Impact of geriatric comorbidity and polypharmacy on cholinesterase inhibitors prescribing in dementia

<p>Abstract</p> <p>Background</p> <p>Although most guidelines recommend the use of cholinesterase inhibitors (ChEIs) for mild to moderate Alzheimer's Disease, only a small proportion of affected patients receive these drugs. We aimed to study if geriatric comorbidity and polypharmacy influence the prescription of ChEIs in patients with dementia in Germany.</p> <p>Methods</p> <p>We used claims data of 1,848 incident patients with dementia aged 65 years and older. Inclusion criteria were first outpatient diagnoses for dementia in at least three of four consecutive quarters (incidence year). Our dependent variable was the prescription of at least one ChEI in the incidence year. Main independent variables were polypharmacy (defined as the number of prescribed medications categorized into quartiles) and measures of geriatric comorbidity (levels of care dependency and 14 symptom complexes characterizing geriatric patients). Data were analyzed by multivariate logistic regression.</p> <p>Results</p> <p>On average, patients were 78.7 years old (47.6% female) and received 9.7 different medications (interquartile range: 6-13). 44.4% were assigned to one of three care levels and virtually all patients (92.0%) had at least one symptom complex characterizing geriatric patients. 13.0% received at least one ChEI within the incidence year. Patients not assigned to the highest care level were more likely to receive a prescription (e.g., no level of care dependency vs. level 3: adjusted Odds Ratio [OR]: 5.35; 95% CI: 1.61-17.81). The chance decreased with increasing numbers of symptoms characterizing geriatric patients (e.g., 0 vs. 5+ geriatric complexes: OR: 4.23; 95% CI: 2.06-8.69). The overall number of prescribed medications had no influence on ChEI prescription and a significant effect of age could only be found in the univariate analysis. Living in a rural compared to an urban environment and contacts to neurologists or psychiatrists were associated with a significant increase in the likelihood of receiving ChEIs in the multivariate analysis.</p> <p>Conclusions</p> <p>It seems that not age as such but the overall clinical condition of a patient including care dependency and geriatric comorbidities influences the process of decision making on prescription of ChEIs.</p

Predictors of serum dioxin levels among adolescent boys in Chapaevsk, Russia: A cross-sectional pilot study

BACKGROUND: Toxicological studies and limited human studies have demonstrated associations between exposure to polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and polychlorinated biphenyls (PCBs) and adverse developmental and reproductive health effects. Given that children may be particularly susceptible to reproductive and developmental effects of organochlorines, and the paucity of information available regarding childhood exposures to dioxins in particular, we undertook a pilot study to describe the distribution of, and identify potential predictors of exposure to, dioxin-like compounds and dioxins among adolescent boys in Chapaevsk, Russia. The pilot study was also designed to guide the development of a large prospective cohort study on the relationship of exposure to PCDDs, PCDFs, and PCBs with growth and pubertal development in peri-pubertal Chapaevsk boys. METHODS: 221 boys age 14 to 17 participated in the pilot study. Each of the boys, with his mother, was asked to complete a nurse-administered detailed questionnaire on medical history, diet, and lifestyle. The diet questions were used to measure the current and lifetime consumption of locally grown or raised foods. Blood samples from 30 of these boys were sent to the Centers for Disease Control and Prevention (CDC) for analysis of dioxins, furans and PCBs. RESULTS: The median (25(th), 75(th )percentile) concentrations for total PCDDs, PCDFs and coplanar PCBs were 95.8 pg/g lipids (40.9, 144), 33.9 pg/g lipids (20.4, 61.8), and 120 pg/g lipids (77.6, 157), respectively. For WHO-TEQs, the median (25(th), 75(th )percentile) for total PCDDs, PCDFs, and coplanar PCBs were 0.29 (0.1, 9.14), 7.98 (5.27, 12.3), and 7.39 (4.51, 11.9), respectively. Although TCDD was largely non-detectable, two boys had high TCDD levels (17.9 and 21.7 pg/g lipid). Higher serum levels of sum of dioxin-like compounds and sum of dioxin TEQs were positively associated with increased age, consumption of fish, local meats other than chicken, PCB 118, and inversely with weeks of gestation. CONCLUSION: The total TEQs among Chapaevsk adolescents were higher than most values previously reported in non-occupationally exposed populations of comparable or even older ages. Dietary consumption of local foods, as well as age and weeks of gestation, predicted dioxin exposure in this population

Prescribing patterns in dementia: a multicentre observational study in a German network of CAM physicians

<p>Abstract</p> <p>Background</p> <p>Dementia is a major and increasing health problem worldwide. This study aims to investigate dementia treatment strategies among physicians specialised in complementary and alternative medicine (CAM) by analysing prescribing patterns and comparing them to current treatment guidelines in Germany.</p> <p>Methods</p> <p>Twenty-two primary care physicians in Germany participated in this prospective, multicentre observational study. Prescriptions and diagnoses were reported for each consecutive patient. Data were included if patients had at least one diagnosis of dementia according to the 10th revision of the International Classification of Diseases during the study period. Multiple logistic regression was used to determine factors associated with a prescription of any anti-dementia drug including <it>Ginkgo biloba</it>.</p> <p>Results</p> <p>During the 5-year study period (2004-2008), 577 patients with dementia were included (median age: 81 years (IQR: 74-87); 69% female). Dementia was classified as unspecified dementia (57.2%), vascular dementia (25.1%), dementia in Alzheimer's disease (10.4%), and dementia in Parkinson's disease (7.3%). The prevalence of anti-dementia drugs was 25.6%. The phytopharmaceutical <it>Ginkgo biloba </it>was the most frequently prescribed anti-dementia drug overall (67.6% of all) followed by cholinesterase inhibitors (17.6%). The adjusted odds ratio (AOR) for receiving any anti-dementia drug was greater than 1 for neurologists (AOR = 2.34; CI: 1.59-3.47), the diagnosis of Alzheimer's disease (AOR = 3.28; CI: 1.96-5.50), neuroleptic therapy (AOR = 1.87; CI: 1.22-2.88), co-morbidities hypertension (AOR = 2.03; CI: 1.41-2.90), and heart failure (AOR = 4.85; CI: 3.42-6.88). The chance for a prescription of any anti-dementia drug decreased with the diagnosis of vascular dementia (AOR = 0.64; CI: 0.43-0.95) and diabetes mellitus (AOR = 0.55; CI: 0.36-0.86). The prescription of <it>Ginkgo biloba </it>was associated with sex (female: AOR = 0.41; CI: 0.19-0.89), patient age (AOR = 1.06; CI: 1.02-1.10), treatment by a neurologist (AOR = 0.09; CI: 0.03-0.23), and the diagnosis of Alzheimer's disease (AOR = 0.07; CI: 0.04-0.16).</p> <p>Conclusions</p> <p>This study provides a comprehensive analysis of everyday practice for treatment of dementia in primary care in physicians with a focus on CAM. The prescribing frequency for anti-dementia drugs is equivalent to those found in other German studies, while the administration of <it>Ginkgo biloba </it>is significantly higher.</p

Methods for the guideline-based development of quality indicators--a systematic review

<p>Abstract</p> <p>Background</p> <p>Quality indicators (QIs) are used in many healthcare settings to measure, compare, and improve quality of care. For the efficient development of high-quality QIs, rigorous, approved, and evidence-based development methods are needed. Clinical practice guidelines are a suitable source to derive QIs from, but no gold standard for guideline-based QI development exists. This review aims to identify, describe, and compare methodological approaches to guideline-based QI development.</p> <p>Methods</p> <p>We systematically searched medical literature databases (Medline, EMBASE, and CINAHL) and grey literature. Two researchers selected publications reporting methodological approaches to guideline-based QI development. In order to describe and compare methodological approaches used in these publications, we extracted detailed information on common steps of guideline-based QI development (topic selection, guideline selection, extraction of recommendations, QI selection, practice test, and implementation) to predesigned extraction tables.</p> <p>Results</p> <p>From 8,697 hits in the database search and several grey literature documents, we selected 48 relevant references. The studies were of heterogeneous type and quality. We found no randomized controlled trial or other studies comparing the ability of different methodological approaches to guideline-based development to generate high-quality QIs. The relevant publications featured a wide variety of methodological approaches to guideline-based QI development, especially regarding guideline selection and extraction of recommendations. Only a few studies reported patient involvement.</p> <p>Conclusions</p> <p>Further research is needed to determine which elements of the methodological approaches identified, described, and compared in this review are best suited to constitute a gold standard for guideline-based QI development. For this research, we provide a comprehensive groundwork.</p

Measurement of ϒ production in pp collisions at √s = 2.76 TeV

The production of ϒ(1S), ϒ(2S) and ϒ(3S) mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 pb−1 collected in proton–proton collisions at a centre-of-mass energy of √s = 2.76 TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the ϒ transverse momentum and rapidity, over the ranges pT &#60; 15 GeV/c and 2.0 &#60; y &#60; 4.5. The total cross-sections in this kinematic region, assuming unpolarised production, are measured to be σ (pp → ϒ(1S)X) × B ϒ(1S)→μ+μ− = 1.111 ± 0.043 ± 0.044 nb, σ (pp → ϒ(2S)X) × B ϒ(2S)→μ+μ− = 0.264 ± 0.023 ± 0.011 nb, σ (pp → ϒ(3S)X) × B ϒ(3S)→μ+μ− = 0.159 ± 0.020 ± 0.007 nb, where the first uncertainty is statistical and the second systematic