Tables for estimating the glomerular filtration rate using the new CKD-EPI equation from serum creatinine concentration
Tablas para la estimación del filtrado glomerular mediante la nueva ecuación CKD-EPI a partir de la concentración de creatinina sérica
C.. Canala, Cristina Canalb, R.. Pellicera, Rodrigo Pellicerb, C.. Facundoa, Carme Facundob, S.. Gràcia-Garciac, Silvia Gràcia-Garciad, R.. Montañés-Bermúdezc, Rosario Montañés-Bermúdezd, C.. Ruiz-Garcíaa, César Ruiz-Garcíab, M.. Furlanoa, Mónica Furlanob, I.. DaSilvaa, Iara K. DaSilvab, J.. Ballarína, José A. Ballarínb, J.. Bovera, Jordi Boverb
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"apellidos" => "Bover" "email" => array:1 [ 0 => "jbover@fundacio-puigvert.cat" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "affa" ] ] ] 19 => array:4 [ "nombre" => "Jordi" "apellidos" => "Bover" "email" => array:1 [ 0 => "jbover@fundacio-puigvert.cat" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "affb" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Servicio de Nefrología, Fundació Puigvert, Spain, " "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "affa" ] 1 => array:3 [ "entidad" => "Servicio de Nefrología, Fundació Puigvert, " "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "affb" ] 2 => array:3 [ "entidad" => "Servicio de Laboratorio, Fundació Puigvert, Spain, " "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "affc" ] 3 => array:3 [ "entidad" => "Servicio de Laboratorio, Fundació Puigvert, " "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "affd" ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Tablas para la estimación del filtrado glomerular mediante la nueva ecuación CKD-EPI a partir de la concentración de creatinina sérica" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig1" "etiqueta" => "Tab. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "figura" => array:1 [ 0 => array:4 [ "imagen" => "12226_16025_56350_en_t1.11.12226_02.jpg" "Alto" => 2628 "Ancho" => 2147 "Tamanyo" => 2083230 ] ] "descripcion" => array:1 [ "en" => "Calculation of the glomerular filtration rate according to serum creatinine concentration (mg/dl) and age using the CKD-EPI equation (white individuals)." ] ] ] "textoCompleto" => "<p class="elsevierStylePara"> INTRODUCTION</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara">Chronic kidney disease (CKD) is a major healthcare problem, as has been stated in different epidemiological studies,<span class="elsevierStyleSup">1-3 </span>not only because patients who reach end-stage ESRD require many healthcare resources, but also due to the high cardiovascular disease burden, hospitalisation and premature death inherent in its diagnosis.<span class="elsevierStyleSup">4</span></p><p class="elsevierStylePara">With the aim of preventing or delaying complications associated with CKD,<span class="elsevierStyleSup">5 </span>in 2002, the American National Kidney Foundation (NKF) Kidney Disease Outcome Quality Initiative (K/DOQI) published clinical guidelines to define and classify it into different stages.<span class="elsevierStyleSup">6 </span>In 2005, the Kidney Disease: Improving Global Outcomes (KDIGO) international initiative accepted the definition and classification initially proposed by the K/DOQI<span class="elsevierStyleSup">7 </span>with minor modifications, and in January 2013, it published guidelines on the diagnosis, classification and management of CKD that confirm the previous definition of CKD and classify it into stages based on glomerular filtration rate (GFR) values and the degree of albuminuria.<span class="elsevierStyleSup">8</span></p><p class="elsevierStylePara">In recent years, GFR has been considered the best index for assessing renal function. Given that it is not feasible to measure it in daily practice, various equations have been developed that allow its estimation from serum creatinine concentration, age, sex and race. However, other renal lesion markers have been required to define CKD when the GFR is >60ml/min/1.73m<span class="elsevierStyleSup">2 </span>(albuminuria, haematuria, abnormalities in imaging tests, etc.), fundamentally due to the imprecision and inaccuracy of estimated glomerular filtration rate (eGFR) equations, especially for higher values.<span class="elsevierStyleSup">6-8 </span>Although many equations have been published, the most used in our country are those of the Modification of Diet in Renal Disease<span class="elsevierStyleSup">9</span> study, whether in its classical version MDRD-4<span class="elsevierStyleSup">10</span> or IDMS-MDRD, according to whether the serum creatinine method is traceable with respect to the isotopic dilution mass spectrometry (IDMS)<span class="elsevierStyleSup">11 </span>reference measuring procedure. These equations also have been used to assess CKD prevalence in epidemiology and public health studies.<span class="elsevierStyleSup">12,13</span></p><p class="elsevierStylePara">The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) is a research group dependent on the National Institute of Diabetes and Digestive and Kidney Disease which has been set up to develop equations to estimate the GFR using data from different studies. In 2009, this group published a new equation using standardised creatinine methods, obtained from a population with higher GFR values, with a mean eGFR of 93.2ml/min/1.73m<span class="elsevierStyleSup">2 </span>being obtained using the CKD-EPI equation compared to 86.3ml/min/1.73m<span class="elsevierStyleSup">2 </span>with the IDMS-MDRD equation.<span class="elsevierStyleSup">14 </span>This is the equation recommended by the new 2013 KDIGO guidelines, given that it is more accurate than IDMS-MDRD for high GFR values, although it is highly imprecise, and as such, it is not useful for classifying CKD in stages 1 and 2, with signs of renal lesion also being required for the latter.<span class="elsevierStyleSup">8 </span>The improvement in the predictive capacity of the real GFR, especially between values of 60 and 90ml/min/1.73m,<span class="elsevierStyleSup">2 </span>and its greater capacity in the prognosis of overall mortality, cardiovascular episodes and risk of ESRD<span class="elsevierStyleSup">15 </span>mean that we must consider the new CKD-EPI equation as the equation of choice in the future. In fact, the recently published “Chronic Kidney Disease Consensus Document”, in which ten scientific societies participated under the direction of the Spanish Society of Nephrology (S.E.N.), recommends using this equation.<span class="elsevierStyleSup">16</span></p><p class="elsevierStylePara">However, the recommendation to use CKD-EPI has not yet been implemented by most clinical laboratories,<span class="elsevierStyleSup">9 </span>and as such, there is a need for tools that allow serum creatinine concentration to be quickly converted to the eGFR value using this equation. With this objective in mind, we have calculated and designed a table that allows the GFR to be estimated from serum creatinine concentration, age and sex, using the CKD-EPI equation, as we did previously with the IDMS-MDRD formula.<span class="elsevierStyleSup">17</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">METHODS</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara">To create these tables, we used a spreadsheet with the Excel 7 software (Microsoft, USA). They are the result of applying the CKD-EPI formula to the mean values for age and creatinine concentration intervals, according to sex. Given the characteristics of the majority population in our country, we have omitted the correction factor for black individuals.</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">RESULTS</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara">The tables show the eGFR value calculated using the CKD-EPI formula according to serum creatinine concentration, age and sex, using mean creatinine and age values for each interval and it is graded according to the different CKD stages. The results are displayed in two different tables, one in which serum creatinine concentration values are expressed in conventional units (mg/dl) and the other, which uses the International System (µmol/l) (Tables 1 and 2). The colour indicates the CKD stage to which the eGFR value corresponds.</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara">As is well-known, most scientific societies,<span class="elsevierStyleSup">6,7,18-24 </span>including the S.E.N. and the Spanish Society of Clinical Biochemistry and Molecular Pathology,<span class="elsevierStyleSup">25 </span>currently advise using eGFR through equations obtained by measuring serum creatinine concentration, age, sex and race. These equations have been a great step forward in early diagnosis and classification of CKD stages, with resulting major advantages, since they allow different treatments to be established that are aimed at stopping or slowing down kidney disease progression and achieving early treatment of its complications (anaemia, secondary hyperparathyroidism, etc.).<span class="elsevierStyleSup">26-28</span></p><p class="elsevierStylePara">Until recently, the MDRD equation was recommended by most clinical guidelines and scientific societies<span class="elsevierStyleSup">6,7,18,29-31 </span>and it has been demonstrated that the eGFR obtained from this equation is also useful for adjusting drug doses, since it is better suited than the Cockcroft-Gault equation for GFR<span class="elsevierStyleSup">32 </span>values lower than 60ml/min/1.73m<span class="elsevierStyleSup">2</span>. However, the MDRD equation has a series of limitations due to the population used in its development,<span class="elsevierStyleSup">33 </span>who were individuals with different degrees of CKD, which resulted in its imprecision and systematic underestimation of the real GFR, particularly for GFR<span class="elsevierStyleSup">34-39 </span>values greater than 60ml/min/1.73m<span class="elsevierStyleSup">2</span>. This underestimation may cause some individuals to undergo unnecessary studies, receive non-optimal doses of renal clearance drugs or avoid important but potentially nephrotoxic diagnostic procedures.</p><p class="elsevierStylePara">Due to all of the above, the need to seek new renal function markers or new GFR estimation equations have been advocated, which may improve the results of MDRD, especially for GFR greater than 60ml/min/1.73m<span class="elsevierStyleSup">2</span>. In 2009, the CKD-EPI group published a new equation developed from a population of 8254 individuals with different clinical characteristics, with or without kidney disease, which included serum creatinine concentration, age, sex and race as variables.<span class="elsevierStyleSup">14 </span>The GFR was measured in all individuals by iothalamate clearance (mean 68ml/min/1.73m<span class="elsevierStyleSup">2</span>, standard deviation = 40ml/min/1.73m<span class="elsevierStyleSup">2</span>) and serum creatinine (mean 145μmol/l) using methods that were traceable with respect to the IDMS reference method. The mean age of the population was 47 years old, with 9% of patients aged between 66 and 70 years old and 3% older than 71. They developed different equations according to race, sex and serum creatinine concentration value. The comparison of CKD-EPI with IDMS-MDRD demonstrated that the former was more accurate, particularly with regard to GFR values greater than 60ml/min/1.73m<span class="elsevierStyleSup">2</span> and this was the reason for which the authors reached the conclusion that CKD-EPI should replace IDMS-MDRD in standard clinical practice, even though it was highly imprecise compared to directly measuring the GFR. The application of CKD-EPI in the NHANES study (1999-2006) (National Survey on Health and Nutrition Examination) demonstrated that the median eGFR was 94.5ml/min/1.73m<span class="elsevierStyleSup">2 </span>compared with 85ml/min/1.73m<span class="elsevierStyleSup">2 </span>estimated with IDMS-MDRD, with a CKD prevalence of 11.5% compared to 13.1%, a reduction basically caused by a decrease in cases classified by IDMS-MDRD as stage 3 CKD.</p><p class="elsevierStylePara">In a study published by our group, the first that attempted to assess the new CKD-EPI equation in our setting in a large patient cohort, we confirmed that the new equation produced higher values than those obtained with IDMS-MDRD, which resulted in a reclassification of patients to higher CKD stages, such that 9.8% of cases that were classified as stage 3b CKD were changed to 3a, 17% of 3a CKD were changed to stage 2 and 15.7% were changed from stage 2 CKD to stage 1.<span class="elsevierStyleSup">40 </span>Furthermore, the analysis of age by subgroup demonstrated that this change towards higher GFR stages was greater in patients under 70 years of age. In the over 70 group, we observed a 90% concordance for CKD stages 2 to 5; by contrast, for those assigned to stage 1 CKD by IDMS-MDRD, a high number of cases were classified as stage 2 CKD by CKD-EPI. These data are similar to those obtained in a study carried out recently in our country in primary care, where fewer differences were observed between both equations for GFR estimation in older individuals than in the younger population.<span class="elsevierStyleSup">41 </span>Similar results were reported in a recently published study in which it was observed that CKD-EPI is less biased and more accurate than MDRD also in an aged European population older than 74 years old, with the equation for this age range being as satisfactory as in young subjects.<span class="elsevierStyleSup">12</span></p><p class="elsevierStylePara">As was previously mentioned, we believe it is important to highlight that in various studies, the CKD-EPI equation was associated with a better prognostic classification than IDMS-MDRD with respect to overall mortality, cardiovascular episodes and end-stage renal disease.<span class="elsevierStyleSup">43-45 </span>Likewise, the results of a recent meta-analysis conclude that CKD-EPI classifies fewer individuals with CKD and more reliably categorises the risk of mortality and ESRD than the IDMS-MDRD equation in a wide population range.<span class="elsevierStyleSup">15</span></p><p class="elsevierStylePara">New equations have recently been published based on serum creatinine concentration that aim to improve precision and decrease bias;<span class="elsevierStyleSup">46 </span>the current guidelines consider their use to be acceptable provided that they demonstrate more accuracy than CKD-EPI. We should also remember that the use of cystatin C serum concentration or eGFR by equations from it is subject to variables that are not dependent on the GFR and that its methods of measurement are being standardised. For now its use is recommend as a confirmatory measurement in adults with a GFR between 45 and 59ml/min/1.73m<span class="elsevierStyleSup">2 </span>without other renal lesion markers. In this case, the recommended equation is CKD-EPI for recently published standardised cystatin C.<span class="elsevierStyleSup">47</span></p><p class="elsevierStylePara">Due to the above, we believe that providing tools that allow a quick conversion of serum creatinine concentration to eGFR using this new equation could be useful, particularly when clinical laboratories do not have it incorporated in their reports, whether it be in our country or abroad, such as Latin America. It is important to note that the CKD-EPI equation is only applicable if standardised methods of measuring creatinine are employed. Furthermore, today, measuring eGFR is an important parameter on which many guidelines base the referral of patients to nephrologists, amongst others.</p><p class="elsevierStylePara">In summary, although the method currently recommended for determining the eGFR would be automatic calculation of CKD-EPI formulae by laboratories, in the meantime the availability of these tables allows the visualisation and conversion of standardised serum creatinine concentration by doctors, in order that they may transform it quickly and simply into a more clinically significant parameter, such as eGFR. Likewise, this additional information may provide a higher predictive capacity than isolated creatinine concentration or the eGFR equations used previously.</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conflicts of interest</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara">The authors declare that they have no conflicts of interest related to the contents of this article.</p><p class="elsevierStylePara"><a href="grande/12226_16025_56350_en_t1.11.12226_02.jpg" class="elsevierStyleCrossRefs"><img src="12226_16025_56350_en_t1.11.12226_02.jpg" alt="Calculation of the glomerular filtration rate according to serum creatinine concentration (mg/dl) and age using the CKD-EPI equation (white individuals)."></img></a></p><p class="elsevierStylePara">Table 1. Calculation of the glomerular filtration rate according to serum creatinine concentration (mg/dl) and age using the CKD-EPI equation (white individuals).</p><p class="elsevierStylePara"><a href="grande/12226_16025_56351_en_t2.11.12226_02.jpg" class="elsevierStyleCrossRefs"><img src="12226_16025_56351_en_t2.11.12226_02.jpg" alt="Calculation of the glomerular filtration rate according to serum creatinine concentration (µmol/l) and age using the CKD-EPI equation (white individuals). "></img></a></p><p class="elsevierStylePara">Table 2. Calculation of the glomerular filtration rate according to serum creatinine concentration (µmol/l) and age using the CKD-EPI equation (white individuals). </p>" "pdfFichero" => "P1-E567-S4548-A12226-EN.pdf" "tienePdf" => true "PalabrasClave" => array:2 [ "es" => array:6 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec438783" "palabras" => array:1 [ 0 => "MDRD" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec438785" "palabras" => array:1 [ 0 => "CKD-EPI" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec438787" "palabras" => array:1 [ 0 => "Tablas" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec438789" "palabras" => array:1 [ 0 => "Enfermedad renal crónica" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec438791" "palabras" => array:1 [ 0 => "Filtrado glomerular" ] ] 5 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec438793" "palabras" => array:1 [ 0 => "Creatinina" ] ] ] "en" => array:6 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec438784" "palabras" => array:1 [ 0 => "MDRD" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec438786" "palabras" => array:1 [ 0 => "CKD-EPI" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec438788" "palabras" => array:1 [ 0 => "Tables" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec438790" "palabras" => array:1 [ 0 => "Chronic kidney disease" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec438792" "palabras" => array:1 [ 0 => "Glomerular filtration rate" ] ] 5 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec438794" "palabras" => array:1 [ 0 => "Creatinine" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "es" => array:1 [ "resumen" => "<p class="elsevierStylePara">La enfermedad renal crónica (ERC) y las complicaciones que de ella se derivan se han convertido en un importante problema sanitario, tanto por los recursos que se requieren en los estadios finales de la enfermedad como por las complicaciones secundarias que conlleva, por lo que su diagnóstico precoz es considerado hoy de gran importancia. Las guías KDIGO 2013 recientemente publicadas basan la definición y clasificación de la ERC en los valores de filtrado glomerular y albuminuria como criterios de estadiaje y marcadores pronóstico de la enfermedad. Las ecuaciones MDRD y MDRD-IDMS (cuando se utilizan valores de creatinina obtenidos por métodos con trazabilidad al método de referencia) son las más utilizadas, pero tanto las guías internacionales KDIGO 2013 como el nuevo documento de consenso sobre la ERC 2013, en el que han participado diez sociedades científicas bajo la dirección de la Sociedad Española de Nefrología, recomiendan su sustitución por la ecuación CKD-EPI. Nuestro objetivo ha sido, tal y como hicimos con ecuaciones previas, elaborar unas tablas que permitan conocer el valor del filtrado glomerular estimado mediante la ecuación CKD-EPI a partir de la concentración sérica de creatinina, la edad y el sexo, y de este modo proporcionar un instrumento que facilite la difusión de esta nueva ecuación, especialmente en ámbitos en los que no se calcule de modo automático.</p>" ] "en" => array:1 [ "resumen" => "<p class="elsevierStylePara">Chronic kidney disease (CKD) and its complications have become a major healthcare problem, both due to the resources that are required in the final stages of the disease and to secondary complications. As such, its early diagnosis is considered to be very important nowadays. The recently published 2013 KDIGO guidelines base the definition and classification of CKD on glomerular filtration values and albuminuria as staging criteria and prognostic markers of the disease. The MDRD and MDRD-IDMS equations (when creatinine values can be traced to the reference method) are those most used, but both the 2013 KDIGO international guidelines and the new 2013 CKD consensus document, in which ten scientific societies participated under the direction of the Spanish Society of Nephrology, recommend to be replaced by the CKD-EPI equation. Our objective has been, as with previous equations, to develop tables that display the estimated glomerular filtration rate value using the CKD-EPI equation from serum creatinine concentration, age and sex, and thereby provide an instrument that facilitates the dissemination of this new equation, particularly in settings where it is not calculated automatically.</p>" ] ] "multimedia" => array:2 [ 0 => array:8 [ "identificador" => "fig1" "etiqueta" => "Tab. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "figura" => array:1 [ 0 => array:4 [ "imagen" => "12226_16025_56350_en_t1.11.12226_02.jpg" "Alto" => 2628 "Ancho" => 2147 "Tamanyo" => 2083230 ] ] "descripcion" => array:1 [ "en" => "Calculation of the glomerular filtration rate according to serum creatinine concentration (mg/dl) and age using the CKD-EPI equation (white individuals)." ] ] 1 => array:8 [ "identificador" => "fig2" "etiqueta" => "Tab. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "figura" => array:1 [ 0 => array:4 [ "imagen" => "12226_16025_56351_en_t2.11.12226_02.jpg" "Alto" => 2614 "Ancho" => 2108 "Tamanyo" => 2261850 ] ] "descripcion" => array:1 [ "en" => "Calculation of the glomerular filtration rate according to serum creatinine concentration (µmol/l) and age using the CKD-EPI equation (white individuals)." ] ] ] "bibliografia" => array:2 [ "titulo" => "Bibliography" "seccion" => array:1 [ 0 => array:1 [ "bibliografiaReferencia" => array:47 [ 0 => array:3 [ "identificador" => "bib1" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:3 [ "referenciaCompleta" => "Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, et al. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 16 | 6 | 22 |
| 2024 October | 104 | 65 | 169 |
| 2024 September | 127 | 65 | 192 |
| 2024 August | 148 | 86 | 234 |
| 2024 July | 155 | 52 | 207 |
| 2024 June | 131 | 72 | 203 |
| 2024 May | 186 | 68 | 254 |
| 2024 April | 139 | 58 | 197 |
| 2024 March | 147 | 36 | 183 |
| 2024 February | 105 | 49 | 154 |
| 2024 January | 104 | 33 | 137 |
| 2023 December | 86 | 37 | 123 |
| 2023 November | 133 | 53 | 186 |
| 2023 October | 140 | 48 | 188 |
| 2023 September | 112 | 403 | 515 |
| 2023 August | 118 | 32 | 150 |
| 2023 July | 148 | 63 | 211 |
| 2023 June | 83 | 36 | 119 |
| 2023 May | 124 | 62 | 186 |
| 2023 April | 112 | 43 | 155 |
| 2023 March | 150 | 29 | 179 |
| 2023 February | 96 | 17 | 113 |
| 2023 January | 95 | 38 | 133 |
| 2022 December | 125 | 21 | 146 |
| 2022 November | 112 | 39 | 151 |
| 2022 October | 111 | 44 | 155 |
| 2022 September | 143 | 46 | 189 |
| 2022 August | 132 | 56 | 188 |
| 2022 July | 121 | 51 | 172 |
| 2022 June | 104 | 60 | 164 |
| 2022 May | 155 | 55 | 210 |
| 2022 April | 193 | 87 | 280 |
| 2022 March | 149 | 73 | 222 |
| 2022 February | 188 | 65 | 253 |
| 2022 January | 157 | 37 | 194 |
| 2021 December | 145 | 57 | 202 |
| 2021 November | 126 | 47 | 173 |
| 2021 October | 173 | 42 | 215 |
| 2021 September | 145 | 54 | 199 |
| 2021 August | 183 | 70 | 253 |
| 2021 July | 127 | 50 | 177 |
| 2021 June | 133 | 38 | 171 |
| 2021 May | 161 | 44 | 205 |
| 2021 April | 426 | 98 | 524 |
| 2021 March | 203 | 63 | 266 |
| 2021 February | 163 | 33 | 196 |
| 2021 January | 171 | 38 | 209 |
| 2020 December | 131 | 19 | 150 |
| 2020 November | 118 | 24 | 142 |
| 2020 October | 100 | 19 | 119 |
| 2020 September | 137 | 20 | 157 |
| 2020 August | 113 | 20 | 133 |
| 2020 July | 108 | 15 | 123 |
| 2020 June | 124 | 28 | 152 |
| 2020 May | 142 | 27 | 169 |
| 2020 April | 120 | 31 | 151 |
| 2020 March | 117 | 20 | 137 |
| 2020 February | 112 | 31 | 143 |
| 2020 January | 103 | 37 | 140 |
| 2019 December | 105 | 43 | 148 |
| 2019 November | 94 | 38 | 132 |
| 2019 October | 103 | 13 | 116 |
| 2019 September | 206 | 37 | 243 |
| 2019 August | 94 | 14 | 108 |
| 2019 July | 101 | 23 | 124 |
| 2019 June | 94 | 25 | 119 |
| 2019 May | 74 | 26 | 100 |
| 2019 April | 168 | 52 | 220 |
| 2019 March | 121 | 32 | 153 |
| 2019 February | 77 | 25 | 102 |
| 2019 January | 76 | 38 | 114 |
| 2018 December | 202 | 53 | 255 |
| 2018 November | 222 | 27 | 249 |
| 2018 October | 176 | 26 | 202 |
| 2018 September | 198 | 27 | 225 |
| 2018 August | 151 | 25 | 176 |
| 2018 July | 127 | 20 | 147 |
| 2018 June | 126 | 25 | 151 |
| 2018 May | 146 | 16 | 162 |
| 2018 April | 150 | 9 | 159 |
| 2018 March | 137 | 11 | 148 |
| 2018 February | 138 | 17 | 155 |
| 2018 January | 142 | 11 | 153 |
| 2017 December | 148 | 16 | 164 |
| 2017 November | 146 | 26 | 172 |
| 2017 October | 129 | 17 | 146 |
| 2017 September | 124 | 8 | 132 |
| 2017 August | 136 | 17 | 153 |
| 2017 July | 148 | 14 | 162 |
| 2017 June | 137 | 11 | 148 |
| 2017 May | 134 | 21 | 155 |
| 2017 April | 120 | 23 | 143 |
| 2017 March | 106 | 9 | 115 |
| 2017 February | 250 | 17 | 267 |
| 2017 January | 91 | 19 | 110 |
| 2016 December | 137 | 14 | 151 |
| 2016 November | 173 | 20 | 193 |
| 2016 October | 292 | 27 | 319 |
| 2016 September | 517 | 7 | 524 |
| 2016 August | 496 | 16 | 512 |
| 2016 July | 338 | 19 | 357 |
| 2016 June | 251 | 0 | 251 |
| 2016 May | 204 | 0 | 204 |
| 2016 April | 226 | 0 | 226 |
| 2016 March | 175 | 0 | 175 |
| 2016 February | 198 | 0 | 198 |
| 2016 January | 230 | 0 | 230 |
| 2015 December | 189 | 0 | 189 |
| 2015 November | 174 | 0 | 174 |
| 2015 October | 161 | 0 | 161 |
| 2015 September | 159 | 0 | 159 |
| 2015 August | 145 | 0 | 145 |
| 2015 July | 205 | 0 | 205 |
| 2015 June | 84 | 0 | 84 |
| 2015 May | 86 | 0 | 86 |
| 2015 April | 11 | 0 | 11 |
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