GRAPHICAL ABSTRACT

Highlights

• Absolute SCA risk is highest among individuals with both hypertension and DM.

• The impact of blood pressure on SCA risk is more pronounced in those without DM.

• Individuals with DM show a J-shaped association, with both low and high SBP raising SCA risk.

INTRODUCTION

The incidence of sudden cardiac arrest (SCA) is low, but its consequences are grave for both the victim and the society [1,2]. Various efforts have been made to identify risk factors for SCA and to prevent it [3-5]. We previously reported that both hypertension and diabetes mellitus (DM), including pre-hypertension and impaired fasting glucose (IFG), are associated with increased risk of SCA [6]. However, interaction between hypertension and DM was not fully examined.

Since DM is associated with autonomic neuropathy which may cause abnormal cardiovascular reflex to maintain adequate blood pressure, diabetic patients can be more vulnerable to baseline low blood pressure [7]. Sudden drop in blood pressure and failure to restore it through neurohormonal activation might result in cardiovascular collapse and SCA. Patients with DM compared to those with normoglycemia or IFG showed significantly higher prevalence of orthostatic hypotension [7]. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, orthostatic hypotension in patients with type 2 diabetes mellitus (T2DM) was associated with increased mortality and heart failure death or hospitalization [8]. A prospective cohort analysis of Swedish people also suggested that orthostatic hypotension was associated with increased mortality and coronary events [9].

Whether high or low blood pressure and DM interact with each other to further increase the risk of SCA also remains to be explored. We performed this analysis to evaluate the association between blood pressure and SCA in both diabetic and non-diabetic patients and to determine interaction between DM and blood pressure on the risk of SCA.

METHODS

Study cohort

We conducted this analysis based on the Korean National Health Insurance Service (K-NHIS) database. All citizens of South Korea are mandatory subscribers of the K-NHIS. People who cannot afford the subscription fee of the K-NHIS are offered with a separate medical aid service, but their medical data are all integrated into the K-NHIS database. Therefore, data of the K-NHIS can represent the entire population of South Korea. Important feature of the K-NHIS database that discriminates from database from other nations is the presence of measured medical data such as blood pressure, body weight, height, waist circumference; laboratory data including complete blood cell count, renal function, liver function, fasting blood glucose, and lipid profiles; and self-reported questionnaires of lifestyles such as alcohol intake pattern, smoking status, and physical exercise level. This is possible because the K-NHIS offers a biennial nationwide health screening program. Another strong point of the K-NHIS is its closed-circuit nature. Entrance and exit to the system are all monitored, and no undetected case can exist. People who emigrate are censored at the moment of change in their nationality. All death events that happened in either South Korea or overseas are mandatorily reported to the K-NHIS system. These characteristics result in absence of under-detection of events originating from follow-up losses. Since SCA victim may not come to the medical researcher’s hospital but rather go to the closest hospital from the scene, traditional registry-based studies are subject to under-detection of SCA events.

Medical researchers can utilize the database of the K-NHIS upon approval from both the official review committee (https://nhiss.nhis.or.kr/) of the K-NHIS and institutional review board of the researcher’s institution. Formal approval from both the Institutional Review Board of Korea University Medicine Anam Hospital and official review committee of the K-NHIS was obtained for this specific study. The Institutional Review Board of Korea University Medicine Anam Hospital and official review committee of the K-NHIS approved this specific study (IRB No.: 2021AN0185). The requirement for written informed consent was waived by the Institutional Review Board of Korea University Medicine Anam Hospital, due to the retrospective nature of the study. Both the principles of 2013 Declaration of Helsinki and legal regulation of South Korea were adhered throughout the study process.

Availability of data and materials

The data underlying this article are available in the article. The raw data underlying this article cannot be shared publicly due to privacy reasons and legal regulations of Republic of Korea. The raw data is stored and analyzed only in the designated server managed by the K-NHIS.

Patient selection

People who underwent nationwide health screening in 2012 and aged equal or older than 20 years were screened. Among these people, 40% were randomly selected for the analysis. The date of 2012 health screening was the start of clinical follow-up for each participant. Excluded people were as follows: (1) those who were younger than 20 years; (2) people who were diagnosed with type 1 diabetes mellitus (T1DM) prior to health screening; (3) people who already experienced SCA prior to health screening; (4) people who experienced SCA within 1 year of clinical follow-up (within 1 year of health screening); and (5) who had missing data.

We excluded SCA events within 1 year of health screening since these events can be either actual SCA events or just repeat claim of International Classification of Disease, 10th edition (ICD-10) codes of a prior SCA event. Participants were followed until December 2022.

Identification of SCA

SCA, either aborted or non-aborted, that occurred 1 year after health screening in 2012 was the main outcome of this study. Identification of SCA was based on reports of ICD-10 codes for SCA and included (1) cardiac arrest with successful resuscitation (I46.0); (2) SCA (I46.1); (3) cardiac arrest, cause unspecified (I46.9); (4) ventricular fibrillation and flutter (I49.0); (5) instantaneous death (R96.0); and (6) death occurring less than 24 hours from symptom onset (R96.1). Only those reported at the emergency department were counted. Since some SCA events might not be accompanied by appropriate report of ICD-10 codes, performance of cardiopulmonary resuscitation in emergency department without a report of ICD-10 codes for SCA was also classified as SCA event. Exclusion criteria for SCA include potential non-cardiac cause of unexpected death that occurred within 6 months of SCA diagnosis. Non-cardiac cause of unexpected death includes drowning, suffocation, asphyxia, sepsis, anaphylaxis, major trauma, burn, gastrointestinal bleeding, hit by lightning, electric shock, and hemorrhagic or ischemic stroke. The ICD-10 codes to detect SCA is summarized in Supplementary Table 1. Our strategy to identify SCA by ICD-10 codes is validated in our prior reports [5,6,10-12].

Hypertension and diabetes mellitus

Only T2DM was analyzed in this study, and patients were classified into three stages: (1) non-DM (fasting blood glucose <100 mg/dL and absence of ICD-10 codes for DM); (2) IFG (fasting blood glucose ranging from 100 to 125 mg/dL and absence of ICD-10 codes for DM); and (3) DM (fasting blood glucose ≥126 mg/dL or report of ICD-10 codes for DM). Hypertension was diagnosed if there was a prior report of ICD-10 codes for hypertension before health screening in 2012 or blood pressure criteria for hypertension (systolic blood pressure [SBP] ≥140 mm Hg or diastolic blood pressure [DBP] ≥90 mm Hg) was met during health screening program. The robustness of these classifications was verified in our prior reports [13-16]. The thresholds for categorizing blood pressure were according to established guidelines for hypertension and prior clinical studies [17-19]. Based on SBP and DBP levels, blood pressure was stratified as following: (1) SBP ≥160 mm Hg or DBP ≥100 mm Hg: defined as severe hypertension; (2) SBP 140–159 mm Hg or DBP 90–99 mm Hg: defined as hypertension; (3) SBP 120–139 mm Hg or DBP 80–89 mm Hg: defined as elevated blood pressure; (4) SBP <120 mm Hg and DBP <80 mm Hg: defined as non-elevated blood pressure; and (5) SBP <100 mm Hg and DBP <70 mm Hg: defined as low blood pressure. The impact of blood pressure that was measured during 2012 health screening on SCA was evaluated in both diabetic and non-diabetic patients. Our strategy to define various medical conditions is summarized in Supplementary Table 1.

Statistical analysis

Continuous variables were expressed as mean±standard deviation or median with interquartile range and compared with Student’s t-test or Mann-Whitney U test as appropriate. The chi-square test of Fisher’s exact test was used as appropriate to compare categorical variables which were expressed as number and its percentile value. Kaplan-Meier survival curve analysis was performed to depict cumulative incidence of SCA and between group difference was compared with log-rank t-test. Cox proportional hazard model was used to calculate hazard ratio (HR) and its 95% confidence interval (CI). Multivariate analysis was performed with three different models: model 1 was non-adjusted model, model 2 was adjusted for age and sex, model 3 was adjusted for age, sex, body mass index (BMI), income level, smoking status, alcohol drinking, regular exercise level, dyslipidemia, chronic kidney disease, and medications for hypertension. Competing risk analysis was performed with model 3 using Fine and Gray method to distinguish the risk of SCA from that of other causes of death. All tests were two-tailed, and P value less than 0.05 was considered as statistical significance. All statistical analyses were performed with SAS version 9.2 (SAS Institute, Cary, NC, USA).

RESULTS

Patients

Among people who underwent nationwide health examination in 2012 and equal or older than 20 years, 40% were randomly selected. A total of 4,910,068 people were screened. People who (1) were diagnosed with T1DM prior to health screening (n=1,140); (2) already experienced SCA prior to health screening (n=823); (3) experienced SCA within 1 year of clinical follow-up (n=11,645) (within 1 year of health screening); or (4) had missing data were excluded n=302, 484). Finally, we analyzed 4,593,706 people, with 3,097,423 in the non-DM group, 1,034,563 in the IFG group, and people in the DM group (Fig. 1).

Baseline characteristics are summarized in Table 1. In the whole cohort, mean age was 48.3±13.8 years, and 2,480,851 (54.0%) were male (Table 1). People in the IFG group and DM group were older (45.9 years vs. 50.9 years vs. 58.6 years, P<0.001) and had higher prevalence of male sex (50.2% vs. 62.3% vs. 61.2%, P<0.001), hypertension (19.8% vs. 34.7% vs. 62.8%, P<0.001), and dyslipidemia (15.3% vs. 24.2% vs. 46.6%, P<0.001). The prevalence of chronic kidney disease was significantly higher in the DM group (2.7% vs. 4.2% vs. 10.3%, P<0.001). People in the IFG and DM group also showed higher SBP (119.8 mm Hg vs. 125.5 mm Hg vs. 128.4 mm Hg, P<0.001), DBP (75.0 mm Hg vs. 78.4 mm Hg vs. 78.6 mm Hg, P<0.001), and fasting blood glucose level (88.2 mg/dL vs. 107.5 mg/dL vs. 140.7 mg/dL, P<0.001).

Hypertension and diabetes mellitus

In the whole cohort, SCA occurred in 21,462 (0.47%) individuals during clinical follow-up (mean 9.19±1.07 years). The incidence of SCA was highest in the DM group (1.34%), followed by IFG group (0.51%), and non-DM group (0.32%) (Table 1). In the non-adjusted analysis, IFG and DM was associated with 1.6-fold (HR, 1.616; 95% CI, 1.563 to 1.670; P<0.001) (Table 2) and 4.4-fold (HR, 4.356; 95% CI, 4.220 to 4.496; P<0.001) increased risk of SCA, respectively. After adjustment of covariates (sex, age, income, BMI, smoking, drinking, regular exercise, hypertension, dyslipidemia, chronic kidney disease), DM was associated with a 1.7-fold increased risk of SCA (adjusted HR, 1.696; 95% CI, 1.639 to 1.755; P<0.001) (Table 2).

As SBP increased from <100 to ≥160 mm Hg, the incidence of SCA gradually increased (Table 2, Fig. 2). Such association was also observed for DBP and pulse pressure, and this trend was consistent across each age category except for the youngest age group (20 to 29 years). In the 20 to 29 years group, those with SBP lower 100 mm Hg showed a higher incidence of SCA compared to those who had 100≤ SBP <120, and same trend was observed for DBP and pulse pressure (Table 2, Fig. 2, and Supplementary Table 2).

Interactions

We evaluated the interaction between blood pressure and DM on SCA risk. We observed significant interactions between DM and both SBP and DBP (P value for interaction was 0.005 for SBP and 0.002 for DBP) (Fig. 3, Supplementary Table 3, and Supplementary Fig. 1), and these interactions were consistent in the competing risk analysis. In the non-diabetes group, the risk of SCA increased gradually as SBP increased. However, such linear association was less prominent in the IFG and DM group. In the DM group, SBP lower than 100 mm Hg was associated with a statistically significant increase in SCA risk compared to those who had 100≤ SBP <120 (adjusted HR, 0.74; 95% CI, 0.60 to 0.90) and 120≤ SBP <140 (adjusted HR, 0.75; 95% CI, 0.62 to 0.91). Therefore, the association between SBP and SCA was more likely a J-type rather than a linear association and was consistent in the competing risk analysis. DBP also showed a significant interaction with non-DM patients having more linear type association compared with the IFG or DM group. However, no such interaction was observed between pulse pressure and DM.

DISCUSSION

On top of previous study that established hypertension and diabetes as significant risk factors for SCA, both individually and combined, the current study adds several novel findings [6]. We demonstrated a statistically significant interaction between blood pressure and DM on a population-level, revealing that the magnitude of impact of blood pressure on SCA risk varies depending on the presence of DM with stronger association found in non-diabetic people. Although people with both high blood pressure and DM were at highest risk of SCA, the degree of association between blood pressure and SCA was more prominent in non-diabetic people. Observation of increased risk of SCA in diabetic people with not only high but also low SBP is another important finding of this study (Fig. 4).

The main strong point of this study is the lack of detection failure of SCA originating from follow-up losses although under- or over-detection by our coding strategy of SCA definition can exist. Large sample size of our cohort enabled analysis of SCA in specific subgroups stratified by age, diabetic stage, and blood pressure categories. Availability of measured medical data such as body weight status and self-questionnaire data including alcohol and smoking status is another advantage of this study.

Interaction between blood pressure and diabetes mellitus

Both hypertension and DM are known risk factors of SCA [6]. However, their interaction with each other is not fully determined. According to our analysis, significant interactions existed between blood pressure and DM, but it was not synergistic: impact of blood pressure on SCA was stronger in the non-DM group. However, it is important to interpret this finding carefully. The statistical interaction observed in this study indicates that increase in SCA risk per unit increase in blood pressure is more pronounced in non-diabetic individuals. However, this does not diminish the clinical importance of hypertension in diabetic patients. In fact, our data clearly shows that the highest absolute risk of SCA occurred in patients with both diabetes and high blood pressure. The novelty of our study lies in clarifying the nature of this interaction: the association between SBP and SCA risk showed a linear trend in non-diabetics and a J-shaped curve in those with DM. This J-shaped association, particularly the finding that low SBP is associated with a significantly increased risk of SCA only in the diabetic population, has important clinical implications.

The underlying mechanism for such interaction can be due to the susceptibility of diabetic patients to hypotension. Compared with diabetic people who maintained SBP between 100 and 120 mm Hg, those who showed over or equal to 160 mm Hg had significantly higher risk of SCA. However, diabetic people who had SBP below 100 mm Hg also demonstrated a significantly higher risk of SCA which was the main difference compared with non-diabetic population. Susceptibility of diabetic patients to low blood pressure can be the driver of interaction between blood pressure and DM.

Low blood pressure in diabetes mellitus

Maintenance of adequate blood pressure via autonomic nervous system is a critical part of our circulation system. However, such mechanism might not work appropriately in people with DM since autonomic neuropathy is a common complication which can happen in about 20% of diabetic patients [20]. Prior reports suggest that presence of cardiovascular autonomic neuropathy was associated with 5-fold increased risk of 5-year mortality in diabetic patients [21]. In diabetic patients with underlying cardiovascular autonomic neuropathy, elevation of blood pressure by physiologic demand can be limited and lead to orthostatic hypotension which is associated with adverse clinical outcomes [8,9,22]. Underlying low SBP (less than 100 mm Hg in this study) can further aggravate hypotensive events in patients with diabetes and cardiovascular autonomic neuropathy.

While we have highlighted autonomic neuropathy as a key mechanism explaining the vulnerability to low blood pressure, the elevated burden of atherosclerotic cardiovascular disease (ASCVD) in diabetic patients is a primary driver of SCA risk [23]. Our findings suggest that these two pathways, atherosclerosis and autonomic dysfunction, may work synergistically. For instance, an acute ischemic event due to underlying ASCVD can lower blood pressure or trigger a fatal arrhythmia [23,24]. In a diabetic patient with concurrent autonomic neuropathy, the physiological ability to maintain adequate blood pressure during such ischemic stress may be severely compromised, leading to hemodynamic collapse and subsequent SCA [8,20]. Therefore, underlying autonomic neuropathy and ASCVD might explain the susceptibility of diabetic people to low SBP in our study.

Limitations

This study has several limitations. First, coding errors can exist. However, our coding strategies to identify various medical conditions including SCA using ICD-10 codes are validated in our prior studies [5,6,10-12]. Second, our study cohort is exclusively consisted with East Asians, which may limit the generalizability of our findings to other populations. Ethnic differences might exist in prevalence and incidence of underlying etiologies of SCA including hypertension and DM [2]. For example, the prevalence and incidence of DM in South Koreans are lower than western populations, but is catching-up rapidly [25]. Furthermore, the prevalence and clinical impact of diabetic autonomic neuropathy can also vary across diverse ethnic groups [20]. Therefore, further study in diverse populations is needed to establish the generalizability of the result of this paper. Third, we could not adjust the influence of statins, sodium-glucose cotransporter-2 (SGLT2) inhibitors, or glucagon-like peptide-1 (GLP-1) receptor agonists since our database used for this analysis does not contain detailed information on prescriptions of these drugs. Fourth, there is no uniform protocol for blood pressure measurement because the blood pressure data was obtained from a nationwide health screening program conducted throughout the entire nation. However, only licensed healthcare facilities by Ministry of Health and Welfare can participate in nationwide healthcare screening program. Therefore, we assume that the quality of blood pressure data is appropriate for clinical research.

Conclusion

The association between blood pressure and SCA was pronounced in non-diabetic patients and diminished in diabetic people. High SBP and DBP was associated with SCA irrespective of the presence of DM. Low SBP was associated with a significantly higher risk of SCA in diabetic patients but not in non-diabetics. Avoiding both low and high blood pressure can be important to prevent SCA in people with DM.

SUPPLEMENTARY MATERIALS

NOTES

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Conception or design: Y.G.K., K.D.H., J.I.C.

Acquisition, analysis, or interpretation of data: all authors.

Drafting the work or revising: Y.G.K., H.S.L., K.D.H., J.I.C.

Final approval of the manuscript: all authors.

FUNDING

This work was supported by a Korea University grant (Jong-Il Choi) and a grant from Korea University Anam Hospital, Seoul, Republic of Korea (Jong-Il Choi) and Korean Heart Rhythm Society (KHRS 2025-3, Yun Gi Kim). The funders had no role in data collection, analysis, or interpretation; trial design; patient recruitment; or any other aspect pertinent to the study.

ACKNOWLEDGMENTS

None

Fig. 1.

Flowsheet of the study. DM, diabetes mellitus; IFG, impaired fasting glucose; SCA, sudden cardiac arrest.

Fig. 2.

Cumulative incidence of sudden cardiac arrest according to blood pressure. (A) Systolic blood pressure, (B) diastolic blood pressure, and (C) pulse pressure (difference between systolic and diastolic blood pressure).

Fig. 3.

Risk of sudden cardiac arrest stratified by blood pressure and diabetic stage. Significant interactions between diabetes status and both systolic (A) and diastolic (B) blood pressure were observed. However, no interaction was observed for (C) pulse pressure. Diabetic patients were especially susceptible to low systolic blood pressure (A). Hazard ratios were adjusted for age, sex, income, body mass index, smoking, drinking, regular exercise, dyslipidemia, chronic kidney disease, and medications for hypertension. IR, incidence per 1,000 person-year follow-up; aHR, adjusted hazard ratio; IFG, impaired fasting glucose; DM, diabetes mellitus.

Fig. 4.

Summary of the study. SCA, sudden cardiac arrest; DM, diabetes mellitus; IFG, impaired fasting glucose; HR, hazard ratio; SBP, systolic blood pressure.

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About this article

Kim YG, Lee HS, Seo CO, Kim Y, Jeong JH, Han KD, Shim J, Kim YH, Choi JI. Impact of Blood Pressure on Sudden Cardiac Arrest in Diabetic Patients. Diabetes Metab J. 2026 Mar 6. doi: 10.4093/dmj.2025.0339. Epub ahead of print.

Received: Apr 15, 2025; Accepted: Oct 07, 2025

DOI: https://doi.org/10.4093/dmj.2025.0339.

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