PURPOSE We wanted to determine the effect of promoting the effective communication of absolute cardiovascular disease (CVD) risk and shared decision making through disseminating a simple decision aid for use in family practice consultations. METHODSThe study was based on a pragmatic, cluster randomized controlled trial (phase III) with continuing medical education (CME) groups of family physicians as the unit of randomization. In the intervention arm, 44 physicians (7 CME groups) consecutively recruited 550 patients in whom cholesterol levels were measured. Forty-seven physicians in the control arm (7 CME groups) similarly included 582 patients. Four hundred sixty patients (83.6%) of the intervention arm and 466 patients (80.1%) of the control arm were seen at follow-up. Physicians attended 2 interactive CME sessions and received a booklet, a paper-based risk calculator, and individual summary sheets for each patient. Control physicians attended 1 CME-session on an alternative topic. Main outcome measures were patient satisfaction and participation after the index consultation, change in CVD risk status, and decisional regret at 6 months' follow-up. RESULTSIntervention patients were signifi cantly more satisfi ed with process and result (Patient Participation Scale, difference 0.80, P <.001). Decisional regret was signifi cantly lower at follow-up (difference 3.39, P = .02). CVD risk decreased in both groups without a signifi cant difference between study arms. CONCLUSION A simple transactional decision aid based on calculating absolute individual CVD risk and promoting shared decision making in CVD prevention can be disseminated through CME groups and may lead to higher patient satisfaction and involvement and less decisional regret, without negatively affecting global CVD risk.

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Active implementation of the German LBP guideline results in slightly better outcomes during 6 months follow-up than its postal dissemination. Results are more distinct when practice nurses are trained in motivational counseling.

Background/objective: Chest pain is a common complaint and reason for consultation. We aimed to study the epidemiology of chest pain with respect to underlying aetiologies and to establish pre-work-up probabilities for the primary care setting. Methods: We included 1212 consecutive patients with chest pain, aged 35 years and older, attending 74 general practitioners (GPs). GPs recorded symptoms and fi ndings of each patient and provided follow-up information. An independent interdisciplinary reference panel reviewed clinical data of every patient and decided on the aetiology of chest pain at the time of patient recruitment. Results: The prevalence of chest pain among all attending patients was 0.7%. The majority (55.9%) of patients were women. Mean age was 59 (35-93) years. Of these patients, 53.2% had chest pains at the time of consultation and 29.6% presented with acute (Ͻ 48 hours' duration) chest pain. Pain originating from the chest wall was diagnosed in 46.6% of all patients, stable ischaemic heart disease (IHD) in 11.1%, and psychogenic disorders in 9.5%; 3.6% had acute coronary syndrome (ACS). Conclusion:The study adds important information about the epidemiology of chest pain as a frequent reason for consulting primary care practitioners. We provide updated pre-work-up probabilities for IHD for each age and sex category.

Interventions designed to reduce high health care costs for LBP should focus on patients with severe LBP and depressive comorbidity. Our results add to the economic understanding of LBP care and may give guidance for future actions on health care improvement and cost reduction.

Background: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. Methods:We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). Results:The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result ≤ 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). Interpretation:The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care. AbstractPreviously published at www.cmaj.ca @@

ZusammenfassungDiese DVO Leitlinien, die in erster Linie für Allgemeinmediziner und Spezialisten für Knochenerkrankungen bestimmt sind, sollten von allen im klinischen und ambulanten Bereich tätigen medizinischen Fachkräften angewendet werden. Ziel der Leitlinie ist die Verbesserung der Diagnose, Prävention und Behandlung von Osteoporose und der Folgen der Erkrankung auf der Grundlage evidenzbasierter Medizin.Klare Empfehlungen, welche Patienten zu diagnostizieren und behandeln sind (basierend auf Risikofaktoren [einschließlich sekundärer Osteoporose]) sowie Primär-, Sekundär- oder Tertiärprävention werden dargestellt, mit dem Schwerpunkt auf der postmenopausalen Osteoporose und der Osteoporose bei Männern.Die Identifizierung von Patienten mit einem hohen Risiko für Frakturen wird hervorgehoben, und spezifische Schwellenwerte für die Intervention sind definiert (20 % Hüftfrakturrisiko innerhalb von 10 Jahren diagnostischer Schwellenwert, 30 % Hüftfrakturrisiko innerhalb von 10 Jahren therapeutische Schwelle). Die Diagnose von Osteoporose basiert auf der Anamnese des Patienten, der körperlichen Untersuchung, dem Funktionstest (z. B. Timed Up and Go Test), konventionellen Röntgenaufnahmen der Brust- und Lendenwirbelsäule und der Bestimmung der Knochenmineraldichte (BMD) durch das DXA Verfahren.Die Anamnese ist entscheidend für die Abschätzung des Frakturrisikos auf der Grundlage von 40 wissenschaftlich überprüften Risikofaktoren, die das Frakturrisiko mindestens verdoppeln (z. B. Begleiterkrankungen, Hüftfrakturen in der Familie, prävalente Frakturen an jedem Ort, Lebensstil, Anwendung von Medikamenten, körperliche Aktivität und Stürze). Röntgenaufnahmen der Brust- und Lendenwirbelsäule sind wichtig, um prävalente Wirbelkörperfrakturen zu erkennen. Beim Fehlen eines großen Traumas kann jede Fraktur bei Erwachsenen über dem Alter von 50 Jahren eine Diagnose von Osteoporose nahelegen, mit dem höchsten Risiko für eine nachfolgende Fraktur innerhalb einer kurzen Zeit nach der ersten Fraktur. BMD-Messungen mit DXA sind wichtig, um das individuelle Frakturrisiko besser abschätzen zu können. Eine grundlegende Laboruntersuchung ist obligatorisch, um verschiedene Formen der sekundären Osteoporose ausschließen zu können.Der DVO-Patientenfindungs-Algorithmus basiert auf dem Geschlecht, Alter, Knochenmineraldichte und vorbestehenden Frakturen als wichtigste Informationen. Die Indikation für eine aktive anti-osteoporotische Therapie kann durch multiple Risikofaktoren modifiziert und verfeinert werden. Dieser Algorithmus wurde seit dem Richtlinien-Update 2006 verwendet und wurde entsprechend der internationalen Literatur zu Risikofaktoren für Osteoporose und osteoporotische Frakturen aktualisiert und angepasst.Die Behandlung der Osteoporose enthält viele Therapiepfeiler. Zusammen mit Empfehlungen für Bewegung, Physiotherapie und Sturzprävention sowie Ernährung (z. B. Calcium, Vit. D), werden pharmakologische Behandlungen basierend auf evidenzbasierter Medizin empfohlen. Die aktiven Anti-Osteoporose-Medikamente müssen für die Indikation postmenopausale Osteoporose und männliche Osteoporose in Deutschland, Österreich und der Schweiz zugelassen sein. Das Management und die Vorbeugung von häufigen oder seltenen Nebenwirkungen aufgrund von Anti-Osteoporose-Behandlungen, die in der klinischen Praxis angewendet werden, werden ebenfalls detailliert behandelt.

The study aims to report service use and costs for patients with Alzheimer's disease (AD) and to explore the incremental influence of sociodemographic and illness-related determinants in ambulatory and inpatient settings within the German health care system. 395 patients with dementia were recruited at the following sites: 1) University hospital, 2) general practitioners' offices, 3) office-based neurologists, 4) a regional psychiatric hospital, and 5) nursing homes. Sociodemographic, economic, and clinical parameters were assessed using a standardized questionnaire. Informal care was not evaluated. Disease severity was measured using the Mini-Mental Status Examination and the Alzheimer's Disease Assessment Scale - Cognitive Subscale. Neuropsychiatric status was assessed using the Geriatric Depression Scale, the Neuropsychiatric Inventory, and the Alzheimer's Disease Cooperative-Study-Activities of Daily Living. Annual total costs were estimated to be €13,080 per patient. The most important cost component was (long-term) care, constituting about 43% of total costs. Indirect costs comprised about 18% of total costs and were mainly due to reductions in working time of caregivers. Poorer functional status was associated with higher total and caregiving costs. In multivariate analyses, we identified younger age, female gender, and impaired activities of daily living as independent predictors of higher costs. Given that care for patients with AD is complex and expensive, our models were only able to explain about 17-43% of the variability in total costs. This suggests that further social and individual factors considerably influence the costs associated with AD. Direct medical care costs and long-term care costs related differently to the patient's clinical characteristics. Longitudinal and population-based studies are necessary for thoroughly evaluating the burden of disease.