253 research outputs found
Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany
<p>Abstract</p> <p>Background</p> <p>Growing interest in multimorbidity is observable in industrialized countries. For Germany, the increasing attention still goes still hand in hand with a small number of studies on multimorbidity. The authors report the first results of a cross-sectional study on a large sample of policy holders (n = 123,224) of a statutory health insurance company operating nationwide. This is the first comprehensive study addressing multimorbidity on the basis of German claims data. The main research question was to find out which chronic diseases and disease combinations are specific to multimorbidity in the elderly.</p> <p>Methods</p> <p>The study is based on the claims data of all insured policy holders aged 65 and older (n = 123,224). Adjustment for age and gender was performed for the German population in 2004. A person was defined as multimorbid if she/he had at least 3 diagnoses out of a list of 46 chronic conditions in three or more quarters within the one-year observation period. Prevalences and risk-ratios were calculated for the multimorbid and non-multimorbid samples in order to identify diagnoses more specific to multimorbidity and to detect excess prevalences of multimorbidity patterns.</p> <p>Results</p> <p>62% of the sample was multimorbid. Women in general and patients receiving statutory nursing care due to disability are overrepresented in the multimorbid sample. Out of the possible 15,180 combinations of three chronic conditions, 15,024 (99%) were found in the database. Regardless of this wide variety of combinations, the most prevalent individual chronic conditions do also dominate the combinations: Triads of the six most prevalent individual chronic conditions (hypertension, lipid metabolism disorders, chronic low back pain, diabetes mellitus, osteoarthritis and chronic ischemic heart disease) span the disease spectrum of 42% of the multimorbid sample. Gender differences were minor. Observed-to-expected ratios were highest when purine/pyrimidine metabolism disorders/gout and osteoarthritis were part of the multimorbidity patterns.</p> <p>Conclusions</p> <p>The above list of dominating chronic conditions and their combinations could present a pragmatic start for the development of needed guidelines related to multimorbidity.</p
Multimorbidity Patterns in the Elderly: A New Approach of Disease Clustering Identifies Complex Interrelations between Chronic Conditions
Objective: Multimorbidity is a common problem in the elderly that is significantly associated with higher mortality, increased disability and functional decline. Information about interactions of chronic diseases can help to facilitate diagnosis, amend prevention and enhance the patients ’ quality of life. The aim of this study was to increase the knowledge of specific processes of multimorbidity in an unselected elderly population by identifying patterns of statistically significantly associated comorbidity. Methods: Multimorbidity patterns were identified by exploratory tetrachoric factor analysis based on claims data of 63,104 males and 86,176 females in the age group 65+. Analyses were based on 46 diagnosis groups incorporating all ICD-10 diagnoses of chronic diseases with a prevalence $ 1%. Both genders were analyzed separately. Persons were assigned to multimorbidity patterns if they had at least three diagnosis groups with a factor loading of 0.25 on the corresponding pattern. Results: Three multimorbidity patterns were found: 1) cardiovascular/metabolic disorders [prevalence female: 30%; male: 39%], 2) anxiety/depression/somatoform disorders and pain [34%; 22%], and 3) neuropsychiatric disorders [6%; 0.8%]. The sampling adequacy was meritorious (Kaiser-Meyer-Olkin measure: 0.85 and 0.84, respectively) and the factors explained a large part of the variance (cumulative percent: 78 % and 75%, respectively). The patterns were largely age-dependent an
Prevalence of chronic medical conditions in Switzerland: exploring estimates validity by comparing complementary data sources
The influence of age, gender and socio-economic status on multimorbidity patterns in primary care. first results from the multicare cohort study
Background: Multimorbidity is a phenomenon with high burden and high prevalence in the elderly. Our previous research has shown that multimorbidity can be divided into the multimorbidity patterns of 1) anxiety, depression, somatoform disorders (ADS) and pain, and 2) cardiovascular and metabolic disorders. However, it is not yet known, how these patterns are influenced by patient characteristics. The objective of this paper is to analyze the association of socio-demographic variables, and especially socio-economic status with multimorbidity in general and with each multimorbidity pattern.
Methods: The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses.
Results: Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status.
Conclusions: Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups
Selection effects may account for better outcomes of the German Disease Management Program for type 2 diabetes
<p>Abstract</p> <p>Background</p> <p>The nationwide German disease management program (DMP) for type 2 diabetes was introduced in 2003. Meanwhile, results from evaluation studies were published, but possible baseline differences between DMP and usual-care patients have not been examined. The objective of our study was therefore to find out if patient characteristics as socio-demographic variables, cardiovascular risk profile or motivation for life style changes influence the chance of being enrolled in the German DMP for type 2 diabetes and may therefore account for outcome differences between DMP and usual-care patients.</p> <p>Methods</p> <p>Case control study comparing DMP patients with usual-care patients at baseline and follow up; mean follow-up period of 36 ± 14 months. We used chart review data from 51 GP surgeries. Participants were 586 DMP and 250 usual-care patients with type 2 diabetes randomly selected by chart registry. Data were analysed by multivariate logistic and linear regression analyses. Significance levels were p ≤ 0.05.</p> <p>Results</p> <p>There was a better chance for enrolment if patients a) had a lower risk status for diabetes complications, i.e. non-smoking (odds ratio of 1.97, 95% confidence interval of 1.11 to 3.48) and lower systolic blood pressure (1.79 for 120 mmHg vs. 160 mmHg, 1.15 to 2.81); b) had higher activity rates, i.e. were practicing blood glucose self-monitoring (1.67, 1.03 to 2.76) and had been prescribed a diabetes patient education before enrolment (2.32, 1.29 to 4.19) c) were treated with oral medication (2.17, 1.35 to 3.49) and d) had a higher GP-rated motivation for diabetes education (4.55 for high motivation vs. low motivation, 2.21 to 9.36).</p> <p>Conclusions</p> <p>At baseline, future DMP patients had a lower risk for diabetes complications, were treated more intensively and were more active and motivated in managing their disease than usual-care patients. This finding a) points to the problem that the German DMP may not reach the higher risk patients and b) selection bias may impair the assessment of differences in outcome quality between enrolled and usual-care patients. Suggestions for dealing with this bias in evaluation studies are being made.</p
Patterns of Multimorbidity in the Aged Population. Results from the KORA-Age Study
Multimorbidity is a common problem in aged populations with a wide range of individual and societal consequences. The objective of the study was to explore patterns of comorbidity and multimorbidity in an elderly population using different analytical approaches. Data were gathered from the population-based KORA-Age project, which included 4,127 persons aged 65–94 years living in the city of Augsburg and its two surrounding counties in Southern Germany. Information on the presence of 13 chronic conditions was collected in a standardized telephone interview and a self-administered questionnaire. Patterns of comorbidity and multimorbidity were analyzed using prevalence figures, logistic regression models and exploratory tetrachoric factor analysis. The prevalence of multimorbidity (≥2 diseases) was 58.6% in the total sample. Hypertension and diabetes (Odds Ratio [OR] 2.95, 99.58% confidence interval [CI] [2.19–3.96]), as well as hypertension and stroke (OR 2.00, 99.58% CI [1.26–3.16]) most often occurred in combination. This association was independent of age, sex and the presence of other conditions. Using factor analysis, we identified four patterns of multimorbidity: the first pattern includes cardiovascular and metabolic diseases, the second includes joint, liver, lung and eye diseases, the third covers mental and neurologic diseases and the fourth pattern includes gastrointestinal diseases and cancer. 44% of the persons were assigned to at least one of the four multimorbidity patterns; 14% could be assigned to both the cardiovascular/metabolic and the joint/liver/lung/eye pattern. Further common pairs were the mental/neurologic pattern combined with the cardiovascular/metabolic pattern (7.2%) or the joint/liver/lung/eye pattern (5.3%), respectively. Our results confirmed the existence of co-occurrence of certain diseases in elderly persons, which is not caused by chance. Some of the identified patterns of multimorbidity and their overlap may indicate common underlying pathological mechanisms
Multimorbidity and comorbidity in the Dutch population - data from general practices
<p>Abstract</p> <p>Background</p> <p>Multimorbidity is increasingly recognized as a major public health challenge of modern societies. However, knowledge about the size of the population suffering from multimorbidity and the type of multimorbidity is scarce. The objective of this study was to present an overview of the prevalence of multimorbidity and comorbidity of chronic diseases in the Dutch population and to explore disease clustering and common comorbidities.</p> <p>Methods</p> <p>We used 7 years data (2002–2008) of a large Dutch representative network of general practices (212,902 patients). Multimorbidity was defined as having two or more out of 29 chronic diseases. The prevalence of multimorbidity was calculated for the total population and by sex and age group. For 10 prevalent diseases among patients of 55 years and older (N = 52,014) logistic regressions analyses were used to study disease clustering and descriptive analyses to explore common comorbid diseases.</p> <p>Results</p> <p>Multimorbidity of chronic diseases was found among 13% of the Dutch population and in 37% of those older than 55 years. Among patients over 55 years with a specific chronic disease more than two-thirds also had one or more other chronic diseases. Most disease pairs occurred more frequently than would be expected if diseases had been independent. Comorbidity was not limited to specific combinations of diseases; about 70% of those with a disease had one or more extra chronic diseases recorded which were not included in the top five of most common diseases.</p> <p>Conclusion</p> <p>Multimorbidity is common at all ages though increasing with age, with over two-thirds of those with chronic diseases and aged 55 years and older being recorded with multimorbidity. Comorbidity encompassed many different combinations of chronic diseases. Given the ageing population, multimorbidity and its consequences should be taken into account in the organization of care in order to avoid fragmented care, in medical research and healthcare policy.</p
Non-cognate translation priming in masked priming lexical decision experiments: a meta-analysis
The masked translation priming paradigm has been widely used in the last 25 years to investigate word processing in bilinguals. Motivated by studies reporting mixed findings, in particular for second language (L2) to first language (L1) translation priming, we conducted, for the first time in the literature, a meta-analysis of 64 lexical decision experiments across 24 studies to assess the effect sizes of L1-L2 and L2-L1 non-cognate translation priming effects in bilinguals. Our meta-analysis also investigated the influence of potential moderators of translation priming effects. The results provided clear evidence of significant translation priming effects for both directions, with L1-L2 translation priming significantly larger than L2-L1 translation priming (i.e., effect size of 0.86 vs. 0.31). The analyses also revealed that L1-L2 translation effect sizes were moderated by the interval between prime and target (ISI), whereas L2-L1 translation effect sizes were modulated by the number of items per cell. Theoretical and methodological implications of this meta-analysis are discussed and recommendations for future studies are provided
A genome-wide survey of human short-term memory
Recent advances in the development of high-throughput genotyping platforms allow for the unbiased identification of genes and genomic sequences related to heritable traits. In this study, we analyzed human short-term memory, which refers to the ability to remember information over a brief period of time and which has been found disturbed in many neuropsychiatric conditions, including schizophrenia and depression. We performed a genome-wide survey at 909 622 polymorphic loci and report six genetic variations significantly associated with human short-term memory performance after genome-wide correction for multiple comparisons. A polymorphism within SCN1A (encoding the α subunit of the type I voltage-gated sodium channel) was replicated in three independent populations of 1699 individuals. Functional magnetic resonance imaging during an n-back working memory task detected SCN1A allele-dependent activation differences in brain regions typically involved in working memory processes. These results suggest an important role for SCN1A in human short-term memory
Towards an international language for incontinence-associated dermatitis (IAD): design and evaluation of psychometric properties of the Ghent Global IAD Categorization Tool (GLOBIAD) in 30 countries
Background Incontinence-associated dermatitis (IAD) is a specific type of irritant contact dermatitis with different severity levels. An internationally accepted instrument to assess the severity of IAD in adults, with established diagnostic accuracy, agreement and reliability, is needed to support clinical practice and research. Objectives To design the Ghent Global IAD Categorization Tool (GLOBIAD) and evaluate its psychometric properties.
Methods The design was based on expert consultation using a three-round Delphi procedure with 34 experts from 13 countries. The instrument was tested using IAD photographs, which reflected different severity levels, in a sample of 823 healthcare professionals from 30 countries. Measures for diagnostic accuracy (sensitivity and specificity), agreement, interrater reliability (multirater Fleiss kappa) and intrarater reliability (Cohen’s kappa) were assessed. Results The GLOBIAD consists of two categories based on the presence of persistent redness (category 1) and skin loss (category 2), both of which are subdivided based on the presence of clinical signs of infection. The agreement for differentiating between category 1 and category 2 was 0 86 [95% confidence interval (CI) 0 86–0 87], with a sensitivity of 90% and a specificity of 84%. The overall agreement was 0 55 (95% CI 0 55–0 56). The Fleiss kappa for differentiating between category 1 and category 2 was 0 65 (95% CI 0 65–0 65). The overall Fleiss kappa was 0 41 (95% CI 0 41–0 41). The Cohen’s kappa for differentiating between category 1 and category 2 was 0 76 (95% CI 0 75–0 77). The overall Cohen’s kappa was 0 61 (95% CI 0 59–0 62). Conclusions The development of the GLOBIAD is a major step towards a better systematic assessment of IAD in clinical practice and research worldwide. However, further validation is needed.info:eu-repo/semantics/acceptedVersio
- …