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      "pt" => array:1 [
        "titulo" => "Estratifica&#231;&#227;o de risco nas s&#237;ndromas coron&#225;rias agudas&#58; como poder&#225; o Grace ser destronado&#63;"
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic curve analysis for the prediction of in-hospital mortality using the ProACS and GRACE scores&#46; AUC&#58; area under the curve&#59; CI&#58; confidence interval&#59; SE&#58; standard error&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">We read with much interest the recently published paper by Tim&#243;teo et al&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> This study makes an important contribution to the expanding field of risk stratification in myocardial infarction &#40;MI&#41;&#44; which is the cornerstone for patient management&#46; The authors developed a simple risk model from a large cohort of real-world MI patients&#44; comprising common and easily accessible clinical variables&#44; constructing a high-performing in-hospital mortality risk score&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Several risk scores have been developed to predict outcomes in patients with acute coronary syndromes&#46; The GRACE score<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">2</span></a> is the most widely used and has been shown to outperform other previously developed mortality risk models&#46;<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">3</span></a> The ACHTUNG-Rule&#44;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">4</span></a> based on clinical and laboratory parameters&#44; outperformed the GRACE score in its derivation and validation sets but&#44; in addition to requiring a calculator&#44; it still lacks calibration and validation in larger and external cohorts&#46; McNamara et al&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">5</span></a> recently developed a novel in-hospital mortality risk score from a large contemporary cohort&#44; with calibration curves demonstrating its utility even in patients presenting with cardiac arrest&#44; a significant advantage in the context of MI given the difficulty in accurately predicting outcomes in this patient subgroup&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Although the GRACE and ProACS<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> scores share some variables&#44; the latter does have some advantages&#58; &#40;i&#41; it is simpler to use in clinical practice&#44; with fewer variables and no need for a calculator&#59; &#40;ii&#41; it uses the same cutoffs for ST-elevation &#40;STEMI&#41; and non-ST-elevation &#40;NSTEMI&#41; MI&#44; unlike GRACE&#59; and &#40;iii&#41; it is particularly useful in identifying truly low-risk patients&#44; as a score of 0 is associated with very low risk of in-hospital mortality &#40;0&#46;4&#37;&#41;&#46; In contrast&#44; the GRACE score predicts mortality risk as a continuum&#44; although low-risk strata have been proposed for STEMI and NSTEMI cases&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">We validated the ProACS risk model in an independent and somewhat more contemporary &#40;2010-2013&#41; cohort of 1000 consecutive MI patients &#40;43&#46;5&#37; with STEMI&#41;&#46; <a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a> illustrates the performance of both GRACE and ProACS for predicting in-hospital mortality in our cohort&#46; Although the intermediate and high-risk strata of the ProACS score identified nearly 98&#37; of in-hospital deaths&#44; confirming the utility of the score in the stratification of ACS patients&#44; its discriminative power was significantly inferior to that reported in its internal and external validation cohorts&#46; Perhaps more importantly&#44; the discriminative performance of ProACS was significantly inferior to that of GRACE&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">We believe that any new risk score should provide simplicity without significantly compromising accuracy of risk stratification&#46; Using a more intuitive approach with a measure of risk reclassification&#44; known as the integrated discrimination improvement &#40;IDI&#41; index&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> we noticed that compared with GRACE&#44; the ProACS score is indeed particularly useful in identifying truly low-risk patients who could potentially be considered for conservative management or early discharge &#40;a 56&#46;3&#37; improvement in prediction for patients who did not die during hospitalization&#41;&#46; However&#44; this comes at the expense of a significantly lower &#40;61&#46;8&#37;&#41; predictive ability in the identification of patients who eventually die during their hospitalization&#46; The relative IDI index was -5&#46;5&#37;&#46; We further expanded on this by using a category-based measure of risk reclassification known as net reclassification improvement &#40;NRI&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> A positive and significant NRI index translates a net overall successful reclassification of subjects into more appropriate risk categories &#40;e&#46;g&#46; a patient who reaches the primary endpoint who is reclassified into a higher risk group with the new model or a subject who does not reach the primary endpoint who is reclassified into a lower risk category&#41;&#46; We used the same risk categories proposed by the GRACE and ProACS investigators&#46; As seen in <a class="elsevierStyleCrossRefs" href="#tbl0005">Tables 1 and 2</a>&#44; altogether the ProACS score reclassified 26&#46;2&#37; of STEMI patients and 17&#46;7&#37; of NSTEMI patients into risk strata which were less accurate representations of their observed mortality risks&#46; However&#44; ProACS did reclassify low-risk NSTEMI patients into more appropriate &#40;lower&#41; risk categories &#40;partial NRI of &#43;9&#46;3&#37;&#41;&#46; The above observations suggest that the GRACE score is superior in identifying high-risk patients&#44; whereas ProACS may be more useful in identifying low-risk patients who present with NSTEMI &#40;but not STEMI&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0030" class="elsevierStylePara elsevierViewall">Furthermore&#44; the ability to also estimate mortality during clinical follow-up and across different types of MI would surely improve the applicability of ProACS&#44; since risk models differ significantly in their predictive performance when applied to MI that arises from a primary coronary event &#40;type 1&#41; vs&#46; supply&#47;demand mismatch &#40;type 2&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">7</span></a></p><p id="par0035" class="elsevierStylePara elsevierViewall">In summary&#44; although the authors should be commended for their attempt to improve and simplify risk stratification of MI patients&#44; it remains to be determined whether the simplicity of this new score&#44; derived from a large Portuguese registry&#44; is offset by its inferior prognostic power compared to the gold standard ACS risk score&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Conflicts of interest</span><p id="par0040" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic curve analysis for the prediction of in-hospital mortality using the ProACS and GRACE scores&#46; AUC&#58; area under the curve&#59; CI&#58; confidence interval&#59; SE&#58; standard error&#46;</p>"
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          "leyenda" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">NRI&#58; net reclassification improvement&#46;</p><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">For patients with ST-elevation myocardial infarction &#40;STEMI&#41;&#44; a GRACE score below 126 was considered low risk&#44; a score between 126 and 154 was assigned to the intermediate risk category and above 154 was assigned to the high risk group&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col">In-hospital all-cause mortality</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">GRACE &#40;STEMI&#41;</th><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Events &#40;n&#61;48&#41;</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="middle">ProACS</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="top">NRI&#58; -26&#46;5&#37;<br>p&#60;0&#46;001</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">36&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Non-Events &#40;n&#61;387&#41;</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">81&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">86&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">56&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">146&nbsp;\t\t\t\t\t\t\n
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          "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">NRI&#58; net reclassification improvement&#46;</p><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">For patients with non-ST-segment elevation myocardial infarction &#40;NSTEMI&#41;&#44; a GRACE score below 109 was considered low risk&#44; while scores between 109 and 140 and above 140 were assigned to intermediate and high risk categories&#44; respectively&#46;</p>"
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                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " rowspan="2" align="center" valign="top" scope="col" colspan="3" style="border-bottom: 2px solid black">In-hospital all-cause mortality</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">GRACE &#40;NSTEMI&#41;</th><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Events &#40;n&#61;37&#41;</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="middle">ProACS</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="top">NRI&#58; -17&#46;6&#37;<br>p&#61;0&#46;051</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">26&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Non-Events &#40;n&#61;528&#41;</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">55&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">82&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">101&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">27&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">213&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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Letter to the Editor
Risk stratification in acute coronary syndromes: Graced by a new score?
Estratificação de risco nas síndromas coronárias agudas: como poderá o Grace ser destronado?
Luís Paivaa,b,
Corresponding author
luisvpaiva@gmail.com

Corresponding author.
, Sérgio Barrac, Lino Gonçalvesa,b
a Hospital Geral, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
b Universidade de Coimbra, Coimbra, Portugal
c Cardiology Department, Papworth Hospital NHS Foundation Trust, Cambridge, UK
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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">We read with much interest the recently published paper by Tim&#243;teo et al&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> This study makes an important contribution to the expanding field of risk stratification in myocardial infarction &#40;MI&#41;&#44; which is the cornerstone for patient management&#46; The authors developed a simple risk model from a large cohort of real-world MI patients&#44; comprising common and easily accessible clinical variables&#44; constructing a high-performing in-hospital mortality risk score&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Several risk scores have been developed to predict outcomes in patients with acute coronary syndromes&#46; The GRACE score<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">2</span></a> is the most widely used and has been shown to outperform other previously developed mortality risk models&#46;<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">3</span></a> The ACHTUNG-Rule&#44;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">4</span></a> based on clinical and laboratory parameters&#44; outperformed the GRACE score in its derivation and validation sets but&#44; in addition to requiring a calculator&#44; it still lacks calibration and validation in larger and external cohorts&#46; McNamara et al&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">5</span></a> recently developed a novel in-hospital mortality risk score from a large contemporary cohort&#44; with calibration curves demonstrating its utility even in patients presenting with cardiac arrest&#44; a significant advantage in the context of MI given the difficulty in accurately predicting outcomes in this patient subgroup&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Although the GRACE and ProACS<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> scores share some variables&#44; the latter does have some advantages&#58; &#40;i&#41; it is simpler to use in clinical practice&#44; with fewer variables and no need for a calculator&#59; &#40;ii&#41; it uses the same cutoffs for ST-elevation &#40;STEMI&#41; and non-ST-elevation &#40;NSTEMI&#41; MI&#44; unlike GRACE&#59; and &#40;iii&#41; it is particularly useful in identifying truly low-risk patients&#44; as a score of 0 is associated with very low risk of in-hospital mortality &#40;0&#46;4&#37;&#41;&#46; In contrast&#44; the GRACE score predicts mortality risk as a continuum&#44; although low-risk strata have been proposed for STEMI and NSTEMI cases&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">We validated the ProACS risk model in an independent and somewhat more contemporary &#40;2010-2013&#41; cohort of 1000 consecutive MI patients &#40;43&#46;5&#37; with STEMI&#41;&#46; <a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a> illustrates the performance of both GRACE and ProACS for predicting in-hospital mortality in our cohort&#46; Although the intermediate and high-risk strata of the ProACS score identified nearly 98&#37; of in-hospital deaths&#44; confirming the utility of the score in the stratification of ACS patients&#44; its discriminative power was significantly inferior to that reported in its internal and external validation cohorts&#46; Perhaps more importantly&#44; the discriminative performance of ProACS was significantly inferior to that of GRACE&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">We believe that any new risk score should provide simplicity without significantly compromising accuracy of risk stratification&#46; Using a more intuitive approach with a measure of risk reclassification&#44; known as the integrated discrimination improvement &#40;IDI&#41; index&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> we noticed that compared with GRACE&#44; the ProACS score is indeed particularly useful in identifying truly low-risk patients who could potentially be considered for conservative management or early discharge &#40;a 56&#46;3&#37; improvement in prediction for patients who did not die during hospitalization&#41;&#46; However&#44; this comes at the expense of a significantly lower &#40;61&#46;8&#37;&#41; predictive ability in the identification of patients who eventually die during their hospitalization&#46; The relative IDI index was -5&#46;5&#37;&#46; We further expanded on this by using a category-based measure of risk reclassification known as net reclassification improvement &#40;NRI&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> A positive and significant NRI index translates a net overall successful reclassification of subjects into more appropriate risk categories &#40;e&#46;g&#46; a patient who reaches the primary endpoint who is reclassified into a higher risk group with the new model or a subject who does not reach the primary endpoint who is reclassified into a lower risk category&#41;&#46; We used the same risk categories proposed by the GRACE and ProACS investigators&#46; As seen in <a class="elsevierStyleCrossRefs" href="#tbl0005">Tables 1 and 2</a>&#44; altogether the ProACS score reclassified 26&#46;2&#37; of STEMI patients and 17&#46;7&#37; of NSTEMI patients into risk strata which were less accurate representations of their observed mortality risks&#46; However&#44; ProACS did reclassify low-risk NSTEMI patients into more appropriate &#40;lower&#41; risk categories &#40;partial NRI of &#43;9&#46;3&#37;&#41;&#46; The above observations suggest that the GRACE score is superior in identifying high-risk patients&#44; whereas ProACS may be more useful in identifying low-risk patients who present with NSTEMI &#40;but not STEMI&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0030" class="elsevierStylePara elsevierViewall">Furthermore&#44; the ability to also estimate mortality during clinical follow-up and across different types of MI would surely improve the applicability of ProACS&#44; since risk models differ significantly in their predictive performance when applied to MI that arises from a primary coronary event &#40;type 1&#41; vs&#46; supply&#47;demand mismatch &#40;type 2&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">7</span></a></p><p id="par0035" class="elsevierStylePara elsevierViewall">In summary&#44; although the authors should be commended for their attempt to improve and simplify risk stratification of MI patients&#44; it remains to be determined whether the simplicity of this new score&#44; derived from a large Portuguese registry&#44; is offset by its inferior prognostic power compared to the gold standard ACS risk score&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Conflicts of interest</span><p id="par0040" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col">In-hospital all-cause mortality</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">GRACE &#40;STEMI&#41;</th><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Low risk&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Events &#40;n&#61;48&#41;</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="middle">ProACS</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="top">NRI&#58; -26&#46;5&#37;<br>p&#60;0&#46;001</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">36&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Non-Events &#40;n&#61;387&#41;</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">81&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">86&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">56&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">146&nbsp;\t\t\t\t\t\t\n
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          "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">NRI&#58; net reclassification improvement&#46;</p><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">For patients with non-ST-segment elevation myocardial infarction &#40;NSTEMI&#41;&#44; a GRACE score below 109 was considered low risk&#44; while scores between 109 and 140 and above 140 were assigned to intermediate and high risk categories&#44; respectively&#46;</p>"
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                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " rowspan="2" align="center" valign="top" scope="col" colspan="3" style="border-bottom: 2px solid black">In-hospital all-cause mortality</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">GRACE &#40;NSTEMI&#41;</th><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Events &#40;n&#61;37&#41;</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="middle">ProACS</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " rowspan="6" align="left" valign="top">NRI&#58; -17&#46;6&#37;<br>p&#61;0&#46;051</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">26&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">Non-Events &#40;n&#61;528&#41;</td><td class="td" title="table-entry  " align="left" valign="top">Low risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">55&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">82&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">101&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">High risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">27&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">213&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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Article information
ISSN: 21742049
Original language: English
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2021 January 26 13 39
2020 December 22 17 39
2020 November 21 13 34
2020 October 12 10 22
2020 September 32 12 44
2020 August 17 9 26
2020 July 27 4 31
2020 June 27 8 35
2020 May 19 9 28
2020 April 34 6 40
2020 March 24 12 36
2020 February 38 25 63
2020 January 19 9 28
2019 December 20 9 29
2019 November 11 15 26
2019 October 15 4 19
2019 September 32 7 39
2019 August 22 10 32
2019 July 18 10 28
2019 June 24 13 37
2019 May 20 15 35
2019 April 14 12 26
2019 March 9 13 22
2019 February 16 10 26
2019 January 12 9 21
2018 December 17 9 26
2018 November 49 13 62
2018 October 112 17 129
2018 September 33 8 41
2018 August 24 5 29
2018 July 16 7 23
2018 June 18 9 27
2018 May 26 13 39
2018 April 19 8 27
2018 March 28 5 33
2018 February 7 3 10
2018 January 18 6 24
2017 December 27 16 43
2017 November 18 15 33
2017 October 32 20 52
2017 September 11 5 16
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Idiomas
Revista Portuguesa de Cardiologia (English edition)
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