The Role of Multidimensional Prognostic Index to Identify Hospitalized Older Adults with COVID-19 Who Can Benefit from Remdesivir Treatment: An Observational, Prospective, Multicenter Study.

BACKGROUND: Data regarding the importance of multidimensional frailty to guide clinical decision making for remdesivir use in older patients with coronavirus disease 2019 (COVID-19) are largely unexplored. OBJECTIVE: The aim of this research was to evaluate if the Multidimensional Prognostic Index (MPI), a multidimensional frailty tool based on the Comprehensive Geriatric Assessment (CGA), may help physicians in identifying older hospitalized patients affected by COVID-19 who might benefit from the use of remdesivir. METHODS: This was a multicenter, prospective study of older adults hospitalized for COVID-19 in 10 European hospitals, followed-up for 90 days after hospital discharge. A standardized CGA was performed at hospital admission and the MPI was calculated, with a final score ranging between 0 (lowest mortality risk) and 1 (highest mortality risk). We assessed survival with Cox regression, and the impact of remdesivir on mortality (overall and in hospital) with propensity score analysis, stratified by MPI = 0.50. RESULTS: Among 496 older adults hospitalized for COVID-19 (mean age 80 years, female 59.9%), 140 (28.2% of patients) were treated with remdesivir. During the 90 days of follow-up, 175 deaths were reported, 115 in hospital. Remdesivir treatment significantly reduced the risk of overall mortality (hazard ratio [HR] 0.54, 95% confidence interval CI 0.35-0.83 in the propensity score analysis) in the sample as whole. Stratifying the population, based on MPI score, the effect was observed only in less frail participants (HR 0.47, 95% CI 0.22-0.96 in propensity score analysis), but not in frailer subjects. In-hospital mortality was not influenced by remdesivir use. CONCLUSIONS: MPI could help to identify less frail older adults hospitalized for COVID-19 who could benefit more from remdesivir treatment in terms of long-term survival.

A multidimensional approach to older patients during COVID-19 pandemic: a position paper of the Special Interest Group on Comprehensive Geriatric Assessment of the European Geriatric Medicine Society (EuGMS).

PURPOSE: The COVID-19 pandemic has been a dramatic trigger that has challenged the intrinsic capacity of older adults and of society. Due to the consequences for the older population worldwide, the Special Interest Group on Comprehensive Geriatric Assessment (CGA) of the European Geriatric Medicine Society (EuGMS) took the initiative of collecting evidence on the usefulness of the CGA-based multidimensional approach to older people during the COVID-19 pandemic. METHODS: A narrative review of the most relevant articles published between January 2020 and November 2022 that focused on the multidimensional assessment of older adults during the COVID-19 pandemic. RESULTS: Current evidence supports the critical role of the multidimensional approach to identify older adults hospitalized with COVID-19 at higher risk of longer hospitalization, functional decline, and short-term mortality. This approach appears to also be pivotal for the adequate stratification and management of the post-COVID condition as well as for the adoption of preventive measures (e.g., vaccinations, healthy lifestyle) among non-infected individuals. CONCLUSION: Collecting information on multiple health domains (e.g., functional, cognitive, nutritional, social status, mobility, comorbidities, and polypharmacy) provides a better understanding of the intrinsic capacities and resilience of older adults affected by SARS-CoV-2 infection. The EuGMS SIG on CGA endorses the adoption of the multidimensional approach to guide the clinical management of older adults during the COVID-19 pandemic.

Frailty trajectories in community-dwelling older adults during COVID-19 pandemic: The PRESTIGE study.

BACKGROUND: Frailty has been recognized as potential surrogate of biological age and relevant risk factor for COVID-19 severity. Thus, it is important to explore the frailty trajectories during COVID-19 pandemic and understand how COVID-19 directly and indirectly impacts on frailty condition. METHODS: We enrolled 217 community-dwelling older adults with available information on frailty condition as assessed by multidimensional frailty model both at baseline and at one-year follow-up using Multidimensional Prognostic Index (MPI) tools. Pre-frail/frail subjects were identified at baseline as those with MPI score >0.33 (MPI grades 2-3). Frailty worsening was defined by MPI difference between 12 months follow-up and baseline ≥0.1. Multivariable logistic regression was modelled to identify predictors of worsening of frailty condition. RESULTS: Frailer subjects at baseline (MPI grades 2-3 = 48.4%) were older, more frequently female and had higher rates of hospitalization and Sars-CoV-2 infection compared to robust ones (MPI grade 1). Having MPI grades 2-3 at baseline was associated with higher risk of further worsening of frailty condition (adjusted odd ratio (aOR): 13.60, 95% confidence interval (CI): 4.01-46.09), independently by age, gender and Sars-CoV-2 infection. Specifically, frail subjects without COVID-19 (aOR: 14.84, 95% CI: 4.26-51.74) as well as those with COVID-19 (aOR: 12.77, 95% CI: 2.66-61.40, p = 0.001) had significantly higher risk of worsening of frailty condition. CONCLUSIONS: Effects of COVID-19 pandemic among community-dwelling frailer individuals are far beyond the mere infection and disease, determining a significant deterioration of frailty status both in infected and non-infected subjects.

Can the Multidimensional Prognostic Index Improve the Identification of Older Hospitalized Patients with COVID-19 Likely to Benefit from Mechanical Ventilation? An Observational, Prospective, Multicenter Study.

OBJECTIVE: Data on prognostic tools for indicating mechanical ventilation in older people with COVID-19 are still limited. The aim of this research was to evaluate if the Multidimensional Prognostic Index (MPI), based on the Comprehensive Geriatric Assessment (CGA), may help physicians in identifying older hospitalized patients affected by COVID-19 who might benefit from mechanical ventilation. DESIGN: Longitudinal, multicenter study. SETTINGS AND PARTICIPANTS: 502 older people hospitalized for COVID-19 in 10 European hospitals. METHODS: MPI was calculated using 8 different domains typical of the CGA. A propensity score, Cox's regression analysis was used for assessing the impact of mechanical ventilation on rehospitalization/mortality for 90 days' follow-up, stratified by MPI = 0.50. The accuracy of MPI in predicting negative outcomes (ie, rehospitalization/mortality) was assessed using the area under the curve (AUC), and the discrimination with several indexes like the Net Reclassification Improvement (NRI) and the Integrated Discrimination Improvement (IDI). RESULTS: Among 502 older people hospitalized for COVID-19 (mean age: 80 years), 152 were treated with mechanical ventilation. In the propensity score analysis, during the 90-day follow-up period, there were 44 rehospitalizations and 95 deaths. Mechanical ventilation in patients with MPI values ≥ 0.50, indicating frailer participants, was associated with a higher risk of rehospitalization/mortality (hazard ratio 1.56, 95% CI 1.09-2.23), whereas in participants with MPI values < 0.50 this association was not significant. The accuracy of the model including age, sex, respiratory parameters, and MPI was good (AUC = 0.783) as confirmed by an NRI of 0.2756 (P < .001) and an IDI of 0.1858 (P < .001), suggesting a good discrimination of the model in predicting negative outcomes. CONCLUSIONS AND IMPLICATIONS: MPI could be useful for better individualizing older people hospitalized by COVID-19 who could benefit from mechanical ventilation.

Multidimensional Prognostic Index and Mortality in Intermediate Care Facilities: A Retrospective Study.

Multidimensional prognostic index (MPI) is a frailty assessment tool used for stratifying prognosis in older hospitalized people, but data regarding older people admitted to intermediate care facilities (ICFs) are missing. The aim of this study is to evaluate whether MPI can predict mortality in older patients admitted to the ICFs. MPI was calculated using different domains explored by a standard comprehensive geriatric assessment and categorized into tertiles (MPI-1 ≤ 0.20, MPI-2 0.20-0.34, MPI-3 > 0.34). A Cox's regression analysis, taking mortality as the outcome, was used, reporting the results as hazard ratios (HRs) with 95% confidence intervals (CIs). In total, 653 older patients were enrolled (mean age: 82 years, 59.1% females). Patients in MPI-2 (HR = 3.66; 95%CI: 2.45-5.47) and MPI-3 (HR = 6.22; 95%CI: 4.22-9.16) experienced a higher risk of mortality, compared to MPI-1. The accuracy of MPI in predicting mortality was good (area under the curve (AUC) = 0.74, 95%CI: 0.70-0.78). In conclusion, our study showed that prognostic stratification, as assessed by the MPI, was associated with a significantly different risk of mortality in older patients admitted to the ICFs, indicating the necessity of using a CGA-based tool for better managing older people in this setting as well.

Validation and implementation of telephone-administered version of the Multidimensional Prognostic Index (TELE-MPI) for remote monitoring of community-dwelling older adults.

BACKGROUND: During the recent lockdown measures adopted by national authorities to contain the COVID-19 pandemic, many vulnerable older patients with chronic conditions, normally followed in ambulatory setting, needed to be monitored and managed in alternative ways, including telemedicine. AIMS: In the framework of a telemedicine program, we aimed to validate and implement a telephone-administered version of the Multidimensional Prognostic Index (TELE-MPI) among community-dwelling older outpatients. METHOD: From March 9 to May 11, 2020, 131 older patients (82.1 years; 74% females) were interviewed using a telephone-based survey to calculate the TELE-MPI. The standard MPI was performed face-to-face three months apart. The Bland-Altman methodology measured the agreement between the two tools. Multivariate logistic regression models were built to ascertain the prognostic value of TELE-MPI and TELE-MPI classes (low, moderate, or severe risk) on negative outcomes occurring during the lockdown period. RESULTS: Mean MPI and TELE-MPI values were 0.523 and 0.522, respectively. Lower and upper 95% limits of agreement were - 0.122 and + 0.124, respectively, with only 4.6% of observations outside the limits. Each 0.1 increase of TELE-MPI score was significantly correlated with higher incidence of psychiatric disorders [odd ratio (OR): 1.57; 95% confidence interval (CI) 1.27, 1.95] and falls (OR: 1.41; 95% CI 1.08, 1.82) in community-dwelling-older adults. DISCUSSION: TELE-MPI showed a strong agreement with the standard MPI and was able to predict psychiatric disorders and falls during lockdown period. CONCLUSION: TELE-MPI may represent a useful way to follow by remote the health status of older adults.

Mortality attributable to COVID-19 in nursing home residents: a retrospective study.

AIM: Coronavirus-19 disease (COVID-19) is a widespread condition in nursing home (NH). It is not known whether COVID-19 is associated with a higher risk of death than residents without COVID-19. Therefore, the aim of this study was to assess whether COVID-19 is associated with a higher mortality rate in NH residents, considering frailty status assessed with the Multidimensional Prognostic Index (MPI). METHODS: In this retrospective study, made in 31 NHs in Venice, Italy, the presence of COVID-19 was ascertained with a nasopharyngeal swab. Frailty was evaluated using the MPI, modified according to the tools commonly used in our NHs. A Cox's regression analysis was used reporting the results as hazard ratios (HRs) with 95% confidence intervals (CIs), using COVID-19 as exposure and mortality as outcome and stratified by MPI tertiles. Similar analyses were run using MPI tertiles as exposure. RESULTS: Overall, 3946 NH residents (median age = 87 years, females: 73.9%) were eligible, with 1136 COVID-19 + . During a median follow-up of 275 days, higher values of MPI, indicating frailer people, were associated with an increased risk of mortality. The incidence of mortality in COVID-19 + was more than doubled than COVID-19- either in MPI-1, MPI-2 and MPI-3 groups. The presence of COVID-19 increased the risk of death (HR = 1.85; 95% CI 1.59-2.15), also in the propensity score model using MPI as confounder (HR = 2.48; 95% CI 2.10-2.93). CONCLUSION: In this retrospective study of NH residents, COVID-19 was associated with a higher risk of all-cause mortality than those not affected by COVID-19 also considering the different grades of frailty.

The multidimensional prognostic index (MPI) for the prognostic stratification of older inpatients with COVID-19: A multicenter prospective observational cohort study.

BACKGROUND: The topic of prognosis in COVID-19 research may be important in adopting appropriate clinical decisions. Multidimensional prognostic index (MPI) is a frailty assessment tool widely used for stratifying prognosis in older people, but data regarding inpatients, affected by COVID-19, are not available. OBJECTIVES: To evaluate whether MPI can predict in-hospital mortality and the admission to intensive care unit (ICU) in older inpatients hospitalized for COVID-19 infection. METHODS: In this longitudinal, Italian, multi-center study, older patients with COVID-19 were included. MPI was calculated using eight different domains typical of comprehensive geriatric assessment and categorized in three groups (MPI 1 ≤ 0.33, MPI 2 0.34-0.66, MPI 3 > 0.66). A multivariable Cox's regression analysis was used reporting the results as hazard ratios (HRs) with 95% confidence intervals (CIs). RESULTS: 227 older patients hospitalized for SARS-CoV-2 infection were enrolled (mean age: 80.5 years, 59% females). Inpatients in the MPI 3 were subjected less frequently than those in the MPI 1 to non-invasive ventilation (NIV). In the multivariable analysis, people in MPI 3 experienced a higher risk of in hospital mortality (HR = 6.30, 95%CI: 1.44-27.61), compared to MPI 1. The accuracy of MPI in predicting in hospital mortality was good (Area Under the Curve (AUC) = 0.76, 95%CI: 0.68-0.83). People in MPI 3 experienced a significant longer length of stay (LOS) in hospital compared to other participants. No association between MPI and ICU admission was found. CONCLUSIONS: Frailty- as assessed by high MPI score - was associated with a significant higher risk of in-hospital mortality, longer LOS, and lower use NIV, whilst the association with ICU admission was not significant. These findings suggest that prognostic stratification by using the MPI could be useful in clinical decision making in older inpatients affected by COVID-19.

Evaluation of novel coronavirus disease (COVID-19) using quantitative lung CT and clinical data: prediction of short-term outcome.

BACKGROUND: Computed tomography (CT) enables quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, helping in outcome prediction. METHODS: From 1 to 22 March 2020, patients with pneumonia symptoms, positive lung CT scan, and confirmed SARS-CoV-2 on reverse transcription-polymerase chain reaction (RT-PCR) were consecutively enrolled. Clinical data was collected. Outcome was defined as favourable or adverse (i.e., need for mechanical ventilation or death) and registered over a period of 10 days following CT. Volume of disease (VoD) on CT was calculated semi-automatically. Multiple linear regression was used to predict VoD by clinical/laboratory data. To predict outcome, important features were selected using a priori analysis and subsequently used to train 4 different models. RESULTS: A total of 106 consecutive patients were enrolled (median age 63.5 years, range 26-95 years; 41/106 women, 38.7%). Median duration of symptoms and C-reactive protein (CRP) was 5 days (range 1-30) and 4.94 mg/L (range 0.1-28.3), respectively. Median VoD was 249.5 cm3 (range 9.9-1505) and was predicted by lymphocyte percentage (p = 0.008) and CRP (p < 0.001). Important variables for outcome prediction included CRP (area under the curve [AUC] 0.77), VoD (AUC 0.75), age (AUC 0.72), lymphocyte percentage (AUC 0.70), coronary calcification (AUC 0.68), and presence of comorbidities (AUC 0.66). Support vector machine had the best performance in outcome prediction, yielding an AUC of 0.92. CONCLUSIONS: Measuring the VoD using a simple CT post-processing tool estimates SARS-CoV-2 burden. CT and clinical data together enable accurate prediction of short-term clinical outcome.