The presence of multiple chronic conditions (i.e., multimorbidity) increases the risk of hospitalisation in older adults. We aimed to examine the association between different multimorbidity patterns and unplanned hospitalisations over 5 years. To that end, 2,250 community-dwelling individuals aged 60 years and older from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K) were studied. Participants were grouped into six multimorbidity patterns using a fuzzy c-means cluster analysis. The associations between patterns and outcomes were tested using Cox models and negative binomial models. After 5 years, 937 (41.6%) participants experienced at least one unplanned hospitalisation. Compared to participants in the unspecific multimorbidity pattern, those in the cardiovascular diseases, anaemia and dementia pattern, the psychiatric disorders pattern and the metabolic and sleep disorders pattern presented with a higher hazard of first unplanned hospitalisation (hazard ratio range: 1.49–2.05; p < 0.05 for all), number of unplanned hospitalisations (incidence rate ratio (IRR) range: 1.89–2.44; p < 0.05 for all), in-hospital days (IRR range: 1.91–3.61; p < 0.05 for all), and 30-day unplanned readmissions (IRR range: 2.94–3.65; p < 0.05 for all). Different multimorbidity patterns displayed a differential association with unplanned hospital care utilisation. These findings call for a careful primary care follow-up of older adults with complex multimorbidity patterns.
The aim was to analyze the association between specific patterns of multimorbidity and risk of disability in older persons. Data were gathered from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K); 2066 60 + year-old participants living in the community and free from disability at baseline were grouped according to their multimorbidity patterns and followed-up for six years. The association between multimorbidity patterns and disability in basic (ADL) and instrumental (IADL) activities of daily living was examined through multinomial models. Throughout the follow-up, 434 (21.0%) participants developed at least one ADL and 310 (15.0%) at least one IADL. Compared to the unspecific pattern, which included diseases not exceeding their expected prevalence in the total sample, belonging to the cardiovascular/anemia/dementia, the sensory impairment/cancer and the musculoskeletal/respiratory/gastrointestinal patterns was associated with a higher risk of developing both ADL and IADL, whereas subjects in the metabolic/sleep disorders pattern showed a higher risk of developing only IADL. Multimorbidity patterns are differentially associated with incident disability, which is important for the design of future prevention strategies aimed at delaying functional impairment in old age, and for a better healthcare resource planning.
There are many uncertainties on the future management of the coronavirus disease 19 (COVID-19) in Africa. By July 2021, Africa had lagged behind the rest of the world in Covid-19 vaccines uptake, accounting for just 1.6% of doses administered globally. During that time COVID 19 was causing an average death rate of 2.6% in Africa, surpassing the then global average of 2.2%. There were no clear therapeutic guidelines, yet inappropriate and unnecessary treatments may have led to unwanted adverse events such as worsening of hyperglycemia and precipitating of ketoacidosis in administration of steroid therapy. in order to provide evidence-based policy guidelines, we examined peer-reviewed published articles in PubMed on COVID 19, or up-to date data, we focused our search on publications from 1st May 2020 to 15th July, 2021. For each of the studies, weextracted data on pathophysiology, selected clinical chemistry and immunological tests, clinical staging and treatment. Our review reports a gross unmet need for vaccination, inadequate laboratory capacity for immunological tests and the assessment of individual immune status, clinical staging and prediction of disease severity. We recommend selected laboratory tools in the assessment of individual immune status, prediction of disease severity and determination of the exact timing for suitable therapy, especially in individuals with co-morbidities.Keywords: COVID-19; antibodies; cytokines; clinical chemistry; biomarkers; hematology; viral load (VL) RNA copy numbers;SARS-CoV-2
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