At the beginning of June 2020, there were nearly 7 million reported cases of coronavirus disease 2019 (COVID-19) worldwide and over 400,000 deaths in people with COVID-19. The objective of this study was to determine associations between comorbidities listed in the Charlson comorbidity index and mortality among patients in the United States with COVID-19. A retrospective cohort study of adults with COVID-19 from 24 healthcare organizations in the US was conducted. The study included adults aged 18–90 years with COVID-19 coded in their electronic medical records between January 20, 2020, and May 26, 2020. Results were also stratified by age groups (<50 years, 50–69 years, or 70–90 years). A total of 31,461 patients were included. Median age was 50 years (interquartile range [IQR], 35–63) and 54.5% (n = 17,155) were female. The most common comorbidities listed in the Charlson comorbidity index were chronic pulmonary disease (17.5%, n = 5,513) and diabetes mellitus (15.0%, n = 4,710). Multivariate logistic regression analyses showed older age (odds ratio [OR] per year 1.06; 95% confidence interval [CI] 1.06–1.07; p < 0.001), male sex (OR 1.75; 95% CI 1.55–1.98; p < 0.001), being black or African American compared to white (OR 1.50; 95% CI 1.31–1.71; p < 0.001), myocardial infarction (OR 1.97; 95% CI 1.64–2.35; p < 0.001), congestive heart failure (OR 1.42; 95% CI 1.21–1.67; p < 0.001), dementia (OR 1.29; 95% CI 1.07–1.56; p = 0.008), chronic pulmonary disease (OR 1.24; 95% CI 1.08–1.43; p = 0.003), mild liver disease (OR 1.26; 95% CI 1.00–1.59; p = 0.046), moderate/severe liver disease (OR 2.62; 95% CI 1.53–4.47; p < 0.001), renal disease (OR 2.13; 95% CI 1.84–2.46; p < 0.001), and metastatic solid tumor (OR 1.70; 95% CI 1.19–2.43; p = 0.004) were associated with higher odds of mortality with COVID-19. Older age, male sex, and being black or African American (compared to being white) remained significantly associated with higher odds of death in age-stratified analyses. There were differences in which comorbidities were significantly associated with mortality between age groups. Limitations include that the data were collected from the healthcare organization electronic medical record databases and some comorbidities may be underreported and ethnicity was unknown for 24% of participants. Deaths during an inpatient or outpatient visit at the participating healthcare organizations were recorded; however, deaths occurring outside of the hospital setting are not well captured. Identifying patient characteristics and conditions associated with mortality with COVID-19 is important for hypothesis generating for clinical trials and to develop targeted intervention strategies.

Background:This systematic overview reports findings from systematic reviews of randomized controlled trials of pharmacological and non-pharmacological interventions for behavioural and psychological symptoms of dementia (BPSD). The Cochrane Database of Systematic Reviews, DARE, Medline, EMBASE, and PsycINFO were searched to September 2015. Fifteen systematic reviews of eighteen different interventions were included. A significant improvement in BPSD was seen with: functional analysis-based interventions (GRADE quality of evidence moderate; standardized mean difference (SMD) -0.10, 95%CI -0.20 to 0.00), music therapy (low; SMD -0.49, 95%CI -0.82 to -0.17), analgesics (low; SMD -0.24, 95%CI -0.47 to -0.01), donepezil (high; SMD -0.15 95% CI -0.29 to -0.01), galantamine (high; SMD -0.15, 95%CI -0.28 to -0.03), and antipsychotics (high; SMD -0.13, 95%CI -0.21 to -0.06). The estimate of effect size for most interventions was small. Although some pharmacological interventions had a slightly larger effect size, current evidence suggests functional analysis-based interventions should be used as first line management of BPSD whenever possible due to the lack of associated adverse events. Music therapy may also be beneficial, but further research is required as the quality of evidence to support its use is low. Cholinesterase inhibitors donepezil and galantamine should be trialled for the management of BPSD where non-pharmacological treatments have failed. Low-quality evidence suggests that assessment of pain should be conducted and a stepped analgesic approach trialled when appropriate. Antipsychotics have proven effectiveness but should be avoided where possible due to the high risk of serious adverse events and availability of safer alternatives.

Background: Stroke is associated with an increased risk of dementia; however, the impact of stroke on cognition has been found to be variable, such that stroke survivors can show decline, remain stable, or revert to baseline cognitive functioning. Knowing the natural history of cognitive impairment after stroke is important for intervention. The aim of this systematic review is to investigate the longitudinal course of cognitive function in stroke survivors. Methods and Results: Three electronic databases (Medline, Embase, PsycINFO) were searched using OvidSP from inception to July 15, 2016. Longitudinal studies with ≥2 time points of cognitive assessment after stroke were included. In total, 5952 articles were retrieved and 14 were included. There was a trend toward significant deterioration in cognitive test scores in stroke survivors (8 studies). Cognitive stability (3 studies) and improvement (3 studies) were also demonstrated, although follow‐up time tended to be shorter in these studies. Variables associated with impairment included age, ethnicity, premorbid cognitive performance, depression, stroke location, and history of previous stroke. Associations with APOE*E4 (apolipoprotein E with the E4 allele) allele status and sex were mixed. Conclusions: Stroke is associated with an increased risk of cognitive decline, but cognitive decline is not a consequence. Factors associated with decline, such as sociodemographic status, health‐related comorbidity, stroke history, and clinical features could be used in models to predict future risk of dementia after stroke. A risk model approach could identify patients at greatest risk for timely intervention to reduce the frequency or delay the onset of poststroke cognitive impairment and dementia.

Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance. Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included. In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model. There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.

Aims: To consolidate evidence to determine (i) the association between cardiovascular risk factors and health outcomes with coronavirus 2019 (COVID-19); and (ii) the impact of COVID-19 on cardiovascular health. Methods and results: An umbrella review of systematic reviews was conducted. Fourteen medical databases and pre-print servers were searched from 1 January 2020 to 5 November 2020. The review focused on reviews rated as moderate or high-quality using the AMSTAR 2 tool. Eighty-four reviews were identified; 31 reviews were assessed as moderate quality and one was high-quality. The following risk factors were associated with higher mortality and severe COVID-19: renal disease [odds ratio (OR) (95% confidence interval) for mortality 3.07 (2.43–3.88)], diabetes mellitus [OR 2.09 (1.80–2.42)], hypertension [OR 2.50 (2.02–3.11)], smoking history [risk ratio (RR) 1.26 (1.20–1.32)], cerebrovascular disease [RR 2.75 (1.54–4.89)], and cardiovascular disease [OR 2.65 (1.86–3.78)]. Liver disease was associated with higher odds of mortality [OR 2.81 (1.31–6.01)], but not severe COVID-19. Current smoking was associated with a higher risk of severe COVID-19 [RR 1.80 (1.14–2.85)], but not mortality. Obesity associated with higher odds of mortality [OR 2.18 (1.10–4.34)], but there was an absence of evidence for severe COVID-19. In patients hospitalized with COVID-19, the following incident cardiovascular complications were identified: acute heart failure (2%), myocardial infarction (4%), deep vein thrombosis (7%), myocardial injury (10%), angina (10%), arrhythmias (18%), pulmonary embolism (19%), and venous thromboembolism (25%). Conclusion: Many of the risk factors identified as associated with adverse outcomes with COVID-19 are potentially modifiable. Primary and secondary prevention strategies that target cardiovascular risk factors may improve outcomes for people following COVID-19.

The cognitive reserve hypothesis suggests that across the lifespan, higher education, regular participation in social or mentally stimulating activities, and complexity of occupation increase an individual's resistance to dementia. However, there is currently no consensus regarding how to assess or measure cognitive reserve. We performed a systematic review of reviews focused on the concept of cognitive reserve to examine key elements of the definition and highlight limitations. We searched Embase.com, MEDLINE (OvidSP), the Cochrane Library, Web of Science, Scopus, Google Scholar, and PubMed. Five systematic reviews were identified. These incorporated findings from cohort, cross-sectional, and case-control studies, and the outcomes examined included Alzheimer's disease, vascular dementia, nonspecified dementia, all dementias, and cognitive decline or cognitive impairment. Education, occupation, and leisure or mentally stimulating activities were suggested to supply cognitive reserve and offer a protective effect against the risk of dementia. Premorbid IQ and socioeconomic status have not been investigated as thoroughly and showed inconsistent results. Two of the reviews showed that when combining different indicators in the analyses/definition, including education, occupation, mentally stimulating activities, and premorbid IQ, cognitive reserve had a protective effect against cognitive decline. However, other indicators may also supply the reserve, including dietary habits and genetic indicators, but research is lacking with regard to creating a full cognitive reserve model. This review highlights the lack of consensus regarding a definition of cognitive reserve. Further research is required to clarify how the indicators already identified may provide cognitive reserve and offer a protective effect against dementia. Agreement on the indicators that constitute the cognitive reserve model is needed before testing possible interventions that may increase the reserve supply and improve cognition.