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The study of industrial agglomeration is not new, dating back at least to the work of Marshall (1890). The recent revival of interest in the phenomenon has two important sources. The first is a growing body of North American empirical work showing high and rising levels of agglomeration across a wide range of industries. Rosenfeld (1996) calculates that 380 US agglomerations account for 57% of the nation's employment, for 61% of its output and for 78% of its export. Using a more conservative methodology, Porter (2001) still calculates that 30% of US employment occurs in agglomerations. Furthermore, Kim's (2002) longitudinal study finds that the geographical density of employment in many US sectors is increasing. The second source of renewed interest is another growing body of empirical work, which shows that industrial agglomeration is linked to superior economic performance: that firms in strong agglomerations grow faster than average and that strong agglomerations attract a disproportionate amount of new entrants (for example, Pandit et al, 2002;Swann et al, 1998); and that productivity (for example, Henderson, 1986) and innovation (for example, Baptista and Swann, 1998) are higher within strong agglomerations. In response to this renewed interest new attempts have been made to explain the prevalence of industrial agglomeration by elucidating the link between the geographical concentration of production and superior economic performance.

ObjectiveWe aimed to derive and validate a clinical decision rule (CDR) for suspected cardiac chest pain in the emergency department (ED). Incorporating information available at the time of first presentation, this CDR would effectively risk-stratify patients and immediately identify: (A) patients for whom hospitalisation may be safely avoided; and (B) high-risk patients, facilitating judicious use of resources.MethodsIn two sequential prospective observational cohort studies at heterogeneous centres, we included ED patients with suspected cardiac chest pain. We recorded clinical features and drew blood on arrival. The primary outcome was major adverse cardiac events (MACE) (death, prevalent or incident acute myocardial infarction, coronary revascularisation or new coronary stenosis >50%) within 30 days. The CDR was derived by logistic regression, considering reliable (κ>0.6) univariate predictors (p<0.05) for inclusion.ResultsIn the derivation study (n=698) we derived a CDR including eight variables (high sensitivity troponin T; heart-type fatty acid binding protein; ECG ischaemia; diaphoresis observed; vomiting; pain radiation to right arm/shoulder; worsening angina; hypotension), which had a C-statistic of 0.95 (95% CI 0.93 to 0.97) implying near perfect diagnostic performance. On external validation (n=463) the CDR identified 27.0% of patients as ‘very low risk’ and potentially suitable for discharge from the ED. 0.0% of these patients had prevalent acute myocardial infarction and 1.6% developed MACE (n=2; both coronary stenoses without revascularisation). 9.9% of patients were classified as ‘high-risk’, 95.7% of whom developed MACE.ConclusionsThe Manchester Acute Coronary Syndromes (MACS) rule has the potential to safely reduce unnecessary hospital admissions and facilitate judicious use of high dependency resources.

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