Evaluating methods for risk prediction of Covid-19 mortality in nursing home residents before and after vaccine availability: a retrospective cohort study.

BACKGROUND: SARS-CoV-2 vaccines are effective in reducing hospitalization, COVID-19 symptoms, and COVID-19 mortality for nursing home (NH) residents. We sought to compare the accuracy of various machine learning models, examine changes to model performance, and identify resident characteristics that have the strongest associations with 30-day COVID-19 mortality, before and after vaccine availability. METHODS: We conducted a population-based retrospective cohort study analyzing data from all NH facilities across Ontario, Canada. We included all residents diagnosed with SARS-CoV-2 and living in NHs between March 2020 and July 2021. We employed five machine learning algorithms to predict COVID-19 mortality, including logistic regression, LASSO regression, classification and regression trees (CART), random forests, and gradient boosted trees. The discriminative performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) for each model using 10-fold cross-validation. Model calibration was determined through evaluation of calibration slopes. Variable importance was calculated by repeatedly and randomly permutating the values of each predictor in the dataset and re-evaluating the model's performance. RESULTS: A total of 14,977 NH residents and 20 resident characteristics were included in the model. The cross-validated AUCs were similar across algorithms and ranged from 0.64 to 0.67. Gradient boosted trees and logistic regression had an AUC of 0.67 pre- and post-vaccine availability. CART had the lowest discrimination ability with an AUC of 0.64 pre-vaccine availability, and 0.65 post-vaccine availability. The most influential resident characteristics, irrespective of vaccine availability, included advanced age (≥ 75 years), health instability, functional and cognitive status, sex (male), and polypharmacy. CONCLUSIONS: The predictive accuracy and discrimination exhibited by all five examined machine learning algorithms were similar. Both logistic regression and gradient boosted trees exhibit comparable performance and display slight superiority over other machine learning algorithms. We observed consistent model performance both before and after vaccine availability. The influence of resident characteristics on COVID-19 mortality remained consistent across time periods, suggesting that changes to pre-vaccination screening practices for high-risk individuals are effective in the post-vaccination era.

Potentially Modifiable Risk Factors for Dementia and Mild Cognitive Impairment: An Umbrella Review and Meta-Analysis.

INTRODUCTION: The prevalence of mild and major neurocognitive disorders (NCDs), also referred to as mild cognitive impairment and dementia, is rising globally. The prevention of NCDs is a major global public health interest. We sought to synthesize the literature on potentially modifiable risk factors for NCDs. METHODS: We conducted an umbrella review using a systematic search across multiple databases to identify relevant systematic reviews and meta-analyses. Eligible reviews examined potentially modifiable risk factors for mild or major NCDs. We used a random-effects multi-level meta-analytic approach to synthesize risk ratios for each risk factor while accounting for overlap in the reviews. We further examined risk factors for major NCD due to two common etiologies: Alzheimer's disease and vascular dementia. RESULTS: A total of 45 reviews with 212 meta-analyses were synthesized. We identified fourteen broadly defined modifiable risk factors that were significantly associated with these disorders: alcohol consumption, body weight, depression, diabetes mellitus, diet, hypertension, less education, physical inactivity, sensory loss, sleep disturbance, smoking, social isolation, traumatic brain injury, and vitamin D deficiency. All 14 factors were associated with the risk of major NCD, and five were associated with mild NCD. We found considerably less research for vascular dementia and mild NCD. CONCLUSION: Our review quantifies the risk associated with 14 potentially modifiable risk factors for mild and major NCDs, including several factors infrequently included in dementia action plans. Prevention strategies should consider approaches that reduce the incidence and severity of these risk factors through health promotion, identification, and early management.

Clinical Comorbidities and Transitions Between Care Settings Among Residents of Assisted Living Facilities: A Repeated Cross-Sectional Study.

OBJECTIVE: We investigate the changes in the sociodemographic characteristics, clinical comorbidities, and transitions between care settings among residents of assisted living facilities. DESIGN: Repeated cross-sectional study. SETTING AND PARTICIPANTS: Linked, individual-level health system administrative data on residents of assisted living facilities in Ontario, Canada, from January 1, 2013, to December 31, 2019. METHODS: Counts and proportions were calculated to describe the sociodemographic characteristics and clinical comorbidities. Relative changes and trend tests were calculated to quantify the longitudinal changes in the characteristics of residents of assisted living facilities between 2013 and 2019. A Sankey plot was graphed to display transitions between different care settings (ie, hospital admission, nursing home admission, died, or remained in the assisted living facility) each year from 2013 to 2019. RESULTS: There was a 34% relative increase in the resident population size of assisted living facilities (56,9752019 vs 42,6002013). These older adults had a mean age of 87 years, and women accounted for nearly two-thirds of the population across all years. The 5 clinical comorbidities that had the highest relative increases were renal disease (24.3%), other mental health conditions (16.8%), cardiac arrhythmias (9.6%), diabetes (8.5%), and cancer (6.9%). Nearly 20% of the original cohort from 2013 remained in an assisted living facility at the end of 2019, and approximately 10% of that cohort transitioned to a nursing home in any year from 2013 to 2019. CONCLUSIONS AND IMPLICATIONS: Residents of assisted living facilities are an important older adult population that has progressively increased in clinical complexity within less than a decade. Clinicians and policy makers should advocate for the implementation of on-site medical care that is aligned with the needs of these older adults.

Nursing home crowding and its association with outbreak-associated respiratory infection in Ontario, Canada before the COVID-19 pandemic (2014-19): a retrospective cohort study.

BACKGROUND: Studies conducted during the COVID-19 pandemic have shown that crowding in nursing homes is associated with high incidence of SARS-CoV-2 infections, but this effect has not been shown for other respiratory pathogens. We aimed to measure the association between crowding in nursing homes and outbreak-associated respiratory infection incidence and related mortality before the COVID-19 pandemic. METHODS: We conducted a retrospective cohort study of nursing homes in Ontario, Canada. We identified, characterised, and selected nursing homes through the Ontario Ministry of Long-Term Care datasets. Nursing homes that were not funded by the Ontario Ministry of Long-Term Care and homes that closed before January, 2020 were excluded. Outcomes consisting of respiratory infection outbreaks were obtained from the Integrated Public Health Information System of Ontario. The crowding index equalled the mean number of residents per bedroom and bathroom. The primary outcomes were the incidence of outbreak-associated infections and mortality per 100 nursing home residents per year. We examined the incidence of infections and deaths as a function of the crowding index by use of negative binomial regression with adjustment for three home characteristics (ie, ownership, number of beds, and region) and nine mean resident characteristics (ie, age, female sex, dementia, diabetes, chronic heart failure, renal failure, cancer, chronic obstructive pulmonary disease, and activities of daily living score). FINDINGS: Between Sept 1, 2014, and Aug 31, 2019, 5107 respiratory infection outbreaks in 588 nursing homes were recorded, of which 4921 (96·4%), involving 64 829 cases of respiratory infection and 1969 deaths, were included in this analysis. Nursing homes with a high crowding index had higher incidences of respiratory infection (26·4% vs 13·8%; adjusted rate ratio per one resident per room increase in crowding 1·89 [95% CI 1·64-2·17]) and mortality (0·8% vs 0·4%; 2·34 [1·88-2·92]) than did homes with a low crowding index. INTERPRETATION: Respiratory infection and mortality rates were higher in nursing homes with high crowding index than in homes with low crowding index, and the association was consistent across various respiratory pathogens. Decreasing crowding is an important safety target beyond the COVID-19 pandemic to help to promote resident wellbeing and decrease the transmission of prevalent respiratory pathogens. FUNDING: None.

Nursing Home Resident Admission Characteristics and Potentially Preventable Emergency Department Transfers.

OBJECTIVES: To determine which nursing home (NH) resident-level admission characteristics are associated with potentially preventable emergency department (PPED) transfers. DESIGN: We conducted a population-level retrospective cohort study on NH resident data collected using the Resident Assessment Instrument-Minimum Data Set Version 2.0 and linked to the National Ambulatory Care Reporting System for ED transfers. SETTING: We used all NH resident admission assessments from January 1, 2017, to December 31, 2018, in Ontario. PARTICIPANTS: The cohort included the admission assessment of 56,433 NH residents. METHODS: PPED transfers were defined based on the International Classification of Disease, Version 10 (Canadian) We used logistic regression with 10-fold cross-validation and computed average marginal effects to identify the association between resident characteristics at NH admission and PPED transfers within 92 days after admission. RESULTS: Overall, 6.2% of residents had at least 1 PPED transfer within 92 days of NH admission. After adjustment, variables that had a prevalence of 10% or more that were associated with a 1% or more absolute increase in the risk of a PPED transfer included polypharmacy [of cohort (OC) 84.4%, risk difference (RD) 2.0%], congestive heart failure (OC 29.0%, RD 3.0%), and renal failure (OC 11.6%, RD 1.2%). Female sex (OC 63.2%, RD -1.3%), a do not hospitalize directive (OC 24.4%, RD -2.6%), change in mood (OC 66.9%, RD -1.2%), and Alzheimer's or dementia (OC 62.1%, RD -1.2%) were more than 10% prevalent and associated with a 1% or more absolute decrease in the risk of a PPED. CONCLUSIONS AND IMPLICATIONS: Though many routinely collected resident characteristics were associated with a PPED transfer, the absence of sufficiently discriminating characteristics suggests that emergency department visits by NH residents are multifactorial and difficult to predict. Future studies should assess the clinical utility of risk factor identification to prevent transfers.

Associations with rates of falls among home care clients in Ontario, Canada: a population-based, cross-sectional study.

BACKGROUND: Accidental falls among older adults are a leading cause of injury-related hospitalizations. Reducing falls is an ongoing quality improvement priority for home care, given that many home care clients experience falls. In this study, we identify factors associated with the rate of falls among home care clients. METHODS: We conducted a population-based, cross-sectional study using secondary data from the Hamilton, Niagara, Haldimand, and Brant health region of Ontario, Canada from January 1 - March 31, 2018. We captured person-level characteristics with falls from the Resident Assessment Instrument - Home Care (RAI-HC). Negative binomial regression was used to model the rate of falls. RESULTS: Functional characteristics of home care clients had strong, statistically significant associations with the rate of falls. Declines in activities of daily living, assistive device use for locomotion indoors, polypharmacy, and health conditions, such as dizziness or lightheadedness, and parkinsonism, were associated with a higher rate of falls. Males who used assistive devices had a higher rate of falls compared to females; however, males with neurological and cardiovascular health conditions had a decrease in the rate of falls compared to females. Home care clients with parkinsonism who used a cane and took eight or more drugs had stronger associations with an increased rate of falls compared to those who do not have parkinsonism. CONCLUSIONS: Functional characteristics, polypharmacy, and health conditions are associated with increased rates of falls among home care clients. Home care clients who are at a greater risk of falls may require environmental adjustments in their home to reduce or eliminate the possibility of falling.

Elder Abuse in the Out-of-Hospital and Emergency Department Settings: A Scoping Review.

This scoping review aimed to synthesize the available evidence on the epidemiology, patient- and caregiver-associated factors, clinical characteristics, screening tools, prevention, interventions, and perspectives of health care professionals in regard to elder abuse in the out-of-hospital or emergency department (ED) setting. Literature search was performed with MEDLINE, EMBASE, the Cumulative Index of Nursing and Allied Health, PsycINFO, and the Cochrane Library. Studies were eligible if they were observational or experimental and reported on elder abuse in the out-of-hospital or ED setting. A qualitative approach, performed independently by 2 reviewers, was used to synthesize and report the findings. A total of 413 citations were retrieved, from which 55 studies published between 1988 and 2019 were included. The prevalence of elder abuse reported during the ED visit was lower than reported in the community. The most commonly detected type of elder abuse was neglect, and then physical abuse. The following factors were more common in identified cases of elder abuse: female sex, cognitive impairment, functional disability, frailty, social isolation, and lower socioeconomic status. Psychiatric and substance use disorders were more common among victims and their caregivers. Screening tools have been proposed, but multicenter validation and influence of screening on patient-important outcomes were lacking. Health care professionals reported being poorly trained and acknowledged numerous barriers when caring for potential victims. There is insufficient knowledge, limited training, and a poorly organized system in place for elder abuse in the out-of-hospital and ED settings. Studies on the processes and effects of screening and interventions are required to improve care of this vulnerable population.