Prediction of fatal and non-fatal cardiovascular events in young and middle-aged healthy workers: The IberScore model

Validation of the IberScore model in a primary care population

BACKGROUND

This study aimed to validate the IberScore cardiovascular risk model in a population attended in the primary care setting.

METHODS

A cohort of patients with no history of cardiovascular disease visited in a primary care center during the years 2008 and/or 2009 and followed up until 2018 was selected. Cardiovascular risk was calculated with the IberScore formula for all the subjects of the cohort and the model was calibrated, graphically represented by risk deciles the proportion of expected events and proportion of observed events at 10-year follow-up, stratified by sex. The area under the ROC curve was calculated to assess the discrimination of the model.

RESULTS

A total of 10,085 patients visited during the years 2008 and/or 2009 were included in the study. Men showed a mean 10-year risk of suffering a fatal or non-fatal cardiovascular events according to IberScore of 17.07% (SD 20.13), with a mean estimated vascular age of more than 4 years higher than the biological age; while women had a mean 10-year risk of 7.91% (SD 9.03), with an estimated vascular age of more than 2 years above the biological age. The area under the ROC curve showed a discrimination index of the model of 0.86 (95% CI 0.84-0.88) in men and 0.82 (95% CI 0.79-0.85) in women.

CONCLUSION

IberScore model discriminates well in the population attended in primary care but the model overestimates the risk.

Choroidal thickness and granulocyte colony-stimulating factor in tears improve the prediction model for coronary artery disease

BACKGROUND

Coronary artery disease (CAD) detection in asymptomatic patients still remains controversial. The aim of our study was to evaluate the usefulness of ophthalmologic findings as predictors of the presence of CAD when added to cardiovascular classic risk factors (CRF) in patients with acute coronary cardiopathy suspicion.

METHODS

After clinical stabilization, 96 patients with acute coronary cardiopathy suspicion were selected and divided in two groups: 69 patients with coronary lesions and 27 patients without coronary lesions. Their 192 eyes were subjected to a complete routine ophthalmologic examination. Samples of tear fluid were also collected to be used in the detection of cytokines and inflammatory mediators. Logistic regression models, receiver operating characteristic curves and their area under the curve (AUC) were analysed.

RESULTS

Suggestive predictors were choroidal thickness (CT) (OR: 1.02, 95% CI 1.01-1.03) and tear granulocyte colony-stimulating factor (G-CSF) (OR: 0.97, 95% CI 0.95-0.99). We obtained an AUC of 0.9646 (95% CI 0.928-0.999) when CT and tear G-CSF were added as independent variables to the logistic regression model with cardiovascular CRF: sex, age, diabetes, high blood pressure, hypercholesterolemia, smoking habit and obesity. This AUC was significantly higher (p = 0.003) than the prediction derived from the same logistic regression model without CT and tear G-CSF (AUC = 0.828, 95% CI 0.729-0.927).

CONCLUSIONS

CT and tear G-CSF improved the predictive model for CAD when added to cardiovascular CRF in our sample of symptomatic patients. Subsequent studies are needed for validation of these findings in asymptomatic patients.

Cardiovascular risk prediction: from classical statistical methods to machine learning approaches

Nowadays, cardiovascular risk prediction scores are commonly used in primary prevention settings. Estimating the cardiovascular individual risk is of crucial importance for effective patient management and optimal therapy identification, with relevant consequences on secondary prevention settings. To reach this goal, a plethora of risk scores have been developed in the past, most of them assuming that each cardiovascular risk factor is linearly dependent on the outcome. However, the overall accuracy of these methods often remains insufficient to solve the problem at hand. In this scenario, machine learning techniques have repeatedly proved successful in improving cardiovascular risk predictions, being able to capture the non-linearity present in the data. In this concern, we present a detailed discussion concerning the application of classical versus machine learning-based cardiovascular risk scores in the clinical setting. This review aimed to give an overview of the current risk scores based on classical statistical approaches and machine learning techniques applied to predict the risk of several cardiovascular diseases, comparing them, discussing their similarities and differences, and highlighting their main drawbacks to aid the physician having a more critical understanding of these tools.

A Cardiovascular Risk Score for Use in Occupational Medicine

Cardiovascular disease is one of the most frequent causes of long-term sickness absence from work. The study aims to develop and validate a score to assess the 10-year risk of unsuitability for work accounting for the cardiovascular risk. The score can be considered as a prevention tool that would improve the cardiovascular risk assessment during health surveillance visits under the assumption that a high cardiovascular risk might also translate into high risk of unsuitability for work. A total of 11,079 Italian workers were examined, as part of their scheduled occupational health surveillance. Cox proportional hazards regression models were employed to derive risk equations for assessing the 10-year risk of a diagnosis of unsuitability for work. Two scores were developed: the CROMA score (Cardiovascular Risk in Occupational Medicine) included age, sex, smoking status, blood pressure (systolic and diastolic), body mass index, height, diagnosis of hypertension, diabetes, ischemic heart disease, mental disorders and prescription of antidiabetic and antihypertensive medications. The CROMB score was the same as CROMA score except for the inclusion of only variables statistically significant at the 0.05 level. For both scores, the expected risk of unsuitability for work was higher for workers in the highest risk class, as compared with the lowest. Moreover results showed a positive association between most of cardiovascular risk factors and the risk of unsuitability for work. The CROMA score demonstrated better calibration than the CROMB score (11.624 (p-value: 0.235)). Moreover, the CROMA score, in comparison with existing CVD risk scores, showed the best goodness of fit and discrimination.

Association of premature atherosclerotic cardiovascular disease with higher risk of cancer: a behavioral risk factor surveillance system study

AIM 

The aim of this study was to investigate a possible association between atherosclerotic cardiovascular disease (ASCVD) and risk of cancer in young adults.

METHODS 

We utilized data from the Behavioral Risk Factor Surveillance System, a nationally representative US telephone-based survey to identify participants in the age group of 18-55 years who reported a history of ASCVD. These patients were defined as having premature ASCVD. Weighted multivariable logistic regression models were used to study the association between premature ASCVD and cancer including various cancer subtypes.

RESULTS 

Between 2016 and 2019, we identified 28 522 (3.3%) participants with a history of premature ASCVD. Compared with patients without premature ASCVD, individuals with premature ASCVD were more likely to be Black adults, have lower income, lower levels of education, reside in states without Medicaid expansion, have hypertension, diabetes mellitus, chronic kidney disease, obesity, and had delays in seeking medical care. Individuals with premature ASCVD were more likely to have been diagnosed with any form of cancer (13.7% vs 3.9%), and this association remained consistent in multivariable models (odds ratio, 95% confidence interval: 2.08 [1.72-2.50], P < 0.01); this association was significant for head and neck (21.08[4.86-91.43], P < 0.01), genitourinary (18.64 [3.69-94.24], P < 0.01), and breast cancer (3.96 [1.51-10.35], P < 0.01). Furthermore, this association was consistent when results were stratified based on gender and race, and in sensitivity analysis using propensity score matching.

CONCLUSION 

Premature ASCVD is associated with a higher risk of cancer. These data have important implications for the design of strategies to prevent ASCVD and cancer in young adults.

Relationship between plasma high-sensitivity c-reactive protein and traditional cardiovascular risk factors among active-duty military personnel in Republic of Serbia

Background/Aim. Approximately one third of individuals with no or one risk factor, as well as 40% individuals with concentraction of cholesterol less than average die from cardiovascular disease (CVD). Recent study underlined significant role of inflammation in atherosclerosis and its complications. Our study is the first one in Serbia which have for the aim that analyses the association of high-sensitivity C-reactive protein (hs-CRP) with traditional risk factors for coronary heart disease. Metods: This study is observational cross-sectional study which included 205 active-duty military personnel similar socioepidemiological and economic characteristics. Plasma high-sensitivity C-reactive protein (hs-CRP) and traditional cardiovascular risk factors were evaluated. The relative cardiovascular risk was staged as low (hs-CRP <1mg/L), intermediate (hs-CRP between 1 and 3mg/L) and high (hs-CRP >3mg/L). The Systematic COronary Risk Evaluation (SCORE) system was used for absolute cardiovascular risk assessment, and total risk (fatal and non-fatal events). Results: Our study included 205 participants, average age of 39 (35-43) years, with median and interquartile range values of hs-CRP 0.80 mg/L (0.43-1.75), with average hs-CRP values 0.71mg/L in the youngers than 40 years and 1.2 mg/L in the olders. Between the study groups the significant diferrence in hsCRP-a values was registrated; hs-CRP was significantly higher in the group older than 40 years ( p=0.006). There was a significant positive correlation between hsCRP and age (r=0.266, p<0.001); weight (r=0.223 p=0.001), body mass index (BMI) (r=0.344, p<0.001), diastolic hypertension (r=0.190, p=0.007), LDL cholesterol (r=0.152, p=0.032), triglycerides (r=0.144, p=0.039), number of risk factors (r=0.210, p<0.003), as well as negative correlation with HDL cholesterol concentration (r=-0.159, p<0.023). There was no significant correlation between hsCRP concentration and total cholesterol (r=0.131, p=0.062). According to hs-CRP values, high CV risk was found in 17.7% participants older than 40 years, and based on SCORE system staging, 90% participants have intermmediate CV risk. The results of stepwise multiple regression analyses showed that BMI was independently associated with hsCRP concentration in the group younger than 40 years. Among the olders, age was found to be associated with fibrinogen values. Conclusions. In the population of active military personnel in the Republic of Serbia, hs-CRP is correlated with some of the risk factors for CVD, and only BMI is independently 4 correlated with hs-CRP in those under 40 years of age. Levels of serum hs-CRP are increased with aging, imply that hs-CRP measurement may provide a more accurate assessment of the individual overall risk profile for CVD in the Serbian military personnel population.

Patterns of change in cardiovascular risks of Korean male workers: a 10-year cohort analysis using the National Health Insurance Service-National Sample Cohort (NHIS-NSC) 2.0 database

OBJECTIVE

Health behaviour is one of the major determinants of cardiovascular diseases in working population. This study was tried to investigate the trend of cardiovascular health level, the relationship between continuous health behaviours, and changes in the risk of cardiovascular diseases of male workers by using a nationwide database.

DESIGN

This study is a retrospective cohort study.

SETTING AND PARTICIPANTS

The study analysed data of 57 837 male workers whose personal health examination data were continuously traced using Korea's National Health Insurance Service-National Sample Cohort 2.0 database.

PRIMARY OUTCOME MEASURES

A 10-year trend for all cardiovascular risks and change for the risks according to the consistent performance of healthy behaviours.

RESULTS

The results showed that the risk of being overweight (adjusted OR (aOR) 1.63, 95% CI 1.59 to 1.68) and obese (aOR 1.51, 95% CI 1.47 to 1.56) increased. The index of cardiovascular risk also increased for high fasting glucose (aOR 1.77, 95% CI 1.62 to 1.95) and high total cholesterol (aOR 1.68, 95% CI 1.60 to 1.76), respectively. The risks of high fasting glucose (aOR 2.09, 95% CI 1.40 to 3.13), high triglycerides (aOR 1.27, 95% CI 1.14 to 1.42) and high low-density lipoprotein cholesterol (aOR 1.38, 95% CI 1.14 to 1.66) were increased among high-risk smokers. Similarly, the risk of high total cholesterol (aOR 2.20, 95% CI 1.35 to 3.58) and high triglycerides (aOR 1.42, 95% CI 1.09 to 1.85) were increased among high-risk drinkers. In addition, the increase in the risk of being overweight (aOR 2.20, 95% CI 1.83 to 2.65) and obese (aOR 1.90, 95% CI 1.59 to 2.27) were analysed among who had not consistently exercised.

CONCLUSIONS

Since the pattern of change in the level of cardiovascular risk related to the continuous health behaviours of male workers was identified, the findings of the present study can be used as basic data to develop health promotion policies for the population.

COVID-19 and Sick Leave: An Analysis of the Ibermutua Cohort of Over 1,651,305 Spanish Workers in the First Trimester of 2020

Objectives: The worldwide SARS-COV2 pandemic has impacted the health of workers and companies. The aim is to quantify it according to sick leave. Methods: Using ICD-9 codes, we analyzed Ibermutua records of all sick leaves during the first trimester of 2020, compared to during the same months of 2017, 2018, and 2019. We stratified the analysis by causes, patient sex, activity sectors, and regional data. All sick leaves were adjusted by the number of Ibermutua-affiliated persons in each period. Results: In March 2020, there was an unprecedented (116%) increase in total sick leaves, mainly due to infectious and respiratory diseases. Men and women were equally affected. All activity sectors were impacted, with the highest increase (457%) observed among health-related workers, especially due to contagious disease. The incidences of sick leaves were heterogeneous among different regions. Cost-analysis of sick leaves during the first trimester of 2020 compared with in previous years showed 40.3% increment (mean 2,813 vs. 2,005 € per 100 affiliated workers). Conclusions: The SARS-COV2 pandemic is having a huge impact on workers' health, as shown by data regarding sick leaves in March 2020. This is associated with greater economic burden for companies, both due to the cost associated with sick leaves and the losses in productivity due to confinement.