Coronary heart disease and cerebrovascular disease mortality in young adults: recent trends in Europe.

Background: Over the last two decades, mortality from coronary heart disease (CHD) and cerebrovascular disease (CVD) declined by about 30% in the European Union (EU). Design: We analyzed trends in CHD (X ICD codes: I20-I25) and CVD (X ICD codes: I60-I69) mortality in young adults (age 35-44 years) in the EU as a whole and in 12 selected European countries, over the period 1980-2007. Methods: Data were derived from the World Health Organization mortality database. With joinpoint regression analysis, we identified significant changes in trends and estimated average annual percent changes (AAPC). Results: CHD mortality rates at ages 35-44 years have decreased in both sexes since the 1980s for most countries, except for Russia (130/100,000 men and 24/100,000 women, in 2005-7). The lowest rates (around 9/100,000 men, 2/100,000 women) were in France, Italy and Sweden. In men, the steepest declines in mortality were in the Czech Republic (AAPC = -6.1%), the Netherlands (-5.2%), Poland (-4.5%), and England and Wales (-4.5%). Patterns were similar in women, though with appreciably lower rates. The AAPC in the EU was -3.3% for men (rate = 16.6/100,000 in 2005-7) and -2.1% for women (rate = 3.5/100,000). For CVD, Russian rates in 2005-7 were 40/100,000 men and 16/100,000 women, 5 to 10-fold higher than in most western European countries. The steepest declines were in the Czech Republic and Italy for men, in Sweden and the Czech Republic for women. The AAPC in the EU was -2.5% in both sexes, with steeper declines after the mid-late 1990s (rates = 6.4/100,000 men and 4.3/100,000 women in 2005-7). Conclusions: CHD and CVD mortality steadily declined in Europe, except in Russia, whose rates were 10 to 15-fold higher than those of France, Italy or Sweden. Hungary and Poland, and also Scotland, where CHD trends were less favourable than in other western European countries, also emerge as priorities for preventive interventions.

Device-specific weighted T-score for two quantitative ultrasounds: operational propositions for the management of osteoporosis for 65 years and older women in Switzerland.

The World Health Organization (WHO) criteria for the diagnosis of osteoporosis are mainly applicable for dual X-ray absorptiometry (DXA) measurements at the spine and hip levels. There is a growing demand for cheaper devices, free of ionizing radiation such as promising quantitative ultrasound (QUS). In common with many other countries, QUS measurements are increasingly used in Switzerland without adequate clinical guidelines. The T-score approach developed for DXA cannot be applied to QUS, although well-conducted prospective studies have shown that ultrasound could be a valuable predictor of fracture risk. As a consequence, an expert committee named the Swiss Quality Assurance Project (SQAP, for which the main mission is the establishment of quality assurance procedures for DXA and QUS in Switzerland) was mandated by the Swiss Association Against Osteoporosis (ASCO) in 2000 to propose operational clinical recommendations for the use of QUS in the management of osteoporosis for two QUS devices sold in Switzerland. Device-specific weighted "T-score" based on the risk of osteoporotic hip fractures as well as on the prediction of DXA osteoporosis at the hip, according to the WHO definition of osteoporosis, were calculated for the Achilles (Lunar, General Electric, Madison, Wis.) and Sahara (Hologic, Waltham, Mass.) ultrasound devices. Several studies (totaling a few thousand subjects) were used to calculate age-adjusted odd ratios (OR) and area under the receiver operating curve (AUC) for the prediction of osteoporotic fracture (taking into account a weighting score depending on the design of the study involved in the calculation). The ORs were 2.4 (1.9-3.2) and AUC 0.72 (0.66-0.77), respectively, for the Achilles, and 2.3 (1.7-3.1) and 0.75 (0.68-0.82), respectively, for the Sahara device. To translate risk estimates into thresholds for clinical application, 90% sensitivity was used to define low fracture and low osteoporosis risk, and a specificity of 80% was used to define subjects as being at high risk of fracture or having osteoporosis at the hip. From the combination of the fracture model with the hip DXA osteoporotic model, we found a T-score threshold of -1.2 and -2.5 for the stiffness (Achilles) determining, respectively, the low- and high-risk subjects. Similarly, we found a T-score at -1.0 and -2.2 for the QUI index (Sahara). Then a screening strategy combining QUS, DXA, and clinical factors for the identification of women needing treatment was proposed. The application of this approach will help to minimize the inappropriate use of QUS from which the whole field currently suffers.

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.