Predicting the Development of Myocardial Infarction in Middle-Aged Adults with Type 2 Diabetes: A Risk Model Generated from a Nationwide Population-Based Cohort Study in Korea

Investigating the impact of extreme weather events and related indicators on cardiometabolic multimorbidity

BACKGROUND

The impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored.

OBJECTIVES

Investigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations.

DESIGNS

Time-stratified case-crossover design.

METHODS

A distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM.

RESULTS

There are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854).

CONCLUSIONS

Extreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM.

A literature review of quality assessment and applicability to HTA of risk prediction models of coronary heart disease in patients with diabetes

This literature review had two objectives: to identify models for predicting the risk of coronary heart diseases in patients with diabetes (DM); and to assess model quality in terms of risk of bias (RoB) and applicability for the purpose of health technology assessment (HTA). We undertook a targeted review of journal articles published in English, Dutch, Chinese, or Spanish in 5 databases from 1st January 2016 to 18th December 2022, and searched three systematic reviews for the models published after 2012. We used PROBAST (Prediction model Risk Of Bias Assessment Tool) to assess RoB, and used findings from Betts et al. 2019, which summarized recommendations and criticisms of HTA agencies on cardiovascular risk prediction models, to assess model applicability for the purpose of HTA. As a result, 71 % and 67 % models reporting C-index showed good discrimination abilities (C-index >= 0.7). Of the 26 model studies and 30 models identified, only one model study showed low RoB in all domains, and no model was fully applicable for HTA. Since the major cause of high RoB is inappropriate use of analysis method, we advise clinicians to carefully examine the model performance declared by model developers, and to trust a model if all PROBAST domains except analysis show low RoB and at least one validation study conducted in the same setting (e.g. country) is available. Moreover, since general model applicability is not informative for HTA, novel adapted tools may need to be developed.

Serum/plasma biomarkers and the progression of cardiometabolic multimorbidity: a systematic review and meta-analysis

Background

The role of certain biomarkers in the development of single cardiometabolic disease (CMD) has been intensively investigated. Less is known about the association of biomarkers with multiple CMDs (cardiometabolic multimorbidity, CMM), which is essential for the exploration of molecular targets for the prevention and treatment of CMM. We aimed to systematically synthesize the current evidence on CMM-related biomarkers.

Methods

We searched PubMed, Embase, Web of Science, and Ebsco for relevant studies from inception until August 31st, 2022. Studies reported the association of serum/plasma biomarkers with CMM, and relevant effect sizes were included. The outcomes were five progression patterns of CMM: (1) no CMD to CMM; (2) type 2 diabetes mellitus (T2DM) followed by stroke; (3) T2DM followed by coronary heart disease (CHD); (4) T2DM followed by stroke or CHD; and (5) CHD followed by T2DM. Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the quality of the included studies. A meta-analysis was conducted to quantify the association of biomarkers and CMM.

Results

A total of 68 biomarkers were identified from 42 studies, which could be categorized into five groups: lipid metabolism, glycometabolism, liver function, immunity, and others. Lipid metabolism biomarkers were most reported to associate with CMM, including TC, TGs, HDL-C, LDL-C, and Lp(a). Fasting plasma glucose was also reported by several studies, and it was particularly associated with coexisting T2DM with vascular diseases. According to the quantitative meta-analysis, HDL-C was negatively associated with CHD risk among patients with T2DM (pooled OR for per 1 mmol/L increase = 0.79, 95% CI = 0.77-0.82), whereas a higher TGs level (pooled OR for higher than 150 mg/dL = 1.39, 95% CI = 1.10-1.75) was positively associated with CHD risk among female patients with T2DM.

Conclusion

Certain serum/plasma biomarkers were associated with the progression of CMM, in particular for those related to lipid metabolism, but heterogeneity and inconsistent findings still existed among included studies. There is a need for future research to explore more relevant biomarkers associated with the occurrence and progression of CMM, targeted at which is important for the early identification and prevention of CMM.

Coronary Artery Calcium Score as a Sensitive Indicator of Cardiovascular Disease in Patients with Type 2 Diabetes Mellitus: A Long-Term Cohort Study

BACKGRUOUND

Coronary artery calcium score (CACS) has become an important tool for evaluating cardiovascular disease (CVD). This study evaluated the significance of CACS for future CVD through more than 10 years of follow-up in asymptomatic Korean populations with type 2 diabetes mellitus (T2DM) known to have a relatively low CACS burden.

METHODS

We enrolled 981 asymptomatic T2DM patients without CVD at baseline who underwent CACS evaluation using multidetector computed tomography between January 2008 and December 2014. They were grouped into five predefined CACS categories based on Agatston scores and followed up by August 2020. The primary endpoint was incident CVD events, including coronary, cerebrovascular, and peripheral arterial disease.

RESULTS

The relative risk of CVD was significantly higher in patients with CACS ≥10, and the significance persisted after adjustment for known confounders. A higher CACS category indicated a higher incidence of future CVD: hazard ratio (95% confidence interval) 4.09 (1.79 to 9.36), 12.00 (5.61 to 25.69), and 38.79 (16.43 to 91.59) for 10≤ CACS <100, 100≤ CACS <400, and CACS ≥400, respectively. During the 12-year follow-up period, the difference in event-free survival more than doubled as the category increased. Patients with CACS below 10 had very low CVD incidence throughout the follow-up. The receiver operating characteristic analysis showed better area under curve when the CACS cutoff was 10 than 100.

CONCLUSION

CACS can be a sensitive marker of CVD risk. Specifically, CACS above 10 is an indicator of CVD high-risk requiring more intensive medical treatment in Koreans with T2DM.

Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea

BACKGRUOUND

The severity of gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes. We aimed to generate a risk model for predicting insulin-requiring GDM before pregnancy in Korean women.

METHODS

A total of 417,210 women who received a health examination within 52 weeks before pregnancy and delivered between 2011 and 2015 were recruited from the Korean National Health Insurance database. The risk prediction model was created using a sample of 70% of the participants, while the remaining 30% were used for internal validation. Risk scores were assigned based on the hazard ratios for each risk factor in the multivariable Cox proportional hazards regression model. Six risk variables were selected, and a risk nomogram was created to estimate the risk of insulin-requiring GDM.

RESULTS

A total of 2,891 (0.69%) women developed insulin-requiring GDM. Age, body mass index (BMI), current smoking, fasting blood glucose (FBG), total cholesterol, and γ-glutamyl transferase were significant risk factors for insulin-requiring GDM and were incorporated into the risk model. Among the variables, old age, high BMI, and high FBG level were the main contributors to an increased risk of insulin-requiring GDM. The concordance index of the risk model for predicting insulin-requiring GDM was 0.783 (95% confidence interval, 0.766 to 0.799). The validation cohort's incidence rates for insulin-requiring GDM were consistent with the risk model's predictions.

CONCLUSION

A novel risk engine was generated to predict insulin-requiring GDM among Korean women. This model may provide helpful information for identifying high-risk women and enhancing prepregnancy care.

Evaluating Triglyceride and Glucose Index as a Simple and Easy-to-Calculate Marker for All-Cause and Cardiovascular Mortality

OBJECTIVE

The triglyceride and glucose (TyG) index is a useful marker of insulin resistance and is a predictor of several metabolic diseases. The aim of this study was to evaluate the association between the TyG index and all-cause or cardiovascular mortality using a large population-based cohort study database.

METHODS

A total of 255,508 subjects in the Kangbuk Samsung Health Study cohort were enrolled. Cox proportional hazards models were used to analyze the risk of mortality.

RESULTS

During a median 5.7-year follow-up, the cumulative all-cause and cardiovascular mortality was 0.47% and 0.07%. There was a nonlinear relationship between the TyG index and death, and moving from moderate to high, the TyG index levels were associated with an increase in the risk of death. The hazard ratio (HR) for all-cause and cardiovascular mortality of the TyG index was 1.21 [95% confidence interval (CI) 1.14-1.28] and 1.45 (95% CI 1.26-1.66) in the unadjusted model, respectively. After adjustment for covariates, the association between the TyG index and all-cause and cardiovascular mortality was attenuated. In the multivariable-adjusted model, the TyG index was associated with an elevated risk of all-cause mortality in women (HR 1.13, 95% CI 1.02-1.26) and a decreased risk in men (HR 0.92, 95% CI 0.85-0.99). The association between cardiovascular mortality and the TyG index was not statistically significant among either men or women in the multivariable-adjusted model.

CONCLUSIONS

The TyG index in a young, relatively healthy, population is associated with an elevated risk of all-cause and cardiovascular mortality. This association between the TyG index and all-cause mortality persists in women after multivariable adjustment.

Lipid cutoffs for increased cardiovascular disease risk in nondiabetic young people

AIMS

The relevance of blood lipid abnormalities to cardiovascular disease (CVD) risk in young populations is unclear. Here, we aimed to identify the cutoff levels of lipid parameters for increased risk of CVD among nondiabetic young adults aged 20-39 years.

METHODS

Using data from a nationally representative Korean National Health Insurance System database, we followed up 6,204,153 subjects who underwent health examinations between 2009 and 2012 until the end of 2018. The primary outcome was incident CVD, defined as a composite of myocardial infarction and stroke. We assessed the associations between pre-specified lipid levels and CVD risk. Subgroup analysis of the number of cardiovascular risk factors (obesity, hypertension, and current smoking) was also conducted.

RESULTS

During a median follow-up of 7.7 years, there were 14,569 (0.23%) cases of myocardial infarction, 9,459 (0.15%) cases of stroke, and 23,680 (0.38%) cases of composite CVD. Using total cholesterol (TC) level of <140 mg/dL, triglyceride (TG) level of <60 mg/dL, LDL-cholesterol level of <100 mg/dL, and non-HDL-cholesterol level of <130 mg/dL as reference groups, a significantly higher risk of CVD was observed in subjects with a TC level of ≥200 mg/dL, TG level of ≥60 mg/dL, LDL-cholesterol level of ≥130 mg/dL, or non-HDL-cholesterol level of ≥140 mg/dL. The cutoff levels of TC that had statistical significance for increased risk of CVD were 240, 220, and 200 mg/dL in subjects with 0, 1, or 2-3 risk factors, respectively.

CONCLUSIONS

Even modest increases in lipid levels were associated with increased risk of CVD in this nondiabetic young population. Our data provide potential criteria for stratifying CVD risk based on real-world evidence.

Current Trends of Big Data Research Using the Korean National Health Information Database

Recently, medical research using big data has become very popular, and its value has become increasingly recognized. The Korean National Health Information Database (NHID) is representative of big data that combines information obtained from the National Health Insurance Service collected for claims and reimbursement of health care services and results obtained from general health examinations provided to all Korean adults. This database has several strengths and limitations. Given the large size, various laboratory data, and questionnaires obtained from medical check-ups, their longitudinal nature, and long-term accumulation of data since 2002, carefully designed studies may provide valuable information that is difficult to obtain from other forms of research. However, consideration of possible bias and careful interpretation when defining causal relationships is also important because the data were not collected for research purposes. After the NHID became publicly available, research and publications based on this database have increased explosively, especially in the field of diabetes and metabolism. This article reviews the history, structure, and characteristics of the Korean NHID. Recent trends in big data research using this database, commonly used operational diagnosis, and representative studies have been introduced. We expect further progress and expansion of big data research using the Korean NHID.

Effects of exercise initiation and smoking cessation after new-onset type 2 diabetes mellitus on risk of mortality and cardiovascular outcomes

Lifestyle changes after a diagnosis of type 2 diabetes mellitus (DM) can affect vascular health outcomes. The objective of this study was to investigate the effects of changes in smoking and exercise on the risk of cardiovascular disease (CVD) and mortality in patients with newly diagnosed DM. Data were analyzed for 181,591 people with newly diagnosed type 2 DM who underwent 2 serial health examinations within 2 years before and after DM diagnosis. The study population was followed from the baseline to the date of death or cardiovascular events, or until December 31, 2018 and median follow-up was 6.07 years. Based on the change in status from before to after the diagnosis, participants were grouped into smoking groups (continuous smokers, quitters, new smokers, and nonsmokers) and exercise groups (constant exercisers, new exercisers, exercise dropouts, and nonexercisers). Compared with the nonexercisers, those who initiated exercise after their DM diagnosis had a lower risk of myocardial infarction (MI), stroke, and all-cause mortality: the hazard ratio (HR; 95% confidence interval [CI]) was 0.85 (0.76–0.94) for MI, 0.86 (0.78–0.94) for stroke, and 0.84 (0.89–0.90) for all-cause mortality. Quitters had a higher risk of MI, stroke, and all-cause mortality than nonsmokers, but their risk level was much lower than that in continuous smokers. When the group of continuous smokers and nonexercisers was considered as the reference group, participants who quit smoking and remained nonexercisers had a 21% lower risk of CVD (HR 0.79; 95% CI 0.70–0.90). Those who quit smoking and started exercising had a 46% reduced risk of CVD (HR 0.54; 95% CI 0.41–0.71) and a 22% reduced risk in all-cause mortality (HR 0.78; 95% CI 0.63–0.96). Smoking cessation and exercise initiation after a diagnosis of new-onset type 2 DM was associated with a reduced risk of CVD and all-cause mortality.

Assessing the Validity of the Criteria for the Extreme Risk Category of Atherosclerotic Cardiovascular Disease: A Nationwide Population-Based Study

Objective

To validate the criteria for the extreme risk category for atherosclerotic cardiovascular disease (ASCVD).

Methods

An observational cohort study of 35,464 individuals with established ASCVD was performed using the National Health Information Database. Incident myocardial infarction (MI), ischemic stroke, and death in patients with established ASCVD was investigated to validate the criteria for the extreme risk category of ASCVD defined as the presence of diabetes mellitus (DM), chronic kidney disease (CKD), and history of premature ASCVD.

Results

Among 35,464 patients, 77.97% of them were classified into the extreme risk group of ASCVD. A total of 28.10%, 39.61%, and 32.12% had DM, CKD, and a history of premature ASCVD, respectively. During a mean follow-up of 8.39 years, MI, ischemic stroke, and all-cause death were found in 3.87%, 8.51%, and 23.98% of participants, respectively. In multivariate analysis, patients with DM had higher risk for MI (hazard ratio [HR], 1.62; 95% confidence interval [CI], 1.45–1.81), ischemic stroke (HR, 1.39; 95% CI, 1.29–1.50), and all-cause death (HR, 1.52; 95% CI, 1.45–1.59) than those without DM. Patients with CKD had 1.56 times higher risk for MI, 1.12 times higher risk for ischemic stroke, and 1.34 times higher risk for death than those without CKD. However, the risk for MI, ischemic stroke, and all-cause death was not different between patients with and without a history of premature ASCVD.

Conclusion

DM and CKD, but not a history of premature ASCVD, could be considered as reasonable criteria of an extreme risk for ASCVD.

Low-Density Lipoprotein Cholesterol Level, Statin Use and Myocardial Infarction Risk in Young Adults

Objective

The consequences of blood lipid abnormalities for cardiovascular disease risk in young adults is unclear. Optimal lipid levels may also vary depending on whether a statin drug is taken. It aimed to determine whether the optimal lipid levels in young adults differ depending on statin use.

Methods

Using a nationally representative database from the Korean National Health Insurance System, 6,350,400 participants aged 20–39 years who underwent a health examination between 2009–2012 were followed through to 2018. The primary outcome was incident myocardial infarction (MI). We assessed the associations between prespecified lipid levels and MI risk according to statin use.

Results

Among participants not taking statins, low-density lipoprotein cholesterol (LDL-C) levels ≥120 mg/dL were significantly associated with MI risk (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.27–1.40) compared with statin nonusers with LDL-C <80 mg/dL. Statin users with LDL-C categories <80, 80–100, 100–120, and ≥120 mg/dL all had significantly higher MI risk compared with statin nonusers with LDL-C <80 mg/dL; these HRs (95% CIs) were 1.66 (1.39–1.99), 1.68 (1.36–2.09), 1.63 (1.31–2.02), and 2.32 (2.07–2.60), respectively.

Conclusion

Young adults taking statins have an increased MI risk compared with statin nonusers, even when they have similar LDL-C levels. Specific lipid targets may need to differ depending on statin use.

Nonalcoholic fatty liver disease and the risk of insulin-requiring gestational diabetes

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases; however, there has been little research into its impact on gestational diabetes mellitus (GDM).

METHODS

This study included 308,095 women registered in the Korean National Health Insurance Service database, who delivered between 2011 and 2015 and received a health examination within 52 weeks before pregnancy. Insulin-requiring GDM was defined as no insurance claims for diabetes mellitus and a fasting blood glucose level of < 126 mg/dL before pregnancy, and initiation of insulin treatment during pregnancy. A fatty liver index (FLI) was calculated using body mass index, waist circumference, and blood triglyceride and γ-glutamyl transferase levels. FLI scores < 30 ruled out hepatic steatosis, while FLI scores ≥ 60 indicated NAFLD.

RESULTS

The prevalence of NAFLD was 0.8% (2355/308,095) and 1984 (0.6%) subjects developed insulin-requiring GDM. FLIs of 30-59 and ≥ 60 were significantly associated with increased risk of insulin-requiring GDM (odds ratio [OR] 3.50; 95% confidence interval [CI] 2.99-4.10; OR 4.19; 95% CI 3.37-5.23), respectively. Further exploration of the association of FLI with GDM across FLI decile categories revealed a steady increase in OR across the categories. The association was more prominent among those without metabolic syndrome.

CONCLUSION

NAFLD in women is an independent risk factor for insulin-requiring GDM.