Objective-To describe the clinical features, prognosis, and treatment of patients presenting with atypical forms of acute myocardial infarction. Design-Consecutive cases of possible acute myocardial infarction were sought from coronary care registers, biochemistry records, and hospital management systems. Case notes were reviewed and predefined epidemiological and clinical variables were abstracted. Setting-20 adjacent hospitals in the former Yorkshire region. Patients-3684 consecutive cases of possible acute myocardial infarction admitted in a three month period were identified, of whom 2096 had a first episode of confirmed acute myocardial infarction. Results-20.2% of all patients admitted with an eventual diagnosis of acute myocardial infarction presented with symptoms other than chest pain. Compared with the group presenting with chest pain, these patients were older (76.6 v 69.1 years, p < 0.001), were more often women (54.6% v 35.3%, p < 0.001), and were more likely to have a history of heart failure (18.6% v 6.9%, p < 0.001). They had a higher 30 and 365 day mortality (49.2% and 61.0%, respectively) compared with patients presenting with chest pain (17.9% and 26.2%). In a Cox regression analysis the hazard ratio for presentation without chest pain was 1.60 (95% confidence interval 1.30 to 1.97) (p < 0.001) adjusted for age, heart rate, blood pressure, left ventricular impairment, and infarction with ST segment elevation as covariates. Importantly, they were also less likely to receive treatments with a proven ability to improve prognosis. Conclusions-Atypical presentation of myocardial infarction without chest pain is common and associated with increased mortality. This may result in part from a failure to use beneficial treatment strategies. (Heart 2001;86:494-498)

on behalf of the SPACE ROCKET Trial GroupBackground-Pharmacogenetics aims to maximize benefits and minimize risks of drug treatment. Our objectives were to examine the influence of common variants of hepatic metabolism and transporter genes on the lipid-lowering response to statin therapy. Methods and Results-The Genetic Effects On STATins (GEOSTAT-1) Study was a genetic substudy of Secondary Prevention of Acute Coronary Events-Reduction of Cholesterol to Key European Targets (SPACE ROCKET) (a randomized, controlled trial comparing 40 mg of simvastatin and 10 mg of rosuvastatin) that recruited 601 patients after myocardial infarction. We genotyped the following functional single nucleotide polymorphisms in the genes coding for the cytochrome P450 (CYP) metabolic enzymes, CYP2C9*2 (430CϾT), CYP2C9*3 (1075AϾC), CYP2C19*2 (681GϾA), CYP3A5*1 (6986AϾG), and hepatic influx and efflux transporters SLCO1B1 (521TϾC) and breast cancer resistance protein (BCRP; 421CϾA). We assessed 3-month LDL cholesterol levels and the proportion of patients reaching the current LDL cholesterol target of Ͻ70 mg/dL (Ͻ1.81 mmol/L). An enhanced response to rosuvastatin was seen for patients with variant genotypes of either CYP3A5 (Pϭ0.006) or BCRP (Pϭ0.010). Furthermore, multivariate logistic-regression analysis revealed that patients with at least 1 variant CYP3A5 and/or BCRP allele (nϭ186) were more likely to achieve the LDL cholesterol target (odds ratio: 2.289; 95% CI: 1.157, 4.527; Pϭ0.017; rosuvastatin 54.0% to target vs simvastatin 33.7%). There were no differences for patients with variants of CYP2C9, CYP2C19, or SLCO1B1 in comparison with their respective wild types, nor were differential effects on statin response seen for patients with the most common genotypes for CYP3A5 and BCRP (nϭ415; odds ratio: 1.207; 95% CI: 0.768, 1.899; Pϭ0.415). Conclusion-The

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Objectives Use of cumulative mortality adjusted for case mix in patients with acute myocardial infarction for early detection of variation in clinical practice. Design Observational study. Setting 20 hospitals across the former Yorkshire region. Participants All 2153 consecutive patients with confirmed acute myocardial infarction identified during three months. Main outcome measures Variable life-adjusted displays showing cumulative differences between observed and expected mortality of patients; expected mortality calculated from risk model based on admission characteristics of age, heart rate, and systolic blood pressure. Results The performance of two individual hospitals over three months was examined as an example. One, the smallest district hospital in the region, had a series of 30 consecutive patients but had five more deaths than predicted. The variable life-adjusted display showed minimal variation from that predicted for the first 15 patients followed by a run of unexpectedly high mortality. The second example was the main tertiary referral centre for the region, which admitted 188 consecutive patients. The display showed a period of apparently poor performance followed by substantial improvement, where the plot rose steadily from a cumulative net lives saved of − 4 to 7. These variations in patient outcome are unlikely to have been revealed during conventional audit practice. Conclusions Variable life-adjusted display has been integrated into surgical care as a graphical display of risk-adjusted survival for individual surgeons or centres. In combination with a simple risk model, it may have a role in monitoring performance and outcome in patients with acute myocardial infarction.

Objective-To develop a simple risk model as a basis for evaluating care of patients admitted with acute myocardial infarction. Methods-From coronary care registers, biochemistry records and hospital management systems, 2153 consecutive patients with confirmed acute myocardial infarction were identified. With 30 day all cause mortality as the end point, a multivariable logistic regression model of risk was constructed and validated in independent patient cohorts. The areas under receiver operating characteristic curves were calculated as an assessment of sensitivity and specificity. The model was reapplied to a number of commonly studied subgroups for further assessment of robustness. Results-A three variable model was developed based on age, heart rate, and systolic blood pressure on admission. This produced an individual probability of death by 30 days (P 30 ) where P 30 = 1/(1 + exp(−L 30 )) and L 30 = −5.624 + (0.085 × age) + (0.014 × heart rate) − (0.022 × systolic blood pressure). The areas under the receiver operating characteristic curves for the reference and test cohorts were 0.79 (95% CI 0.76 to 0.82) and 0.76 (95% CI 0.72 to 0.79), respectively. To aid application of the model to routine clinical audit, a normogram relating observed mortality and sample size to the likelihood of a significant deviation from the expected 30 day mortality rate was constructed.Conclusions-This risk model is simple, reproducible, and permits quality of care of acute myocardial infarction patients to be reliably evaluated both within and between centres. (Heart 2001;86:150-154)