Delirium in Older Patients With COVID-19: Prevalence, Risk Factors, and Clinical Relevance.

BACKGROUND: Delirium prevalence increases with age and is associated with poor outcomes. We aimed to investigate the prevalence and risk factors for delirium in older patients hospitalized with COVID-19, as well as its association with length of stay and mortality. METHOD: This was a retrospective study of patients aged 65 years and older hospitalized with COVID-19. Data were collected from computerized medical records and all patients had delirium assessment at admission. Risk factors for delirium as well as the outcomes mentioned above were studied by 2-group comparison, logistic regression, and Cox proportional hazard models. RESULTS: Of a total of 235 Caucasian patients, 48 (20.4%) presented with delirium, which was hypoactive in 41.6% of cases, and hyperactive and mixed in 35.4% and 23.0%, respectively. Patients with cognitive impairment had a nearly 4 times higher risk of developing delirium compared to patients who were cognitively normal before SARS-CoV-2 infection (odds ratio 3.7; 95% CI: 1.7-7.9, p = .001). The presence of delirium did not modify the time from symptoms' onset to hospitalization or the length of stay in acute care, but it was associated with an increased risk of dying (hazard ratio 2.1; 95% CI: 1.2-3.7, p = .0113). CONCLUSION: Delirium was a prevalent condition in older people admitted with COVID-19 and preexisting cognitive impairment was its main risk factor. Delirium was associated with higher in-hospital mortality. These results highlight the importance of early recognition of delirium especially when premorbid cognitive comorbidities are present.

Predictors of In-Hospital Mortality in Older Patients With COVID-19: The COVIDAge Study.

OBJECTIVE: To determine predictors of in-hospital mortality related to COVID-19 in older patients. DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: Patients aged 65 years and older hospitalized for a diagnosis of COVID-19. METHODS: Data from hospital admission were collected from the electronic medical records. Logistic regression and Cox proportional hazard models were used to predict mortality, our primary outcome. Variables at hospital admission were categorized according to the following domains: demographics, clinical history, comorbidities, previous treatment, clinical status, vital signs, clinical scales and scores, routine laboratory analysis, and imaging results. RESULTS: Of a total of 235 Caucasian patients, 43% were male, with a mean age of 86 ± 6.5 years. Seventy-six patients (32%) died. Nonsurvivors had a shorter number of days from initial symptoms to hospitalization (P = .007) and the length of stay in acute wards than survivors (P < .001). Similarly, they had a higher prevalence of heart failure (P = .044), peripheral artery disease (P = .009), crackles at clinical status (P < .001), respiratory rate (P = .005), oxygen support needs (P < .001), C-reactive protein (P < .001), bilateral and peripheral infiltrates on chest radiographs (P = .001), and a lower prevalence of headache (P = .009). Furthermore, nonsurvivors were more often frail (P < .001), with worse functional status (P < .001), higher comorbidity burden (P < .001), and delirium at admission (P = .007). A multivariable Cox model showed that male sex (HR 4.00, 95% CI 2.08-7.71, P < .001), increased fraction of inspired oxygen (HR 1.06, 95% CI 1.03-1.09, P < .001), and crackles (HR 2.42, 95% CI 1.15-6.06, P = .019) were the best predictors of mortality, while better functional status was protective (HR 0.98, 95% CI 0.97-0.99, P = .001). CONCLUSIONS AND IMPLICATIONS: In older patients hospitalized for COVID-19, male sex, crackles, a higher fraction of inspired oxygen, and functionality were independent risk factors of mortality. These routine parameters, and not differences in age, should be used to evaluate prognosis in older patients.