Prevalence of disability according to multimorbidity and disease clustering: a population-based study

Background: The prevalence of chronic diseases has increased with population ageing, and research has attempted to elucidate the correlation between chronic diseases and disability. However, most studies in older populations have focused on the effect of single disabling conditions, even though most older adults have more than one chronic disease (multimorbidity). Objective: The aims of this study were to evaluate the association of disability with disease, in terms of multimorbidity and specified pairs of diseases, in a population-based study of older adults. Materials and Methods: Using the Kungsholmen Project, we estimated the prevalence of disability by the number of chronic diseases, disease status by organ systems, and in specific pairs of chronic conditions, in a Swedish population (n=1,099; ≥77 years). Disability was defined as need of assistance in at least one activity of daily living (Katz index). Results: Functional disability was seen in 17.9% of participants. It increased as the number of chronic diseases increased. The prevalence of disability varied greatly amongst specific pairs of diseases: from 6.7% in persons affected by hypertension and atrial fibrillation to 82.4% in persons affected by dementia and hip fracture. In multivariate logistic regression models, the disease pairs that were significantly associated with the highest increased relative odds of disability contained dementia (dementia–hip fracture, dementia–CVD, and dementia–depression). Conclusions: Our findings suggest specific pairs of diseases are much more highly associated with disability than others, particularly diseases coupled with dementia. This knowledge may improve prevention of disablement and planning of resource distribution.Journal of Comorbidity 2011;1(1):11–1

Predictive validity of the CriSTAL tool for short-term mortality in older people presenting at Emergency Departments: a prospective study

© 2018, The Author(s). Abstract: To determine the validity of the Australian clinical prediction tool Criteria for Screening and Triaging to Appropriate aLternative care (CRISTAL) based on objective clinical criteria to accurately identify risk of death within 3 months of admission among older patients. Methods: Prospective study of ≥ 65 year-olds presenting at emergency departments in five Australian (Aus) and four Danish (DK) hospitals. Logistic regression analysis was used to model factors for death prediction; Sensitivity, specificity, area under the ROC curve and calibration with bootstrapping techniques were used to describe predictive accuracy. Results: 2493 patients, with median age 78–80 years (DK–Aus). The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% CI 7.7–8.6 vs. 5.8 95% CI 5.6–5.9) and Danish mean 7.1 (95% CI 6.6–7.5 vs. 5.5 95% CI 5.4–5.6). The model with Fried Frailty score was optimal for the Australian cohort but prediction with the Clinical Frailty Scale (CFS) was also good (AUROC 0.825 and 0.81, respectively). Values for the Danish cohort were AUROC 0.764 with Fried and 0.794 using CFS. The most significant independent predictors of short-term death in both cohorts were advanced malignancy, frailty, male gender and advanced age. CriSTAL’s accuracy was only modest for in-hospital death prediction in either setting. Conclusions: The modified CriSTAL tool (with CFS instead of Fried’s frailty instrument) has good discriminant power to improve prognostic certainty of short-term mortality for ED physicians in both health systems. This shows promise in enhancing clinician’s confidence in initiating earlier end-of-life discussions

Co-morbidity burden in Parkinson’s disease : Comparison with controls and its influence on prognosis

Financial support This study was funded by Parkinson’s UK, the Scottish Chief Scientist Office, NHS Grampian endowments, the BMA Doris Hillier award, RS Macdonald Trust, the BUPA Foundation, and SPRING. The funders had no involvement in the study. Acknowledgements We acknowledge funding for the PINE study from Parkinson’s UK (G-0502, G-0914, G-1302), the Scottish Chief Scientist Office(CAF/12/05), the BMA Doris Hillier award, RS Macdonald Trust, the BUPA Foundation, NHS Grampian endowments and SPRING. We thank the patients and controls for their participation and the research staff who collected data and supported the study database.Peer reviewedPostprintPostprintPublisher PD

Multimorbidity Patterns and 6-Year Risk of Institutionalization in Older Persons: The Role of Social Formal and Informal Care

Abstract Objectives The aim was to evaluate patterns of multimorbidity that increase the risk of institutionalization in older persons, also exploring the potential buffering effect of formal and informal care. Design Prospective cohort study. Setting and Participants The population-based Swedish National study on Aging and Care in Kungsholmen, Stockholm, Sweden. Measures In total, 2571 community-dwelling older adults were grouped at baseline according to their underlying multimorbidity patterns, using a fuzzy c-means cluster algorithm, and followed up for 6 years to test the association between multimorbidity patterns and institutionalization. Results Six patterns of multimorbidity were identified: psychiatric diseases; cardiovascular diseases, anemia, and dementia; metabolic and sleep disorders; sensory impairments and cancer; musculoskeletal, respiratory, and gastrointestinal diseases; and an unspecific pattern including diseases of which none were overrepresented. In total, 110 (4.3%) participants were institutionalized during the follow-up, ranging from 1.7% in the metabolic and sleep disorders pattern to 8.4% in the cardiovascular diseases, anemia, and dementia pattern. Compared with the unspecific pattern, only the cardiovascular diseases, anemia, dementia pattern was significantly associated with institutionalization [relative risk ratio (RRR) = 2.23; 95% confidence interval (CI) 1.07‒4.65)], after adjusting for demographic characteristics and disability status at baseline. In stratified analyses, those not receiving formal care in the psychiatric diseases pattern (RRR 3.34; 95% CI 1.20‒9.32) and those not receiving formal or informal care in the 'cardiovascular diseases, anemia, dementia' pattern (RRR 2.99; 95% CI 1.20‒7.46; RRR 2.79; 95% CI 1.16‒6.71, respectively) had increased risks of institutionalization. Conclusions and Implications Older persons suffering from specific multimorbidity patterns have a higher risk of institutionalization, especially if they lack formal or informal care. Interventions aimed at preventing the clustering of diseases could reduce the associated burden on residential long-term care. Formal and informal care provision may be effective strategies in reducing the risk of institutionalization

Ricostruzione e valutazione dello stato anteriore

Il 22% della popolazione anziana in Italia ha pi\uf9 di 65 anni, con un costo complessivo per le assicurazioni nel 2017 per i sinistri per macroinvalidit\ue0 e morte pari a 4,6 miliardi di euro. Si pone pertanto per il sistema sanitario nazionale e per i medici legali il problema di come valutare il danno biologico nella persona anziana. Infatti, le tabelle per la valutazione del danno a persona prendono in considerazione l\u2019entit\ue0 della lesione, ma non l\u2019et\ue0 del paziente. Si \ue8 deciso quindi di applicare per la prima volta alla medicina legale la metodologia della Consensus Conference, utilizzata generalmente per dirimere questioni controverse in ambito clinico, al fine di affrontare un tema di fondamentale interesse scientifico e produrre un unico documento contenente indicazioni per valutare in maniera metodologicamente corretta e condivisa il danno biologico nella persona anziana. Ad oggi la mancanza di una condivisione di opinioni su questo tema produce una forte disomogeneit\ue0 di comportamenti sul piano clinico e valutativo e il documento comporter\ue0 grandi ripercussioni sull\u2019attivit\ue0 quotidiana stante il costante invecchiamento della popolazione generale e le grandi problematiche che la fragilit\ue0 dell\u2019anziano crea nella valutazione del danno alla persona

Cycles of Sums of Integers

We study the period of the linear map $T:\textbf{Z}_m^n\rightarrow \textbf{Z}_m^n:(a_0,\dots,a_{n-1})\mapsto(a_0+a_1,\dots,a_{n-1}+a_0)$ as a function of $m$ and $n$, where $\textbf{Z}_m$ stands for the ring of integers modulo $m$. This map being a variant of the Ducci map, several known results are adapted in the context of $T$. The main theorem of this paper states that the period modulo $m$ can be deduced from the prime factorization of $m$ and the periods of its prime factors. We give some other interesting properties.Comment: Submitted March 8 201

Multimorbidity: disease of society?

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A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods

Objectives: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.Study design and setting: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.Results: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.Conclusion: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed