- Email: [email protected]
Use of the CHADS2 score as a predictor of the risk of mortality in hypertensive patients. The FAPRES study
Med Clin (Barc). 2016;146(11):478–483
www.elsevier.es/medicinaclinica
Original article
Use of the CHADS2 score as a predictor of the risk of mortality in hypertensive patients. The FAPRES study夽 Elena Castilla a,∗ , Pedro Morillas a , Manuel Gómez a , Miguel Ahumada a , Marta Monteagudo a , Lorenzo Fácila b , Vicente Pallares c a b c
Servicio de Cardiología, Hospital General Universitario de Elche, Elche, Alicante, Spain Servicio de Cardiología, Hospital General de Valencia, Valencia, Spain Unidad de Vigilancia de la Salud, Unión de Mutuas, Departamento de Medicina, Universitat Jaume I, Castellón, Spain
a r t i c l e
i n f o
Article history: Received 2 November 2015 Accepted 3 March 2016 Available online 25 July 2016 Keywords: Cardiovascular mortality Hypertension Coagulation
a b s t r a c t Foundations and aim: The aim of this study is to analyze the CHADS2 score as a marker of the risk of mortality in hypertensive patients, with and without the presence of atrial fibrillation. Methods: We included 1003 hypertensive patients ≥65 years. Risk factors, and CHADS2 score were recorded among other factors, as well as clinical follow-up of number and type of deaths. Results: Mean age was 72.8 ± 5.8 years, and 47.5% were men. During follow-up there were 41 deaths, 20 were of cardiovascular origin. Patients with higher CHADS2 had a higher mortality: 1.5% CHADS2 = 1; 4.7% in CHADS2 = 2; 9.1% in CHADS2 = 3, and 7.8% in CHADS2 ≥ 4. Conclusions: The CHADS2 score can be a clinical instrument of easy application to identify hypertensive patients with a high risk of mortality. ˜ S.L.U. All rights reserved. © 2016 Elsevier Espana,
Uso de la escala CHADS2 como predictor de riesgo de mortalidad en pacientes hipertensos. El estudio FAPRES r e s u m e n Palabras clave: Mortalidad cardiovascular Hipertensión arterial Coagulación arterial
Fundamentos y objetivo: El objetivo del estudio es analizar la escala CHADS2 como marcador de riesgo de mortalidad en pacientes hipertensos, independientemente de la presencia o no de fibrilación auricular. ˜ Métodos: Se incluyó a 1.003 pacientes hipertensos ≥ 65 anos, recogiendo factores de riesgo y puntuación CHADS2 . Se realizó un seguimiento clínico de la mortalidad. ˜ Resultados: La media de edad de la población fue 72,8 ± 5,8 anos; el 47,5% eran varones. Durante el seguimiento hubo 41 muertes, 20 de origen cardiovascular. Los pacientes con mayor CHADS2 tuvieron una mayor mortalidad: 1,5% en CHADS2 = 1; 4,7% en CHADS2 = 2; 9,1% en CHADS2 = 3, y 7,8% en CHADS2 ≥ 4. Conclusiones: La puntuación CHADS2 puede ser un instrumento clínico de sencilla aplicación para identificar pacientes hipertensos con alto riesgo de mortalidad. ˜ S.L.U. Todos los derechos reservados. © 2016 Elsevier Espana,
Introduction
夽 Please cite this article as: Castilla E, Morillas P, Gómez M, Ahumada M, Monteagudo M, Fácila L, et al. Uso de la escala CHADS2 como predictor de riesgo de mortalidad en pacientes hipertensos. El estudio FAPRES. Med Clin (Barc). 2016;146:478–483. ∗ Corresponding author. E-mail address: elena [email protected] (E. Castilla). ˜ S.L.U. All rights reserved. 2387-0206/© 2016 Elsevier Espana,
The CHADS2 score – heart failure, hypertension, age, diabetes, stroke (double) – is the recommended clinical score for stroke risk stratification in patients with non-valvular atrial fibrillation and used to determine if anticoagulant therapy is indicated.1 Today it is widely known and used in routine clinical practice because of its uncomplicated operation and reproducibility.2,3 The scoring criteria that make it up are also important risk factors for atherosclerotic disease and cardiovascular disease in general.4 Based on this premise, it is possible that this score can
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
have important applications for predicting a wider range of cardiovascular events beyond its usual field of use, that is, atrial fibrillation. In this regard, a recent study showed that the CHADS2 score predicted the risk of stroke and death in patients with acute myocardial infarction, especially those without atrial fibrillation.5 It has also demonstrated its predictive value for cardiovascular mortality in high-risk patients without atrial fibrillation.6 The aim of this study is to analyze the role of this score as a risk marker for mortality in a sample of hypertensive patients aged ≥65 years from an area along the Mediterranean, regardless of the presence or absence of atrial fibrillation. Methods The FAPRES record (atrial fibrillation + blood pressure) is an epidemiologic, observational, multicenter study conducted within a healthcare setting, designed to determine the prevalence of atrial fibrillation in patients over 65 years with a clinical diagnosis of hypertension in the Valencian Region. 69 researchers from primary care and hypertension hospital units located in Alicante, Castellon and Valencia participated in it, in a proportion which was in line with the population weight of each of the 3 provinces. A detailed description of the study and a definition of the variables have been previously published.7 A total of 1028 patients were included in the baseline study. The researchers were invited to conduct a clinical follow-up of these patients for 2 years, recording any major cardiovascular events, including mortality. A written informed consent was obtained from all patients and the study was conducted following the principles of the Declaration of Helsinki, after approval by a hospital ethics committee (Clinical Research Ethics Committee of the General University Hospital of Castellón). Study population All patients enrolled in the FAPRES study that had completed the follow-up period were included in this study. Their risk factors and cardiovascular history were collected using a standardized questionnaire. Any patient who had a history of high cholesterol together with a low density of lipoproteins (>160 mg/dl) or had already been treated with a diet or lipid-lowering drugs8 was considered as having hypercholesterolemia. Any patient with a history of diabetes mellitus or who were already receiving treatment for that condition was considered diabetic. Any patient who smoked some kind of tobacco (cigarettes, pipes, cigars or non-inhaled tobacco) on a daily basis during the previous month was considered a smoker.9 On the contrary, the patient who had stopped smoking at least one year before was considered a non-smoker. Anyone who recognized actively walking during at least 30 min/day or doing some kind of sport 3 days/week10 was considered as someone who practiced physical exercise. Any drug treatment the patient was receiving at the time of the consultation was recorded, specifically any antihypertensive drugs and any cardio embolic prevention treatment (anticoagulants and/or antiplatelet agents). Also, a physical examination was performed, collecting anthropometric data (weight, height and waist circumference) and blood pressure was taken. Blood pressure was measured following the recommendations of clinical practice guidelines,11 taking it 5 min after the patient had rested, on 2 occasions separated by 2 min and in a sitting position, to calculate the arithmetic average of both. To do so, calibrated and validated automated devices were used. Blood test data were collected from medical records whenever these were available for the last 6 months, otherwise they were requested from the laboratory at the time. Glomerular filtration rate was determined by the Modification of Diet in Renal Disease Study formula. The questionnaire together with the medical history was sent through a contract
479
research organization for automatic data processing. An electrocardiogram was also performed to all patients, which was then submitted by ordinary mail to a reference center, where it was independently analyzed by 2 expert cardiologists who were blinded to the clinical data of patients. The presence of atrial fibrillation and left ventricular hypertrophy was assessed using the Sokolow, Cornell or ventricular overload criteria. A random external audit of 10% of the questionnaires registered was performed in order to verify the reliability of the data. The patient’s CHADS2 score was determined (heart failure, hypertension, 75 years of age, diabetes mellitus [one point each] and prior stroke or transient ischemic attack [TIA] [2 points])2 and they were classified into 4 groups according to their score: 1, 2, 3 and ≥4 points. Patients underwent a follow-up, collecting both overall as well as cardiovascular mortality. Statistic analysis All data collected in the study are described in terms of central tendency, measures of dispersion and relative frequencies. The Student t test or ANOVA was used to compare quantitative variables between groups, and for comparison of categorical variables, the 2 test. Overall survival was calculated according to the CHADS2 score by the Kaplan–Meier method. To determine the variables independently associated with the overall and cardiovascular mortality during follow-up, a multivariate logistic regression analysis was conducted, in which all significant variables of the univariate analysis and those with recognized clinical relevance were included, together with the CHADS2 score. To analyze the validity of the CHADS2 score in calculating the mortality risk, the receiver operating characteristic (ROC) curve was determined and the area under the curve was calculated. When p < 0.05, it was considered statistically significant. An SPSS® statistical program was used 21 version was used for the analysis. Results Of the 1028 hypertensive patients at baseline in the FAPRES study, 1003 completed follow-up (97.5%), with a median of 804 (723–895) days. The average age of the population was 72.8 ± 5.8 years and 47.5% were male. 48.3% of patients had a history of hypercholesterolemia, 27.5% had diabetes mellitus and 9% were active smokers. Also, 60 patients had a history of renal failure (6%), 75, of prior stroke/TIA (7.5%), 72 cases were diagnosed with heart failure (7.2%), 146 of ischemic heart disease (14.5%) and 6.9% had atrial fibrillation on the electrocardiogram. After calculating the CHADS2 score it was observed that 466 cases (46.5%) had a value of one point; 340 (36.9%), a value of 2 points, 146 (14.6%) of 3 points, and 51 (5.1%), higher than or equal to 4 points. Table 1 shows the main characteristics of these populations. Patients with a high CHADS2 score were significantly older and had a higher prevalence of risk factors, as well as more cardiovascular disease (especially heart failure, ischemic heart disease, ventricular hypertrophy, atrial fibrillation and previous stroke). They also had lower plasma concentrations of cholesterol bound to high density lipoproteins (HDL, “high density lipoprotein”) and worse glomerular filtration. Regarding the treatment being administered, no significant differences were found in the use of angiotensin-converting enzyme inhibitors, angiotensin receptor antagonists, ii, beta blockers or diuretics between the 4 populations; however, patients with a higher CHADS2 score received calcium channel blockers, statins, anticoagulants and antiplatelet agents more frequently. In short, if we compare patients with a CHADS2 score of 3 or ≥4 with respect to those who have a CHADS2 = 2, the first ones clearly have a worse risk profile.
480
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
Table 1 Baseline characteristics of the population according to the CHADS2 score. Variable
CHADS2 = 1 (n = 466)
CHADS2 = 2 (n = 340)
CHADS2 = 3 (n = 146)
CHADS2 ≥ 4 (n = 51)
p
Age (in years) Men Smoking Diabetes mellitus Hypercholesterolemia Ischemic heart disease Heart failure Kidney failure Previous stroke Physical exercise Evolution HBP (in years) SBP in clinic (mmHg) DBP in clinic (mmHg) BMI Hemoglobin (g/dl) Glucose (mg/dl) c-LDL (mg/dl) c-HDL (mg/dl) Glomerular filtration rate (ml/min) ECG LVHa Atrial fibrillation in ECG
69.5 ± 3.4 207 (44.4) 45 (9.7) 2 (0.4) 208 (44.6) 48 (10.3) 1 (0.2) 15 (3.2) 1 (0.2) 196 (42.1) 9.2 ± 9.2 146.4 ± 18.5 93.1 ± 10.1 29.2 ± 3.9 13.7 ± 1.5 98.6 ± 18 124.1 ± 32.7 54.4 ± 12.6 78.1 ± 21.3 62 (13.3) 20 (4.3)
75 ± 6.1 166 (48.8) 30 (8.8) 150 (44.1) 165 (48.5) 56 (16.5) 19 (5.6) 27 (7.9) 0 (0) 111 (32.6) 12 ± 8.7 146.9 ± 19.2 80.1 ± 11.2 29.2 ± 4.4 13.4 ± 1.7 115.4 ± 37.2 117.3 ± 32.8 51.8 ± 12.8 72.8 ± 22.1 64 (18.8) 17 (5)
77.2 ± 5.3 72 (49.3) 13 (8.9) 90 (61.6) 74 (50.7) 29 (19.9) 37 (14.6) 13 (8.9) 30 (20.5) 43 (29.5) 12.8 ± 8.1 149.9 ± 19 77.8 ± 11.1 28.5 ± 4.5 13.3 ± 2 125.1 ± 38.8 111.1 ± 36.1 51.7 ± 14.8 72.1 ± 25.9 37 (25.3) 23 (15.8)
76.7 ± 4.4 31 (60.8) 2 (3.9) 34 (66.7) 37 (72.5) 16 (25.5) 15 (29.4) 5 (9.8) 44 (86.3) 19 (37.3) 13.3 ± 9.5 146.4 ± 19.8 77.6 ± 12.8 29.1 ± 4.2 13.3 ± 2 108.5 ± 32 100.9 ± 36.5 47.7 ± 10.6 58.3 ± 19.4 9 (17.6) 9 (17.6)
<0.001 0.12 0.60 <0.001 0.002 <0.001 <0.001 0.007 <0.001 0.009 <0.001 0.72 <0.001 0.34 0.01 <0.001 <0.001 0.001 <0.001 0.006 <0.001
c-HDL: cholesterol bound to high density lipoproteins; c-LDL: cholesterol bound to low density lipoproteins; ECG: electrocardiogram; HBP: high blood pressure; LVH: left ventricular hypertrophy; BMI: body mass index; DBP: diastolic blood pressure; SBP, systolic blood pressure. Data are expressed as n (%) or mean ± standard deviation. a Sokolow or Cornell criteria or ventricular overload.
During follow-up, 41 deaths occurred, 20 of which were of cardiovascular origin. Patients who died were older and had a history of heart disease and worst CHADS2 score (2.39 ± 0.94 versus 1.77 ± 0.92; p < 0.05); on the contrary, they had lower HDL plasma concentrations and practiced less physical exercise. There were no differences in the prevalence of diabetes mellitus, smoking or hypercholesterolemia between the two populations (Table 2). Moreover, it was observed that the patients who died were taking more anticoagulants (14.6 versus 6.10%; p < 0.05) and digoxin (4.9 versus 0.70%, p < 0.05), with no difference in antihypertensive treatment or the use of statins between the two populations. Patients with higher CHADS2 had a significantly higher mortality: 1.5% in CHADS2 = 1; 4.7% in CHADS2 = 2; 9.1% in CHADS2 = 3
and 7.8% in CHADS2 ≥ 4. Figs. 1 and 2 show the Kaplan–Meier curves, reflecting the higher mortality (overall and cardiovascular) of patients with higher CHADS scores2 (log rank test, p < 0.001). In the multivariate analysis, risk factors associated with overall mortality were history of ischemic heart disease, male sex and CHADS2 score, with increased risk for patients with values ≥3 (Table 3). By contrast, protective factors associated with overall mortality were a history of high cholesterol, physical exercise and female sex. Very similar data were found in cardiovascular mortality (Table 4). The area under the ROC curve of the CHADS2 score for the risk of overall death was low (0.68; 95% confidence interval [95% CI] 0.61–0.76; p < 0.05), and moderate for cardiovascular death (0.78, 95% CI from 0.69 to 0.86; p < 0.05) (Figs. 3 and 4).
Table 2 Comparative study between patients according to follow-up mortality. Variable
Deaths n = 41
Living n = 962
p
Age (in years) Men Smoking Diabetes mellitus Hypercholesterolemia Ischemic heart disease Heart failure Kidney failure Previous stroke Physical exercise Evolution HBP (in years) SBP in clinic (mmHg) DBP in clinic (mmHg) BMI Hemoglobin (g/dl) Glucose (mg/dl) c-LDL (mg/dl) c-HDL (mg/dl) Glomerular filtration rate (ml/min) ECG LVHa Atrial fibrillation in ECG CHADS2 score
77.29 ± 5.7 20 (65.9) 5 (12.2) 14 (34.1) 14 (34.1) 15 (36.6) 10 (24.4) 4 (9.8) 5 (12.2) 5 (12.2) 12 ± 7.5 147.6 ± 20 76.3 ± 8.1 28.7 ± 24.5 13.5 ± 1.7 109.5 ± 25.2 112.6 ± 32.5 46.9 ± 9.46 71.6 ± 32.4 10 (24.4) 5 (12.2) 2.39 ± 0.94
72.7 ± 5.1 449 (65.6) 85 (12.2) 262 (27.2) 470 (48.9) 131 (13.6) 62 (6.4) 56 (5.8) 70 (7.3) 364 (37.8) 10.88 ± 8.28 146.6 ± 18.8 81.2 ± 11 29.1 ± 4.19 13.5 ± 1.7 108.54 ± 32.9 118.83 ± 34.1 53 ± 13 75 ± 21.9 162 (16.8) 64 (6.7) 1.77 ± 0.92
<0.001 0.12 0.30 0.33 0.65 <0.001 <0.001 0.29 0.24 0.001 0.39 0.75 0.005 0.54 0.35 0.35 0.27 0.006 0.32 0.20 0.17 0.03
c-HDL: cholesterol bound to high density lipoproteins; c-LDL: cholesterol bound to low density lipoproteins; ECG: electrocardiogram; HBP: high blood pressure; LVH: left ventricular hypertrophy; BMI: body mass index; DBP: diastolic blood pressure; SBP, systolic blood pressure. Data are expressed as n (%) or mean ± standard deviation. a Sokolow or Cornell criteria or ventricular overload.
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
Table 3 Multivariate analysis. Factors associated with overall mortality during follow-up.
1.00
0.95
Survival
481
0.90
0.85
Log Rank test 22.19 (P<.001) 0.80 0
250
500
750
1000
1250
Follow-up (days) CHADS group CHADS2 =1 CHADS2 =2 CHADS2 =3 CHADS2 ≥4 Fig. 1. Kaplan–Meier curve of overall mortality according to CHADS2 score.
Discussion This study is one of the first in assessing the CHADS2 score prognostic impact in order to establish mortality risk in a Mediterranean cohort of hypertensive patients regardless of the presence or absence of atrial fibrillation. The results show that CHADS2 is a good predictor of overall and cardiovascular mortality, so that patients with a ≥3 score have an increased risk of mortality in the medium term. The importance of hypertension as one of the main risk factors involved in the development of cardiovascular disease has
Variable
Overall mortality, OR (95% CI)
p
Physical exercise Female Hypercholesterolemia Ischemic heart disease CHADS2 = 2a CHADS2 = 3a CHADS2 ≥ 4a
0.39 (0.19–0.82) 0.15 (0.05–0.46) 0.32 (0.15–0.69) 3.61 (1.7–7.6) 2.93 (1.10–7.82) 6.35 (2.25–17.89) 6.43 (1.62–25.57)
0.0013 0.001 0.004 0.001 0.03 <0.001 0.008
95% CI: 95% confidence interval; OR: odds ratio. The variables included in the model are: sex, smoking, high cholesterol, physical exercise, atrial fibrillation, angiotensin-converting enzyme inhibitors, angiotensin ii receptor antagonists, Beta blockers, statins, antiplatelet agents, anticoagulants, ischemic heart disease, mean systolic and diastolic blood pressure, glomerular filtration rate, body mass index and CHADS2 score. a Regarding CHADS2 = 1. Table 4 Multivariate analysis. Factors associated with cardiovascular mortality during follow-up. Variable
Cardiovascular mortality, OR (95% CI)
p
Physical exercise Female Hypercholesterolemia Ischemic heart disease CHADS2 = 2a CHADS2 = 3a CHADS2 ≥ 4a
0.36 (0.13–1.05) 0.09 (0.01–0.63) 0.21 (0.07–0.63) 6.18 (2.22–17.21) 7.31 (0.87–61.29) 24.4 (2.96–201.33) 33.12 (3.15–347.82)
0.063 0.016 0.006 <0.001 0.066 0.003 0.004
95% CI: 95% confidence interval; OR: odds ratio. The variables included in the model are: sex, smoking, high cholesterol, physical exercise, atrial fibrillation, angiotensin-converting enzyme inhibitors, angiotensin ii receptor antagonists, Beta blockers, statins, antiplatelet agents, anticoagulants, ischemic heart disease, mean systolic and diastolic blood pressure, glomerular filtration rate, body mass index and CHADS2 score. a Regarding CHADS2 = 1.
been widely demonstrated and also involves a major public health problem. In addition, its association with other cardiovascular risk factors exponentially increases the risk of cardiovascular events and cardiovascular mortality.12 This knowledge has led to the widespread development of different risk assessment scales13,14 and therapeutic strategies in recent decades, so as to reduce its
1.00 1.0
0.8 0.96
Sensitivity
Cumulative survival
0.98
0.94
0.92
0.6
0.4
Log Rank test 24.8 (P<.001)
0.90 0
250
500
750
1000
1250
0.2
AUC P<.001
Follow-up (days) CHADS group CHADS2 =1 CHADS2 =2 CHADS2 =3 CHADS2 ≥4 Fig. 2. Kaplan–Meier curve of cardiovascular mortality according to CHADS2 score.
0.0 0.0
0.2
0.4
0.6
0.8
1.0
Specificity Fig. 3. Receiver operating characteristic curve to predict the risk of overall mortality by CHADS2 score.
482
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483 1.0
0.8
Sensitivity
0.6
0.4
0.2
AUC P<.001 0.0 0.0
0.2
0.4
0.6
0.8
1.0
Specificity Fig. 4. Receiver operating characteristic curve to predict the risk of cardiovascular mortality by CHADS2 score.
incidence, mortality and the social and health costs involved. Having a tool that can predict the risk of death in this hypertensive patient’s population can help in this task.15 The CHADS2 score4 was originally developed as a model for predicting the risk of stroke in patients with non-valvular atrial fibrillation.1,3 However, in recent years its use has expanded beyond the typical atrial fibrillation setting,16,17 and presents some advantages over other scales (SCORE or Framingham), such as the inclusion of older patients and less complexity in everyday use. Henriksson et al. have applied this score to a wide range of patients surviving a stroke included in the Swedish Stroke Registry, and demonstrate that the risk of mortality 5 years after a cerebral episode increases gradual and linearly with the CHADS2 score, both for patients with atrial fibrillation and sinus rhythm.18 These data have been recently confirmed in other studies, showing a higher mortality and greater recurrence of stroke and cardiovascular events in patients with stroke and a score ≥2, regardless of whether there is atrial fibrillation or not.19,20 Recently, our group has also demonstrated the association between CHADS2 and the risk of stroke in hypertensive patients with sinus rhythm, so that patients with CHADS2 ≥ 4 had 9 times more risk of stroke.21 The role of CHADS2 score has also been investigated in the field of ischemic heart disease. Poci et al. have shown that high CHADS2 scores at the time of admission due to acute coronary syndrome were associated to an increased risk of stroke-induced hospitalization and increased mortality during follow-up.5 In the present study we extend the usage scenario of that score to the field of hypertension, one of the most common risk factors and of an increased risk of cardiovascular events, and demonstrate the association between CHADS2 and medium term risk of both overall as well as cardiovascular mortality in a sample of hypertensive patients aged ≥65 years, with a progressive increase proportional to the increasing CHADS2 value. This can provide valuable support when using this attractive and simple model for risk prediction in our midst. There are several potential mechanisms that may explain the ability of CHADS2 to predict the risk of mortality in hypertensive patients regardless of the presence of atrial fibrillation. Clearly, some of the score components make up cardiovascular risk factors
individually and we can get to predict long-term mortality as we can quantify their importance through a score and by associating them, as shown by our study. In his work, Henriksson et al. highlighted the ability of the score to determine post-stroke mortality at 6 months regardless of the presence of atrial fibrillation, mainly due to the great weight of 2 components, age and heart failure, and suggested that they should have a higher value.15 A paradoxical association between cholesterol and lower mortality in hypertensive patients stands out in our results, against the evidence held by large primary and secondary prevention studies published to date.22,23 However, some recent studies in the elderly have also shown that lack of association between hypercholesterolemia and a worse cardiovascular prognosis, especially in women.24 It is likely that what is really important is not the presence of dyslipidaemia itself, but the time of progression of the same, without being able to rule out that elderly patients who have participated in the study have some resistance to hypercholesterolemia producing cardiovascular disease in their case. The study has some limitations. First, there is a selection bias, since patients included in the study were those who came spontaneously to the health system, so our findings cannot be extrapolated to other scenarios. On the other hand, there is no second independent validation cohort confirming clinical prediction results obtained in our sample. Finally, our analysis is not a study of causality, so it does not allow us to establish a cause-effect relationship, but, rather, a significant association. In summary, our study shows that the CHADS2 score can be an easy-to-apply clinical tool for everyday clinical practice, which does not need too many resources to identify hypertensive patients with a high risk of mortality. It also raises the question of whether the cases with high CHADS2 scores could benefit from more intensive preventive treatment or therapy to improve survival, reason why it would be advisable to conduct studies in this regard. Conflict of interest None. Acknowledgements We would like to thank Lacer laboratories for their contributions and altruistic help in this project. To all participating researchers, without whose daily work and effort the study would not have been possible. Appendix. FAPRES registry researchers Juan Alberola, Vicente Javier; Maestre Amat, Luis; Mateo ˜ Liminana, Jose Manuel; Monleon Gomez, Jose; Montagud Moncho, Miguel; Guinot Martinez, Enrique; Gamon Pastor, Jose Blas; Salanova Penalba, Alejandro; Sanchis Domenech, Carlos; Pallares Carratala, Vicente; Palacios del Cerro, Antonio; Perez Martinez, Rafael; Baudet Dejean, Chantal; Perez Alonso, Manuel; Facila Rubio, Lorenzo; Sipan Sarrion, Yolanda; Saro Perez, Eugenia; Villaro Gumpert, Juan; Cabrera Ferriols, M. Angeles; Fraile, Belen; Carbonell Franco, Francisco; Cornejo Mari, Francisco Javier; Bar˜ bera Comes, Javier; Quiles Anon, Fernando; Llisterri Caro, Jose Luis; Almenar Cubells, Enrique; Casado Gonzalez, Joaquin; Godoy Rocati, Diego; Martinez Guerola, Carmen; Bonet Garcia, Jorge Alejo; Blazquez Encinar, Julio Cesar; Botella Estrada, Carlos; Saen lcoy, Montepio; Almarcha Perez, Natividad; Salanova Chilet, Lorena; Torres Ferrando, Miquel; Debon Belda, Manuel; Fluixa Carrascosa, Carlos; Aznar Baset, Lucia; Vivancos Aparicio, Diego; ˜ Pineda Cuenca, Manuel; Obarrio Moreno, Alicia; Nunez Jorge, ˜ Aracil, Manuel; Balanza Carlos; Matoses Nacher, Daniel; Bano
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
˜ Forcada, Enrique; Garzon, Alicia; Garcia Palomar, Carlos; Pena ˜ Raga Casasus, Jose; Martinez Lahuerta, Juan; Mendizabal Nunez, Andrea; Santos Alonso, Eufrosina; Corbi Pascual, Miguel; Lillo Sanchez, Antonio; Martorell Adsuara, Vicente; Sanchez Ruiz, Tomas; Ortiz Diaz, Francisco; Llinares Orts, Jose Francisco; Lahoz Ferrer, Julio; Morillas Blasco, Pedro; Pertusa Martinez, Salvador; Manclus Montoya, Carlos; Adria Mico, Jose Manuel; Llaudes Soler, Ricardo; Castillo, Jesus; Llopis Martinez, Francisco; Ruiz de la Prada Abarzuza, Ignacio; Nebot Rico, Lidia. References 1. Lip GY. Stroke and bleeding risk assessment in atrial fibrillation: when, how, and why? Eur Heart J. 2013;34:1041–9. 2. Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285:2864–70. 3. Ruiz M, Romo E, Mesa D, Delgado M, Anguita M, López A, et al. Predicción de eventos embólicos en pacientes con fibrilación auricular no valvular: evaluación del score CHADS2 en una población mediterránea. Rev Esp Cardiol. 2008;61:29–35. 4. Skanes AC, Healey JS, Cairns JA, Dorian P, Gillis AM, McMurtry MS, et al. Focused 2012 update of the Canadian Cardiovascular Society atrial fibrillation guidelines: recommendations for stroke prevention and rate/rhythm control. Can J Cardiol. 2012;28:125–36. 5. Poci D, Hartford M, Karlsson T, Herlitz J, Edvardsson N, Caidahl K. Role of the CHADS2 score in acute coronary syndromes: risk of subsequent death or stroke in patients with and without atrial fibrillation. Chest. 2012;141:1431–40. 6. Chan Y, Yiu K, Lau K, Yiu Y, Li S, Lam T, et al. The CHADS2 and CHA2DS2-VASc scores predict adverse vascular function, ischemic stroke and cardiovascular death in high-risk patients without atrial fibrillation: role of incorporating PR prolongation. Atherosclerosis. 2014;237:504–13. 7. Morillas P, Pallarés V, Llisterri JL, Sanchis C, Sánchez T, Fácila L, et al. Prevalencia de fibrilación auricular y uso de fármacos antritrombóticos en el paciente ˜ El registro FAPRES. Rev Esp Cardiol. 2010;63:943–50. hipertenso ≥ 65 anos. 8. National Cholesterol Education Program (NCEP) Expert panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation. 2002;106:3143–421. 9. World Health Organization. Guidelines for controlling and monitoring the tobacco epidemic. Geneva: WHO; 1998. p. 76–101. 10. Villar F, Maiques A, Brotons C, Torcal J, Lorenzo A, Vilaseca J, et al. Prevención cardiovascular en atención primaria. Aten Primaria. 2001;28 Suppl. 2:S13–36. 11. Mancia G, Fagard R, Narkiewicz K, Redón J, Zanchetti A, Böhm M, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the task force
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
483
for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2013;31:1281–357. Weber MA, Bakris GL, Hester A, Weir MR, Hua TA, Zappe D, et al. Systolic blood pressure and cardiovascular outcomes during treatment of hypertension. Am J Med. 2013;126:501–8. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Memotti A, de Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24:987–1003. Mancia G, de Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G, et al. 2007 guidelines for the management of arterial hypertension: the task force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2007;25:1105–87. Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest. 2010;137:263–72. Hsu PC, Lin TH, Lee WH, Chu CY, Chiu CA, Lee HH, et al. Association between the CHADS2 score and an ankle-brachial index of <0.9 in patients without atrial fibrillation. J Atheroscler Thromb. 2014;21:322–8. Hoshino T, Ishizuka K, Shimizu S, Uchiyama S. CHADS2 score predicts functional outcome of stroke in patients with a history of coronary artery disease. J Neurol Sci. 2013;331:57–60. Henriksson KM, Farahmand B, Johansson S, Asberg S, Terent A, Edvardsson N. Survival after stroke – the impact of CHADS2 score and atrial fibrillation. Int J Cardiol. 2010;141:18–23. Tu HT, Campbell BC, Meretoja A, Churilov L, Lees KR, Donnan GA, et al. Prestroke CHADS2 and CHA2DS2-VASc scores are useful in stratifying three-month outcomes in patients with and without atrial fibrillation. Cerebrovasc Dis. 2013;36:273–80. Ntaios G, Lip GY, Makaritsis K, Papavasileiou V, Vemmou A, Koroboki E, et al. CHADS2, CHA2DS2-VASc, and long-term stroke outcome in patients without atrial fibrillation. Neurology. 2013;80:1009–17. Morillas P, Pallarés V, Fácila L, Llisterri JL, Sebastián ME, Gómez M, et al. La puntuación CHADS2 como predictor de riesgo de ictus en ausencia de fibri˜ Rev Esp Cardiol. lación auricular en pacientes hipertensos de 65 o más anos. 2015;68:485–91. Taylor F, Huffman MD, Macedo AF, Moore TH, Burke M, Davey Smith G, et al. Statins for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2013;31:CD004816. Mihaylova B, Emberson J, Blackwell L, Keech A, Simes J, Barnes EH, et al. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: meta-analysis of individual data from 27 randomised trials. Lancet. 2012;380:581–90. Nagasawa SY, Okamura T, Iso H, Tamakoshi A, Yamada M, Watanabe M, et al. Relation between serum total cholesterol level and cardiovascular disease stratified by sex and age group: a pooled analysis of 65.594 individuals from 10 cohort studies in Japan. J Am Heart Assoc. 2012;1:e001974.
www.elsevier.es/medicinaclinica
Original article
Use of the CHADS2 score as a predictor of the risk of mortality in hypertensive patients. The FAPRES study夽 Elena Castilla a,∗ , Pedro Morillas a , Manuel Gómez a , Miguel Ahumada a , Marta Monteagudo a , Lorenzo Fácila b , Vicente Pallares c a b c
Servicio de Cardiología, Hospital General Universitario de Elche, Elche, Alicante, Spain Servicio de Cardiología, Hospital General de Valencia, Valencia, Spain Unidad de Vigilancia de la Salud, Unión de Mutuas, Departamento de Medicina, Universitat Jaume I, Castellón, Spain
a r t i c l e
i n f o
Article history: Received 2 November 2015 Accepted 3 March 2016 Available online 25 July 2016 Keywords: Cardiovascular mortality Hypertension Coagulation
a b s t r a c t Foundations and aim: The aim of this study is to analyze the CHADS2 score as a marker of the risk of mortality in hypertensive patients, with and without the presence of atrial fibrillation. Methods: We included 1003 hypertensive patients ≥65 years. Risk factors, and CHADS2 score were recorded among other factors, as well as clinical follow-up of number and type of deaths. Results: Mean age was 72.8 ± 5.8 years, and 47.5% were men. During follow-up there were 41 deaths, 20 were of cardiovascular origin. Patients with higher CHADS2 had a higher mortality: 1.5% CHADS2 = 1; 4.7% in CHADS2 = 2; 9.1% in CHADS2 = 3, and 7.8% in CHADS2 ≥ 4. Conclusions: The CHADS2 score can be a clinical instrument of easy application to identify hypertensive patients with a high risk of mortality. ˜ S.L.U. All rights reserved. © 2016 Elsevier Espana,
Uso de la escala CHADS2 como predictor de riesgo de mortalidad en pacientes hipertensos. El estudio FAPRES r e s u m e n Palabras clave: Mortalidad cardiovascular Hipertensión arterial Coagulación arterial
Fundamentos y objetivo: El objetivo del estudio es analizar la escala CHADS2 como marcador de riesgo de mortalidad en pacientes hipertensos, independientemente de la presencia o no de fibrilación auricular. ˜ Métodos: Se incluyó a 1.003 pacientes hipertensos ≥ 65 anos, recogiendo factores de riesgo y puntuación CHADS2 . Se realizó un seguimiento clínico de la mortalidad. ˜ Resultados: La media de edad de la población fue 72,8 ± 5,8 anos; el 47,5% eran varones. Durante el seguimiento hubo 41 muertes, 20 de origen cardiovascular. Los pacientes con mayor CHADS2 tuvieron una mayor mortalidad: 1,5% en CHADS2 = 1; 4,7% en CHADS2 = 2; 9,1% en CHADS2 = 3, y 7,8% en CHADS2 ≥ 4. Conclusiones: La puntuación CHADS2 puede ser un instrumento clínico de sencilla aplicación para identificar pacientes hipertensos con alto riesgo de mortalidad. ˜ S.L.U. Todos los derechos reservados. © 2016 Elsevier Espana,
Introduction
夽 Please cite this article as: Castilla E, Morillas P, Gómez M, Ahumada M, Monteagudo M, Fácila L, et al. Uso de la escala CHADS2 como predictor de riesgo de mortalidad en pacientes hipertensos. El estudio FAPRES. Med Clin (Barc). 2016;146:478–483. ∗ Corresponding author. E-mail address: elena [email protected] (E. Castilla). ˜ S.L.U. All rights reserved. 2387-0206/© 2016 Elsevier Espana,
The CHADS2 score – heart failure, hypertension, age, diabetes, stroke (double) – is the recommended clinical score for stroke risk stratification in patients with non-valvular atrial fibrillation and used to determine if anticoagulant therapy is indicated.1 Today it is widely known and used in routine clinical practice because of its uncomplicated operation and reproducibility.2,3 The scoring criteria that make it up are also important risk factors for atherosclerotic disease and cardiovascular disease in general.4 Based on this premise, it is possible that this score can
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
have important applications for predicting a wider range of cardiovascular events beyond its usual field of use, that is, atrial fibrillation. In this regard, a recent study showed that the CHADS2 score predicted the risk of stroke and death in patients with acute myocardial infarction, especially those without atrial fibrillation.5 It has also demonstrated its predictive value for cardiovascular mortality in high-risk patients without atrial fibrillation.6 The aim of this study is to analyze the role of this score as a risk marker for mortality in a sample of hypertensive patients aged ≥65 years from an area along the Mediterranean, regardless of the presence or absence of atrial fibrillation. Methods The FAPRES record (atrial fibrillation + blood pressure) is an epidemiologic, observational, multicenter study conducted within a healthcare setting, designed to determine the prevalence of atrial fibrillation in patients over 65 years with a clinical diagnosis of hypertension in the Valencian Region. 69 researchers from primary care and hypertension hospital units located in Alicante, Castellon and Valencia participated in it, in a proportion which was in line with the population weight of each of the 3 provinces. A detailed description of the study and a definition of the variables have been previously published.7 A total of 1028 patients were included in the baseline study. The researchers were invited to conduct a clinical follow-up of these patients for 2 years, recording any major cardiovascular events, including mortality. A written informed consent was obtained from all patients and the study was conducted following the principles of the Declaration of Helsinki, after approval by a hospital ethics committee (Clinical Research Ethics Committee of the General University Hospital of Castellón). Study population All patients enrolled in the FAPRES study that had completed the follow-up period were included in this study. Their risk factors and cardiovascular history were collected using a standardized questionnaire. Any patient who had a history of high cholesterol together with a low density of lipoproteins (>160 mg/dl) or had already been treated with a diet or lipid-lowering drugs8 was considered as having hypercholesterolemia. Any patient with a history of diabetes mellitus or who were already receiving treatment for that condition was considered diabetic. Any patient who smoked some kind of tobacco (cigarettes, pipes, cigars or non-inhaled tobacco) on a daily basis during the previous month was considered a smoker.9 On the contrary, the patient who had stopped smoking at least one year before was considered a non-smoker. Anyone who recognized actively walking during at least 30 min/day or doing some kind of sport 3 days/week10 was considered as someone who practiced physical exercise. Any drug treatment the patient was receiving at the time of the consultation was recorded, specifically any antihypertensive drugs and any cardio embolic prevention treatment (anticoagulants and/or antiplatelet agents). Also, a physical examination was performed, collecting anthropometric data (weight, height and waist circumference) and blood pressure was taken. Blood pressure was measured following the recommendations of clinical practice guidelines,11 taking it 5 min after the patient had rested, on 2 occasions separated by 2 min and in a sitting position, to calculate the arithmetic average of both. To do so, calibrated and validated automated devices were used. Blood test data were collected from medical records whenever these were available for the last 6 months, otherwise they were requested from the laboratory at the time. Glomerular filtration rate was determined by the Modification of Diet in Renal Disease Study formula. The questionnaire together with the medical history was sent through a contract
479
research organization for automatic data processing. An electrocardiogram was also performed to all patients, which was then submitted by ordinary mail to a reference center, where it was independently analyzed by 2 expert cardiologists who were blinded to the clinical data of patients. The presence of atrial fibrillation and left ventricular hypertrophy was assessed using the Sokolow, Cornell or ventricular overload criteria. A random external audit of 10% of the questionnaires registered was performed in order to verify the reliability of the data. The patient’s CHADS2 score was determined (heart failure, hypertension, 75 years of age, diabetes mellitus [one point each] and prior stroke or transient ischemic attack [TIA] [2 points])2 and they were classified into 4 groups according to their score: 1, 2, 3 and ≥4 points. Patients underwent a follow-up, collecting both overall as well as cardiovascular mortality. Statistic analysis All data collected in the study are described in terms of central tendency, measures of dispersion and relative frequencies. The Student t test or ANOVA was used to compare quantitative variables between groups, and for comparison of categorical variables, the 2 test. Overall survival was calculated according to the CHADS2 score by the Kaplan–Meier method. To determine the variables independently associated with the overall and cardiovascular mortality during follow-up, a multivariate logistic regression analysis was conducted, in which all significant variables of the univariate analysis and those with recognized clinical relevance were included, together with the CHADS2 score. To analyze the validity of the CHADS2 score in calculating the mortality risk, the receiver operating characteristic (ROC) curve was determined and the area under the curve was calculated. When p < 0.05, it was considered statistically significant. An SPSS® statistical program was used 21 version was used for the analysis. Results Of the 1028 hypertensive patients at baseline in the FAPRES study, 1003 completed follow-up (97.5%), with a median of 804 (723–895) days. The average age of the population was 72.8 ± 5.8 years and 47.5% were male. 48.3% of patients had a history of hypercholesterolemia, 27.5% had diabetes mellitus and 9% were active smokers. Also, 60 patients had a history of renal failure (6%), 75, of prior stroke/TIA (7.5%), 72 cases were diagnosed with heart failure (7.2%), 146 of ischemic heart disease (14.5%) and 6.9% had atrial fibrillation on the electrocardiogram. After calculating the CHADS2 score it was observed that 466 cases (46.5%) had a value of one point; 340 (36.9%), a value of 2 points, 146 (14.6%) of 3 points, and 51 (5.1%), higher than or equal to 4 points. Table 1 shows the main characteristics of these populations. Patients with a high CHADS2 score were significantly older and had a higher prevalence of risk factors, as well as more cardiovascular disease (especially heart failure, ischemic heart disease, ventricular hypertrophy, atrial fibrillation and previous stroke). They also had lower plasma concentrations of cholesterol bound to high density lipoproteins (HDL, “high density lipoprotein”) and worse glomerular filtration. Regarding the treatment being administered, no significant differences were found in the use of angiotensin-converting enzyme inhibitors, angiotensin receptor antagonists, ii, beta blockers or diuretics between the 4 populations; however, patients with a higher CHADS2 score received calcium channel blockers, statins, anticoagulants and antiplatelet agents more frequently. In short, if we compare patients with a CHADS2 score of 3 or ≥4 with respect to those who have a CHADS2 = 2, the first ones clearly have a worse risk profile.
480
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
Table 1 Baseline characteristics of the population according to the CHADS2 score. Variable
CHADS2 = 1 (n = 466)
CHADS2 = 2 (n = 340)
CHADS2 = 3 (n = 146)
CHADS2 ≥ 4 (n = 51)
p
Age (in years) Men Smoking Diabetes mellitus Hypercholesterolemia Ischemic heart disease Heart failure Kidney failure Previous stroke Physical exercise Evolution HBP (in years) SBP in clinic (mmHg) DBP in clinic (mmHg) BMI Hemoglobin (g/dl) Glucose (mg/dl) c-LDL (mg/dl) c-HDL (mg/dl) Glomerular filtration rate (ml/min) ECG LVHa Atrial fibrillation in ECG
69.5 ± 3.4 207 (44.4) 45 (9.7) 2 (0.4) 208 (44.6) 48 (10.3) 1 (0.2) 15 (3.2) 1 (0.2) 196 (42.1) 9.2 ± 9.2 146.4 ± 18.5 93.1 ± 10.1 29.2 ± 3.9 13.7 ± 1.5 98.6 ± 18 124.1 ± 32.7 54.4 ± 12.6 78.1 ± 21.3 62 (13.3) 20 (4.3)
75 ± 6.1 166 (48.8) 30 (8.8) 150 (44.1) 165 (48.5) 56 (16.5) 19 (5.6) 27 (7.9) 0 (0) 111 (32.6) 12 ± 8.7 146.9 ± 19.2 80.1 ± 11.2 29.2 ± 4.4 13.4 ± 1.7 115.4 ± 37.2 117.3 ± 32.8 51.8 ± 12.8 72.8 ± 22.1 64 (18.8) 17 (5)
77.2 ± 5.3 72 (49.3) 13 (8.9) 90 (61.6) 74 (50.7) 29 (19.9) 37 (14.6) 13 (8.9) 30 (20.5) 43 (29.5) 12.8 ± 8.1 149.9 ± 19 77.8 ± 11.1 28.5 ± 4.5 13.3 ± 2 125.1 ± 38.8 111.1 ± 36.1 51.7 ± 14.8 72.1 ± 25.9 37 (25.3) 23 (15.8)
76.7 ± 4.4 31 (60.8) 2 (3.9) 34 (66.7) 37 (72.5) 16 (25.5) 15 (29.4) 5 (9.8) 44 (86.3) 19 (37.3) 13.3 ± 9.5 146.4 ± 19.8 77.6 ± 12.8 29.1 ± 4.2 13.3 ± 2 108.5 ± 32 100.9 ± 36.5 47.7 ± 10.6 58.3 ± 19.4 9 (17.6) 9 (17.6)
<0.001 0.12 0.60 <0.001 0.002 <0.001 <0.001 0.007 <0.001 0.009 <0.001 0.72 <0.001 0.34 0.01 <0.001 <0.001 0.001 <0.001 0.006 <0.001
c-HDL: cholesterol bound to high density lipoproteins; c-LDL: cholesterol bound to low density lipoproteins; ECG: electrocardiogram; HBP: high blood pressure; LVH: left ventricular hypertrophy; BMI: body mass index; DBP: diastolic blood pressure; SBP, systolic blood pressure. Data are expressed as n (%) or mean ± standard deviation. a Sokolow or Cornell criteria or ventricular overload.
During follow-up, 41 deaths occurred, 20 of which were of cardiovascular origin. Patients who died were older and had a history of heart disease and worst CHADS2 score (2.39 ± 0.94 versus 1.77 ± 0.92; p < 0.05); on the contrary, they had lower HDL plasma concentrations and practiced less physical exercise. There were no differences in the prevalence of diabetes mellitus, smoking or hypercholesterolemia between the two populations (Table 2). Moreover, it was observed that the patients who died were taking more anticoagulants (14.6 versus 6.10%; p < 0.05) and digoxin (4.9 versus 0.70%, p < 0.05), with no difference in antihypertensive treatment or the use of statins between the two populations. Patients with higher CHADS2 had a significantly higher mortality: 1.5% in CHADS2 = 1; 4.7% in CHADS2 = 2; 9.1% in CHADS2 = 3
and 7.8% in CHADS2 ≥ 4. Figs. 1 and 2 show the Kaplan–Meier curves, reflecting the higher mortality (overall and cardiovascular) of patients with higher CHADS scores2 (log rank test, p < 0.001). In the multivariate analysis, risk factors associated with overall mortality were history of ischemic heart disease, male sex and CHADS2 score, with increased risk for patients with values ≥3 (Table 3). By contrast, protective factors associated with overall mortality were a history of high cholesterol, physical exercise and female sex. Very similar data were found in cardiovascular mortality (Table 4). The area under the ROC curve of the CHADS2 score for the risk of overall death was low (0.68; 95% confidence interval [95% CI] 0.61–0.76; p < 0.05), and moderate for cardiovascular death (0.78, 95% CI from 0.69 to 0.86; p < 0.05) (Figs. 3 and 4).
Table 2 Comparative study between patients according to follow-up mortality. Variable
Deaths n = 41
Living n = 962
p
Age (in years) Men Smoking Diabetes mellitus Hypercholesterolemia Ischemic heart disease Heart failure Kidney failure Previous stroke Physical exercise Evolution HBP (in years) SBP in clinic (mmHg) DBP in clinic (mmHg) BMI Hemoglobin (g/dl) Glucose (mg/dl) c-LDL (mg/dl) c-HDL (mg/dl) Glomerular filtration rate (ml/min) ECG LVHa Atrial fibrillation in ECG CHADS2 score
77.29 ± 5.7 20 (65.9) 5 (12.2) 14 (34.1) 14 (34.1) 15 (36.6) 10 (24.4) 4 (9.8) 5 (12.2) 5 (12.2) 12 ± 7.5 147.6 ± 20 76.3 ± 8.1 28.7 ± 24.5 13.5 ± 1.7 109.5 ± 25.2 112.6 ± 32.5 46.9 ± 9.46 71.6 ± 32.4 10 (24.4) 5 (12.2) 2.39 ± 0.94
72.7 ± 5.1 449 (65.6) 85 (12.2) 262 (27.2) 470 (48.9) 131 (13.6) 62 (6.4) 56 (5.8) 70 (7.3) 364 (37.8) 10.88 ± 8.28 146.6 ± 18.8 81.2 ± 11 29.1 ± 4.19 13.5 ± 1.7 108.54 ± 32.9 118.83 ± 34.1 53 ± 13 75 ± 21.9 162 (16.8) 64 (6.7) 1.77 ± 0.92
<0.001 0.12 0.30 0.33 0.65 <0.001 <0.001 0.29 0.24 0.001 0.39 0.75 0.005 0.54 0.35 0.35 0.27 0.006 0.32 0.20 0.17 0.03
c-HDL: cholesterol bound to high density lipoproteins; c-LDL: cholesterol bound to low density lipoproteins; ECG: electrocardiogram; HBP: high blood pressure; LVH: left ventricular hypertrophy; BMI: body mass index; DBP: diastolic blood pressure; SBP, systolic blood pressure. Data are expressed as n (%) or mean ± standard deviation. a Sokolow or Cornell criteria or ventricular overload.
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
Table 3 Multivariate analysis. Factors associated with overall mortality during follow-up.
1.00
0.95
Survival
481
0.90
0.85
Log Rank test 22.19 (P<.001) 0.80 0
250
500
750
1000
1250
Follow-up (days) CHADS group CHADS2 =1 CHADS2 =2 CHADS2 =3 CHADS2 ≥4 Fig. 1. Kaplan–Meier curve of overall mortality according to CHADS2 score.
Discussion This study is one of the first in assessing the CHADS2 score prognostic impact in order to establish mortality risk in a Mediterranean cohort of hypertensive patients regardless of the presence or absence of atrial fibrillation. The results show that CHADS2 is a good predictor of overall and cardiovascular mortality, so that patients with a ≥3 score have an increased risk of mortality in the medium term. The importance of hypertension as one of the main risk factors involved in the development of cardiovascular disease has
Variable
Overall mortality, OR (95% CI)
p
Physical exercise Female Hypercholesterolemia Ischemic heart disease CHADS2 = 2a CHADS2 = 3a CHADS2 ≥ 4a
0.39 (0.19–0.82) 0.15 (0.05–0.46) 0.32 (0.15–0.69) 3.61 (1.7–7.6) 2.93 (1.10–7.82) 6.35 (2.25–17.89) 6.43 (1.62–25.57)
0.0013 0.001 0.004 0.001 0.03 <0.001 0.008
95% CI: 95% confidence interval; OR: odds ratio. The variables included in the model are: sex, smoking, high cholesterol, physical exercise, atrial fibrillation, angiotensin-converting enzyme inhibitors, angiotensin ii receptor antagonists, Beta blockers, statins, antiplatelet agents, anticoagulants, ischemic heart disease, mean systolic and diastolic blood pressure, glomerular filtration rate, body mass index and CHADS2 score. a Regarding CHADS2 = 1. Table 4 Multivariate analysis. Factors associated with cardiovascular mortality during follow-up. Variable
Cardiovascular mortality, OR (95% CI)
p
Physical exercise Female Hypercholesterolemia Ischemic heart disease CHADS2 = 2a CHADS2 = 3a CHADS2 ≥ 4a
0.36 (0.13–1.05) 0.09 (0.01–0.63) 0.21 (0.07–0.63) 6.18 (2.22–17.21) 7.31 (0.87–61.29) 24.4 (2.96–201.33) 33.12 (3.15–347.82)
0.063 0.016 0.006 <0.001 0.066 0.003 0.004
95% CI: 95% confidence interval; OR: odds ratio. The variables included in the model are: sex, smoking, high cholesterol, physical exercise, atrial fibrillation, angiotensin-converting enzyme inhibitors, angiotensin ii receptor antagonists, Beta blockers, statins, antiplatelet agents, anticoagulants, ischemic heart disease, mean systolic and diastolic blood pressure, glomerular filtration rate, body mass index and CHADS2 score. a Regarding CHADS2 = 1.
been widely demonstrated and also involves a major public health problem. In addition, its association with other cardiovascular risk factors exponentially increases the risk of cardiovascular events and cardiovascular mortality.12 This knowledge has led to the widespread development of different risk assessment scales13,14 and therapeutic strategies in recent decades, so as to reduce its
1.00 1.0
0.8 0.96
Sensitivity
Cumulative survival
0.98
0.94
0.92
0.6
0.4
Log Rank test 24.8 (P<.001)
0.90 0
250
500
750
1000
1250
0.2
AUC P<.001
Follow-up (days) CHADS group CHADS2 =1 CHADS2 =2 CHADS2 =3 CHADS2 ≥4 Fig. 2. Kaplan–Meier curve of cardiovascular mortality according to CHADS2 score.
0.0 0.0
0.2
0.4
0.6
0.8
1.0
Specificity Fig. 3. Receiver operating characteristic curve to predict the risk of overall mortality by CHADS2 score.
482
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483 1.0
0.8
Sensitivity
0.6
0.4
0.2
AUC P<.001 0.0 0.0
0.2
0.4
0.6
0.8
1.0
Specificity Fig. 4. Receiver operating characteristic curve to predict the risk of cardiovascular mortality by CHADS2 score.
incidence, mortality and the social and health costs involved. Having a tool that can predict the risk of death in this hypertensive patient’s population can help in this task.15 The CHADS2 score4 was originally developed as a model for predicting the risk of stroke in patients with non-valvular atrial fibrillation.1,3 However, in recent years its use has expanded beyond the typical atrial fibrillation setting,16,17 and presents some advantages over other scales (SCORE or Framingham), such as the inclusion of older patients and less complexity in everyday use. Henriksson et al. have applied this score to a wide range of patients surviving a stroke included in the Swedish Stroke Registry, and demonstrate that the risk of mortality 5 years after a cerebral episode increases gradual and linearly with the CHADS2 score, both for patients with atrial fibrillation and sinus rhythm.18 These data have been recently confirmed in other studies, showing a higher mortality and greater recurrence of stroke and cardiovascular events in patients with stroke and a score ≥2, regardless of whether there is atrial fibrillation or not.19,20 Recently, our group has also demonstrated the association between CHADS2 and the risk of stroke in hypertensive patients with sinus rhythm, so that patients with CHADS2 ≥ 4 had 9 times more risk of stroke.21 The role of CHADS2 score has also been investigated in the field of ischemic heart disease. Poci et al. have shown that high CHADS2 scores at the time of admission due to acute coronary syndrome were associated to an increased risk of stroke-induced hospitalization and increased mortality during follow-up.5 In the present study we extend the usage scenario of that score to the field of hypertension, one of the most common risk factors and of an increased risk of cardiovascular events, and demonstrate the association between CHADS2 and medium term risk of both overall as well as cardiovascular mortality in a sample of hypertensive patients aged ≥65 years, with a progressive increase proportional to the increasing CHADS2 value. This can provide valuable support when using this attractive and simple model for risk prediction in our midst. There are several potential mechanisms that may explain the ability of CHADS2 to predict the risk of mortality in hypertensive patients regardless of the presence of atrial fibrillation. Clearly, some of the score components make up cardiovascular risk factors
individually and we can get to predict long-term mortality as we can quantify their importance through a score and by associating them, as shown by our study. In his work, Henriksson et al. highlighted the ability of the score to determine post-stroke mortality at 6 months regardless of the presence of atrial fibrillation, mainly due to the great weight of 2 components, age and heart failure, and suggested that they should have a higher value.15 A paradoxical association between cholesterol and lower mortality in hypertensive patients stands out in our results, against the evidence held by large primary and secondary prevention studies published to date.22,23 However, some recent studies in the elderly have also shown that lack of association between hypercholesterolemia and a worse cardiovascular prognosis, especially in women.24 It is likely that what is really important is not the presence of dyslipidaemia itself, but the time of progression of the same, without being able to rule out that elderly patients who have participated in the study have some resistance to hypercholesterolemia producing cardiovascular disease in their case. The study has some limitations. First, there is a selection bias, since patients included in the study were those who came spontaneously to the health system, so our findings cannot be extrapolated to other scenarios. On the other hand, there is no second independent validation cohort confirming clinical prediction results obtained in our sample. Finally, our analysis is not a study of causality, so it does not allow us to establish a cause-effect relationship, but, rather, a significant association. In summary, our study shows that the CHADS2 score can be an easy-to-apply clinical tool for everyday clinical practice, which does not need too many resources to identify hypertensive patients with a high risk of mortality. It also raises the question of whether the cases with high CHADS2 scores could benefit from more intensive preventive treatment or therapy to improve survival, reason why it would be advisable to conduct studies in this regard. Conflict of interest None. Acknowledgements We would like to thank Lacer laboratories for their contributions and altruistic help in this project. To all participating researchers, without whose daily work and effort the study would not have been possible. Appendix. FAPRES registry researchers Juan Alberola, Vicente Javier; Maestre Amat, Luis; Mateo ˜ Liminana, Jose Manuel; Monleon Gomez, Jose; Montagud Moncho, Miguel; Guinot Martinez, Enrique; Gamon Pastor, Jose Blas; Salanova Penalba, Alejandro; Sanchis Domenech, Carlos; Pallares Carratala, Vicente; Palacios del Cerro, Antonio; Perez Martinez, Rafael; Baudet Dejean, Chantal; Perez Alonso, Manuel; Facila Rubio, Lorenzo; Sipan Sarrion, Yolanda; Saro Perez, Eugenia; Villaro Gumpert, Juan; Cabrera Ferriols, M. Angeles; Fraile, Belen; Carbonell Franco, Francisco; Cornejo Mari, Francisco Javier; Bar˜ bera Comes, Javier; Quiles Anon, Fernando; Llisterri Caro, Jose Luis; Almenar Cubells, Enrique; Casado Gonzalez, Joaquin; Godoy Rocati, Diego; Martinez Guerola, Carmen; Bonet Garcia, Jorge Alejo; Blazquez Encinar, Julio Cesar; Botella Estrada, Carlos; Saen lcoy, Montepio; Almarcha Perez, Natividad; Salanova Chilet, Lorena; Torres Ferrando, Miquel; Debon Belda, Manuel; Fluixa Carrascosa, Carlos; Aznar Baset, Lucia; Vivancos Aparicio, Diego; ˜ Pineda Cuenca, Manuel; Obarrio Moreno, Alicia; Nunez Jorge, ˜ Aracil, Manuel; Balanza Carlos; Matoses Nacher, Daniel; Bano
E. Castilla et al. / Med Clin (Barc). 2016;146(11):478–483
˜ Forcada, Enrique; Garzon, Alicia; Garcia Palomar, Carlos; Pena ˜ Raga Casasus, Jose; Martinez Lahuerta, Juan; Mendizabal Nunez, Andrea; Santos Alonso, Eufrosina; Corbi Pascual, Miguel; Lillo Sanchez, Antonio; Martorell Adsuara, Vicente; Sanchez Ruiz, Tomas; Ortiz Diaz, Francisco; Llinares Orts, Jose Francisco; Lahoz Ferrer, Julio; Morillas Blasco, Pedro; Pertusa Martinez, Salvador; Manclus Montoya, Carlos; Adria Mico, Jose Manuel; Llaudes Soler, Ricardo; Castillo, Jesus; Llopis Martinez, Francisco; Ruiz de la Prada Abarzuza, Ignacio; Nebot Rico, Lidia. References 1. Lip GY. Stroke and bleeding risk assessment in atrial fibrillation: when, how, and why? Eur Heart J. 2013;34:1041–9. 2. Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285:2864–70. 3. Ruiz M, Romo E, Mesa D, Delgado M, Anguita M, López A, et al. Predicción de eventos embólicos en pacientes con fibrilación auricular no valvular: evaluación del score CHADS2 en una población mediterránea. Rev Esp Cardiol. 2008;61:29–35. 4. Skanes AC, Healey JS, Cairns JA, Dorian P, Gillis AM, McMurtry MS, et al. Focused 2012 update of the Canadian Cardiovascular Society atrial fibrillation guidelines: recommendations for stroke prevention and rate/rhythm control. Can J Cardiol. 2012;28:125–36. 5. Poci D, Hartford M, Karlsson T, Herlitz J, Edvardsson N, Caidahl K. Role of the CHADS2 score in acute coronary syndromes: risk of subsequent death or stroke in patients with and without atrial fibrillation. Chest. 2012;141:1431–40. 6. Chan Y, Yiu K, Lau K, Yiu Y, Li S, Lam T, et al. The CHADS2 and CHA2DS2-VASc scores predict adverse vascular function, ischemic stroke and cardiovascular death in high-risk patients without atrial fibrillation: role of incorporating PR prolongation. Atherosclerosis. 2014;237:504–13. 7. Morillas P, Pallarés V, Llisterri JL, Sanchis C, Sánchez T, Fácila L, et al. Prevalencia de fibrilación auricular y uso de fármacos antritrombóticos en el paciente ˜ El registro FAPRES. Rev Esp Cardiol. 2010;63:943–50. hipertenso ≥ 65 anos. 8. National Cholesterol Education Program (NCEP) Expert panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation. 2002;106:3143–421. 9. World Health Organization. Guidelines for controlling and monitoring the tobacco epidemic. Geneva: WHO; 1998. p. 76–101. 10. Villar F, Maiques A, Brotons C, Torcal J, Lorenzo A, Vilaseca J, et al. Prevención cardiovascular en atención primaria. Aten Primaria. 2001;28 Suppl. 2:S13–36. 11. Mancia G, Fagard R, Narkiewicz K, Redón J, Zanchetti A, Böhm M, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the task force
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
483
for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2013;31:1281–357. Weber MA, Bakris GL, Hester A, Weir MR, Hua TA, Zappe D, et al. Systolic blood pressure and cardiovascular outcomes during treatment of hypertension. Am J Med. 2013;126:501–8. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Memotti A, de Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24:987–1003. Mancia G, de Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G, et al. 2007 guidelines for the management of arterial hypertension: the task force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2007;25:1105–87. Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest. 2010;137:263–72. Hsu PC, Lin TH, Lee WH, Chu CY, Chiu CA, Lee HH, et al. Association between the CHADS2 score and an ankle-brachial index of <0.9 in patients without atrial fibrillation. J Atheroscler Thromb. 2014;21:322–8. Hoshino T, Ishizuka K, Shimizu S, Uchiyama S. CHADS2 score predicts functional outcome of stroke in patients with a history of coronary artery disease. J Neurol Sci. 2013;331:57–60. Henriksson KM, Farahmand B, Johansson S, Asberg S, Terent A, Edvardsson N. Survival after stroke – the impact of CHADS2 score and atrial fibrillation. Int J Cardiol. 2010;141:18–23. Tu HT, Campbell BC, Meretoja A, Churilov L, Lees KR, Donnan GA, et al. Prestroke CHADS2 and CHA2DS2-VASc scores are useful in stratifying three-month outcomes in patients with and without atrial fibrillation. Cerebrovasc Dis. 2013;36:273–80. Ntaios G, Lip GY, Makaritsis K, Papavasileiou V, Vemmou A, Koroboki E, et al. CHADS2, CHA2DS2-VASc, and long-term stroke outcome in patients without atrial fibrillation. Neurology. 2013;80:1009–17. Morillas P, Pallarés V, Fácila L, Llisterri JL, Sebastián ME, Gómez M, et al. La puntuación CHADS2 como predictor de riesgo de ictus en ausencia de fibri˜ Rev Esp Cardiol. lación auricular en pacientes hipertensos de 65 o más anos. 2015;68:485–91. Taylor F, Huffman MD, Macedo AF, Moore TH, Burke M, Davey Smith G, et al. Statins for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2013;31:CD004816. Mihaylova B, Emberson J, Blackwell L, Keech A, Simes J, Barnes EH, et al. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: meta-analysis of individual data from 27 randomised trials. Lancet. 2012;380:581–90. Nagasawa SY, Okamura T, Iso H, Tamakoshi A, Yamada M, Watanabe M, et al. Relation between serum total cholesterol level and cardiovascular disease stratified by sex and age group: a pooled analysis of 65.594 individuals from 10 cohort studies in Japan. J Am Heart Assoc. 2012;1:e001974.