59	60–64	65–69	70–74	≥ 75
Age (years)	0	1	2	3	4	5	6
BMI (kg/m²)	< 25	25–34	35–39	≥ 40
BMI (kg/m²)	0	1	2	3
Systolic BP (mmHg)	< 100	100–139	140–159	≥ 160
Systolic BP (mmHg)	0	1	2	3
Diastolic BP (mmHg)	< 60	60–80	≥ 80
Diastolic BP (mmHg)	2	1	0
FPG (mg/dL)	< 125	125–199	200–299	≥ 300
FPG (mg/dL)	0	1	2	3
HDL-c (mg/dL)	< 30	30–59	≥ 60
HDL-c (mg/dL)	2	1	0
Serum Cr (mg/dL)	< 1.0	1.0-1.49	≥ 1.50
Serum Cr (mg/dL)	0	2	5
Ischemic events	Prior CABG		Prior MI
Ischemic events	2		3

The WATCH-DM score was calculated as the sum of scores, which are shown in the bottom row corresponding to each factor.

BMI depicts body mass index; BP, blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; Cr, serum creatinine; CABG, coronary artery bypass grafting; MI, myocardial infarction.

To compare the ability of the WATCH-DM risk score to predict 1-year mortality with other HF risk scores, we calculated the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score[10] and the mortality risk using the Barcelona Bio-Heart Failure Risk (BCN Bio-HF) calculator[11]. We calculated the MAGGIC risk score as the sum of scores provided from the following factors: LVEF (0 point to all present patients with HFpEF), age (0 to 15 points), systolic BP (0 to 2 points), BMI (0 to 6 points), creatinine (0 to 8 points), New York Heart Association (NYHA) class (0 to 8 points), male sex (0 or 1 point), current smoker (0 or 1 point), DM (3 points for all preset patients), diagnosis of chronic obstructive pulmonary disease (0 or 2 points), first diagnosis of heart failure in the 18 months (0 or 2 points), not on beta blockers (0 or 3 points) and not on renin-angiotensin-aldosterone blockers (0 or 1 point)[10]. We estimated 1-year mortality by the web-based BCN Bio-HF calculator (http://ww2.bcnbiohfcalculator.org/web/, accessed at September and October 2021) using age, sex, NYHA class, LVEF, serum sodium, estimated glomerular filtration rate (eGFR), hemoglobin, loop diuretic dose, beta blocker, angiotensin converting enzyme inhibitor/angiotensin-2 receptor blocker, and statin treatments[11]. We did not include biomarkers for the present analysis because NT-proBNP was not measured in some patients, and cardiac troponin T or ST-2 was not measured at all.

Statistical Analysis

Continuous variables are expressed as the mean and standard deviation or median [the interquartile range (IQR)]. Categorical variables are expressed as absolute frequencies or relative percentages. We made comparisons by one-way ANOVA for continuous variables, and the significance of differences among groups was calculated with the Bonferroni correction. Categorical variables were compared with Fisher’s exact test. For the correlation between WATCH-DM score and continuous or ordinal values, Spearman's rank correlation coefficient was calculated. A Cox proportional hazard model for all-cause death was constructed including factors that showed significant differences (p < 0.05) among the 3 risk groups, although factors that were included by or highly related to the WATCH-DM score were not included. Event-free survival analysis was performed using the Kaplan‒Meier method with the log-rank test for group comparisons.

We constructed time-dependent receiver operating characteristic (ROC) curves of the risk scores for all-cause death at 1 year after hospitalization using the “time ROC” package (ver 0.4) for R. We compared the difference between the estimated area under the curves (AUC) of both risk scores for each time point, and the variance of the difference using the independent and identically distributed (iid) representation of the AUC estimators was used to obtain the p value of the comparison test. All statistical analyses were performed using R (version 4.1.1) or R with a graphical user interface EZR (Saitama Medical Centre, Jichi Medical University, Japan).

Patient Characteristics. Among 1095 patients hospitalized for decompensated HFpEF and registered in PURSUIT-HFpEF between June 2016 and December 2020, 418 patients (38.2%) had T2DM. The mean age of the study patients was 80 ± 9 years, and 207 (49.5%) patients were male. The mean HbA1c was 6.8 ± 1.0%, and the mean BMI was 23.1 ± 4.4 kg/m². Diabetes was diagnosed before hospitalization in 316 patients (75.6%), and it was newly diagnosed after hospitalization in 102 patients (24.4%).

The Watch-DM Score. The mean WATCH-DM risk score in the study group was 12.8 ± 3.1 points, 108 patients (25.8%) had very low to average, 147 patients (35.2%) had high, and 163 patients (39.0%) had very high HF risk (Fig. 1). There were differences in clinical risk factors among groups, most of which were included in the WATCH-DM score: age (p < 0.0001), male sex (p = 0.003), BMI (p = 0.02), systolic (p = 0.02) and diastolic (p < 0.0001) BP, fasting plasma glucose (p = 0.003), serum creatinine (p < 0.0001) and LDL cholesterol (p = 0.002), whereas no difference was found in HbA1c (p = 0.70) and HDL cholesterol (p = 0.07) (Table 2).

The number of patients with each score is shown as a bar. The heart failure (HF) risk was determined as the 5-year incidental HF risk in the original article[7]: ≤ 7 points very low; 8–9 points, low; 10 points, average; 11–13 points, high; ≥ 14 points, very high risk.

Table 2

Patient Characteristics
Heart failure risk	Average or lower	High	Very High	P value
N	108	147	163
WATCH-DM score	9.1 ± 1.1	12.0 ± 0.8^¶	16.0 ± 1.7^¶,\|\|	< 0.001
Age, years	76.6 ± 11.2	81.1 ± 7.8^¶	81.5 ± 6.8^¶	< 0.001
Male gender, %	39.8	45.6	59.5^†	0.003
BMI, kg/m²	22.3 ± 4.1	22.8 ± 4.5	23.8 ± 4.3*	0.02
Hypertension, %	82.4	91.2	93.9*	0.009
Dyslipidemia, %	41.7	54.4	67.5*	0.0002
Smokers, %	42.6	36.7	46.6	0.21
Chronic kidney disease, %	59.3	83.6^¶	98.8^¶	< 0.001
History of atrial fibrillation, %	42.5	40.1	33	0.23
Systolic BP, mmHg	118 ± 17	123 ± 18	123 ± 20*	0.02
Diastolic BP, mmHg	70 ± 12	65 ± 12	63 ± 13	< 0.001
Creatinine, µmol/L	77.8 ± 26.5	102.5 ± 45.1	225.4 ± 192.7	< 0.001
Estimated GFR, mL/min/1.73m²	57.3 ± 14.9	45.4 ± 15.0^¶	26.0 ± 14.0^¶,\|\|,	< 0.001
Fasting plasma glucose, mmol/L	6.38 ± 1.6	7.2 ± 2.5*	7.4 ± 2.7^‡	0.003
HbA1c, %	6.8 ± 1.0	6.8 ± 0.7	6.9 ± 1.1	0.70
Triglyceride, mmol/L	1.22 ± 0.50	1.33 ± 0.61	1.49 ± 0.56	0.316
HDL, mmol/L	1.14 ± 0.31	1.11 ± 0.34	1.06 ± 0.36	0.08
LDL, mmol/L	2.51 ± 0.70	2.46 ± 0.80^‡	2.20 ± 0.75^‡	0.002

* p < 0.05, † p < 0.01, ‡ p < 0.005, ¶ p < 0.001 vs. the average or lower risk group

§p < 0.01, || p < 0.001 vs. the high-risk group

The smokers included former and current smokers.

NT-proBNP was measured in 359 patients (85.9%), and it was correlated with WATCH-DM score (ρ = 0.33, p < 0.0001). The “very high” risk group had a higher NT-proBNP value (1638 [774, 4848] ng/L) than the “average or lower” (696 [400, 1442] ng/L, p = 0.002) and the “high” risk (836 [386, 1665] ng/L, p = 0.003) groups.

Clinical Outcomes and the WATCH-DM Score. During the follow-up period of 386 [IQR 221 to 729] days, 77 patients (18.4%) died. We constructed a Cox proportional hazard model using sex, history of hypertension, CKD, dyslipidemia, LDL-cholesterol and the WATCH-DM score, which were significantly different among the 3 risk groups (Table 2), for all-cause mortality. We did not include age, BMI, systolic/diastolic BP, serum creatinine, or fasting plasma glucose because these factors were included in the WATCH-DM score. We did not include eGFR because creatine was used in the WATCH-DM score, while history of CKD was included in the analysis.

The Cox proportional hazard model selected the WATCH-DM score as an independent predictor for all-cause death (hazard ratio (HR) per unit 1.10, 95% CI 1.01 to 1.20, p = 0.006), together with dyslipidemia and CKD (Table 3). Kaplan‒Meier curves showed the difference in all-cause mortality among the 3 groups (p = 0.047 by log-rank test), and the “very high” risk group had higher mortality than the “average or lower” risk group (p = 0.043) (Fig. 2).

Table 3

Cox proportional hazard model analysis for all-cause mortality.
	Hazard Ratio [95% confidence interval]	P values
Gender	1.311 [0.787–2.184]	0.298
Hypertension	0.566 [0.272–1.178]	0.128
Dyslipidemia	0.590 [0.35–0.998]	0.049
CKD	1.703 [1.002–2.895]	0.049
LDL-c	0.999 [0.989–1.008]	0.749
WATCH-DM score	1.102 [1.009–1.203]	0.031

CKD depicts chronic kidney disease; LDL-c, low-density lipoprotein cholesterol.

All-cause mortality during the follow-up period (median 386 days, IQR 221 to 729 days) was observed in 12 patients with average or lower risk, in 27 patients with high risk and in 38 patients with very high risk. There were significant differences in mortality among the three groups (p = 0.047 by log-rank test). Patients with very high risk (≥ 14 points) had a higher mortality than those with average or lower risk (≤ 10 points, p = 0.043).

Comparison of the WATCH-DM score and the other risk scores. The MAGGIC score in the study group was 25.7 ± 5.6, and it was significantly correlated with WATCH-DM (ρ = 0.395, p < 0.001) (Fig. 3). The AUC of the WATCH-DM for all-cause death at 1 year was 0.64 (95% CI 0.45 to 0.74). The AUC of the MAGGIC score was 0.72 (95% CI: 0.63 to 0.80), and there was no difference in AUC between the two scores (p = 0.08) (Fig. 3). The AUC for 1-year mortality prediction by the BCN Bio-HF calculator was 0.70 (95% CI: 0.61 to 0.80), which was not different from that of the WATCH-DM risk score (p = 0.25).

Time-dependent ROC curves of the WATCH-DM score (top, left), the MAGGIC score (top, right) and BCN Bio-HF (bottom) for all-cause death at 1 year after hospitalization. The areas under the curve (AUCs) of the WATCH-DM score and MAGGIC score were 0.64 (95% CI 0.45 to 0.74) and 0.72 (95% CI: 0.63 to 0.80), respectively. The AUC of BCN Bio-HF was 0.70 (95% CI 0.61 to 0.80), which was not different from that of the WATCH-DM risk score (p = 0.25).

We investigated the ability of the WATCH-DM risk score to predict all-cause mortality in 418 T2DM patients hospitalized for decompensated HFpEF. The WATCH-DM score was significantly correlated with predischarge NT-proBNP (ρ = 0.33, p < 0.0001). During the follow-up period of 386 (median) days, all-cause death was observed in 77 patients, and the WATCH-DM score was selected as an independent predictor for all-cause death (HR per unit 1.10, 95% CI 1.01 to 1.20, p = 0.006), along with dyslipidemia and CKD. Significant differences in all-cause mortality were observed among the “average or lower“ (≤ 10 points), the “high” and the “very high” (≥ 14 points) risk groups (p = 0.047 by log-rank test), and the very high risk group had higher mortality than the “average or lower" risk group (p = 0.043). The WATCH-DM score was significantly correlated with the MAGGIC score (ρ = 0.395, p < 0.001). The AUC for the prediction of all-cause mortality by the WATCH-DM score was not different from that of the MAGGIC score (p = 0.08) and that by the BCN Bio-HF calculator (p = 0.25). These results indicate that the WATCH-DM score was associated with all-cause mortality in T2DM patients with HFpEF, and a 1-point increase was associated with a 10% increase in mortality.

The heart failure risk scores for diabetic patients

Glycemic control affects mortality and morbidity in patients with concomitant DM and HF. The risk of HF hospitalization is progressively increased with fasting blood glucose[12] or HbA1c[13, 14], particularly in patients with HbA1c > 8%[14]. Most of the risk scores for predicting HF prognosis have been derived from the data of HF patients with or without diabetes, and they may not adequately consider the influence of glycemic control. The presence of DM is used to calculate the MAGGIC score, but blood glucose or HbA1c is not included. BCN Bio-HF does not use any factors related to DM or glycemic control. The WATCH-DM score uses fasting plasma glucose for its calculation, reflecting the importance of metabolic factors in the development and prognosis of HF in diabetic patients. The MAGGIC score and the BCN Bio-HF use LVEF and NYHA classification for calculation, which may not be readily available to non-cardiologists. The WATCH-DM scores use factors most of which are available in the usual DM practice. Therefore, WATCH-DM is more suitable for the risk assessment of T2DM patients than other risk scores, especially for non-cardiologists.

Although poor glycemic control is associated with a worse prognosis of HF, strict glycemic control does not always reduce HF or cardiovascular events[15]. Most glucose-lowering agents did not reduce the incidence of HF in T2DM patients in randomized control trials[16], and thiazolidinediones[17] and saxagliptin[18] even increased HF events. On the other hand, sodium–glucose cotransporter 2 (SGLT2) inhibitors can reduce HF incidence, leading to fewer MACE and cardiovascular death in patients with T2DM[19–21]. SGLT2 inhibitors reduce cardiovascular death and HF hospitalization in both HFrEF-[22, 23] and HFpEF[24, 25] patients with or without DM. Guidelines recommend an SGLT2 inhibitor as part of the glucose-lowering regimen and comprehensive cardiovascular risk reduction among individuals with T2DM and HF instead of baseline HbA1c, individualized HbA1c target, or metformin use[16].

However, SGLT2 inhibitors or glucagon-like peptide 1 receptor agonists, another agent with cardioprotective effects, are more expensive than traditional treatments. Guidelines recommend that DM treatment regimens need to be continuously reviewed for efficacy, side effects, and burden, and in some cases, reduction or discontinuation of medication should be considered for several reasons, including cost[16]. Patients suitable for these more expensive treatments should be appropriately selected, and the WATCH-DM score may be useful to identify high-risk patients among those with DM and HFpEF.

Study limitations

The present study was a retrospective study from a registered database, and the number of study patients was limited. Oral glucose tolerance testing was not mandatory, and DM may not have been diagnosed in some patients. We did not analyze the effects of antidiabetic agents, which may affect clinical outcomes in HFpEF. We only examined 1-year mortality, and it is not clear whether the WATCH-DM score can predict the longer-term prognosis.

Ethnic differences exist in the mortality and morbidity of T2DM[26] and HFpEF[27, 28]. The mean BMI was only 23.1 kg/m^2, and the mean age was 80 years in the present Japanese study group, which may be different from typical Western patients with HFpEF. It is unclear whether the present results are applicable to patients outside East Asia. Despite these study limitations, the present study suggested that the WATCH-DM score may be useful for the risk management of T2DM patients with HFpEF. The present study was a small-scale study for proof of the concepts, and a large-scale, prospective study is expected to establish the role of the WATCH-DM score in this challenging patient population.

In this analysis of the data from the PURSUIT-HFpEF registry, we found that the WATCH-DM score was an independent predictor for all-cause mortality in T2DM patients hospitalized for decompensated HFpEF and that significant differences in all-cause mortality were observed among the risk groups defined by the risk score. The score showed comparable predictive ability for 1-year mortality to the MAGGIC score and the BCN Bio-HF calculator. The WATCH-DM score, which includes factors readily available in routine diabetes management, can be a valuable tool for risk assessment in T2DM patients with HFpEF and can be useful to identify patients at higher risk of mortality.

heart failure

diabetes mellitus

T2DM

type 2 diabetes mellitus

HFpEF

heart failure with preserved ejection fraction

HFrEF

heart failure with reduced ejection fraction

ECG

electrocardiogram

PURSUIT-HFpEF

the Prospective Multicenter Observational Study of Patients with Heart Failure with Preserved Ejection Fraction

LVEF

left ventricular ejection fraction

NT-proBNP

N-terminal pro-B type natriuretic peptide

HbA1c

hemoglobin A1c

CKD

chronic kidney disease

CABG

coronary artery bypass graft

MACE

major adverse cardiovascular outcome

BMI

body mass index

blood pressure

HDL-c

high-density lipoprotein cholesterol

MAGGIC

the Meta-Analysis Global Group in Chronic Heart Failure

BCN Bio-HF

the Barcelona Bio-Heart Failure Risk

NYHA

New York Heart Association

eGFR

estimated glomerular filtration rate

IQR

the interquartile range

ROC

receiver operating characteristic

AUC

area under the curve

SGLT2

sodium–glucose cotransporter 2

Ethics approval and consent to participate. This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the ethics committee of each hospital according to the Ethical Guidelines for Medical and Health Research Involving Human Subjects issued by the Ministry of Health, Labor and Welfare in Japan. The study was conducted in accordance with the Declaration of Helsinki, the Ethical Guidelines for Medical and Health Research Involving Human Subjects, and other current legal regulations in Japan. Informed consent was obtained from each patient by one of the investigators before the study.

Consent for publication. Not applicable.

Availability of data and materials. The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflict of interest. KI received honoraria from AstraZeneca, Eli Lilly, Boehringer Ingelheim and Ono Pharmacy. NT received an honorarium from AstraZeneca. SH received research support from Roche Diagnostics, Toyama Chemical, and Acterlion Pharmaceutical and honoraria from Daiichi Sankyo Company, Bayer, Astellas Pharma, Pfizer Pharmaceuticals, and Boehringer Ingelheim. YS received a research grant from Acterlion Pharmaceutical and honoraria from Astellas Pharma, Daiichi Sankyo Company, and Otsuka Pharmaceutical. The remaining authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work.

Funding. This work was funded by Roche Diagnostics K.K. and Fuji Film Toyama Chemical Co. Ltd.

Authors' contributions. KI formulated the research question, analyzed the data, and wrote the manuscript. TO and AO formulated the research question and provided support in the data analysis. YK, NT, MO and KF provided support in the data collection and contributed to the discussion. MS, TY, MY, TH, AN, YY, YN and ST provided support in the data collection as investigators of PURSUIT-HFpEF. YS, SH and DN collected long-term follow-up data as main investigators of PURSUIT-HFpEF and reviewed and edited the manuscript. YS is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Acknowledgments. The authors thank Nagisa Yoshioka, Kyoko Tatsumi, Satomi Kishimoto, Noriko Murakami, and Sugako Mitsuoka for their excellent assistance with data collection and all PURSUIT-HFpEF study participants whose names are listed in Additional File for their support of the present study.

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No competing interests reported.

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The WATCH-DM Risk Score Estimates Clinical Outcomes in Type 2 Diabetic Patients with Heart Failure with Preserved Ejection Fraction

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