International Journal of Endocrinology

International Journal of Endocrinology / 2014 / Article
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Disease of Adrenal Glands

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Research Article | Open Access

Volume 2014 |Article ID 138653 |

Yuh-Feng Wang, Mei-Hua Chuang, Tzyy-Ling Chuang, Kung-Yung Huang, Shaw-Ruey Lyu, Chih-Yuan Huang, Ching-Chih Lee, "CHADS2 Scores in the Prediction of Major Adverse Cardiovascular Events in Patients with Cushing’s Syndrome", International Journal of Endocrinology, vol. 2014, Article ID 138653, 5 pages, 2014.

CHADS2 Scores in the Prediction of Major Adverse Cardiovascular Events in Patients with Cushing’s Syndrome

Academic Editor: Gian Paolo Rossi
Received02 Apr 2014
Revised08 Jun 2014
Accepted09 Jun 2014
Published01 Jul 2014


Vascular events are one of the major causes of death in case of Cushing’s syndrome (CS). However, due to the relative low frequency of CS, it is hard to perform a risk assessment for these events. As represented congestive heart failure (C), hypertension (H), age (A), diabetes (D), and stroke (S), the CHADS2 score is now accepted to classify the risk of major adverse cardiovascular events (MACEs) in patients with atrial fibrillation. In this study, participants were enrolled from the National Health Research Institute Database (NHIRD) of Taiwan, and we reviewed 551 patients with their sequential clinically diagnosed CS data between 2002 and 2009 in relation to MACEs risk using CHADS2 score. Good correlation could be identified between the CS and CHADS2 score . Our results show that patients with CS show significantly higher risk of vascular events and the CHADS2 score could be applied for MACEs evaluation. Adequate lifestyle modifications and aggressive cardiovascular risks treatment are suggested for CS patients with higher CHADS2 score.

1. Introduction

Cushing’s syndrome (CS) represents the pattern of symptoms and signs caused by prolonged exposure of inappropriately high levels of the hormone cortisol [13]. It is relatively rare and most commonly affects adults between the ages of 20 and 50, affecting approximately 2 to 3 per million people in each year [4]. Obesity has been linked with this diagnosis. Other signs and symptoms include thinning of the reddish purple striae, plethora, proximal muscle weakness, weight gain, bruising with no obvious trauma, hypertension, diabetes, and osteoporosis [48]. Vascular events, either cardiovascular or cerebrovascular, are the major causes of death [4, 6, 7, 9]. However, due to the relatively low incidents of CS, it is hard to make a risk assessment for these events.

The most frequently used schema designed to stratify risk of thromboembolism in patients with atrial fibrillation is CHADS2 score [1014], which closely correlate major adverse cardiovascular events (MACEs), such as myocardial infarction, stroke, and mortality risk. Clinically, CHADS2 score is simple to use, with one point given for congestive heart failure, hypertension, age, and diabetes and two points for stroke or transient ischemic attack. Higher score has been associated with the risk of developing MACEs and for these patients, early anticoagulation therapy should be recommended [13, 15].

Recent studies have indicated that the risks of MACEs other than atrial fibrillation have been reported and the risk assessment was performed by using CHADS2 [1618]. In this study, participants with clinically diagnosed CS were adopted from the NHIRD of Taiwan. This database enrolls up to 99% of the 23 million residents of Taiwan who receive medical care through the National Health Insurance (NHI) program which consists of ambulatory and inpatient care records and the registration files of the insured. The aim of the study was to explore the relationship between CS and the risk of vascular events. Furthermore, we evaluated the predictive value of CHADS2 on MACEs in patients with CS.

2. Materials and Methods

2.1. Study Population

This observational study was conducted in a retrospective cohort of the Taiwanese population from the year 2002 to 2009, enrolled in NHIRD in Taiwan. The National Health Insurance Bureau of Taiwan randomly reviews the charts of 1 out of every 100 ambulatory cases and one out of every 20 inpatient cases; it also performs patient interviews to verify the accuracy of the diagnosis. In patients ≥18 years of age diagnosed with Cushing’s syndrome (ICD-9-CM codes 255.0) between the years 2002 and 2009 were recruited for this study. CS patients with stroke and previous acute myocardial infarction were excluded.

2.2. Risk Score Calculation

The CHADS2 scores were calculated for each patient by assigning 1 point each for the presence of chronic heart failure, hypertension, age below 75 years, and diabetes and by assigning 2 points for history of stroke or transient ischemic attack (TIA). The study patients were divided into 4 groups by their CHADS2 scores: 0, 1, 2, and ≧3, respectively.

2.3. Study End Point and Patient Followup

Mortality data covering the years from 2002 to 2009 were used to calculate the mortality rate in each group. Each patient was tracked for 5 years from the time of their first diagnosis using administrative data to identify all patients who had MACEs such as myocardial infarction, stroke, and mortality or censored during the study period.

2.4. Statistical Analysis

SPSS (version 15, SPSS Inc., Chicago, IL, USA) was used for data analysis. Receiver operating characteristics curve was used to assess the prediction accuracy for MACEs by using CHADS2 score and plots of observed and predicted MACEs were presented. The cumulative rates of MACEs were estimated using the log rank test to examine the differences in the risk of mortality between different groups among the CS patients. The Cox proportional hazards regression model was used to compare the outcomes between different risk groups. We calculated hazard ratios (HR) along with 95% confidence intervals (CI) using a significance level of 0.05. A two-sided value () was used to determine statistical significance.

3. Results

There are 551 patients diagnosed with CS from 2002 to 2009 within the NHIRD. The number of patients, age, gender, and distribution of number of patients in different CHADS2 score groups are shown in Table 1. The mean age at diagnosis was years. 67.9% of patients were female. The mean CHADS2 score was . Severe comorbidity (CHADS2 score ≧3) was noted in 10.7% in all CS patients.

VariablesStudy population

Total551 (100)
Mean age, years (±SD)
CHADS2 score
 Mean ± SD
 0271 (49.2)
 1121 (22.0)
 2100 (18.1)
 ≧359 (10.7)
 Male177 (32.1)
 Female374 (67.9)
Hyperlipidemia126 (22.9)
Chronic kidney disease26 (4.7)
Coronary artery disease42 (7.6)
Atrial fibrillation5 (0.9)
Socioeconomic status
 Low227 (50.3)
 Moderate195 (35.4)
 High79 (14.3)

Figure 1 showed that the c-statistics was 0.795 (95% CI, 0.724–0.866). Figure 2(a) was the Kaplan-Meier survival curves. CS patients with higher CHADS2 score were more likely to have MACEs (). We further divided the CS patients into four groups based on the CHADS2 scores (Table 2). CS patients with a score of ≧3 are associated with the highest rate in MACEs (Figure 2(b), ).

Case (%)P value Case (%)P value

CHADS2 score<0.001<0.001
 0 ( )77 5 (6.5) 194 1 (0.5)
 1 ( )41 6 (14.6) 80 2 (2.5)
 2 ( )38 5 (13.2) 62 8 (12.9)
 ≧3 ( )21 9 (42.9) 38 12 (31.6)

In multivariate analysis, each additional CHADS2 score is associated with 1.63-fold (95% CI, 1.29–2.06) increased risk for MACEs when CHADS2 score is a continuous variable (Table 3, model A). In model B of Table 3, where CHADS2 is an ordinal variable and divided into three groups, patients with the score ≧3 remained as an independent prognostic factor for the risk of MACEs with hazard ratios of 7.16 (95% CI, 2.31–22.15), compared with CHADS2 0-1 after adjusting with other factors. As compared to male, female is associated with decreased risk for MACEs in patients with CS (model B, adjusted HR 0.45, 95% CI 0.25–0.81, and ). Age is associated with increased risk for MACEs (model B, adjusted HR 1.05, 95% CI 1.00–1.05, and ).

Model A*Model B**
Adjusted HR95% CI valueAdjusted HR95% CI value

CHADS2 score1.631.29–2.06<0.001
Chronic kidney disease1.26 0.52–3.030.5991.350.58–3.140.484
Coronary artery disease1.440.67–3.090.3431.590.76–3.320.216
Atrial fibrillation1.170.24–5.530.8431.170.25–5.470.839
Socioeconomic status

Adjusted HR: adjusted hazard ratio; 95% CI: 95% confidence interval.
*Model A: CHADS2 score as continuous variable.
**Model B: CHADS2 score as ordinal variable.

4. Discussion

The main finding of this study is that the CHADS2 score can be useful in the evaluation of the global cardiovascular risk (i.e., MACEs and death) of patients with CS. We provide the general calculation of mortality and morbidity rate as well as a risk assessment for MACEs in cases of CS. We validated the application of CHADS2 score in the MACEs of CS patient for the accuracy of our prediction is 79.5%.

The strengths of these data are based on the fact that it was a nationwide population-based cross-sectional study, with nearly complete follow-up information about access to healthcare institutes, as well as the fact that the dataset was routinely monitored for diagnostic accuracy by the National Health Insurance Bureau of Taiwan. The National Health Insurance (NHI) program was conducted since 1995 which requires mandatory enrollment in the government-run, universal, single-payer insurance system and provides comprehensive benefits coverage. Currently, up to 99% of the 23 million residents of Taiwan receive medical care through this program. Over 97% of the hospitals and clinics in Taiwan are contracted to provide health care services [19], which are reimbursed by the Bureau of NHI, and all data related to these services are collected and stored into the NHIRD by the National Health Research Institutes to provide a comprehensive medical care record. The data consisted of ambulatory care records, inpatient care records, and the registration files of the insured. The dataset included all claims data from Taiwan’s NHI program, which was implemented as a means of financing health care for all Taiwanese citizens. The average age and gender distribution of CS patients were also compatible with a previous report [20].

There are many reports about the mortality and morbidity of CS that have been documented [2124]. However, due to the relative rarity of CS, data collection on the incidence, mortality, and cause of death is scarce. Our results show a 8.7% overall risk of MACEs in CS patients. Poor prognosis was demonstrated in 35.6% of the patients in high risk population (CHADS2 ≧3), 13.0% of the CHADS2 = 2, 6.6% of the CHADS2 = 1, and 2.2% in the cases of the CHADS2 = 0. Current guidelines for atrial fibrillation suggest that the CHADS2 is useful in the selection of antithrombotic therapy; therefore, those with high risk (CHADS2 score ≧2) would benefit from anticoagulation therapy. For those with low (score 0) or moderate (score 1) risk, aspirin may be an alternative given that the risk of bleeding caused by anticoagulation therapy may not justify its use [14]. Antithrombotic therapy is also essential for the CS patients within the high risk population.

Our study had several limitations related to the NHIRD database. The diagnoses of CS, AMI, and stroke were dependent on ICD codes used in the NHIRD database. Another limitation is that the design of the study is retrospective. Validation of scores in retrospective cohort presents always with several limitations that weaken the strength of the results. However, we believe the relatively large number of patients may compensate for these limitations. The National Health Insurance Bureau of Taiwan, however, has made every effort to verify the accuracy of diagnosis based upon random chart reviews and patient interviews. An additional limitation of the NHIRD database was its lack of information on tobacco use, dietary habits, metabolic profiles, or other behavioral factors, which may be risk factors for AMI among CS patients. Nonetheless, given the magnitude and statistical significance of the observed effects in this study, these limitations were unlikely to have compromised our results. In fact, the strength of our study lies in its large sample size. In addition, because the NHI has 99% coverage in Taiwan, our study had minimal risk of selection bias.

5. Conclusion

In the present study, CHADS2 score could be a good tool to predict the incidence of MACEs in patients with Cushing’s syndrome. Cardiovascular risks evaluation and management should be applied more aggressively for CS patients with CHADS2 score ≧3.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.


  1. F. Castinetti, I. Morange, B. Conte-Devolx, and T. Brue, “Cushings disease,” Orphanet Journal of Rare Diseases, vol. 7, no. 1, article 41, 2012. View at: Publisher Site | Google Scholar
  2. G. Obiols Alfonso, B. Biagetti Biagetti, A. Chacon Oreja, and J. Salvador Rodriguez, “Cushing's disease in 2012,” Endocrinología y Nutrición, vol. 61, no. 2, pp. 93–99, 2014. View at: Google Scholar
  3. X. Bertagna, L. Guignat, L. Groussin, and J. Bertherat, “Cushing's disease,” Best Practice and Research: Clinical Endocrinology and Metabolism, vol. 23, no. 5, pp. 607–623, 2009. View at: Publisher Site | Google Scholar
  4. L. K. Nieman, B. M. Biller, J. W. Findling et al., “The diagnosis of Cushing's syndrome: an Endocrine Society Clinical Practice Guideline,” The Journal of Clinical Endocrinology & Metabolism, vol. 93, no. 5, pp. 1526–1540, 2008. View at: Publisher Site | Google Scholar
  5. M. Minetto, G. Reimondo, G. Osella, M. Ventura, A. Angeli, and M. Terzolo, “Bone loss is more severe in primary adrenal than in pituitary-dependent Cushing's syndrome,” Osteoporosis International, vol. 15, no. 11, pp. 855–861, 2004. View at: Publisher Site | Google Scholar
  6. T. Mancini, B. Kola, F. Mantero, M. Boscaro, and G. Arnaldi, “High cardiovascular risk in patients with Cushing's syndrome according to 1999 WHO/ISH guidelines,” Clinical Endocrinology, vol. 61, no. 6, pp. 768–777, 2004. View at: Publisher Site | Google Scholar
  7. G. di Dalmazi, V. Vicennati, S. Garelli et al., “Cardiovascular events and mortality in patients with adrenal incidentalomas that are either non-secreting or associated with intermediate phenotype or subclinical Cushing's syndrome: a 15-year retrospective study,” The Lancet Diabetes & Endocrinology, 2014. View at: Google Scholar
  8. O. M. Dekkers, E. Horváth-Puhó, J. O. Jørgensen et al., “Multisystem morbidity and mortality in Cushing's syndrome: a cohort study,” The Journal of Clinical Endocrinology & Metabolism, vol. 98, no. 6, pp. 2277–2284, 2013. View at: Publisher Site | Google Scholar
  9. C. Steffensen, A. M. Bak, K. Zøylner Rubeck, and J. O. L. Jørgensen, “Epidemiology of Cushing's syndrome,” Neuroendocrinology, vol. 92, no. 1, pp. 1–5, 2010. View at: Publisher Site | Google Scholar
  10. L. Baruch, B. F. Gage, J. Horrow et al., “Can patients at elevated risk of stroke treated with anticoagulants be further risk stratified?” Stroke, vol. 38, no. 9, pp. 2459–2463, 2007. View at: Publisher Site | Google Scholar
  11. E. M. Hylek, C. Evans-Molina, C. Shea, L. E. Henault, and S. Regan, “Major hemorrhage and tolerability of warfarin in the first year of therapy among elderly patients with atrial fibrillation,” Circulation, vol. 115, no. 21, pp. 2689–2696, 2007. View at: Publisher Site | Google Scholar
  12. D. Poli, E. Antonucci, R. Marcucci et al., “Risk of bleeding in very old atrial fibrillation patients on warfarin: relationship with ageing and CHADS2 score,” Thrombosis Research, vol. 121, no. 3, pp. 347–352, 2007. View at: Publisher Site | Google Scholar
  13. V. Fuster, L. E. Ryden, and D. S. Cannom, “ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation–executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to Revise the 2001 Guidelines for the Management of Patients With Atrial Fibrillation),” Journal of the American College of Cardiology, vol. 48, no. 4, pp. 854–906, 2006. View at: Publisher Site | Google Scholar
  14. B. F. Gage, A. D. Waterman, W. Shannon, M. Boechler, M. W. Rich, and M. J. Radford, “Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation,” The Journal of the American Medical Association, vol. 285, no. 22, pp. 2864–2870, 2001. View at: Publisher Site | Google Scholar
  15. J. M. Ruiz-Nodar, F. Marín, S. Manzano-Fernández et al., “An evaluation of the CHADS2 stroke risk score in patients with atrial fibrillation who undergo percutaneous coronary revascularization,” Chest, vol. 139, no. 6, pp. 1402–1409, 2011. View at: Publisher Site | Google Scholar
  16. M. H. Ruwald, A. Ruwald, C. Jons et al., “Evaluation of the chads2 risk score on short- and long-term all-cause and cardiovascular mortality after syncope,” Clinical Cardiology, vol. 36, no. 5, pp. 262–268, 2013. View at: Publisher Site | Google Scholar
  17. F. Hornero, E. Martin, F. Paredes et al., “Stroke after coronary artery bypass grafting: preoperative predictive accuracies of CHADS2 and CHA2DS2VASc stroke risk stratification schemes,” The Journal of Thoracic and Cardiovascular Surgery, vol. 144, no. 6, pp. 1428–1435, 2012. View at: Publisher Site | Google Scholar
  18. C. Stöllberger, C. Wegner, and J. Finsterer, “CHADS2- and CHA2DS2VASc scores and embolic risk in left ventricular hypertrabeculation/noncompaction,” Journal of Stroke and Cerebrovascular Diseases, vol. 22, no. 6, pp. 709–712, 2013. View at: Publisher Site | Google Scholar
  19. T. L. Chiang, “Taiwan's 1995 health care reform,” Health Policy, vol. 39, no. 3, pp. 225–239, 1997. View at: Publisher Site | Google Scholar
  20. S.-C. Tung, P.-W. Wang, R.-T. Liu et al., “Clinical characteristics of endogenous cushings syndrome at a medical center in Southern Taiwan,” International Journal of Endocrinology, vol. 2013, Article ID 685375, 7 pages, 2013. View at: Publisher Site | Google Scholar
  21. M. Yaneva, K. Kalinov, and S. Zacharieva, “Mortality in Cushing's syndrome: data from 386 patients from a single tertiary referral center,” European Journal of Endocrinology, vol. 169, no. 5, pp. 621–627, 2013. View at: Publisher Site | Google Scholar
  22. G. Ntali, A. Asimakopoulou, T. Siamatras et al., “Mortality in Cushing's syndrome: systematic analysis of a large series with prolonged follow-up,” European Journal of Endocrinology, vol. 169, no. 5, pp. 715–723, 2013. View at: Publisher Site | Google Scholar
  23. D. Graversen, P. Vestergaard, K. Stochholm, C. H. Gravholt, and J. O. L. Jørgensen, “Mortality in Cushing's syndrome: a systematic review and meta-analysis,” European Journal of Internal Medicine, vol. 23, no. 3, pp. 278–282, 2012. View at: Publisher Site | Google Scholar
  24. M. J. Bolland, I. M. Holdaway, J. E. Berkeley et al., “Mortality and morbidity in Cushing's syndrome in New Zealand,” Clinical Endocrinology, vol. 75, no. 4, pp. 436–442, 2011. View at: Publisher Site | Google Scholar

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