Frailty as a mortality predictor in older adults with COVID-19: A systematic review and meta-analysis of cohort studies

COVID-19-related morbidity and mortality in people with multiple long-term conditions: a systematic review and meta-analysis of over 4 million people

OBJECTIVES

To describe the direct impact of coronavirus disease 2019 (COVID-19) infection on morbidity and mortality in people with multiple long-term conditions (MLTCs).

DESIGN

A systematic review and meta-analysis including observational studies.

SETTING

Studies conducted between 1 January 2020 and 4 May 2023 across 51 countries were identified from five databases.

PARTICIPANTS

A total of 4,084,469 patients with confirmed COVID-19 infection.

MAIN OUTCOME MEASURES

Pooled risk ratios (RRs) for mortality, hospitalisation, severe disease, intensive care unit (ICU) admission and mechanical ventilation were estimated with random effect meta-analysis models.

RESULTS

A total of 38,356 studies were identified and 111 included. In most (74%) of the studies, MLTCs referred to having two or more long-term conditions. Others described MLTCs by high weighted indices: the Charlson Comorbidity Index in 11% and the Clinical Frailty Score in 7%. Using the National Institutes of Health quality assessment tool for observational studies, the risk of bias was judged as low and moderate in 86 and 25 studies, respectively. Having MLTCs was associated with increased mortality (RR: 2.61 [95% CI: 2.27 to 3.0]); hospitalisation (2.4 [1.92 to 2.99]); severe disease (2.61 [1.92 to 3.54]); ICU admission (1.22 [1.07 to 1.39]) and mechanical ventilation (1.83 [1.18 to 2.84]) compared with those with no MLTCs. Pooled RRs for adverse outcomes were higher in children and young people compared with all age groups. In meta-regression analyses, men were more likely to need ICU admission (p = 0.013) and mechanical ventilation (p = 0.002).

CONCLUSIONS

Public health policies, clinical and preventative interventions should prioritise people with MLTCs to minimise direct adverse outcomes from COVID-19 disease.

Effectiveness and Satisfaction with Telemedicine in Geriatric Patients at High Risk of Fragility Fractures

Background: Telemedicine has increasingly widespread to improve the monitoring of patients with chronic diseases. Secondary prevention of fragility fractures is an urgent matter to be addressed by means of available technology, although supported by little evidence so far. We investigated the feasibility, efficacy, and satisfaction of managing older adults at high risk of fragility fractures during the COVID-19 lockdown. Methods: During the period January to July 2021, a prospective observational study for safety and adherence purposes was conducted among older adults (n = 407) with ongoing treatments for secondary prevention of fragility fractures. The study procedures comply with national and regional resolutions related to telemedicine service (TS), including equipment, staff behaviors, and patient reports. Results: A majority (86.48% [n = 352]) of the eligible patients joined the remote visits, mainly women (88.2%), 81.4 ± 8.8 years of age, 49.6% independent in 5 out of 6 BADL, despite high comorbidity (4.9 ± 1.5), and polypharmacy (4.9 ± 3.1). Almost all were on second-line antifracture treatments (95.58%) due to previous major (84.03%) and minor (42.5%) fragility fractures. About 58% reported good and very good reliability of the internet network, allowing easy access to the TS platform, and 54% declared the degree of satisfaction with TS as good and very good. About 75% of clinicians acknowledged the efficacy of TS and expressed willingness to recommend the use of TS to colleagues. Ultimately, 68% of specialists defined the time allocated for patients' remote visits as acceptable. Conclusion: TS may be an opportunity to improve the availability of appropriate health care services to satisfy patients' needs and optimize health care resource allocation.

Factors associated with mortality of elderly people due to COVID-19: Protocol for systematic review and meta-analysis

INTRODUCTION

The COVID-19 pandemic has become a significant health crisis, marked by high mortality rates on a global scale, with mortality from the disease being notably concentrated among the elderly due to various factors.

OBJECTIVE

This study aims to investigate the biological and non-biological factors associated with COVID-19 mortality rates among the elderly worldwide.

METHODS

The following databases will be consulted: PubMed, Scopus, EMBASE, Web of Science and ScienceDirect. Longitudinal observational studies (cohort and case-control-risk factors) will be included. The risk of bias, defined as low, moderate, high, will be assessed using the National Heart, Lung and Blood Institute (NHLBI) Quality Assessment Tool for observational cohort and cross-sectional studies. Two independent authors will conduct the searches, and any possible disagreements will be resolved by a third author. Heterogeneity between study results will be assessed using a standard X2 test with a significance level of 0.05, and an I2 value will be calculated to further assess heterogeneity. The random effects model for meta-analyses will be adopted to distribute the weight between the studies and standardize their contributions. The meta-analyses will be conducted using RevMan software.

DISCUSSION

Despite the numerous publications on COVID-19 mortality among the elderly, there is still a gap in knowledge, as there is no systematic review and meta-analysis that summarizes the main biological and non-biological associated factors globally.

CONCLUSION

The results of this study will consolidate the latest evidence and address gaps in the overall understanding of biological or non-biological associated factors. This knowledge will facilitate the development of appropriate health strategies for this demographic group and pave the way for further research.

TRIAL REGISTRATION

PROSPERO (CRD42023400873).

A Systematic Literature Review of the Impact of COVID-19 on the Health of LGBTQIA+ Older Adults: Identification of Risk and Protective Health Factors and Development of a Model of Health and Disease

It is important to understand the differential impact of COVID-19 on the health of older lesbian, gay, bisexual, transgender, queer/questioning, intersex, asexual, and people with other sexual orientations and forms of gender expression (LGBTQIA+). The objective of this study is to systematically review the impact of COVID-19 on LGBTQIA+ older adults' health including risk and protective factors. We reviewed a total of 167 records including LGBTQIA+ older adults published since 2019. Two independent reviewers screened titles and abstracts and extracted information of 21 full-text records meeting inclusion criteria using COVIDENCE software. The results show that the negative health consequences are exacerbated by personal risk (e.g., perceived homo/transphobia and ageism in LGBTQIA+ communities) and environmental factors (e.g., heterosexism within health services). The negative impact seems to be reduced by personal protective (e.g., resilience, spirituality, and hobbies) and environmental factors (e.g., technology use to increase social participation and social rituals). In conclusion, the health of LGBTQIA+ older adults has been disproportionately affected during the pandemic associated to the latest coronavirus (COVID-19). The experiences of LGBTQIA+ older adults during the pandemic are integrated in a Model of Health and Disease for LGBTQIA+ older adults. Specific strategies to promote health and well-being in this community are provided.

The association of technology acceptance and physical activity on frailty in older adults during the COVID-19 pandemic period

BACKGROUND

Physical activity was known to be the protective factor against frailty. Technology acceptance is associated with behavioural intention to technology usage. Technology has been effective in promoting healthy behaviour of physical activity. The purposes of this study were to examine the association between physical activity and technology acceptance with frailty and examine the moderation effect of technology acceptance on physical activity and frailty. We hypothesize that 1) physical activity and technology acceptance are associated with frailty, and 2) technology acceptance moderates the association of physical activity with frailty.

METHODS

This study employed a cross-sectional design and was conducted in the community settings of Hong Kong in 2021. Eligible participants were old people aged ≥60 and were community-dwelling. Key variables included physical activity measured by Rapid Assessment of Physical Activity (RAPA), social network measured by Lubben Social Network Scale-Six items (LSNS-6); depressive symptoms measured by Patient Health Questionnaire-Nine items (PHQ-9), technology acceptance measured by Senior Technology Acceptance Model-14 items (STAM-14) and frailty measured by Fatigue, Resistance, Ambulation, Illnesses, & Loss of Weight scale (FRAIL). Ordinal logistic regression was employed to test the hypotheses. The moderation effect was examined by introducing an interaction term formed by the multiplication of an independent variable (i.e., physical activity) and a moderating variable (i.e., technology acceptance).

RESULTS

This study recruited 380 eligible participants with a mean age of 66.5 years. Technology acceptance (Beta = - 0.031, p < 0.001, Pseudo-R2 = 0.087) and physical activity (Beta = - 0.182, p = 0.003, Pseudo-R2 = 0.027) were associated with frailty in the unadjusted models. Technology acceptance (Beta = - 0.066, p < 0.001) and physical activity (Beta = - 1.192, p < 0.001) were also associated with frailty in the fully adjusted model (Pseudo-R2 = 0.352). Interaction term formed by the multiplication of technology acceptance and physical activity (Beta = 0.012, p = 0.001) was associated with frailty. Physical activity was significantly associated with frailty in the lower technology acceptance subgroup (Beta = - 0.313, p = 0.002) in the subgroup analysis. However, in the subgroup of higher technology acceptance, the association of physical activity (Beta = 0.104, p = 408) on frailty became positive but not significant.

CONCLUSIONS

This study showed that physical activity and technology acceptance were associated with frailty, and technology acceptance moderated the association of physical activity with frailty. This study recommends engaging older adults in physical activity to combat frailty preferentially in those with a lower level of technology acceptance.

What If the Clinical and Older Adults' Perspectives about Frailty Converge? A Call for a Mixed Conceptual Model of Frailty: A Traditional Literature Review

Existing frailty models have enhanced research and practice; however, none of the models accounts for the perspective of older adults upon defining and operationalizing frailty. We aim to propose a mixed conceptual model that builds on the integral model while accounting for older adults' perceptions and lived experiences of frailty. We conducted a traditional literature review to address frailty attributes, risk factors, consequences, perceptions, and lived experiences of older adults with frailty. Frailty attributes are vulnerability/susceptibility, aging, dynamic, complex, physical, psychological, and social. Frailty perceptions and lived experience themes/subthemes are refusing frailty labeling, being labeled "by others" as compared to "self-labeling", from the perception of being frail towards acting as being frail, positive self-image, skepticism about frailty screening, communicating the term "frail", and negative and positive impacts and experiences of frailty. Frailty risk factors are classified into socio-demographic, biological, physical, psychological/cognitive, behavioral, and situational/environmental factors. The consequences of frailty affect the individual, the caregiver/family, the healthcare sector, and society. The mixed conceptual model of frailty consists of interacting risk factors, interacting attributes surrounded by the older adult's perception and lived experience, and interacting consequences at multiple levels. The mixed conceptual model provides a lens to qualify frailty in addition to quantifying it.

Trends in frailty in brain tumor care during the COVID-19 pandemic in a nationwide hospital network in Germany

PURPOSE

Among brain tumor patients, frailty is associated with poor outcomes. The COVID-19 pandemic has led to increased frailty in the general population. To date, evidence on changes in frailty among brain tumor patients during the pandemic is lacking. We aimed to compare frailty among brain tumor patients in Germany during the COVID-19 pandemic to the pre-pandemic era and to assess potential effects on brain tumor care.

METHODS

In this retrospective observational study, we compared frailty among brain tumor patients hospitalized during the COVID-19 pandemic in years 2020 through 2022 to pre-pandemic years 2016 through 2019 based on administrative data from a nationwide network of 78 hospitals in Germany. Using the Hospital Frailty Risk Score (HFRS), frailty was categorized as low, intermediate, or high. We examined changes in frailty, patient demographics, the burden of comorbidity, rates of surgery, and mortality rates for different frailty groups during the pandemic and compared them to pre-pandemic levels.

RESULTS

Of the 20,005 included hospitalizations for brain tumors, 7979 were during the pandemic (mean age 60.0 years (± 18.4); females: 49.8%), and 12,026 in the pre-pandemic period (mean age: 59.0 years [± 18.4]; females: 49.2%). Average daily admissions decreased from 8.2 (± 5.1) during pre-pandemic years to 7.3 (± 4.5) during the pandemic (p < 0.01). The overall median HFRS decreased from 3.1 (IQR: 0.9-7.3) during the pre-pandemic years to 2.6 (IQR: 0.3-6.8) during the pandemic (p < 0.01). At the same time, the Elixhauser Comorbidity Index (ECI) decreased from 17.0 (± 12.4) to 16.1 (± 12.0; p < 0.01), but to a larger degree among high compared to low frailty cases (by 1.8 vs. 0.3 points; p = 0.04). In the entire cohort, the mean length of stay was significantly shorter in the pandemic period (9.5 days [± 10.7]) compared with pre-pandemic levels (10.2 days [± 11.8]; p < 0.01) with similar differences in the three frailty groups. Rates of brain tumor resection increased from 29.9% in pre-pandemic years to 36.6% during the pandemic (p < 0.001) without differences between frailty levels. Rates of in-hospital mortality did not change during the pandemic (6.1% vs. 6.7%, p = 0.07), and there was no interaction with frailty.

CONCLUSION

Even though our findings are limited in that the HFRS is validated only for patients ≥ 75 years of age, our study among patients of all ages hospitalized for brain tumors in Germany suggests a marked decrease in levels of frailty and in the burden of comorbidities during the COVID-19 pandemic.

Frailty and Adverse Outcomes After SARS-CoV-2 Infection in Elderly Patients on Maintenance Hemodialysis: A Cohort Study

Purpose

Frailty is an important geriatric syndrome associated with aging and adverse events, especially in patients with severe infection. To help guide prognosis for elderly patients undergoing maintenance hemodialysis (MHD) who experience acute infection, this study investigated whether baseline (pre-infection) frailty may be associated with adverse outcomes in elderly patients undergoing MHD who suffer SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection.

Patients and Methods

Patients (aged ≥60 y) receiving MHD had been assessed for overall frailty and the 5 frailty components based on the Fried Frailty Phenotype scale within 3 months prior to SARS-CoV-2 infection.

Results

There were 59 and 98 patients in the frail and non-frail groups, respectively. Three months after SARS-CoV-2 infection, 21 (13.4%) and 45 (28.7%) patients had died or were in hospital. The multivariate COX proportional risk model suggested that the all-cause mortality rate in patients judged overall frail or with low activity was significantly higher compared with that of the non-frail (P = 0.049; 0.003). The multivariate logistic regression analysis showed that hospitalization 3 months after SARS-CoV-2 infection was associated with both overall frailty and low activity (OR 2.276, 95% CI: 1.034-5.010, P = 0.041; OR 2.809, 95% CI: 1.311-6.020, P = 0.008, respectively).

Conclusion

Overall frailty and specifically low activity were significantly associated with all-cause mortality and hospitalization in this elderly MHD population after SARS-CoV-2 infection. Early assessment of frailty and effective interventions are recommended to improve the prognosis of patients receiving MHD who are at higher risk of acute infection.

Trends in the COVID-19 Pandemic in Italy during the Summers of 2020 (before Mass Vaccination), 2021 (after Primary Mass Vaccination) and 2022 (after Booster Mass Vaccination): A Real-World Nationwide Study Based on a Population of 58.85 Million People

Like all RNA viruses, SARS-CoV-2 shows a high mutation rate, which has led to the emergence of new variants. Among them, Gamma and Delta developed at the turn of 2020-2021 in Amazonas and India, two ecoregions characterized by hot-humid weather, very similar to that of the summer season in Italy due to climate change, the first Western country to be hit hard by COVID-19 and to experience lockdown restrictions in a democratic framework of 58.85 million people. The aim of our research has been to evaluate the impact of climate on the COVID-19 pandemic in Italy during the summers of 2020 (before mass vaccination), 2021 (after primary mass vaccination) and 2022 (after booster mass vaccination), also taking into account the emergence of these two variants.

METHODS

During the state of national health emergency and the Draghi government, the Civil Defense Department released the aggregate data coming from the Ministry of Health, the Higher Institute of Health, the Independent Provinces and the Italian Regions daily, in order to inform about the pandemic situation in Italy. Among these data there were the number of deaths, hospitalizations in intensive care units (ICU), non-ICU patients, contagions and performed swabs. By means of a team effort, we have collected and elaborated all these data, comparing the COVID-19 pandemic in Italy during the summers of 2020 (following the nationwide lockdown), 2021 and 2022.

RESULTS

from the summer of 2020 to the summers of 2021 and 2022 all pandemic trend indicators have shown a sharp worsening in Italy. COVID-19 deaths increased by ≈298% and ≈834%, ICU hospitalizations by ≈386% and ≈310%, non-ICU hospitalizations by ≈224% and ≈600%, contagions by ≈627% and ≈6850% (i.e., ≈68.50 times), swabs by ≈354% and ≈370%, and the mean positivity rate passed from ≈1% to ≈2% and ≈20%, respectively.

CONCLUSIONS

SARS-CoV-2 can be transmitted in any climate, including areas with hot and humid weather, and the emergence of variants adapted to hot-humid climates may result in summer COVID-19 outbreaks, even in neither tropical nor subtropical countries. Although COVID-19 vaccines can confer cross-protection against newly emerging variants, this cross-immunity is naturally not absolute but limited, considering that vaccine protection wanes significantly after 6 months. It follows that a subject vaccinated at the beginning of the winter will not be completely covered in the height of the summer, and we should not forget the unvaccinated. As a final remark, the long and strict nationwide lockdown made it possible to flatten SARS-CoV-2 circulation and, therefore, its negative impact on Italy during the summer of 2020.

Role of Cardio-Renal Dysfunction, Inflammation Markers, and Frailty on In-Hospital Mortality in Older COVID-19 Patients: A Cluster Analysis

Our study aimed to identify clusters of hospitalized older COVID-19 patients according to their main comorbidities and routine laboratory parameters to evaluate their association with in-hospital mortality. We performed an observational study on 485 hospitalized older COVID-19 adults (aged 80+ years). Patients were aggregated in clusters by a K-medians cluster analysis. The primary outcome was in-hospital mortality. Medical history and laboratory parameters were collected on admission. Frailty, defined by the Clinical Frailty Scale (CFS), referred to the two weeks before hospitalization and was used as a covariate. The median age was 87 (83-91) years, with a female prevalence (59.2%). Three different clusters were identified: cluster 1 (337), cluster 2 (118), and cluster 3 (30). In-hospital mortality was 28.5%, increasing from cluster 1 to cluster 3: cluster 1 = 21.1%, cluster 2 = 40.7%, and cluster 3 = 63.3% (p < 0.001). The risk for in-hospital mortality was higher in clusters 2 [HR 1.96 (95% CI: 1.28-3.01)] and 3 [HR 2.87 (95% CI: 1.62-5.07)] compared to cluster 1, even after adjusting for age, sex, and frailty. Patients in cluster 3 were older and had a higher prevalence of atrial fibrillation, higher admission NT-proBNP and C-reactive protein levels, higher prevalence of concurrent bacterial infections, and lower estimated glomerular filtration rates. The addition of CFS significantly improved the predictive ability of the clusters for in-hospital mortality. Our cluster analysis on older COVID-19 patients provides a characterization of those subjects at higher risk for in-hospital mortality, highlighting the role played by cardio-renal impairment, higher inflammation markers, and frailty, often simultaneously present in the same patient.

Is Age the Most Important Risk Factor in COVID-19 Patients? The Relevance of Comorbidity Burden: A Retrospective Analysis of 10,551 Hospitalizations

Purpose

To assess the contribution of age and comorbidity to the risk of critical illness in hospitalized COVID-19 patients using increasingly exhaustive tools for measuring comorbidity burden.

Patients and Methods

We assessed the effect of age and comorbidity burden in a retrospective, multicenter cohort of patients hospitalized due to COVID-19 in Catalonia (North-East Spain) between March 1, 2020, and January 31, 2022. Vaccinated individuals and those admitted within the first of the six COVID-19 epidemic waves were excluded from the primary analysis but were included in secondary analyses. The primary outcome was critical illness, defined as the need for invasive mechanical ventilation, transfer to the intensive care unit (ICU), or in-hospital death. Explanatory variables included age, sex, and four summary measures of comorbidity burden on admission extracted from three indices: the Charlson index (17 diagnostic group codes), the Elixhauser index and count (31 diagnostic group codes), and the Queralt DxS index (3145 diagnostic group codes). All models were adjusted by wave and center. The proportion of the effect of age attributable to comorbidity burden was assessed using a causal mediation analysis.

Results

The primary analysis included 10,551 hospitalizations due to COVID-19; of them, 3632 (34.4%) experienced critical illness. The frequency of critical illness increased with age and comorbidity burden on admission, irrespective of the measure used. In multivariate analyses, the effect size of age decreased with the number of diagnoses considered to estimate comorbidity burden. When adjusting for the Queralt DxS index, age showed a minimal contribution to critical illness; according to the causal mediation analysis, comorbidity burden on admission explained the 98.2% (95% CI 84.1-117.1%) of the observed effect of age on critical illness.

Conclusion

Comorbidity burden (when measured exhaustively) explains better than chronological age the increased risk of critical illness observed in patients hospitalized with COVID-19.

Estimation of Excess Mortality in Germany During 2020-2022

Background This study estimates the burden of COVID-19 on mortality in Germany. It is expected that many people have died because of the new COVID-19 virus who otherwise would not have died. Estimating the burden of the COVID-19 pandemic on mortality by the number of officially reported COVID-19-related deaths has been proven to be difficult due to several reasons. Because of this, a better approach, which has been used in many studies, is to estimate the burden of the COVID-19 pandemic by calculating the excess mortality for the pandemic years. An advantage of such an approach is that additional negative impacts of a pandemic on mortality are covered as well, such as a possible pandemic-induced strain on the healthcare system. Methods To calculate the excess mortality in Germany for the pandemic years 2020 to 2022, we compare the reported number of all-cause deaths (i.e., the number of deaths independently of underlying causes) with the number of statistically expected all-cause deaths. For this, the state-of-the-art method of actuarial science, based on population tables, life tables, and longevity trends, is used to estimate the expected number of all-cause deaths from 2020 to 2022 if there had been no pandemic. Results The results show that the observed number of deaths in 2020 was close to the expected number with respect to the empirical standard deviation; approximately 4,000 excess deaths occurred. By contrast, in 2021, the observed number of deaths was two empirical standard deviations above the expected number and even more than four times the empirical standard deviation in 2022. In total, the number of excess deaths in the year 2021 is about 34,000 and in 2022 about 66,000 deaths, yielding a cumulated 100,000 excess deaths in both years. The high excess mortality in 2021 and 2022 was mainly due to an increase in deaths in the age groups between 15 and 79 years and started to accumulate only from April 2021 onward. A similar mortality pattern was observed for stillbirths with an increase of about 9.4% in the second quarter and 19.4% in the fourth quarter of the year 2021 compared to previous years. Conclusions These findings indicate that something must have happened in spring 2021 that led to a sudden and sustained increase in mortality, although no such effects on mortality had been observed during the early COVID-19 pandemic so far. Possible influencing factors are explored in the discussion.

The effectiveness of a group-based Otago exercise program on physical function, frailty and health status in older nursing home residents: A systematic review and meta-analysis

OBJECTIVES

To explore the effects of a group-based Otago exercise program (OEP) on physical function (mobility, balance, lower limb strength), frailty and health status in older nursing home residents to determine the optimal scheme and format.

METHODS

This systematic review and meta-analysis was conducted to estimate group-based OEP effects. Subgroup analysis was performed to identify the influences of the participant and intervention characteristics on the effects.

RESULTS

Twelve studies met the eligibility criteria and were included in this meta-analysis, and the overall quality was relatively high. The results showed that the group-based OEP significantly improved physical function, including mobility [SMD=-0.64, 95% CI (-0.83,-0.45), Z=6.55, p<0.001], balance [MD=4.72, 95% CI (3.54, 5.90), Z=7.84, p<0.001], lower limb strength [SMD=-1.09, 95% CI (-1.40, -0.79), Z=7.01, p<0.001]; frailty [SMD=-0.73, 95% CI (-1.01, -0.45), Z=5.13, p<0.001] and health status [SMD=0.47, 95% CI (0.20, 0.74), Z=3.44, p=0.0006]. Subgroup analysis revealed that 30-minute sessions were more beneficial for improving balance than >30-minute sessions (p=0.0004). The training was coordinated with physiotherapists, who were more skilled at improving mobility than providing health training education (p=0.04).

CONCLUSIONS

Group-based OEP is helpful for improving physical function, frailty and health status in older nursing home residents. Specifically, 30-minute sessions and coordinating with physiotherapists may be the most appropriate and effective options.

Two Years with COVID-19: The Electronic Frailty Index Identifies High-Risk Patients in the Stockholm GeroCovid Study

INTRODUCTION

Frailty, a measure of biological aging, has been linked to worse COVID-19 outcomes. However, as the mortality differs across the COVID-19 waves, it is less clear whether a medical record-based electronic frailty index (eFI) that we have previously developed for older adults could be used for risk stratification in hospitalized COVID-19 patients.

OBJECTIVES

The aim of the study was to examine the association of frailty with mortality, readmission, and length of stay in older COVID-19 patients and to compare the predictive accuracy of the eFI to other frailty and comorbidity measures.

METHODS

This was a retrospective cohort study using electronic health records (EHRs) from nine geriatric clinics in Stockholm, Sweden, comprising 3,980 COVID-19 patients (mean age 81.6 years) admitted between March 2020 and March 2022. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the Clinical Frailty Scale, and the Hospital Frailty Risk Score. Comorbidity was measured using the Charlson Comorbidity Index. We analyzed in-hospital mortality and 30-day readmission using logistic regression, 30-day and 6-month mortality using Cox regression, and the length of stay using linear regression. Predictive accuracy of the logistic regression and Cox models was evaluated by area under the receiver operating characteristic curve (AUC) and Harrell's C-statistic, respectively.

RESULTS

Across the study period, the in-hospital mortality rate decreased from 13.9% in the first wave to 3.6% in the latest (Omicron) wave. Controlling for age and sex, a 10% increment in the eFI was significantly associated with higher risks of in-hospital mortality (odds ratio = 2.95; 95% confidence interval = 2.42-3.62), 30-day mortality (hazard ratio [HR] = 2.39; 2.08-2.74), 6-month mortality (HR = 2.29; 2.04-2.56), and a longer length of stay (β-coefficient = 2.00; 1.65-2.34) but not with 30-day readmission. The association between the eFI and in-hospital mortality remained robust across the waves, even after the vaccination rollout. Among all measures, the eFI had the best discrimination for in-hospital (AUC = 0.780), 30-day (Harrell's C = 0.733), and 6-month mortality (Harrell's C = 0.719).

CONCLUSION

An eFI based on routinely collected EHRs can be applied in identifying high-risk older COVID-19 patients during the continuing pandemic.

Aetiological and prognostic roles of frailty, multimorbidity and socioeconomic characteristics in the development of SARS-CoV-2 health outcomes: protocol for systematic reviews of population-based studies

INTRODUCTION

There is growing evidence that the impact of COVID-19 crisis may be stronger for individuals with multimorbidity, frailty and lower socioeconomic status. Existing reviews focus on few, mainly short-term effects of COVID-19 illness and patients with single chronic disease. Information is also largely missing for population representative samples.Applying population-based approach, the systematic reviews will have two objectives: (1) to evaluate the aetiological roles of frailty, multimorbidity and socioeconomic status on SARS-CoV-2 infection probability, hospitalisation, intensive care unit (ICU) admission, mechanical ventilation and COVID-19 related mortality among general population and (2) to investigate the prognostic roles of frailty, multimorbidity and socioeconomic characteristics on the risk of hospitalisation, ICU admission, mechanical ventilation, COVID-19 mortality, functioning, quality of life, disability, mental health and work absence.

METHODS AND ANALYSIS

For this ongoing work, four databases were searched: PubMed, Embase, WHO COVID-19 Global literature on coronavirus disease and PsycINFO, for the period between January 2020 and April 7 2021. Peer-reviewed published literature in English and all types of population-based studies will be considered. Studies using standard tools to assess multimorbidity such as disease count, comorbidity indices or disease combinations will be retained, as well as studies with standard scales and scores for frailty or measurement of a socioeconomic gradient. Initial search included 10 139 articles, 411 for full-text reading. Results will be summarised by risk factor, objective and outcome. The feasibility of meta-analysis will be determined by the findings and will aim to better understand uncertainties of the results. Quality of studies will be assessed using standardised scales.

ETHICS AND DISSEMINATION

The study will be based on published evidence, and it is exempt from the ethical approval. This work is part of the Population Health Information Research Infrastructure (PHIRI) project. Dissemination of the results will imply conference presentation, submission for scientific publication and PHIRI project report.

PROSPERO REGISTRATION NUMBER

CRD42021249444.

COVID-19 Clinical Features and Outcomes in Elderly Patients during Six Pandemic Waves

Many elderly patients with severe SARS-CoV-2 infections and COVID-19 infections are admitted to intensive care units. Age was previously identified as an independent risk factor for death and contributed to the greater severity of COVID-19. The elderly may have diminished lung functions, poor reactions to artificial ventilation, and compromised immune systems. However, it is yet uncertain how each pandemic wave and the predominant SARS-CoV-2 strains contribute to varying results and how patient groups such as the elderly are impacted. Comparing six COVID-19 pandemic waves, the objective of this study was to examine the variation in case severity, symptomatology, ICU hospitalizations, and mortality among SARS-CoV-2-infected elderly individuals. The study followed a retrospective design, including 60 eligible patients older than 70 years in each of the six pandemic wave groups, after matching them by the number of comorbidities and gender. SARS-CoV-2 infection during the first, third, and fourth pandemic waves had a significantly higher risk of mortality for hospitalized patients. Confusion and dyspnea at admission were significant risk factors for ICU admission in elderly patients (β = 1.92, respectively β = 3.65). The laboratory parameters identified decreased lymphocytes (β = 2.11), elevated IL-6 (β = 1.96), and procalcitonin (β = 2.46) as the most significant risk factors. The third and fourth COVID-19 waves had considerably more severe infections (31.7% and 26.7%) than the sixth wave (13.3%). Median ICU stay and percentage of patients receiving oxygen support also differed across pandemic waves. However, mortality rates between the six pandemic waves were similar. The average length of hospitalization varied dramatically among the six pandemic waves. Although senior patients are more likely to have worse COVID-19 outcomes after hospitalization, this risk is mitigated by the greater prevalence of comorbidities and frailty among the elderly. The six pandemic waves that were specifically evaluated did not reveal considerably disproportionate variations in terms of patient mortality; however, during the fourth pandemic wave, there were likely more hospitalized patients with severe COVID-19 in Romania. It is probable that certain circulating SARS-CoV-2 strains were more infectious, resulting in an increase in infections and a strain on healthcare systems, which might explain the variations found in our research.

COVID-19 in Older Individuals Requiring Hospitalization

Older individuals have an increased risk for severe coronavirus disease 2019 (COVID-19) and a higher risk for complications and death. The aim of this study was to investigate the clinical characteristics of older patients admitted with COVID-19 and describe their outcomes. This was a retrospective cohort study of patients older than 65 years admitted to the COVID-19 Department of the University Hospital of Heraklion. Data recorded and evaluated included age, gender, Infectious Diseases Society of America (IDSA) severity score, Charlson comorbidity index (CCI), high-flow nasal oxygen (HFNO) use, admission to the Intensive Care Unit (ICU), laboratory exams, treatment administered, and outcome. In total, 224 patients were evaluated in the present study. The median age was 75 years and 105 (46.9%) were female. In 50 patients (22.7%), HFNO was used and 23 (10.3%) were admitted to the ICU. Mortality was 13.4% (30 patients). Patients that died had higher age, were more likely to be male, had an IDSA severity score of 3, had prior HFNO use, had been admitted to the ICU, and were also more likely to have a higher white blood cell (WBC) count, CRP, ferritin, procalcitonin, d-dimers, and troponin. A multivariate logistic regression analysis identified age and the need for HFNO use to be independently positively associated with mortality. To conclude, COVID-19 carries significant mortality in hospitalized older patients, which increases with age, while the need for HFNO also increased the likelihood of worse outcomes. Clinicians caring for patients with COVID-19 should bear in mind these two factors. Future studies could elaborate on the effect of new variants on the dynamics of mortality in older patients.

Frailty in the context of COVID-19 pandemic: A life-threatening condition

The pandemic outbreak of coronavirus disease 2019 (COVID-19) has caused emerging challenges for healthcare systems regarding the assistance to the older adult population which, added to the increased life expectancy, may be exposing frail older adults to an increased risk of unfavorable health outcomes. Frailty has a pathogenesis of multifactorial etiology and is defined as a condition characterized by progressive decline in physiological function, weakness, decreased strength, and reduced resilience to stressors, leading to vulnerability and an increased risk of fractures, falls, institutionalization, and death. In the context of COVID-19, frail older adults accounted for approximately 51% of hospitalized patients with confirmed cases and elevated risk of mortality in-hospital. In addition, frailty may be associated with recent “excess mortality” reported by the World Health Organization (WHO) in terms of the full death toll associated directly (due to the disease) or indirectly (due to the pandemic's impact on health systems and society) to COVID-19. Therefore, this mini review aimed to provide a summarized discussion from meta-analyses data regarding the impact of frailty in community-dwelling older adults hospitalized with COVID-19 on short-term mortality risk.

Incidence and Outcomes of SARS-CoV-2 Infection in Older Adults Living with Dementia: A Population-Based Cohort Study

Background:

The identification of risk factors for SARS-CoV-2 infection and mortality in patients with dementia is a key aspect to support clinical decisions and public health interventions.

Objective:

To assess the incidence of SARS-CoV-2 infection and COVID-19 related death in a cohort of patients with dementia residing in the Lazio region and to investigate predicting factors for both infection and mortality.

Methods:

This population-based study used information from administrative databases and the SARS-CoV-2 infection surveillance system. Patients with dementia (age ≥65) were enrolled as of December 31, 2019 and followed-up until February 28, 2021. Cumulative risk of infection and death within 60 days of infection onset, and age-standardized incidence (SIR) and mortality (SMR) ratios were calculated. Logistic regression models were applied to identify factors associated with infection and mortality.

Results:

Among 37,729 dementia patients, 2,548 had a diagnosis of SARS-CoV-2 infection. The crude risk of infection was 6.7%. An increase in risk of infection was observed both in women (SIR 1.72; 95% CI 1.64–1.80) and men (SIR 1.43; 95% CI 1.33–1.54). Pneumonia, cerebrovascular and blood diseases, femur fracture, anxiety, antipsychotic and antithrombotic use were associated with an increased risk of infection. The crude risk of death was 31.0%, the SMRs 2.32 (95% CI 2.05–2.65) for men, and 2.82 (95% CI 2.55–3.11) for women. Factors associated with mortality included: male gender, age ≥85, symptoms at the diagnosis, antipsychotic and systemic antibiotics treatment.

Conclusion:

These findings emphasize the need of close and tailored monitoring of dementia patients to reduce the impact of COVID-19 on this fragile population.

Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients

To reduce the mortality of COVID-19 older patients, clear criteria to predict in-hospital mortality are urgently needed. Here, we aimed to evaluate the performance of selected routine laboratory biomarkers in improving the prediction of in-hospital mortality in 641 consecutive COVID-19 geriatric patients (mean age 86.6 ± 6.8) who were hospitalized at the INRCA hospital (Ancona, Italy). Thirty-four percent of the enrolled patients were deceased during the in-hospital stay. The percentage of severely frail patients, assessed with the Clinical Frailty Scale, was significantly increased in deceased patients compared to the survived ones. The age-adjusted Charlson comorbidity index (CCI) score was not significantly associated with an increased risk of death. Among the routine parameters, neutrophilia, eosinopenia, lymphopenia, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, procalcitonin, IL-6, and NT-proBNP showed the highest predictive values. The fully adjusted Cox regressions models confirmed that high neutrophil %, NLR, derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and low lymphocyte count, eosinophil %, and lymphocyte-to-monocyte ratio (LMR) were the best predictors of in-hospital mortality, independently from age, gender, and other potential confounders. Overall, our results strongly support the use of routine parameters, including complete blood count, in geriatric patients to predict COVID-19 in-hospital mortality, independent from baseline comorbidities and frailty.

Clinical Frailty Scale (CFS) indicated frailty is associated with increased in-hospital and 30-day mortality in COVID-19 patients: a systematic review and meta-analysis

BACKGROUND

The concept of frailty provides an age-independent, easy-to-use tool for risk stratification. We aimed to summarize the evidence on the efficacy of frailty tools in risk assessment in COVID-19 patients.

METHODS

The protocol was registered (CRD42021241544). Studies reporting on frailty in COVID-19 patients were eligible. The main outcomes were mortality, length of hospital stay (LOH) and intensive care unit (ICU) admission in frail and non-frail COVID-19 patients. Frailty was also compared in survivors and non-survivors. Five databases were searched up to 24th September 2021. The QUIPS tool was used for the risk of bias assessment. Odds ratios (OR) and weighted mean differences (WMD) were calculated with 95% confidence intervals (CI) using a random effect model. Heterogeneity was assessed using the I² and χ² tests.

RESULTS

From 3640 records identified, 54 were included in the qualitative and 42 in the quantitative synthesis. Clinical Frailty Scale (CFS) was used in 46 studies, the Hospital Frailty Risk Score (HFRS) by 4, the Multidimensional Prognostic Index (MPI) by 3 and three studies used other scores. We found that patients with frailty (CFS 4-9 or HFRS ≥ 5) have a higher risk of mortality (CFS: OR: 3.12; CI 2.56-3.81; HFRS OR: 1.98; CI 1.89-2.07). Patients with frailty (CFS 4-9) were less likely to be admitted to ICU (OR 0.28, CI 0.12-0.64). Quantitative synthesis for LOH was not feasible. Most studies carried a high risk of bias.

CONCLUSIONS

As determined by CFS, frailty is strongly associated with mortality; hence, frailty-based patient management should be included in international COVID-19 treatment guidelines. Future studies investigating the role of frailty assessment on deciding ICU admission are strongly warranted.

The Impact of the Otago Exercise Program on Frailty and Empowerment in Older Nursing Home Residents: A Randomized Controlled Trial

Background

This study assessed the impact of Otago exercises on frailty and empowerment in older nursing home residents.

Methods

This randomized controlled trial included 72 individuals aged over 65 years residing in a single nursing home in Izmir, Turkey. The participants were randomly assigned to the Otago exercise group (OEG) or control group (CG). The OEG performed Otago exercises for 45 minutes, 3 days per week for 12 weeks plus a walking program the 3 other days of the week. In addition to Otago exercise training, the OEG received training based on empowerment consisting of 10 sessions lasting 30 minutes each. The CG received no intervention except routine care in the nursing home. The data collected were sociodemographic characteristics, Edmonton Frail Scale (EFS) scores, and Elderly Empowerment Scale (EES) scores before and 3 months after the intervention.

Results

We observed significant differences between the mean EFS (p=0.0001) and mean EES (p=0.0001) before and 3 months after the intervention in the OEG compared to the CG. We also observed a significant difference between the OEG and CG in mean EFS (p=0.018) and EES (p=0.0001) 3 months after the intervention.

Conclusion

The results of the present study demonstrated the positive impact of the Otago exercise program on preventing/delaying frailty and enhancing empowerment in older people.