Iconic buildings in the making of city identity: The role of aspirational identity artefacts.

Iconic buildings are important meaning generators in cities. This study explores the role that iconic buildings in-the-making have in the discursive construction of city identity in public debate. Through the examination of the Locarno PalaCinema case (Switzerland), our study proposes that iconic buildings - during their planning - can serve as aspirational identity artefacts: objects that are mobilised in discourse to inform productive idealisations of city identity by powerful urban actors. Findings identify the mechanisms through which the aspirational artefact and city identity interact in discourse, showing that iconic building projects orient city identity claims, while at the same time city identity meanings taken from collective memory, present understandings and future aspirations are used by actors to infuse the evolving project with meaning. This study aims to contribute to debates in urban planning and city identity by discussing the identity anticipation role of the planning of iconic buildings and how they can be a productive ground to reflect, re-orient and re-claim the unique features of a city's identity while aspiring to achieve a different future.

An economic assessment of analogue basal-bolus insulin versus human basal-bolus insulin in subjects with type 1 diabetes in the UK.

BACKGROUND: A recent study demonstrated that treatment of type 1 diabetes with an analogue basal-bolus insulin regimen was associated with improved glycaemic control (HbA(1c) -0.22% points, p < 0.001), reduced risk of hypoglycaemic events (-21%, p = 0.036) and reduction in body mass index (-0.30 kg/m(2), p < 0.001) compared to a human basal-bolus regimen after 18 weeks. METHODS: A published and validated computer simulation model was used to project long-term economic and clinical outcomes in a simulated cohort of type 1 diabetes patients treated with either insulin detemir plus insulin aspart (analogue) or Neutral Protamine Hagedorn plus human soluble insulin (human), in a UK setting. Probabilities of complications and HbA(1c)-dependent adjustments were derived from major clinical and epidemiological studies. Complication and treatment costs were projected over patient lifetimes from a National Health Service perspective. Costs and clinical benefits were discounted at 3.5% annually. RESULTS: Quality-adjusted life expectancy (QALE) was 0.66 quality-adjusted life years (QALY) higher in the analogue insulin versus the human insulin group (mean +/- SD) (7.65 +/- 0.09 versus 6.99 +/- 0.08). Direct lifetime costs were 1654 pounds greater with analogue versus human insulin treatment (40,876 pounds +/- 1119 versus 39,222 pounds+/- 1141), producing an incremental cost effectiveness ratio (ICER) of 2500 pounds per QALY gained. Sensitivity analyses showed the results were robust under a range of plausible scenarios. CONCLUSIONS: Treatment with analogue insulin was associated with a decreased incidence of long-term complications and improved QALE, but slightly higher treatment costs compared to human insulin therapy. Analogue insulin treatment had an ICER within the range generally considered to represent good value for money in the UK.

The CORE Diabetes Model: Projecting long-term clinical outcomes, costs and cost-effectiveness of interventions in diabetes mellitus (types 1 and 2) to support clinical and reimbursement decision-making.

OBJECTIVES: We have developed an Internet-based, interactive computer model to determine the long-term health outcomes and economic consequences of implementing different treatment policies or interventions in type 1 and type 2 diabetes mellitus. The model projects outcomes for populations, taking into account baseline cohort characteristics and past history of complications, current and future diabetes management and concomitant medications, screening strategies and changes in physiological parameters over time. The development of complications, life expectancy, quality-adjusted life expectancy and total costs within populations can be calculated. METHODS: The model is based on a series of sub-models that simulate important complications of diabetes (cardiovascular disease, eye disease, hypoglycaemia, nephropathy, neuropathy, foot ulcer, amputation, stroke, ketoacidosis, lactic acidosis and mortality). Each sub-model is a Markov model using Monte Carlo simulation incorporating time, state, time-in state, and diabetes type-dependent probabilities derived from published sources. Analyses can be performed on cohorts with type 1 or type 2 diabetes. Cohorts, defined in terms of age, gender, baseline risk factors and pre-existing complications, can be modified or new cohorts defined by the user. Economic and clinical data in the model can be edited, thus ensuring adaptability by allowing the inclusion of new data as they become available; creation of country- or provider-specific versions of the model; and allowing the investigation of new hypotheses. CONCLUSIONS: The CORE Diabetes Model allows the calculation of long-term outcomes, based on the best data currently available. Diabetes management strategies can be compared in different patient populations in a variety of realistic clinical settings, allowing the identification of efficient diabetes management strategies.

Validation of the CORE Diabetes Model against epidemiological and clinical studies.

OBJECTIVES: The aim of this study was to assess the validity of the CORE Diabetes Model by comparing results from model simulations with observed outcomes from published epidemiological and clinical studies in type 1 and type 2 diabetes. METHODS: A total of 66 second- (internal) and third- (external) order validation analyses were performed across a range of complications and outcomes simulated by the CORE Diabetes Model (amputation, cataract, hypoglycaemia, ketoacidosis, macular oedema, myocardial infarction, nephropathy, neuropathy, retinopathy, stroke and mortality). Published studies were reproduced in the model by recreating cohorts in terms of demographics, baseline risk factors and complications, treatment patterns and patient management strategies, and simulating the progress of the cohort to an equivalent time horizon. RESULTS: Correlation analysis on results from 66 validation simulations produced an R2 value of 0.9224 (perfect fit = 1). A correlation plot of published study data versus values simulated by the CORE Diabetes Model had a trend line with a gradient of 1.0187 (perfect fit = 1). Validation analyses in type 1 and type 2 diabetes were associated with R2 values of 0.9778 and 0.8861 respectively. Correlation of second-order validation analyses (model predictions versus observed outcomes in studies used to construct the model) produced an R2 value of 0.9574, and the value for third-order analyses (model predictions versus observed outcomes in studies not used to construct the model) was 0.9023. CONCLUSIONS: The CORE Diabetes Model provides an accurate representation of patient outcomes when compared to 66 studies of diabetes and its complications. Model flexibility ensures it can be used to compare diabetes management strategies in different cohorts across a variety of clinical settings.