Development and Validation of a Risk Prediction Model for Atherosclerotic Cardiovascular Disease in Japanese Adults: The Hisayama Study

Separating Risk Prediction: Myocardial Infarction vs. Ischemic Stroke in 6.2M Screenings

BACKGROUND

Traditional cardiovascular disease risk prediction models generate a combined risk assessment for myocardial infarction (MI) and ischemic stroke (IS), which may inadequately reflect the distinct etiologies and disparate risk factors of MI and IS. We aim to develop prediction models that separately estimate the risks of MI and IS.

METHODS

Our analysis included 6,242,404 individuals over 40 years old who participated in a cardiovascular health screening examination in 2009. Potential predictors were selected based on a literature review and the available data. Cox proportional hazards models were used to construct 5-year risk prediction models for MI, and IS. Model performance was assessed through discrimination and calibration.

RESULTS

During a follow-up of 39,322,434.39 person-years, 89,140 individuals were diagnosed with MI and 116,259 with IS. Both models included age, sex, body mass index, smoking, alcohol consumption, physical activity, diabetes, hypertension, dyslipidemia, chronic kidney disease, and family history. Statin use was factored into the classification of dyslipidemia. The c-indices for the prediction models were 0.709 (0.707-0.712) for MI, and 0.770 (0.768-0.772) for IS. Age and hypertension exhibited a more pronounced effect on IS risk prediction than MI, whereas smoking, body mass index, dyslipidemia, and chronic kidney disease showed the opposite effect. The models calibrated well for low-risk individuals.

CONCLUSIONS

Our findings underscore the necessity of tailored risk assessments for MI and IS to facilitate the early detection and accurate identification of heterogeneous at-risk populations for atherosclerotic cardiovascular disease.

Association between time to treatment and outcome in branch retinal vein occlusion

PURPOSE

To investigate the association between the time from onset to initial treatment and changes in visual acuity or the number of treatments in patients with branch retinal vein occlusion (BVO).

DESIGN

Retrospective.

METHODS

Thirty-nine eyes of 39 consecutive patients with untreated acute-phase BVO who visited the University of Tokyo Hospital and were followed up for at least one year were included. The patients were initially treated with anti-vascular endothelial growth factor (VEGF) therapy and additional pro re nata therapy within six months of onset. The patients were classified according to the time from disease onset to the first treatment (group A: 28 days or less, group B: over 28 days).

RESULTS

The mean (SD) age was 73 ± 8 years, and 19 patients were male. The mean (SD) time to the first treatment was 31.6 ± 17.9 days. The mean (SD) logMAR visual acuity at first treatment was 0.37 ± 0.30. After 12 months of treatment, the mean (SD) logMAR change was - 0.15 ± 0.23, and the mean number (SD) of treatments was 3.1 ± 1.7. No significant association was observed between the timing of treatment initiation and changes in logMAR visual acuity. Patients in group A and central macular thickness at the initial visit were independently associated with the greater number of treatments at one year (p = 0.03 and p = 0.01, respectively).

CONCLUSIONS

At one year, the time between onset and the start of anti-VEGF therapy for BVO was not associated with subsequent visual acuity changes. Meanwhile, it may have significant association with the number of treatments.

Lifetime Risk of Incident Coronary Heart Disease, Stroke, and Cardiovascular Disease: The Japan Public Health Center-Based Prospective Study

AIM

The constellation of cardiovascular disease (CVD) risk factors greatly impacts the lifetime risk (LTR) of incident CVD, but the LTR has not been thoroughly evaluated in the Japanese population.

METHODS

We conducted a prospective study involving a total of 25,896 individuals 40-69 years old without a history of CVD in 1995 (Cohort I) and 1993-1994 (Cohort II) in Japan. CVD risk factors (blood pressure, non-high-density lipoprotein [HDL] cholesterol levels, smoking status, and glucose concentrations) were used to stratify them by risk. The sex-specific LTR of incident coronary heart disease, stroke, atherosclerotic CVD, and total CVD were estimated for participants 45 years old in the 4 risk categories with the cumulative incidence rate, adjusting for the competing risk of death.

RESULTS

We found apparent differences in the LTR of total CVD according to the risk stratification. Individuals with ≥ 2 of the risk factors of blood pressure ≥ 140/90 mmHg or treated, non-HDL cholesterol level ≥ 170 mg/dL or treated, current smoker, and diabetes had substantially higher adjusted LTRs of CVD than those in other groups, with a LTR of 26.5% (95% confidence interval, 24.0%-29.0%) for men and 15.3% (13.1%-17.5%) for women at 45 years. The LTR of incident stroke was the highest among CVDs, and the presence of hypertension and diabetes mellitus strongly influenced the LTR of total CVD.

CONCLUSION

The impact of risk accumulation on LTR of CVD was greater in men, and 1 in 4 men with ≥ 2 major risk factors at 45 years of age developed CVD in their lifetime.

A risk stratification model modified from the U.S. guideline could be applied in an Asian population with or without ASCVD: Validation study

BACKGROUND

This study aimed to evaluate the performance of a modified U.S. (MUS) model for risk prediction of cardiovascular (CV) events in Asian patients and compare it to European and Japanese models.

METHODS

The MUS model, based on the US ACC/AHA 2018 lipid treatment guideline, was employed to stratify patients under primary or secondary prevention. Two multi-center prospective observational registry cohorts, T-SPARCLE and T-PPARCLE, were used to validate the scoring system, and the primary outcome was the time to first occurrence/recurrence of major adverse cardiac events (MACEs). The MUS model's performance was compared to other models from Europe and Japan.

RESULTS

A total of 10,733 patients with the mean age of 64.2 (SD: 11.9) and 36.5% female were followed up for a median of 5.4 years. The MUS model was validated, with an AUC score of 0.73 (95% CI 0.68-0.78). The European and Japanese models had AUC scores ranging from 0.6 to 0.7. The MUS model categorized patients into four distinct CV risk groups, with hazard ratios (HRs) as follows: very high- vs. high-risk group (HR = 1.91, 95% CI 1.53-2.39), high- vs. moderate-risk group (HR = 2.08, 95% CI 1.60-2.69), and moderate- vs. low-risk group (HR = 3.14, 95% CI 1.63-6.03). After adjusting for the MUS model, a history of atherosclerotic vascular disease (ASCVD) was not a significant predictor of adverse cardiovascular outcomes within each risk group.

CONCLUSION

The MUS model is an effective tool for risk stratification in Asian patients with and without ASCVD, accurately predicting MACEs and performing comparably or better than other established risk models. Our findings suggest that patient management should focus on background risk factors instead of solely on primary or secondary prevention.

Health guidance intervention mitigates the escalation of predicted comprehensive cardiovascular disease risk: Interrupted time series design

INTRODUCTION

Metabolic syndrome increases the risk of cardiovascular events. Despite the Japanese healthcare system's efforts in early detection and intervention, particularly through Specific Health Checkup and Guidance programs, research on their effectiveness is limited. This study evaluated the impact of Specific Health Guidance on the predicted risk of atherosclerotic cardiovascular disease (ASCVD) in working-age Japanese individuals.

METHODS

Employing an Interrupted Time Series (ITS) design, this study compared the trends in predicted ASCVD risk and each individual risk factor used for the prediction of ASCVD risk before and after intervention in individuals participating in the guidance.

RESULTS

Analyses based on the ITS design indicated that participation in Specific Health Guidance programs, specifically the intensive level program, mitigates the increase trend of the predicted ASCVD risk. On the other hand, the impact on the trends of individual cardiovascular risk factors was minimal.

CONCLUSIONS

The intensive level Specific Health Guidance appeared to reduce the increasing trend in ASCVD risk, emphasizing the importance of comprehensive risk assessment in evaluating health interventions. However, the results are limited owing to the specific demographics and short evaluation period. Further research is necessary to understand the long-term impacts and broader applicability.

Association between atherosclerotic cardiovascular disease score and skin carotenoid levels estimated via refraction spectroscopy in the Japanese population: a cross-sectional study

Carotenoids play a role in preventing and impeding the progression of atherosclerotic cardiovascular diseases (ASCVDs) through their anti-oxidative effects. This study evaluated associations between ASCVD risk and skin carotenoid (SC) levels, reflecting dietary carotenoid intake. Participants' ASCVD risk was assessed using the Hisayama ASCVD risk prediction model, and SC levels were measured through a reflection spectroscope (Veggie Meter). The associations between high ASCVD risk and SC levels were analyzed using logistic regression analysis and a restricted cubic spline (RCS) model. A total of 1130 men and women (mean age: 56 years) from participants who underwent a health examination in Seirei Center for Health Promotion and Prevention Medicine in 2019 and 2022 were analyzed. Of these, 4.6% had moderate or high ASCVD risk. Mean SC values were 236, 315, 376, 447, and 606 in quintile Q1 to Q5, respectively. The adjusted odds ratios (95% confidence intervals) of SC quintile for moderate- or high-risk ASCVD was 0.24 (0.12-0.51) in Q5 (495 ≤), 0.42 (0.23-0.77) in Q4, 0.50 (0.29-0.88) in Q3, and 0.68 (0.41-1.12) in Q2 compared to Q1 (< 281). High SC values continuously showed non-linear inverse association with moderate- or high-risk for ASCVD in Japanese adults. Non-invasive SC measurements may be a good indicator for recommending carotenoids to prevent cardiovascular disease.

Development of a simple prediction model for mechanical complication in ST-segment elevation myocardial infarction patients after primary percutaneous coronary intervention

Mechanical complication (MC) is a rare but serious complication in patients with ST-segment elevation myocardial infarction (STEMI). Although several risk factors for MC have been reported, a prediction model for MC has not been established. This study aimed to develop a simple prediction model for MC after STEMI. We included 1717 patients with STEMI who underwent primary percutaneous coronary intervention (PCI). Of 1717 patients, 45 MCs occurred after primary PCI. Prespecified predictors were determined to develop a tentative prediction model for MC using multivariable regression analysis. Then, a simple prediction model for MC was generated. Age ≥ 70, Killip class ≥ 2, white blood cell ≥ 10,000/µl, and onset-to-visit time ≥ 8 h were included in a simple prediction model as "point 1" risk score, whereas initial thrombolysis in myocardial infarction (TIMI) flow grade ≤ 1 and final TIMI flow grade ≤ 2 were included as "point 2" risk score. The simple prediction model for MC showed good discrimination with the optimism-corrected area under the receiver-operating characteristic curve of 0.850 (95% CI: 0.798-0.902). The predicted probability for MC was 0-2% in patients with 0-4 points of risk score, whereas that was 6-50% in patients with 5-8 points. In conclusion, we developed a simple prediction model for MC. We may be able to predict the probability for MC by this simple prediction model.

Prediction of the 4-Year Incidence Risk of Ischemic Stroke in Healthy Japanese Adults: The Fukushima Health Database

AIM

Estimating the risk of developing ischemic stroke (IS) may assist health professionals in motivating individuals to modify their risk behavior.

METHODS

A predictive model was derived from 178,186 participants from Fukushima Health Database, aged 40-74 years, who attended the health checkup in 2014 and completed at least one annual health checkup by 2018 (Cohort I). Cox proportional hazard regression model was used to build a 4-year prediction model, thus the risk scores were based on the regression coefficients. External validation for the risk scores was conducted in another cohort of 46,099 participants following between 2015 and 2019 (Cohort II).

RESULTS

The 4-year cumulated incidence rate of IS was 179.80/100,000 person-years in Cohort I. The predictive model included age, sex, blood pressure, hypertension treatment, diabetes, low- and high-density lipoprotein cholesterol, smoking, walking pace, and body weight change of 3 kg within one year. Risk scores were interpreted based on the Cohort I predictive model function. The Harrell's C-statistics of the discrimination ability of the risk score model (95% confidence interval) was 0.744 (0.729-0.759) in Cohort I and 0.770 (0.743-0.797) in Cohort II. The overall agreement of the risk score probability of IS incidence for the observed/expected case ratio and 95% CI was 0.98 (0.92-1.05) in Cohort I and 1.08 (0.95-1.22) in Cohort II.

CONCLUSIONS

The 4-year risk prediction model revealed a good performance for IS incidence, and risk scores could be used to estimate individual incidence risk of IS. Updated models with additional confirmed risk variables may be needed.

Machine Learning Models for ASCVD Risk Prediction in an Asian Population - How to Validate the Model is Important

Introduction

Atherosclerotic cardiovascular disease (ASCVD) is prevalent worldwide including Taiwan, however widely accepted tools to assess the risk of ASCVD are lacking in Taiwan. Machine learning models are potentially useful for risk evaluation. In this study we used two cohorts to test the feasibility of machine learning with transfer learning for developing an ASCVD risk prediction model in Taiwan.

Methods

Two multi-center observational registry cohorts, T-SPARCLE and T-PPARCLE were used in this study. The variables selected were based on European, U.S. and Asian guidelines. Both registries recorded the ASCVD outcomes of the patients. Ten-fold validation and temporal validation methods were used to evaluate the performance of the binary classification analysis [prediction of major adverse cardiovascular (CV) events in one year]. Time-to-event analyses were also performed.

Results

In the binary classification analysis, eXtreme Gradient Boosting (XGBoost) and random forest had the best performance, with areas under the receiver operating characteristic curve (AUC-ROC) of 0.72 (0.68-0.76) and 0.73 (0.69-0.77), respectively, although it was not significantly better than other models. Temporal validation was also performed, and the data showed significant differences in the distribution of various features and event rate. The AUC-ROC of XGBoost dropped to 0.66 (0.59-0.73), while that of random forest dropped to 0.69 (0.62-0.76) in the temporal validation method, and the performance also became numerically worse than that of the logistic regression model. In the time-to-event analysis, most models had a concordance index of around 0.70.

Conclusions

Machine learning models with appropriate transfer learning may be a useful tool for the development of CV risk prediction models and may help improve patient care in the future.

Predicting multi-vascular diseases in patients with coronary artery disease

Background: Because of its systemic nature, the occurrence of atherosclerosis in the coronary arteries can also indicate a risk for other vascular diseases.  However, screening program targeted for all patients with coronary artery disease (CAD) is highly ineffective and no studies have assessed the risk factors for developing multi-vascular diseases in general. This study constructed a predictive model and scoring system to enable targeted screening for multi-vascular diseases in CAD patients. Methods: This cross-sectional study includes patients with CAD, as diagnosed during coronary angiography or percutaneous coronary intervention from March 2021 to December 2021. Coronary artery stenosis (CAS) and abdominal aortic aneurysm (AAA) were diagnosed using Doppler ultrasound while peripheral artery disease (PAD) was diagnosed based on ABI score. Multivariate logistic regression was conducted to construct the predictive model and risk scores. Validation was conducted using ROC analysis and Hosmer-Lemeshow test. Results: Multivariate analysis showed that ages of >60 years (OR [95% CI] = 1.579 [1.153-2.164]), diabetes mellitus (OR = 1.412 [1.036-1.924]), cerebrovascular disease (OR = 3.656 [2.326-5.747]), and CAD3VD (OR = 1.960 [1.250-3.073]) increased the odds for multi-vascular disease. The model demonstrated good predictive capability (AUC = 0.659) and was well-calibrated (Hosmer-Lemeshow p = 0.379). Targeted screening for high-risk patients reduced the number needed to screen (NNS) from 6 in the general population to 3 and has a high specificity of 96.5% Conclusions: Targeted screening using clinical risk scores was able to decrease NNS with good predictive capability and high specificity.

Epidemiology of Stroke in a General Japanese Population: The Hisayama Study

The Hisayama Study is an ongoing epidemiological study of stroke, coronary artery disease (CAD), and other noncommunicable diseases in a general Japanese population established in 1961. According to the longitudinal data from the Hisayama Study, average levels of systolic blood pressure among hypertensive individuals have decreased with time since 1961. In contrast, the prevalence of metabolic risk factors such as obesity, hypercholesterolemia, and glucose intolerance has increased with time. The incidence rates of ischemic stroke in this population have declined significantly as a result of improvement in hypertension management, but the proportion of atherothrombotic brain infarction (ATBI) and embolic stroke among the total ischemic stroke cases have increased probably due to the increased prevalence of metabolic risk factors and the increased number of patients with atrial fibrillation (AF) with super-aging population. Therefore, a strategy to reduce the risks of ATBI and embolic stroke by comprehensive management of their risk factors is necessary.In this review, we first show the secular trends in the incidence of stroke and the prevalence of its risk factors using the data from the Hisayama Study. Then, the studies for the association of traditional risk factors with stroke development in the Hisayama Study are introduced. Finally, we developed risk prediction models to estimate the absolute risk of atherosclerotic cardiovascular disease (ASCVD; including ATBI and CAD) and AF, that may be used for the stratification of future risk of ATBI and AF-related stroke in clinical practice or health examination.

Association of Low-Density Lipoprotein Cholesterol with Risk of Coronary Heart Disease and Stroke among Middle-Aged Japanese Workers: An Analysis using Inverse Probability Weighting

AIMS

The associations between low-density lipoprotein cholesterol (LDL-C) and the risk of cardiovascular disease (CVD) subtypes are not well established among the Japanese population. This study used longitudinal data from the Aichi Workers' Cohort Study to explore the association between LDL-C levels and the risk of coronary heart disease (CHD) and stroke subtypes.

METHODS

Pooled data of 8966 adults (7093men and 1903 women) who were recruited between (2002) and (2008) were used for the current analysis. Propensity scores for the LDL-C categories were generated using multinomial logistic regression. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated from the inverse probability weighted Cox proportional hazards model for LDL-C category associations with risks of CHD, stroke subtypes, and CVD.

RESULTS

During a median follow-up of 12 years, 122 strokes (57 ischemic strokes, 25 intracerebral hemorrhage, and 40 unknown subtypes) and 82 cases of CHD were observed. LDL-C 160- mg/dL compared to LDL-C 100-119 mg/dL was positively and significantly associated with the risk of CHD (HR: 4.56; 95% CI: 1.91-10.9) but not with ischemic stroke (HR: 0.99; 95% CI: 0.44-2.22). LDL-C was inversely associated with the risk of intracerebral hemorrhage (P for trend=0.009).

CONCLUSION

In middle-aged Japanese workers, LDL-C was significantly and positively associated with CHD, but not with ischemic stroke. LDL-C was inversely significantly associated with intracerebral hemorrhage.

Development of new scores for atherosclerotic cardiovascular disease using specific medical examination items: the Suita Study

BACKGROUND

We previously developed risk models predicting stroke, coronary heart disease (CHD), and cardiovascular disease (CVD) among Japanese people from the Suita Study. Yet, applying these models at the national level was challenging because some of the included risk factors differed from those collected in the Japanese governmental health check-ups, such as Tokutei-Kenshin. We, therefore, conducted this study to develop new risk models for stroke, CHD, and atherosclerotic CVD (ASCVD), based on data from the Suita Study. The new models used traditional cardiovascular risk factors similar to those in the Japanese governmental health check-ups.

METHODS

We included 7,413 participants, aged 30-84 years, initially free from stroke and CHD. All participants received baseline health examinations, including a questionnaire assessing their lifestyle and medical history, medical examination, and blood and urine analysis. The risk factors of stroke, CHD, and ASCVD (cerebral infarction or CHD) were determined using the multivariable-adjusted Cox regression. The models' performance was assessed using the C-statistics for discrimination and the Hosmer-Lemeshow for calibration. We also developed three simple scores (zero to 100) that could predict the 10-year incidence of stroke, CHD, and ASCVD.

RESULTS

Within 110,428 person-years (median follow-up = 16.6 years), 410 stroke events, 288 CHD events, and 527 ASCVD events were diagnosed. Age, smoking, hypertension, and diabetes were associated with stroke, CHD, and ASCVD risk. Men and those with decreased high-density lipoproteins or increased low-density lipoproteins showed a higher risk of CHD and ASCVD. Urinary proteins were associated with an increased risk of stroke and ASCVD. The C-statistic values of the risk models were >0.750 and the p-values of goodness-of-fit were >0.30. The 10-year incidence of stroke, CVD, and ASCVD events was 3.8%, 3.5%, and 5.7% for scores 45-54, 10.3%, 11.8%, and 19.6% for scores 65-74, and 27.7%, 23.5%, and 60.5% for scores ≥85, respectively.

CONCLUSIONS

We developed new Suita risk models for stroke, CHD, and ASCVD using variables similar to those in the Japanese governmental health check-ups. We also developed new risk scores to predict incident stroke, CHD, and ASCVD within 10 years.

A Simple Risk Score to Differentiate Between Coronary Artery Obstruction and Coronary Artery Spasm of Patients With Acute Coronary Syndrome Without Persistent ST-Segment Elevation

BACKGROUND

The aim of this study was to create a risk scoring model to differentiate obstructive coronary artery (CA) from CA spasm in the etioology of acute coronary syndrome (ACS).

METHODS AND RESULTS

We included 753 consecutive patients with ACS without persistent ST-segment elevation (p-STE). The exclusion criteria were: (1) out-of-hospital cardiac arrest; (2) cardiogenic shock; (3) hemodialysis; (4) atrial fibrillation/flutter; (5) severe valvular disease; (6) no coronary angiography; (7) non-obstructive coronary artery without "definite" vasospastic angina definition; and/or (8) missing data. From the multivariate logistic regression analysis for prediction of obstructive CA, an integer score of 2 to each 0.5 increment in odds ratio was given, and values were divided into quartiles according to the total score. The scores were as follows: age >70 years (6 points), non-STE myocardial infarction (9 points), diabetes mellitus (5 points), B-type natriuretic peptide >90 pg/mL (7 points), neutrophil to lymphocyte ratio >2 (5 points), and high-density lipoprotein cholesterol <50 mg/dL (5 points). CA spasm-induced ACS occurred in 50.0% in Quartile 1 (total score: 0-13), 20.5% in Quartile 2 (total score: 14-19), 4.9% in Quartile 3 (total score: 20-26), and 2.2% in Quartile 4 (total score: 27-37) (P<0.001), indicating that a total score of <20 was a potential clinical indicator of CA spasm-induced ACS.

CONCLUSIONS

CA spasm-induced ACS should be suspected if a total score of <20, and a spasm provocation test was being considered.

Human genetics and its impact on cardiovascular disease

Cardiovascular disease (CVD) is a major cause of death worldwide. Given that CVD is a highly heritable trait, researchers have attempted to fully understand the genetic basis of CVD for a long time. The human genome comprises 3,100 Mbp per haploid genome and 6,200 Mbp in total (diploid genome). However, there is a tendency for rare genetic variations to exhibit a large effect size, whereas common genetic variations have a small effect on diseases, because of natural selection. In this sense, dividing genetic variations into two groups based on allele frequency (and effect sizes on diseases) is a good idea. We know there are several important genes (especially lipid-related genes) in which rare genetic variations are apparently associated with CVD risk, while a polygenic risk score comprising common genetic variations appears to work quite well among general populations. That information can be used not only for risk stratification but also for discoveries for novel pharmacologic targets. In this review article, we provide the important and simple idea that human genetics is important for CVD because it is a highly heritable trait, and we believe that it will lead to precision medicine in this field.

The Lifelong Health Support 10: a Japanese prescription for a long and healthy life

BACKGROUND

Although the age-adjusted incidence and mortality of cancer and cardiovascular disease (CVD) have been decreasing steadily in Japan, both diseases remain major contributors to morbidity and mortality along with the aging society. Herein, we aim to provide a prescription of 10 health tips for long and healthy life named the "Lifelong Health Support 10 (LHS10)."

METHOD

The LHS10 was developed by the preventive medicine specialists at the National Cerebral and Cardiovascular Center in Suita, where it has been used for health guidance to prevent CVD, cancer, and cognitive decline in addition to their major risk factors such as hypertension, diabetes, and obesity. It consisted of the lifestyle modification recommendations of the 2014 Japanese Society of Hypertension guidelines and the 2017 Japan Atherosclerosis Society Guidelines for preventing atherosclerotic CVD. Further, it came in line with other international lifestyle modification guidelines. In this narrative review, we summarized the results of several Japanese epidemiological studies investigating the association between the LHS10 items and the risk of cancer, CVD, and other chronic diseases including dementia, diabetes, and chronic kidney disease.

RESULTS

The LHS10 included avoiding smoking and secondhand smoke exposure, engaging in physical activity, refraining from excessive alcohol drinking, reducing fried foods and sugary soft drinks, cutting salt in food, consuming more vegetables, fruits, fish, soy foods, and fibers, and maintaining proper body weight. All items of the LHS10 were shown to reduce the risk of cancer, CVD, and other chronic diseases.

CONCLUSIONS

The LHS10 can be a helpful tool for health guidance.

Effect of Physical Activity on Cardiovascular Event Risk in a Population-Based Cohort of Patients with Type 2 Diabetes

Cardiovascular disease (CVD) is the most common cause of morbidity and mortality among patients with type 2 diabetes (T2D). Physical activity (PA) is one of the few modifiable factors that can reduce this risk. The aim of this study was to estimate to what extent PA can contribute to reducing CVD risk and all-cause mortality in patients with T2D. Information from a population-based cohort including 26,587 patients with T2D from the Navarre Health System who were followed for five years was gathered from electronic clinical records. Multivariate Cox regression models were fitted to estimate the effect of PA on CVD risk and all-cause mortality, and the approach was complemented using conditional logistic regression models within a matched nested case-control design. A total of 5111 (19.2%) patients died during follow-up, which corresponds to 37.8% of the inactive group, 23.9% of the partially active group and 12.4% of the active group. CVD events occurred in 2362 (8.9%) patients, which corresponds to 11.6%, 10.1% and 7.6% of these groups. Compared with patients in the inactive group, and after matching and adjusting for confounders, the OR of having a CVD event was 0.84 (95% CI: 0.66-1.07) for the partially active group and 0.71 (95% CI: 0.56-0.91) for the active group. A slightly more pronounced gradient was obtained when focused on all-cause mortality, with ORs equal to 0.72 (95% CI: 0.61-0.85) and 0.50 (95% CI: 0.42-0.59), respectively. This study provides further evidence that physically active patients with T2D may have a reduced risk of CVD-related complications and all-cause mortality.