Skip to main content
Download PDF

Sex differences in outcomes in patients with acute myocardial infarction

BMC Cardiovascular Disorders volume 25, Article number: 272 (2025) Cite this article

Abstract

Objective

Gender is a vital factor for the development and treatment of cardiovascular diseases. This study aimed to evaluate sex-based differences in the prognosis of patients with acute myocardial infarction (AMI).

Methods

AMI patients who had been registered in the MIMIC III and IV database were enrolled. The primary study endpoint was 1-year all-cause mortality. The secondary study endpoints were in-hospital all-cause mortality, 28-day all-cause mortality, in-hospital complications of acute kidney injury (AKI) and ventricular arrhythmias (VA). Kaplan-Meier analysis was used to assess survival rate between the two groups. Cox proportional hazards regression and logistic regression analyses were performed to evaluate whether gender is an independent predictor of prognosis of AMI patients.

Results

A total of 4890 patients with AMI were included. At 1-year follow-up, 722 (22.5%) men died and 558 (33.2%) women died, and after analysis and adjustment, men had a 17.9% lower risk of all-cause mortality compared to women [Hazard Ratio (HR) = 0.821, 95% confidence interval (CI): 0.684–0.987]. Kaplan-Meier survival analysis showed a higher 1-year survival rate in the male group compared with the female group (HR = 0.532, 95% CI: 0.444–0.638, log-rank P < 0.0001). There was no significant difference in AKI during hospitalization. After adjusting for multivariable analysis, men with AMI had a 25% increased risk of hospitalization for VA compared to women [odds ratio (OR) = 1.250, 95% CI:1.030–1.518].

Conclusion

Women had a higher 1-year mortality but a lower risk of ventricular arrhythmias (VA) during AMI compared to men.

Clinical trial approval statement

This Trial was registered in the Chinese clinical trials registry: ChiCTR1800014583. Registered 22 January 2018 (http://www.chictr.org.cn/searchproj.aspx).

Peer Review reports

Introduction

Cardiovascular disease remains the most common cause of death globally, with the 2013 Global Burden of Disease study estimating that 17.3 million people died from cardiovascular disease worldwide. It accounts for 31.5% of all deaths. The report also noted that cardiovascular disease caused a higher proportion of deaths compared with 1990, when 12.3 million people died from cardiovascular disease, equivalent to 25.9% of all deaths [1]. As the most serious type of cardiovascular disease, acute coronary syndrome (ACS) has naturally become the focus of social research. As the population ages and women live longer, women will continue to account for a large proportion of patients with ACS [2, 3]. Available studies have reported gender difference in the frequency of occurrence of ACS and coronary artery disease, risk factors, severity of clinical symptoms, and benefit of early invasive strategies [4,5,6,7,8,9,10]. And most studies have focused on mortality or recurrent myocardial infarction or revascularization, but for gender differences leading to different clinical outcomes is usually not the focus of these reports on prognosis after myocardial infarction.

The aim of this study was to evaluate gender differences in the incidence of complications and prognosis in patients following acute myocardial infarction (AMI) through a retrospective analysis.

Materials and methods

Data source

Data for individuals experiencing AMI were sourced from the Medical Information Mart for Intensive Care (MIMIC)-III v1.4 and MIMIC-IV v1.0 databases. Beth Israel Deaconess Medical Center and MIT Institutional Review Boards granted approval for the use of the MIMIC database. After completing an online training course and ethics exam, we were granted access to the database (record IDs: 44703031 and 44703032) [11]. Since all patient data in the MIMIC database are anonymized, informed consent was not necessary [12].

At the same time, this research received approval from the institutional ethics committee of the Affiliated Changzhou No. 2 People’s Hospital, Nanjing Medical University (Ethics number: [2018]KY005-01). Informed consent was obtained from all patients participating in the study.

Patient enrollment and data collection

Data collection was carried out using SQL queries within the Navicat Premium software (version 15.0.12). Patients diagnosed with AMI were identified through International Classification of Diseases (ICD) codes. This study included all patients who had been admitted to the hospital for AMI. The exclusion criteria were: (1) patients under 18 years of age or over 90 years of age, and (2) patients with > 10% missing data. Patient data from both the MIMIC-IV and MIMIC-III databases were pooled for the final analysis.

After selecting the eligible subjects, clinical information was gathered, including demographic details, comorbid conditions, vital signs, laboratory test results, and follow-up data related to prognosis. Demographic data consisted of gender and age. Vital signs recorded include arterial systolic blood pressure (ASP), arterial diastolic blood pressure (ADP), mean arterial blood pressure (MAP), as well as body temperature. Common tests also considered were arterial partial pressure of oxygen (PaO2), partial pressure of carbon dioxide (PaCO2), and arterial oxygen saturation (SaO2). The comorbidities examined included atrial fibrillation (AF), diabetes mellitus (DM), hypertension, and chronic kidney disease. Laboratory results were initially obtained upon patient admission and included parameters such as red blood cells (RBC), white blood cells (WBC), platelets, hemoglobin, hematocrit, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), albumin, aspartate aminotransferase (ALT), alanine aminotransferase (AST), total bilirubin (TB), glucose, blood urea nitrogen (BUN), creatinine, creatine kinase MB isoenzyme (CK-MB), lactate, troponin T (TNT), anion gap (AG), bicarbonate, potassium, sodium, chloride, total calcium, magnesium, activated partial thromboplastin time (APTT), prothrombin time (PT), and international normalized ratio (INR).

Study endpoint

Long-term prognosis of AMI, specifically 1-year all-cause mortality, was the primary outcome of this study. Secondary endpoints included the short-term prognosis of AMI, which encompassed the incidence of acute kidney injury (AKI) following AMI, the occurrence of ventricular arrhythmias (VA), in-hospital all-cause mortality, and 28-day post-discharge all-cause mortality. Survival data from the database were used to obtain all follow-up outcomes [13].

The diagnosis of AKI was based on the most recent International AKI Clinical Practice Guidelines [14]. The diagnostic criteria for AKI were referred to our previous study [11]. A diagnosis of AKI was established by three criteria: (a) creatinine elevation ≥ 0.3 mg/dl (≥ 26.5 µmol/l) within 48 h; (b) a known or presumed more than 1.5 times increase in creatinine compared to the baseline within previous 7 days; and (c) a urinary output of < 0.5 ml/kg/h over a period of 6 h. Patients with chronic kidney disease stage 5 were excluded from the AKI diagnosis, even if they met these criteria. Ventricular arrhythmias (VA), including ventricular tachycardia, ventricular flutter, and ventricular fibrillation, were identified using the corresponding ICD codes, with cases linked to the same hospitalization number as the AMI patients.

In-hospital death was defined as death occurring on the same day as discharge or within 12 h following discharge. For patients who survived more than 12 h but less than or equal to 28 days post-discharge, their data were included in the analysis of 28-day all-cause mortality. Those who were followed for more than 12 h but less than or equal to 365 days after discharge were included in the 1-year all-cause mortality analysis.

Statistical analyses

To enhance statistical power and reduce bias caused by removing missing data, multiple imputation methods were applied to fill in the gaps. Categorical variables were expressed as frequencies and percentages, and differences between groups were assessed using the chi-square test or Fisher’s exact test, as appropriate. Continuous variables were presented as either the mean ± standard deviation or the median with interquartile range (IQR), and comparisons between groups were made using either Student’s t-test or the Mann-Whitney U test, depending on the distribution of the data.

A survival analysis was conducted by stratifying patients based on gender, and cumulative survival curves were created as event-time plots using the Kaplan-Meier method. The differences between these curves were then evaluated using log-rank tests. Univariable and adjusted multivariable analyses for endpoint events with time-dependent variables were carried out using Cox proportional hazards regression models. These models were implemented using the ‘surv’ function of the R package ‘survival. Additionally, logistic regression was employed to examine the effect of gender on secondary outcomes, with multivariable adjustments performed using the ‘glm’ function from the ‘glmnet’ package.

Statistical analyses were conducted using R software (version 4.1.2), while GraphPad Prism (version 8.3.0) was utilized to generate figures. A P-value of less than 0.05 was considered to indicate statistical significance.

Results

Patient characteristics

Following the application of the inclusion and exclusion criteria, 1,900 and 2,990 cases, amounting to a total of 4,890 patients with AMI, were extracted from the MIMIC-III and MIMIC-IV databases, respectively (Fig. 1). There were 1679 (34.3%) female patients and 3211 (65.7%) cases that were male. Women were significantly older than men. ADP and MAP were lower on admission, and ASP, temperature, and SaO2 were not significantly different; PaO2 and PaCO2 were the same, but the distribution of the data for both remained different. In laboratory tests, RBC, hemoglobin, Hematocrit, MCH, MCHC, albumin, ALT, AST, TB, creatinine, CK-MB, troponin-T, bicarbonate, potassium, and magnesium were lower and platelets, MCV, glucose, and anion gap were higher in women. Comorbidities were higher only in women with type2 Diabetes Mellitus, but not statistically significant in others (Table 1).

Fig. 1
figure 1

Flow diagram of the selection process of patients. Patient selection, exclusion criteria and setting of study endpoints

Full size image
Table 1 Baseline characteristics
Full size table

Outcomes

Sex differences and clinical outcomes

A total of 4890 patients entered the final analysis, of which 749 (15.3%) experienced in-hospital death (women, 18.3%, versus men, 13.8%, P < 0.001). The remaining 4141 patients were followed after discharge, a cumulative 147 deaths occurring by day 28 post-discharge (women, 4.9%, vs. men, 2.9%, P = 0.001); a cumulative total of 1280 deaths (women, 33.2%, vs. men,22.5%, P < 0.001) were followed up by day 365 post-discharge. The incidence of AKI was observed in 1373 patients (28%) during the course of their hospitalization, with a slightly higher prevalence among women (28.8%) compared to men (27.7%). However, this difference was not statistically significant (P = 0.458). Conversely, the incidence of VA was observed in 748 patients (15.3%), with a higher prevalence among men (16.9%) compared to women (12.3%). This difference was statistically significant (P < 0.001, Table 2).

Table 2 Clinical outcomes
Full size table

Primary endpoint

The median number of days of follow-up was 365 days (interquartile range: 188–365 days). KM survival analysis demonstrated that the one-year survival rate was higher in the male group of patients with AMI compared to the female group (log-rank P < 0.0001, Fig. 2). The results remained consistent regardless of the combination of atrial fibrillation, hypertension, chronic kidney injury, and diabetes. The male group exhibited a higher one-year survival rate. (Figures 2 and 3). In light of the presence or absence of comorbid AKI and VA, the results remained consistent, with a higher one-year survival rate observed in male subjects compared to female subjects (Supplementary Fig. 1).

Fig. 2
figure 2

Cumulative survival risk plot stratified by gender, with all lines having the same meaning as the labels in (A). Survival plots for males versus females in all patients (A); all patients with atrial fibrillation (B); all patients without atrial fibrillation (C); all patients with hypertension (D); and all patients without hypertension (E)

Full size image
Fig. 3
figure 3

Cumulative survival risk plot stratified by gender, with all lines having the same meaning as the labels in (A). All patients with chronic kidney disease (A); all patients with non-chronic kidney disease (B); all patients with type 2 diabetes mellitus (C); all patients with non-type 2 diabetes mellitus (D)

Full size image

A Cox proportional hazards model was employed to evaluate the impact of gender disparities on the risk of all-cause mortality within one year following hospital discharge among patients with AMI. Additionally, five modifications of the risk model were developed. In Model 1, the one-year risk of all-cause mortality was reduced by 46.8% (HR = 0.532, 95% CI: 0.449–0.631) in men with AMI compared with women. Model 2 adjusted for the effect of age on top of Model l. Model 3 adjusted for the effect of variables with P < 0.05 in vital signs basis on Model 2. Model 4 adjusted for the effect of variables with P < 0.05 in laboratory tests basis on Model 3; Model 5 adjusted for the effect of variables with P < 0.05 in comorbid disease-related characteristics basis on Model 4. The results showed that male AMI patients had a higher 1-year survival rate compared with female patients (Table 3).

Table 3 Univariable and multifactorial Cox proportional risk analysis of sex and 1-year all-cause mortality in the AMI cohort
Full size table

Secondary endpoints

The effect of sex differences on the risk of in-hospital all-cause mortality in patients with AMI was assessed using logistic regression models. All variables in Table 1 were subjected to factor regression analysis, and all variables with P < 0.05 were included in the multivariable regression analysis. Adjusted by multifactorial regression analysis, the risk of in-hospital all-cause death was reduced by 5.6% in male patients compared with female patients (ORadjusted =0.944, 95% CI: 0.771–1.156), but the difference was not statistically significant. Univariable and multifactorial regression results are presented in Supplementary Table 1.

Cox proportional hazard models were employed to evaluate the influence of gender disparities on the probability of all-cause mortality within 28 days of hospital discharge among patients with AMI. After correction for multifactorial regression analysis, the risk of in-hospital all-cause death was reduced by 3.2% in male patients compared with female patients (HR = 0.968, 95% CI: 0.682–1.373), but the difference is not significant. Univariable and multifactorial regression results are presented in Supplementary Table 2.

KM survival analysis revealed a higher 28-day survival rate in the male group of AMI patients compared to the female group (log-rank P = 0.0011, Supplementary Fig. 2). The 28-day survival rate was higher in men compared to women, regardless of the presence of combined AF. Among those without comorbid hypertension, chronic kidney injury, and diabetes, 28-day survival was higher in men compared with women, with a statistically significant difference. In patients with combined hypertension, chronic kidney injury and diabetes, there was no statistically significant difference in 28-day survival between men and women. In patients with AMI without comorbid AKI and VA, 28-day survival was significantly higher in men than in women; in patients with these complications, the difference in survival between men and women was not significant. (Supplementary Figs. 2, 3, 4).

The effect of sex differences on the risk of developing AKI in patients with AMI was assessed using logistic regression models. After correction for multifactorial regression analysis, male patients had a 14.4% increased risk of concurrent AKI compared with female patients (ORadjusted = 1.144, 95% CI: 0.987–1.324), but the difference is not significant. The results of univariable and multifactorial regression are shown in Supplementary Table 3.

Logistic regression analysis with 5 risk model modifications was performed to assess the relationship between gender differences in the risk of concomitant VA after AMI. Model 1 was a univariable analysis of gender, and male patients had a 45.2% (OR = 1.452, 95% CI:1.222–1.726, P < 0.001) increased risk of concurrent VA compared with female patients. Model 2 was adjusted for age. Male patients had a 35.8% (ORadjusted = 1.358, 95% CI:1.139–1.618, P = 0.001) increased risk of concurrent VA compared with female patients. Model 3 was based on Model 2 after adjusting for variables at P < 0.05 in vital signs in Table 1. Male patients had a 33.8% (ORadjusted = 1.338, 95% CI:1.120–1.597, P = 0.001) increased risk of concurrent VA compared to female patients. Model 4 was corrected for variables with P < 0.05 in the laboratory indicators in Table 1 basis on Model 3. Male patients had a 23.8% (ORadjusted =1.238, 95% CI:1.020–1.502, P = 0.031) increased risk of concurrent VA compared with female patients. Model 5 was adjusted for variables with P < 0.05 in Table 1 for comorbid diseases basis on Model 4. Male patients had a 25% (ORadjusted =1.250, 95% CI:1.030–1.518, P = 0.024) increased risk of comorbid VA compared with female. Additionally, logistic univariate regression analysis was conducted for all statistical variables, and those exhibiting significantly disparate results (P < 0.05) were incorporated into logistic multivariable regression analysis (Supplementary Table 4). Male patients had a 25% increased risk of complicating VA after AMI compared with female patients (ORadjusted=1.250, 95% CI: 1.030–1.518, Table 4).

Table 4 Univariable and multifactor Cox proportional risk analysis of gender and complicated ventricular arrhythmias during hospitalization in the AMI cohort
Full size table

Subgroup analysis

Subgroup analysis was performed by age, AF, hypertension, DM, AKI, CKD, and VA. The relationship between gender differences and the risk of 1-year all-cause mortality in each subgroup of AMI patients was further investigated, and the forest plot of the subgroup analysis showed that there was no gender difference in 1-year all-cause mortality only in those aged greater than or equal to 75 years or older, and in the other subgroups, the risk of 1-year all-cause mortality was significantly lower in men than in women (Fig. 4).

Fig. 4
figure 4

Subgroup analysis forest plots. Hazard Ratio (HR) and 95% confidence interval for 1-year all-cause mortality in male patients

Full size image

External validation cohort

A total of 922 patients with AMI were included from the medical records of the Affiliated Changzhou No.2 people’s Hospital of Nanjing Medical University. Among them, 659 (71.5%) were male patients and 263 (28.5%) were female patients. At a median follow-up time of 33 days (interquartile range: 30 to 35 days), KM survival analysis showed that AMI patients in the male group had a higher survival rate compared to the female group (log-rank P = 0.0002, HR = 0.3872, 95% CI: 0.2160 ~ 0.6943 (Supplementary Fig. 5).

Discussion

This is a larger study providing detailed data on the immediate prognosis and long-term survival in AMI. Three key findings were identified. First, our findings showed that women had a lower proportion of the 4890 patients with AMI, were older, and had a higher rate of comorbid diabetes. Second, in terms of near-term prognosis, women had higher rates of in-hospital all-cause mortality and 28-day post-discharge all-cause mortality, both of which were statistically significant, but none of the differences existed after multivariable analysis; they had similar rates of AKI; and they had lower rates of VA, and the differences were confirmed by multivariable analysis. Third, in terms of long-term survival, women had a higher 1-year all-cause mortality rate, and multivariable analysis confirmed the difference.

The dramatic increase in AMI mortality has been reported to be mainly attributed to an aging population [15] but there are gender differences in baseline characteristics of patients with AMI, with a lower incidence of myocardial infarction in women compared to men [16]. At the same time, diabetes was associated with excess cardiovascular morbidity and mortality in all age groups [17, 18]. This also explains one of the reasons for the worse prognosis of female patients with AMI compared to males in this study.

In-hospital all-cause mortality in this study was 18.3% in females and 13.8% in males. Previous ACS-related studies had 480 [192 (16%) females versus 288 males (9%)] deaths during hospitalization out of 4347 patients included [19], very similar to the results of the present study. 28-day all-cause mortality was 4.9% in women and 2.9% in men. Several studies have shown that [20,21,22] higher short-term mortality in women is explained by older age or a higher incidence of comorbidities. At the same time, several studies suggest that diabetes may play a key role in the mortality differential in women [21, 23]. A prospective study noted that women with AMI admitted to the CCU performed significantly worse than men at 30 days [24]. Other investigators have noted that despite high risk factors and mortality, women use coronary angiography and angioplasty less frequently and have a higher 3-year adjusted mortality rate by age 70 years [25, 26]. On the one hand, this suggests that we give more attention to women in the secondary prevention phase; on the other hand, this suggests that whether increasing the rate of coronary interventions in women after AMI will improve the short-term survival of female patients, and further prospective studies are expected to confirm it.

The incidence of AKI after AMI in this study was 28%, and previous studies have reported an incidence of AKI after AMI of about 5–31% [27, 28]. An analysis of risk factors for AKI in patients with AMI noted that 292 (26.0%) of 1124 hospitalized patients developed AKI during hospitalization. in parallel, a regression model was created in which age, hypertension, chronic kidney disease (CKD), Killip ≥ 3 grade, LVEF, use of furosemide with and without, and ACEI/ARB were considered as risk factors associated with AKI in patients with AMI [29]. In this study, univariable analysis was used to assess the relationship between gender and the incidence of AKI, although the difference was not statistically significant. The factor of gender was still included in the multifactorial analysis and the final result was P = 0.07, a critical positive.

The incidence of VA in this study was 12.3% in women and 16.9% in men. Women have a more different pathophysiological basis for acute coronary syndrome events compared to men. In addition, cardiovascular risk factors are differentially affected in women, with some risk factors being more common in women than in men. Well-known susceptibility factors such as male, advanced age, hypertension, smoking, obesity, and lipid metabolism disorders are also predisposing factors for sudden cardiac death. This difference in pathophysiology and baseline risk factors has led to the observed differences in outcomes between women and men [30, 31]. The increased likelihood of VA in AMI patients is associated with blood perfusion [32]. From a physiological point of view, the acute ischemia caused by complete and abrupt interruption of coronary blood flow in AMI patients has deleterious effects on myocardial cell function, leading to anaerobic metabolism and subsequent electrical instability that promotes VA [33]. Our multivariable analysis found a small percentage of women among patients who developed VA during infarction similar previous reports, making women a protective factor for the development of such VA.

Although women have a lower risk of VA in the acute phase, their higher 1-year mortality rate suggests that female AMI patients may require more aggressive treatment measures in terms of reperfusion strategies, complication management, and long-term follow-up with secondary prevention. Future studies should validate this idea through multicenter, prospective, randomized controlled clinical data, rigorous statistical analyses, and provide a basis for the development of more gender-specific treatment protocols.

The 1-year all-cause mortality rate in AMI patients in this study was 33.2% in women and 22.5% in men. Few studies have investigated the gender-age effect on long-term mortality after initial AMI hospitalization. This study found a higher risk of death in women than in men among those younger than 75 years; there was no statistical difference among those 75 and older. Two studies observed a higher risk of death in women younger than 60 years or only in those younger than 50 years [21, 34], which is roughly the same as our findings. A previous study assessing age-related functional impairment found a higher prevalence of items such as cognitive impairment, reduced functional mobility, and limitations in activities of daily living in women compared to men [35]. Although substantial progress has been made in improving gender-specific acute coronary syndrome disease management and outcomes, reports suggest that knowledge gaps remain in the optimal risk stratification and management of women with acute coronary syndrome. Significant delays in female AMI patients and systems are due to limited awareness of the potential cardiovascular disease risk in women, the lack of gender-specific thresholds in clinical guidelines, and the subsequent limited performance of modern diagnostic methods in women [36], so these may also account for the differential long-term mortality due to gender differences.

Limitations

There are several limitations to this analysis. First, this study is an observational study based on a single-center database. Despite the very high quality of the database, observational studies are subject to confounding by patient and clinician treatment preferences. For example, during the analysis, the investigators were unable to classify all subjects into STEMI and NSTEMI cohorts based on the ICD codes in the database, yet grouping in this manner exists in several Randomized clinical trials studies, and this warrants further study. Second, the follow-up period in this study was short and did not consider the incidence of heart failure after AMI and the rate of rehospitalization for heart failure, and a large, multicenter, prospective study is needed to validate, supplement, and refine the results of this study.

Conclusions

Women had a higher 1-year mortality but a lower risk of ventricular arrhythmias (VA) during AMI compared to men.

Data availability

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://physionet.org/content/mimiciii-demo/1.4/ and https://physionet.org/content/mimiciv/2.2/.

References

  1. Global regional. National age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the global burden of disease study 2013. Lancet. 2015;385:117–71.

    Article  Google Scholar 

  2. Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Borden WB, Bravata DM, Dai S, Ford ES, Fox CS, Franco S, Fullerton HJ, Gillespie C, Hailpern SM, Heit JA, Howard VJ, Huffman MD, Kissela BM, Kittner SJ, Lackland DT, Lichtman JH, Lisabeth LD, Magid D, Marcus GM, Marelli A, Matchar DB, McGuire DK, Mohler ER, Moy CS, Mussolino ME, Nichol G, Paynter NP, Schreiner PJ, Sorlie PD, Stein J, Turan TN, Virani SS, Wong ND, Woo D, Turner MB. Heart disease and stroke statistics–2013 update: a report from the American heart association. Circulation. 2013;127:e6–245.

    PubMed  Google Scholar 

  3. Roe MT, Parsons LS, Pollack CV Jr., Canto JG, Barron HV, Every NR, Rogers WJ, Peterson ED. Quality of care by classification of myocardial infarction: treatment patterns for ST-segment elevation vs non-ST-segment elevation myocardial infarction. Arch Intern Med. 2005;165:1630–6.

    Article  PubMed  Google Scholar 

  4. Araújo C, Laszczyńska O, Viana M, Melão F, Henriques A, Borges A, Severo M, Maciel MJ, Moreira I, Azevedo A. Sex differences in presenting symptoms of acute coronary syndrome: the epiheart cohort study. BMJ Open. 2018;8:e018798.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Appelman Y, van Rijn BB, Ten Haaf ME, Boersma E, Peters SA. Sex differences in cardiovascular risk factors and disease prevention. Atherosclerosis. 2015;241:211–8.

    Article  CAS  PubMed  Google Scholar 

  6. Lagerqvist B, Säfström K, Ståhle E, Wallentin L, Swahn E. Is early invasive treatment of unstable coronary artery disease equally effective for both women and men? FRISC II study group investigators. J Am Coll Cardiol. 2001;38:41–8.

    Article  CAS  PubMed  Google Scholar 

  7. Alabas OA, Gale CP, Hall M, Rutherford MJ, Szummer K, Lawesson SS, Alfredsson J, Lindahl B, Jernberg T. Sex differences in treatments, relative survival, and excess mortality following acute myocardial infarction: National cohort study using the SWEDEHEART registry. J Am Heart Assoc. 2017;6.

  8. Bucholz EM, Butala NM, Rathore SS, Dreyer RP, Lansky AJ, Krumholz HM. Sex differences in long-term mortality after myocardial infarction: a systematic review. Circulation. 2014;130:757–67.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Marijon E, Bougouin W, Périer MC, Celermajer DS, Jouven X. Incidence of sports-related sudden death in France by specific sports and sex. JAMA. 2013;310:642–3.

    Article  CAS  PubMed  Google Scholar 

  10. Nedbaeva D, Mikhaleva V, Kukharchik G. Adverse outcomes in Non-ST-Elevation acute coronary syndrome: A cluster analysis study. Cardiovasc Innovations Appl. 2024;9:938.

    Google Scholar 

  11. Cai D, Xiao T, Zou A, Mao L, Chi B, Wang Y, Wang Q, Ji Y, Sun L. Predicting acute kidney injury risk in acute myocardial infarction patients: an artificial intelligence model using medical information Mart for intensive care databases. Front Cardiovasc Med. 2022;9:964894.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Han YQ, Yan L, Zhang L, Ouyang PH, Li P, Goyal H, Hu ZD. Red blood cell distribution width provides additional prognostic value beyond severity scores in adult critical illness. Clin Chim Acta. 2019;498:62–7.

    Article  CAS  PubMed  Google Scholar 

  13. Johnson AE, Pollard TJ, Shen L, Lehman LW, Feng M, Ghassemi M, Moody B, Szolovits P, Celi LA, Mark RG. MIMIC-III, a freely accessible critical care database. Sci Data. 2016;3:160035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kellum JA, Lameire N. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1). Crit Care. 2013;17:204.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Chang J, Liu X, Sun Y. Mortality due to acute myocardial infarction in China from 1987 to 2014: secular trends and age-period-cohort effects. Int J Cardiol. 2017;227:229–38.

    Article  PubMed  Google Scholar 

  16. Alkhouli M, Alqahtani F, Jneid H, Al Hajji M, Boubas W, Lerman A. Age-Stratified Sex-Related differences in the incidence, management, and outcomes of acute myocardial infarction. Mayo Clin Proc. 2021;96:332–41.

    Article  PubMed  Google Scholar 

  17. Zhao M, Song L, Sun L, Wang M, Wang C, Yao S, Li Y, Yun C, Zhang S, Sun Y, Hou Z, Wu S, Xue H. Associations of type 2 diabetes onset age with cardiovascular disease and mortality: the Kailuan study. Diabetes Care. 2021;44:1426–32.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wu S, Song Y, Chen S, Zheng M, Ma Y, Cui L, Jonas JB. Blood pressure classification of 2017 associated with cardiovascular disease and mortality in young Chinese adults. Hypertension. 2020;76:251–8.

    Article  CAS  PubMed  Google Scholar 

  19. Simon T, Mary-Krause M, Cambou JP, Hanania G, Guéret P, Lablanche JM, Blanchard D, Genès N, Danchin N. Impact of age and gender on in-hospital and late mortality after acute myocardial infarction: increased early risk in younger women: results from the French nation-wide USIC registries. Eur Heart J. 2006;27:1282–8.

    Article  PubMed  Google Scholar 

  20. Nicolau JC, Auxiliadora Ferraz M, Nogueira PR, Coimbra Garzon SA, Serrano CV Jr., Ramires JA. The role of gender in the long-term prognosis of patients with myocardial infarction submitted to fibrinolytic treatment. Ann Epidemiol. 2004;14:17–23.

    Article  PubMed  Google Scholar 

  21. Rosengren A, Spetz CL, Köster M, Hammar N, Alfredsson L, Rosén M. Sex differences in survival after myocardial infarction in Sweden; data from the Swedish National acute myocardial infarction register. Eur Heart J. 2001;22:314–22.

    Article  CAS  PubMed  Google Scholar 

  22. Heer T, Schiele R, Schneider S, Gitt AK, Wienbergen H, Gottwik M, Gieseler U, Voigtländer T, Hauptmann KE, Wagner S, Senges J. Gender differences in acute myocardial infarction in the era of reperfusion (the MITRA registry). Am J Cardiol. 2002;89:511–7.

    Article  PubMed  Google Scholar 

  23. Abbott RD, Donahue RP, Kannel WB, Wilson PW. The impact of diabetes on survival following myocardial infarction in men vs women. Framingham Study Jama. 1988;260:3456–60.

    CAS  PubMed  Google Scholar 

  24. Gottlieb S, Harpaz D, Shotan A, Boyko V, Leor J, Cohen M, Mandelzweig L, Mazouz B, Stern S, Behar S. Sex differences in management and outcome after acute myocardial infarction in the 1990s: A prospective observational community-based study. Israeli Thrombolytic Surv Group Circulation. 2000;102:2484–90.

    CAS  Google Scholar 

  25. Kostis JB, Wilson AC, O’Dowd K, Gregory P, Chelton S, Cosgrove NM, Chirala A, Cui T. Sex differences in the management and long-term outcome of acute myocardial infarction. A statewide study. MIDAS study group. Myocardial infarction data acquisition system. Circulation. 1994;90:1715–30.

    Article  CAS  PubMed  Google Scholar 

  26. Maynard C, Litwin PE, Martin JS, Weaver WD. Gender differences in the treatment and outcome of acute myocardial infarction. Results from the myocardial infarction triage and intervention registry. Arch Intern Med. 1992;152:972–6.

    Article  CAS  PubMed  Google Scholar 

  27. Shacham Y, Leshem-Rubinow E, Steinvil A, Assa EB, Keren G, Roth A, Arbel Y. Renal impairment according to acute kidney injury network criteria among ST elevation myocardial infarction patients undergoing primary percutaneous intervention: a retrospective observational study. Clin Res Cardiol. 2014;103:525–32.

    Article  PubMed  Google Scholar 

  28. Tsai TT, Patel UD, Chang TI, Kennedy KF, Masoudi FA, Matheny ME, Kosiborod M, Amin AP, Messenger JC, Rumsfeld JS, Spertus JA. Contemporary incidence, predictors, and outcomes of acute kidney injury in patients undergoing percutaneous coronary interventions: insights from the NCDR Cath-PCI registry. JACC Cardiovasc Interv. 2014;7:1–9.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Wang C, Pei YY, Ma YH, Ma XL, Liu ZW, Zhu JH, Li CS. Risk factors for acute kidney injury in patients with acute myocardial infarction. Chin Med J (Engl). 2019;132:1660–5.

    Article  CAS  PubMed  Google Scholar 

  30. Oknińska M, Mączewski M, Mackiewicz U. Ventricular arrhythmias in acute myocardial ischaemia-Focus on the ageing and sex. Ageing Res Rev. 2022;81:101722.

    Article  PubMed  Google Scholar 

  31. Pagidipati NJ, Peterson ED. Acute coronary syndromes in women and men. Nat Rev Cardiol. 2016;13:471–80.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Kalarus Z, Svendsen JH, Capodanno D, Dan GA, De Maria E, Gorenek B, Jędrzejczyk-Patej E, Mazurek M, Podolecki T, Sticherling C, Tfelt-Hansen J, Traykov V, Lip GYH, Fauchier L, Boriani G, Mansourati J, Blomström-Lundqvist C, Mairesse GH, Rubboli A, Deneke T, Dagres N, Steen T, Ahrens I, Kunadian V, Berti S. Cardiac arrhythmias in the emergency settings of acute coronary syndrome and revascularization: an European heart rhythm association (EHRA) consensus document, endorsed by the European association of percutaneous cardiovascular interventions (EAPCI), and European acute cardiovascular care association (ACCA). Europace. 2019;21:1603–4.

    Article  PubMed  Google Scholar 

  33. Mehta RH, Harjai KJ, Grines L, Stone GW, Boura J, Cox D, O’Neill W, Grines CL. Sustained ventricular tachycardia or fibrillation in the cardiac catheterization laboratory among patients receiving primary percutaneous coronary intervention: incidence, predictors, and outcomes. J Am Coll Cardiol. 2004;43:1765–72.

    Article  PubMed  Google Scholar 

  34. Vaccarino V, Krumholz HM, Yarzebski J, Gore JM, Goldberg RJ. Sex differences in 2-year mortality after hospital discharge for myocardial infarction. Ann Intern Med. 2001;134:173–81.

    Article  CAS  PubMed  Google Scholar 

  35. Nanna MG, Hajduk AM, Krumholz HM, Murphy TE, Dreyer RP, Alexander KP, Geda M, Tsang S, Welty FK, Safdar B, Lakshminarayan DK, Chaudhry SI, Dodson JA. Sex-Based differences in presentation, treatment, and complications among older adults hospitalized for acute myocardial infarction: the SILVER-AMI study. Circ Cardiovasc Qual Outcomes. 2019;12:e005691.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Haider A, Bengs S, Luu J, Osto E, Siller-Matula JM, Muka T, Gebhard C. Sex and gender in cardiovascular medicine: presentation and outcomes of acute coronary syndrome. Eur Heart J. 2020;41:1328–36.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Thanks to all authors for their contributions in this study.

Funding

This study was supported by grants from National Natural Science Foundation of China (Grant No.82270328), Changzhou High Level Medical Talents Training Project (2022CZBJ054), Natural Science Foundation of Jiangsu Province (BK20221229), Technology Development Fund of Nanjing Medical University (NMUB2020069), Major Research plan of Changzhou Health Commission of Jiangsu Province of China (ZD202215), Key Projects of Changzhou Medical Center affiliated to Nanjing Medical University (CMCM202306), Postgraduate Practice Innovation Program of Jiangsu Province (SJCX24_0748); Construction Project of High Level Hospital of Jiangsu Province (GSPJS202404); Nanjing Medical University Wuxi Medical Center “Young Talents Program” (WMCQ202403); Key Project of Jiangsu Provincial Health Commission (K2024014); and Nanjing Medical University Wuxi Medical Centre General Projects (WMCG202408).

Author information

Author notes

  1. Dabei Cai, Li Deng and Ye Deng contributed equally to this work.

Authors and Affiliations

  1. Department of Cardiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, 299# Qingyang Road, Wuxi, Jiangsu, 214001, China

    Dabei Cai & Ling Sun

  2. Institute of Cardiovascular Diseases, Jiangsu University, Zhenjiang, Jiangsu, 212000, China

    Dabei Cai

  3. Department of Cardiology, The Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, 29# Xinglong Alley, Changzhou, Jiangsu, 213000, China

    Li Deng, Ye Deng, Tingting Xiao, Qingqing Gu, Yu Wang, Qianwen Chen & Qingjie Wang

  4. Department of Cardiovascular Surgery, The Affiliated Hospital of Xuzhou Medical University, 99# Huaihai West Road, Xuzhou, 221000, China

    Yang Zhang & Jun Wei

Authors
  1. Dabei Cai
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Li Deng
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Ye Deng
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Yang Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Tingting Xiao
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Qingqing Gu
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Yu Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Qianwen Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Jun Wei
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Ling Sun
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Qingjie Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

DC, LD and YD analyzed the data and wrote the paper. YZ, TX, QG, YW and QC collect data. DC, LD, YD, QG, TX, QC, YW, YZ, JW, LS, QW checked the integrity of the data and the accuracy of the data analysis. JW, LS and QW co-designed and revised this article. All authors read and approved the final manuscript for publication.

Corresponding authors

Correspondence to Jun Wei, Ling Sun or Qingjie Wang.

Ethics declarations

Ethics approval and consent to participate

Research involving human participants was reviewed and approved by the Institutional Review Boards of Beth Israel Deaconess Medical Center and the Massachusetts Institute of Technology. The ethics committee waived the requirement for written informed consent for participation in the study. We completed an online course and ethics review and were granted access to the database (record IDs: 44703031 and 44703032). Personally identifiable information about the subjects was removed by the administrators of the MIMIC database. All studies complied with the tenets of the Declaration of Helsinki.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Supplementary Material 3

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cai, D., Deng, L., Deng, Y. et al. Sex differences in outcomes in patients with acute myocardial infarction. BMC Cardiovasc Disord 25, 272 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12872-025-04713-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12872-025-04713-9

Keywords

BMC Cardiovascular Disorders

ISSN: 1471-2261

Contact us