Improving risk stratification in non-ST-segment elevation myocardial infarction with combined assessment of GRACE and CRUSADE risk scores

BACKGROUND: Risk assessment is fundamental in the management of acute coronary syndromes (ACS), enabling estimation of prognosis. AIMS: To evaluate whether the combined use of GRACE and CRUSADE risk stratification schemes in patients with myocardial infarction outperforms each of the scores individually in terms of mortality and haemorrhagic risk prediction. METHODS: Observational retrospective single-centre cohort study including 566 consecutive patients admitted for non-ST-segment elevation myocardial infarction. The CRUSADE model increased GRACE discriminatory performance in predicting all-cause mortality, ascertained by Cox regression, demonstrating CRUSADE independent and additive predictive value, which was sustained throughout follow-up. The cohort was divided into four different subgroups: G1 (GRACE<141; CRUSADE<41); G2 (GRACE<141; CRUSADE≥41); G3 (GRACE≥141; CRUSADE<41); G4 (GRACE≥141; CRUSADE≥41). RESULTS: Outcomes and variables estimating clinical severity, such as admission Killip-Kimbal class and left ventricular systolic dysfunction, deteriorated progressively throughout the subgroups (G1 to G4). Survival analysis differentiated three risk strata (G1, lowest risk; G2 and G3, intermediate risk; G4, highest risk). The GRACE+CRUSADE model revealed higher prognostic performance (area under the curve [AUC] 0.76) than GRACE alone (AUC 0.70) for mortality prediction, further confirmed by the integrated discrimination improvement index. Moreover, GRACE+CRUSADE combined risk assessment seemed to be valuable in delineating bleeding risk in this setting, identifying G4 as a very high-risk subgroup (hazard ratio 3.5; P<0.001). CONCLUSIONS: Combined risk stratification with GRACE and CRUSADE scores can improve the individual discriminatory power of GRACE and CRUSADE models in the prediction of all-cause mortality and bleeding. This combined assessment is a practical approach that is potentially advantageous in treatment decision-making.

Polymyalgia Rheumatica (PMR) Special Interest Group at OMERACT 11: outcomes of importance for patients with PMR

We worked toward developing a core outcome set for clinical research studies in polymyalgia rheumatica (PMR) by conducting (1) patient consultations using modified nominal group technique; (2) a systematic literature review of outcome measures in PMR; (3) a pilot observational study of patients presenting with untreated PMR, and further discussion with patient research partners; and (4) a qualitative focus group study of patients with PMR on the meaning of stiffness, using thematic analysis. (1) Consultations included 104 patients at 4 centers. Symptoms of PMR included pain, stiffness, fatigue, and sleep disturbance. Function, anxiety, and depression were also often mentioned. Participants expressed concerns about diagnostic delay, adverse effects of glucocorticoids, and fear of relapse. (2) In the systematic review, outcome measures previously used for PMR include pain visual analog scores (VAS), morning stiffness, blood markers, function, and quality of life; standardized effect sizes posttreatment were large. (3) Findings from the observational study indicated that asking about symptom severity at 7 AM, or "on waking," appeared more relevant to disease activity than asking about symptom severity "now" (which depended on the time of assessment). (4) Preliminary results were presented from the focus group qualitative study, encompassing broad themes of stiffness, pain, and the effect of PMR on patients' lives. It was concluded that further validation work is required before a core outcome set in PMR can be recommended. Nevertheless, the large standardized effect sizes suggest that pain VAS is likely to be satisfactory as a primary outcome measure for assessing response to initial therapy of PMR. Dissection of between-patient heterogeneity in the subsequent treatment course may require attention to comorbidity as a potential confounding factor.