Decreased glomerular filtration rate as calculated by the Cockckroft-Gault and MDRD formulas does not always predict cardiovascular morbidity and mortality in hypertensive patients treated in primary care
El filtrado glomerular reducido según las fórmulas de Cockcroft-Gault y MDRD no siempre predice la morbimortalidad cardiovascular en los pacientes hipertensos atendidos en atención primaria
, Francisco Javier Tovillas-Moránb, Miguel Vilaplana-Cosculluelac, Artur Dalfò-Pibernatd, Artur Dalfó-Pibernate, Edurne Zabaleta-del-Olmof, Josep María Galceráng, Antonio Cocah, Antoni Dalfò-Baquéi, Antoni Dalfó-Baquéc
b Insitituto de Investigación en Atención Primaria (IDIAP) Jordi Gol y Equipo de Atención Primaria (EAP) Martí i Julià, Cornellá, Barcelona,
c Insitituto de Investigación en Atención Primaria (IDIAP) Jordi Gol y EAP Gòtic, Barcelona,
d EAP Vallcarca, Barcelona, Barcelona, Spain,
e EAP Vallcarca, Barcelona,
f Insitituto de Investigación en Atención Primaria (IDIAP) Jordi Gol, Barcelona,
g Fundación ALTHAIA, Manresa, Barcelona,
h Unidad de Hipertensión, Instituto de Medicina y Dermatología. Hospital Clínico. Universidad de Barcelona., Barcelona,
i EAP Gòtic, Barcelona, Barcelona, Spain,
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Hospital Clínico. Universidad de Barcelona., Barcelona, " "etiqueta" => "<span class="elsevierStyleSup">h</span>" "identificador" => "affh" ] 7 => array:3 [ "entidad" => " EAP Gòtic, Barcelona, Barcelona, Spain, " "etiqueta" => "<span class="elsevierStyleSup">i</span>" "identificador" => "affi" ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "El filtrado glomerular reducido según las fórmulas de Cockcroft-Gault y MDRD no siempre predice la morbimortalidad cardiovascular en los pacientes hipertensos atendidos en atención primaria" ] ] "textoCompleto" => "<p class="elsevierStylePara"><span class="elsevierStyleBold">INTRODUCTION</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Arterial hypertension (AHT) is a major health problem since it is a known risk factor for developing cardiovascular disease.<span class="elsevierStyleSup">1</span> One of the organ disorders derived from AHT is chronic kidney disease (CKD), defined initially by the presence of kidney damage and in later stages, as a decrease in glomerular filtration rate (GFR).</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Various publications have shown that CKD is responsible for increased cardiovascular morbidity and mortality, which is proportional to kidney function deterioration.<span class="elsevierStyleSup">2-4</span> For this reason, various professional associations and organisations<span class="elsevierStyleSup">5-8</span> include reduced GFR as one of the consequences consider in hypertensive patients. They also state that it is useful in therapeutic decision tables. Current recommendations<span class="elsevierStyleSup">9,10</span> are aimed more towards minimising the progression of kidney deterioration and treating the complications inherent in kidney failure, thus reducing the cardiovascular risk associated with CKD.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">CKD is a condition that can be diagnosed in primary care (PC) in its early stages by estimating GFR through various formulas (hidden CKD) since serum creatinine is not usually altered until more advanced stages. The most widely used and validated are the Cockcroft-Gault<span class="elsevierStyleSup">11</span> and MDRD<span class="elsevierStyleSup">12</span> formulas, which have various advantages and limitations. They are recommended depending on the stage of renal function alteration in the literature.<span class="elsevierStyleSup">13-15</span> In addition, their association with the appearance of cardiovascular events (CVE) has been discovered.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">There have been few studies carried out in Spain which have analysed the evolution of long-term cardiovascular morbidity and mortality in cohorts of hypertensive patients monitored in PC, according to renal function. Since AHT is detected and controlled mainly in PC, it stands to reason that the general hypertensive population is better represented by the population cared for in PC.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In 1993, a prospective study was conducted in which the prevalence of left ventricular hypertrophy was determined in a general hypertensive population that was free of cardiovascular disease and that was being treated in a primary care centre.<span class="elsevierStyleSup">16</span> The cohort of patients was monitored from that year onwards.<span class="elsevierStyleSup">17</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The aim of this study was to analyse the association between cardiovascular morbidity/mortality and initial renal function, according to the Cockcroft-Gault and MDRD formulas, in a cohort of hypertensive individuals followed during 12 years.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">MATERIAL AND METHOD</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The "Gòtic" prospective study of a cohort of hypertensive patients treated at a health centre in Barcelona (Spain) was the source of data for this study. Monitoring began in 1993 and lasted 12 years. The selection criteria of the population and the variables analysed have been previously published.<span class="elsevierStyleSup">17</span> For this study, we also excluded patients with extremes of body weight (body mass index [BMI] less than 19 kg/m<span class="elsevierStyleSup">2</span> or greater than 35 kg/m<span class="elsevierStyleSup">2</span>), significant alterations in muscle mass, acute renal failure, pregnancy, severe liver disease, generalised oedema or ascites, and those who continued treatment with drugs that blocked secretion of creatinine. Finally, the study cohort included a total of 223 hypertensive individuals.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">GFR was calculated according to the Cockcroft-Gault (GFR=[140-age]*weight(kg)/[serum creatinine*72]*0.85, if female)<span class="elsevierStyleSup">11</span> and MDRD (GFR=186*serum creatinine<span class="elsevierStyleSup">—1.154</span>*age<span class="elsevierStyleSup">—0.203</span>*1.212, if black*0.742, if female)<span class="elsevierStyleSup">12</span> formulas and was classified according to the CKD stage.<span class="elsevierStyleSup">9</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">A CVE was considered to be the appearance of the following episodes during the follow-up period: heart failure; ischaemic cardiopathy (angina, acute myocardial infarction); stroke (permanent or temporary); peripheral vasculopathy (symptoms of intermittent claudication or confirmation through eco-Doppler); death due to cardiovascular event and sudden death. Sudden death was defined as death occurring within one hour after onset of symptoms or individuals dying without any witnesses who had no prior diagnosis of coronary heart disease or other presumably deadly diseases. The recording of the onset of CVE was done during AHT follow-up visits. All CVEs recorded were confirmed with the patients’ doctor and with the information and registration systems in hospitals and PC centres. </p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Strategies were developed to minimise losses during the follow-up period and to recover information related to mortality.<span class="elsevierStyleSup">17</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The CVEs and the causes of death were evaluated by an external committee of doctors who were unaware of the patients' situations regarding their kidney function.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The study was approved by the Ethics Committee for Clinical Research of IDIAP Jordi Gol of the Catalan Institute of Health.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Survival time was measured from the date when the subject was included in the study until the occurrence of a CVE, if such an event occurred. The censoring variable was the presence or absence of a CVE from the inclusion of subjects in the study (1993) to the end date of the follow-up (2005). Only the initial event was taken into account if there were various episodes of the same event in the same patient. Survival and incidence rates were estimated using the actuarial method. For the bivariate analysis, we used the Student's t-test or its corresponding nonparametric test in the case of continuous variables, and the chi-squared test in the case of categorical variables. We used the kappa index to evaluate the correlation between the estimates of GFR carried out with both formulas.<span class="elsevierStyleSup">18</span> The prognostic value of GFR calculated with each of the two formulas was evaluated using Cox proportional hazards regression models, as well as the prognostic value of the adjustment factors. One model was evaluated for each of the formulas used.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The covariate adjustments for the initial models were: age (years), sex (male/female), time of AHT diagnosis (months), mean systolic and diastolic blood pressure of the last two visits, obesity at the start of the study (BMI>30 kg/m<span class="elsevierStyleSup">2</span>), diabetes mellitus (DM), dyslipidaemia and tobacco consumption. The variables included in the final model were selected by combining statistical and substantive criteria.<span class="elsevierStyleSup">19,20</span> We evaluated the confounding and interaction effects between the model's variables. Furthermore, we checked the proportional hazards assumption for the various covariates and for the group of those included in the final model, as well as the presence of multicollinearity. Quantitative data were described by estimating the mean and standard deviation when they followed a normal distribution. Otherwise, the median was used along with the interquartile range (IQR). The estimates related directly with the objective of the study are accompanied by their respective 95% confidence intervals (CI). The accepted level of statistical significance was <span class="elsevierStyleItalic">P</span><.05. The data analysis was performed using the SPSS 15.0 statistical software for Windows.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">RESULTS</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Of the 265 individuals in the cohort at baseline, GFR could only be measured in 223 (84.2%). The relationship and reasons for exclusion were: 25 (9.4%) had a BMI>35 kg/m<span class="elsevierStyleSup">2</span> and 17 (6.4%) for other reasons, such as consumption of drugs that blocked creatinine secretion, presence of severe liver disease, and creatinine readings were not available.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Table 1 shows the characteristics of the participants at the start of monitoring, as well as the mean analytical values, the frequency of different cardiovascular risk factors (CRF), the distribution of GFR estimates according to the Cockcroft-Gault and MDRD formulas, and the proportion of patients treated with antihypertensive drugs.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The median follow-up time was 10.7 (IQR 6.5 to 12.1) years. Follow-up was complete in 191 participants (85.7%) and incomplete in a total of 32 (14.3%). The latter group differed from the first group in mean age (68.5 years versus 64.2 years) and mean time to diagnosis of hypertension (149 months versus 82 months). The distribution of the remaining study variables was similar in both groups.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The cumulative survival, or the proportion of participants who remained free of cardiovascular events by the end of the study, was 64.7% (95% CI, 57.9-71.6). The mean incidence of CVE during the entire follow-up period was 3.6 (95% CI, 2.7-4.4) per 100 hypertensive individuals/year.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The distribution of estimated GFR with both formulas at the start of the study is shown in Table 2. The agreement between the two estimates was moderate (kappa=0.501; 95% CI, 0.399-0.604). Most patients were classified in stages 2 and 3 by both formulas. Within stage 3, stage 3a was more frequent: 86.8% for calculations performed using the Cockcroft-Gault formula and 76.1% when using the MDRD formula.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Table 3 shows the results obtained in the bivariate analysis, which compared participants according to whether or not they suffered a CVE during follow-up. Only the presence of DM was related with a higher probability of presenting at least one CVE during follow-up. Conversely, female sex and a GFR<60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> according to the MDRD formula were associated with a lower risk of CVE. However, there was no association between the occurrence of CVE and a GFR as estimated by the Cockcroft-Gault formula.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In the final multivariable model (Table 4), only a GFR≥60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> estimated using the MDRD formula and the presence of DM at the start of the study were associated with an increased cardiovascular risk.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In this study, a moderately reduced GFR was not associated with increased cardiovascular risk. Even patients with a GFR≥60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> according to the MDRD formula had a higher incidence of events. This was the opposite to what has been described in the literature.<span class="elsevierStyleSup">2,21</span> These results are not confirmed by the measurement of GFR according to the Cockcroft-Gault formula.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The MDRD formulas is useful to estimate GFR below 60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> and has a tendency to underestimate higher values.<span class="elsevierStyleSup">14,15,22</span> Its author has recently explained<span class="elsevierStyleSup">12</span> the new equation CKD-EPI that has a greater precision than MDRD for GFR≥60 ml/min/1.73 m2.<span class="elsevierStyleSup">12</span> The Cockcroft-Gault formula, which is also appropriate for these values of GFR, underestimates renal function less for values above 60 ml/min/1.73 m<span class="elsevierStyleSup">2</span>.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Other studies have produced conflicting results regarding the performance of the MDRD formula depending on the stages of kidney failure.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In a study performed in Spain with a retrospective cohort of the general population between 35 and 75 years of age and with stage 3 renal function (GFR between 30 and 60 ml/min/1.73 m<span class="elsevierStyleSup">2</span>), Buitrago et al<span class="elsevierStyleSup">14</span> reported that the Cockcroft-Gault formula detected more hidden CKD in men, with higher cardiovascular risk and greater age. MDRD, on the other hand, did this more in women with higher obesity, higher diastolic blood pressure and higher triglyceride readings. The MDRD equation could therefore avert significantly important cases from the point of view of cardiovascular event prevention. These authors found only moderate consistency between the estimates performed with both formulas, which was similar to the results in our study. As with our study, they also did not find any evidence of a relationship between hidden CKD detected by one or the other formula and cardiovascular morbidity and mortality.<span class="elsevierStyleSup">23</span> Similar observations have been reported in other studies with larger sample sizes, such as the NHANES-I<span class="elsevierStyleSup">24</span> study in the general U.S. population.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">This questions the importance of GFR as a predictive tool for cardiovascular risk by itself, or at least the usefulness of considering Stage 3 as a single group.<span class="elsevierStyleSup">25</span> Indeed, various studies found that the risk increased significantly with GFR below 45 ml/min/1.73 m<span class="elsevierStyleSup">2</span> (stage 3b), with the risk of patients with higher GFR (stage 3a) comparable to those with normal renal function.<span class="elsevierStyleSup">2,26</span> In our study, most patients in stage 3 corresponded to stage 3a, both by the Cockcroft-Gault and the MDRD formulas.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The controversy between formulas persists even in more advanced stages of kidney failure (4 and 5) for which some authors advocate the superiority of the Cockcroft-Gault formula over the MDRD.<span class="elsevierStyleSup">27</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Furthermore, ageing reduces the relationship between estimated GFR and morbidity and mortality as shown in some studies.<span class="elsevierStyleSup">28</span> Other authors<span class="elsevierStyleSup">29</span> did not report any increase in mortality in elderly patients with GFR between 45 and 59 ml/min/1.73 m<span class="elsevierStyleSup">2</span>. Other factors, such as sex, may also affect the prognostic value of GFR. A lower correlation has been reported in women<span class="elsevierStyleSup">25,30</span> and it is females that make up the majority of our sample.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">As with other studies<span class="elsevierStyleSup">2-4</span> that did find a relationship between reduced GFR and cardiovascular morbidity and mortality, a first group corresponded to the general population. The mean age in our study was higher than those of patients in the Go et al. and Hallan et al. studies. This may contribute to a different cardiovascular risk and may change the importance of the renal function prognosis. The Keith et al. study, with a mean sample age similar to ours, found that the prognostic differences between stage 2 and 3 were less than 5%, with statistical significance in large samples but not in smaller ones such as ours. Furthermore, the Go et al. study reported that the greatest prognostic differences occurred when GFR<45 ml/min/1.73 m<span class="elsevierStyleSup">2</span> (stages 3b to 5), especially between 60 and 80 years of age, and with an GFR<30 ml/min/1.73 m<span class="elsevierStyleSup">2</span> in those over 80 years of age, which was a lot less among stages with better renal function.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In studies of hypertensive patients, Ruilope et al.<span class="elsevierStyleSup">31</span> found that GFR had a predictive value, but in patients with high cardiovascular risk.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Our study has various limitations. One of them lies in the greater likelihood of losses due to the long duration of the follow-up (longer than in other studies). This could increase the possibility of a selection bias that would affect internal validity. However, a number of strategies used<span class="elsevierStyleSup">17</span> meant that in the end the percentage of losses was 14.3%.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Another drawback was the lack of monitoring of certain parameters such as the evolution of GFR over time. This could be of great importance since it has been recently reported that the rate of decline in renal function for individuals over 65 years old is higher in relation to cardiovascular risk than baseline creatinine.<span class="elsevierStyleSup">32</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Also, albuminuria and proteinuria were not recorded systematically at the start of the study. In 1993, their measurement was not included in the assessment protocols for hypertensive patients. Several studies have emphasised the importance of this parameter, which has a greater prognostic value than GFR estimated by MDRD. Hemmelgarn et al.<span class="elsevierStyleSup">26</span> found an increased cardiovascular risk and progression of renal deterioration in patients in stages 1-2 with proteinuria compared to patients in stage 3a without proteinuria. Furthermore, the PREVEND study<span class="elsevierStyleSup">33</span> showed that individuals with GFR<60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> with no proteinuria did not have a higher cardiovascular risk than those with higher GFR. Combining reduced GFR with proteinuria may improve risk prediction.<span class="elsevierStyleSup">25,26,34</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Other markers, such as cystatin C, have recently been shown to be predictors of cardiovascular risk and renal disorders in elderly patients with GFR≥60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> to a greater extent than GFR according to MDRD<span class="elsevierStyleSup">25,35</span> as occurs with the aforementioned CKD-EPI.<span class="elsevierStyleSup">15</span> However, there is little access to both of these methods in PC.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Lastly, the expected influences of antihypertensive treatment were not evaluated during the follow-up, nor were other treatments such as hypolipidaemic or antiplatelet therapy.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In conclusion, this study does not demonstrate an increased cardiovascular risk in hypertensive patients with moderately reduced GFR.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">The formula estimates of GFR on its own, currently recommended by clinical practice guidelines, may be less useful for predicting CVE in hypertension as they do not reflect the real risk of some important populations. It may be advisable to consider redefining the values of risk factors of renal function (stages 3 or 3b) and assess the possible benefit of incorporating gender and the value of albuminuria to improve the predictive value of estimated GFR. Hypertensive patients in stages 2-3a are the most prevalent in PC and are therefore the ones who need the best strategies to prevent cardiovascular events.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">ACKNOWLEDGEMENTS</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">This study was made possible thanks to the collaboration of the entire "Gothic" PCT of Barcelona who contributed to the optimal monitoring of the patients. Furthermore, the study was supported by the IDIAP Jordi Gol, as well as assistance (FIS Exp. PI040356) from the Carlos III Health Institute of the Ministry for Science and Innovation. The authors of this study declare that there are no conflicts of interest.</p><p class="elsevierStylePara"><a href="10297_108_11173_en_10297_18107_1784_es_10297_16032_1784_es_tabla_1_en.doc" class="elsevierStyleCrossRefs">10297_108_11173_en_10297_18107_1784_es_10297_16032_1784_es_tabla_1_en.doc</a></p><p class="elsevierStylePara">Table 1. Characteristics of the study cohort at the start of follow-up (n=223)</p><p class="elsevierStylePara"><a href="10297_108_11174_en_10297_18107_1785_es_10297_16032_1785_es_tabla_2_en.doc" class="elsevierStyleCrossRefs">10297_108_11174_en_10297_18107_1785_es_10297_16032_1785_es_tabla_2_en.doc</a></p><p class="elsevierStylePara">Table 2. Distribution of the study population according to glomerular filtration rates (GFR) at the start of the study, estimated using the MDRD and Cockcroft-Gault formulas</p><p class="elsevierStylePara"><a href="10297_108_11175_en_10297_18107_1786_es_10297_16032_1786_es_tabla_3_en.doc" class="elsevierStyleCrossRefs">10297_108_11175_en_10297_18107_1786_es_10297_16032_1786_es_tabla_3_en.doc</a></p><p class="elsevierStylePara">Table 3. Characteristics at the start of the study of patients who completed the follow-up (n=191) according to the presence or absence of cardiovascular events (CVE) during that period</p><p class="elsevierStylePara"><a href="10297_108_11176_en_10297_18107_1787_es_10297_16032_1787_es_tabla_4.doc" class="elsevierStyleCrossRefs">10297_108_11176_en_10297_18107_1787_es_10297_16032_1787_es_tabla_4.doc</a></p><p class="elsevierStylePara">Table 4. Final Cox regression model to determine the predictive power of cardiovascular events on the study variables at 12 years follow-up of the cohort of hypertensive individuals (n=223)</p>" "pdfFichero" => "P1-E506-S2860-A10297-EN.pdf" "tienePdf" => true "PalabrasClave" => array:2 [ "es" => array:6 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441535" "palabras" => array:1 [ 0 => "Insuficiencia Renal" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441537" "palabras" => array:1 [ 0 => "Filtrado glomerular" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441539" "palabras" => array:1 [ 0 => "Análisis de supervivencia" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441541" "palabras" => array:1 [ 0 => "Atención Primaria de salud" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441543" "palabras" => array:1 [ 0 => "Enfermedad cardiovascular" ] ] 5 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441545" "palabras" => array:1 [ 0 => "Hipertensión" ] ] ] "en" => array:6 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441536" "palabras" => array:1 [ 0 => "Renal Insufficiency" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441538" "palabras" => array:1 [ 0 => "Glomerular Filtration Rate" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441540" "palabras" => array:1 [ 0 => "Survival Análisis" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441542" "palabras" => array:1 [ 0 => "Primary Health Care" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441544" "palabras" => array:1 [ 0 => "Cardiovascular disease" ] ] 5 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441546" "palabras" => array:1 [ 0 => "Hipertensión" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:1 [ "resumen" => "<p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleBold">Background:</span><span class="elsevierStyleBold"> </span>A decrease in renal function is associated with cardiovascular morbidity and mortality. The aim of this study was to analyse the association of cardiovascular morbidity and mortality with baseline glomerular filtration rate (GFR), calculated according to the Cockcroft-Gault and MDRD formulas, with the incidence of major adverse cardiovascular events (MACEs) in a cohort of hypertensive individuals followed for 12 years. <span class="elsevierStyleBold">Method:</span> We performed a prospective study of a random sample of 223 hypertensive patients free of MACEs, who were followed in an urban Primary Care Centre. GFR was estimated using both formulas. MACEs were considered as the onset of ischaemic heart disease, heart failure, heart attacks, peripheral vascular disease or cardiovascular death. Data were analysed using the life-table method and Cox regression modeling. <span class="elsevierStyleBold">Results:</span><span class="elsevierStyleBold"> </span>The median follow-up was 10.7 (interquartile range, 6.5-12.1) years. Follow-up was completed in 191 participants (85.7%). The cumulative survival was 64.7% (95% Confidence Interval (CI), 57.9-71.6). The incidence of MACEs during the follow-up period was 3.6 (95% CI, 2.7-4.4) per 100 subject-years. The final multivariable model showed that the most predictive variables of MACEs in the study population were the presence of diabetes mellitus and the estimation of GFR >60ml/min/1.73 m<span class="elsevierStyleSup">2</span><span class="elsevierStyleBold"> Conclusions:</span><span class="elsevierStyleBold"> </span>There was a relationship between the occurrence of MACEs and an estimated GFR by MDRD above 60 ml/min/1.73 m<span class="elsevierStyleSup">2</span> at study entry, inversely to what was expected. GFR estimated by the C-G formula was not associated with cardiovascular risk.</span> by the MDRD equation.</p>" ] "es" => array:1 [ "resumen" => "<p class="elsevierStylePara"><span class="elsevierStyleBold">Antecedentes:</span> El deterioro de la función renal se ha asociado con un incremento de la morbimortalidad cardiovascular. El objetivo del estudio fue analizar la asociación del filtrado glomerular (FG) basal, según las fórmulas de Cockcroft-Gault y MDRD, con la incidencia de eventos cardiovasculares (ECV) en una cohorte de personas hipertensas seguida durante 12 años. <span class="elsevierStyleBold">Métodos: </span>Estudio prospectivo de una muestra aleatoria de 223 hipertensos libres de ECV atendidos en un centro de atención primaria urbano. Se estimó el FG mediante ambas fórmulas. Se consideró ECV la aparición de cardiopatía isquémica, insuficiencia cardíaca, accidente cerebrovascular, vasculopatía periférica o muerte por ECV. Se analizaron los datos mediante el método actuarial y modelos de regresión de Cox. <span class="elsevierStyleBold">Resultados:</span> La mediana de tiempo de seguimiento fue de 10,7 años (rango intercuartílico, 6,5-12,1). El seguimiento fue completo en 191 participantes (85,7%). La supervivencia acumulada fue del 64,7% (intervalo de confianza [IC] del 95%: 57,9-71,6%). La tasa media de incidencia de ECV durante todo el período de seguimiento fue de 3,6 (IC del 95%, 2,7-4,4%) por 100 personas hipertensas/año. El modelo multivariable final mostró que las variables con mayor poder predictivo de ECV en la población de estudio fueron la diabetes y la estimación del FG >60 ml/min/1,73 m<span class="elsevierStyleSup">2</span> mediante fórmula MDRD. <span class="elsevierStyleBold">Conclusiones: </span>Se observó una relación entre la aparición de ECV y los valores de FG estimados por la fórmula MDRD al inicio del seguimiento superiores a 60 ml/min/1,73 m<span class="elsevierStyleSup">2</span>, inversa a la esperada. La estimación del FG mediante fórmula de Cockcroft-Gault no se asoció con el riesgo cardiovascular.</p>" ] ] "multimedia" => array:4 [ 0 => array:8 [ "identificador" => "mmc1" "etiqueta" => "Tab. 1" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "10297_108_11173_en_10297_18107_1784_es_10297_16032_1784_es_tabla_1_en.doc" "ficheroTamanyo" => 52224 ] "descripcion" => array:1 [ "en" => "Characteristics of the study cohort at the start of follow-up (n=223)" ] ] 1 => array:8 [ "identificador" => "mmc2" "etiqueta" => "Tab. 2" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "10297_108_11174_en_10297_18107_1785_es_10297_16032_1785_es_tabla_2_en.doc" "ficheroTamanyo" => 71680 ] "descripcion" => array:1 [ "en" => "Distribution of the study population according to glomerular filtration rates (GFR) at the start of the study, estimated using the MDRD and Cockcroft-Gault formulas" ] ] 2 => array:8 [ "identificador" => "mmc3" "etiqueta" => "Tab. 3" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "10297_108_11175_en_10297_18107_1786_es_10297_16032_1786_es_tabla_3_en.doc" "ficheroTamanyo" => 57856 ] "descripcion" => array:1 [ "en" => "Characteristics at the start of the study of patients who completed the follow-up (n=191) according to the presence or absence of cardiovascular events (CVE) during that period" ] ] 3 => array:8 [ "identificador" => "mmc4" "etiqueta" => "Tab. 4" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "10297_108_11176_en_10297_18107_1787_es_10297_16032_1787_es_tabla_4.doc" "ficheroTamanyo" => 37376 ] "descripcion" => array:1 [ "en" => "Final Cox regression model to determine the predictive power of cardiovascular events on the study variables at 12 years follow-up of the cohort of hypertensive individuals (n=223)" ] ] ] "bibliografia" => array:2 [ "titulo" => "Bibliography" "seccion" => array:1 [ 0 => array:1 [ "bibliografiaReferencia" => array:35 [ 0 => array:3 [ "identificador" => "bib1" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:3 [ "referenciaCompleta" => "Kaplan NM. Clinical Hypertension (9.ª ed.) Philadelphia: Lippincott Williams & Wilkins, 2006." "contribucion" => array:1 [ 0 => null ] "host" => array:1 [ 0 => null ] ] ] ] 1 => array:3 [ "identificador" => "bib2" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:3 [ "referenciaCompleta" => "Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296-305. <a href="http://www.ncbi.nlm.nih.gov/pubmed/15385656" target="_blank">[Pubmed]</a>" "contribucion" => array:1 [ 0 => null ] "host" => array:1 [ 0 => null ] ] ] ] 2 => array:3 [ "identificador" => "bib3" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:3 [ "referenciaCompleta" => "Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH. Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization. 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| Year/Month | Html | Total | |
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| 2024 November | 14 | 9 | 23 |
| 2024 October | 61 | 42 | 103 |
| 2024 September | 70 | 32 | 102 |
| 2024 August | 81 | 71 | 152 |
| 2024 July | 61 | 26 | 87 |
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| 2024 May | 69 | 43 | 112 |
| 2024 April | 67 | 43 | 110 |
| 2024 March | 48 | 25 | 73 |
| 2024 February | 38 | 41 | 79 |
| 2024 January | 41 | 30 | 71 |
| 2023 December | 36 | 35 | 71 |
| 2023 November | 35 | 37 | 72 |
| 2023 October | 48 | 55 | 103 |
| 2023 September | 45 | 34 | 79 |
| 2023 August | 60 | 22 | 82 |
| 2023 July | 42 | 43 | 85 |
| 2023 June | 81 | 23 | 104 |
| 2023 May | 85 | 42 | 127 |
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| 2023 March | 91 | 21 | 112 |
| 2023 February | 55 | 24 | 79 |
| 2023 January | 47 | 27 | 74 |
| 2022 December | 79 | 36 | 115 |
| 2022 November | 74 | 30 | 104 |
| 2022 October | 45 | 52 | 97 |
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| 2022 May | 69 | 33 | 102 |
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| 2021 October | 100 | 46 | 146 |
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| 2021 July | 46 | 40 | 86 |
| 2021 June | 31 | 30 | 61 |
| 2021 May | 34 | 30 | 64 |
| 2021 April | 87 | 50 | 137 |
| 2021 March | 43 | 34 | 77 |
| 2021 February | 50 | 18 | 68 |
| 2021 January | 43 | 28 | 71 |
| 2020 December | 27 | 12 | 39 |
| 2020 November | 47 | 10 | 57 |
| 2020 October | 23 | 20 | 43 |
| 2020 September | 19 | 7 | 26 |
| 2020 August | 46 | 8 | 54 |
| 2020 July | 31 | 7 | 38 |
| 2020 June | 33 | 14 | 47 |
| 2020 May | 65 | 9 | 74 |
| 2020 April | 32 | 17 | 49 |
| 2020 March | 40 | 8 | 48 |
| 2020 February | 38 | 18 | 56 |
| 2020 January | 49 | 27 | 76 |
| 2019 December | 67 | 19 | 86 |
| 2019 November | 85 | 25 | 110 |
| 2019 October | 31 | 13 | 44 |
| 2019 September | 36 | 23 | 59 |
| 2019 August | 37 | 10 | 47 |
| 2019 July | 36 | 20 | 56 |
| 2019 June | 47 | 16 | 63 |
| 2019 May | 52 | 18 | 70 |
| 2019 April | 70 | 39 | 109 |
| 2019 March | 35 | 20 | 55 |
| 2019 February | 26 | 14 | 40 |
| 2019 January | 45 | 22 | 67 |
| 2018 December | 74 | 31 | 105 |
| 2018 November | 92 | 9 | 101 |
| 2018 October | 87 | 20 | 107 |
| 2018 September | 58 | 11 | 69 |
| 2018 August | 36 | 13 | 49 |
| 2018 July | 44 | 14 | 58 |
| 2018 June | 44 | 17 | 61 |
| 2018 May | 43 | 13 | 56 |
| 2018 April | 72 | 10 | 82 |
| 2018 March | 21 | 7 | 28 |
| 2018 February | 25 | 7 | 32 |
| 2018 January | 26 | 8 | 34 |
| 2017 December | 34 | 8 | 42 |
| 2017 November | 38 | 6 | 44 |
| 2017 October | 45 | 11 | 56 |
| 2017 September | 41 | 7 | 48 |
| 2017 August | 28 | 6 | 34 |
| 2017 July | 23 | 13 | 36 |
| 2017 June | 28 | 21 | 49 |
| 2017 May | 49 | 10 | 59 |
| 2017 April | 41 | 9 | 50 |
| 2017 March | 21 | 6 | 27 |
| 2017 February | 23 | 13 | 36 |
| 2017 January | 8 | 11 | 19 |
| 2016 December | 65 | 9 | 74 |
| 2016 November | 78 | 13 | 91 |
| 2016 October | 96 | 11 | 107 |
| 2016 September | 120 | 1 | 121 |
| 2016 August | 200 | 5 | 205 |
| 2016 July | 197 | 7 | 204 |
| 2016 June | 156 | 0 | 156 |
| 2016 May | 144 | 0 | 144 |
| 2016 April | 125 | 0 | 125 |
| 2016 March | 98 | 0 | 98 |
| 2016 February | 129 | 0 | 129 |
| 2016 January | 126 | 0 | 126 |
| 2015 December | 142 | 0 | 142 |
| 2015 November | 112 | 0 | 112 |
| 2015 October | 99 | 0 | 99 |
| 2015 September | 78 | 0 | 78 |
| 2015 August | 88 | 0 | 88 |
| 2015 July | 75 | 0 | 75 |
| 2015 June | 36 | 0 | 36 |
| 2015 May | 61 | 0 | 61 |
| 2015 April | 8 | 0 | 8 |
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