Elderly People with Dementia Admitted for COVID-19: How Different are They?

Roig-Marín, Noel; Roig-Rico, Pablo

doi:10.1080/0361073x.2021.1943794

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…To date, few studies have presented follow-up data on mortality one year after COVID-19 and these have evaluated specific risk factors or specific populations. For example, a recent meta-analysis [42] evaluating all-cause mortality after discharge in patients recovered from COVID-19 only found four studies with one-year follow-up [43][44][45][46]. Pourhoseingholi et al predicted one-year mortality after COVID-19 based on chest computed tomography [44], Roig-Marí n et al evaluated dementia as a risk factor for mortality in elderly patients admitted for COVID-19 [45], Maestre-Muñiz et al described the causes of death per year in a sample of older adults [43], and Chai et al evaluated risk factors related to one-year COVID-19 mortality in patients with cancer [46].…”

Section: Discussionmentioning

confidence: 99%

“…For example, a recent meta-analysis [42] evaluating all-cause mortality after discharge in patients recovered from COVID-19 only found four studies with one-year follow-up [43][44][45][46]. Pourhoseingholi et al predicted one-year mortality after COVID-19 based on chest computed tomography [44], Roig-Marí n et al evaluated dementia as a risk factor for mortality in elderly patients admitted for COVID-19 [45], Maestre-Muñiz et al described the causes of death per year in a sample of older adults [43], and Chai et al evaluated risk factors related to one-year COVID-19 mortality in patients with cancer [46]. Therefore, to our knowledge, our study is the first to evaluate multiple risk factors for mortality one-year after diagnosis of COVID-19 in cases of hospitalization for severe disease.…”

Section: Discussionmentioning

confidence: 99%

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Risk Factors for One-Year Mortality in Hospitalized Adults with Severe COVID-19

López‐Bueno¹,

Torres‐Castro²,

Soto-Carmona³

et al. 2023

Aging and disease

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As the body's immunity declines with age, elderly-hospitalized patients due to COVID-19 might be at higher mortality risk. Therefore, the aim of this prospective study was to examine the possible risk factors (demographic, social or comorbidities) most associated with mortality one-year after diagnosis of COVID-19. Routine data were collected from a cohort of hospitalized adults with severe COVID-19. The primary endpoint was mortality at one-year after diagnosis of COVID-19. We used a Cox proportional hazard model to estimate the hazard ratios (HRs) for both all-cause and specific cardiorespiratory mortality. A fully adjusted model included sex, socioeconomic status, institutionalization status, disability, smoking habit, and comorbidities as confounders. A total of 368 severe cases hospitalized on average 67.3 ± 15.9 years old were included. Participants aged ≥ 71 years had significantly higher HRs for all-cause mortality (adjusted HRs = 2.86, 95%CI: 2.01-4.07) and cardiorespiratory mortality (adjusted HRs = 2.86, 95%CI: 1.99-4.12). The association between age and mortality after diagnosis of COVID-19 due to both all-causes and cardiorespiratory mortality showed a consistent dose-response fashion. Institutionalization, disability, and socioeconomic status also showed a significant association with mortality. In conclusion, aging itself was the most important risk factor associated with mortality one year after diagnosis of COVID-19. People with disabilities, institutionalized or low socioeconomic status are significantly more likely to die after COVID-19.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Risk Factors for One-Year Mortality in Hospitalized Adults with Severe COVID-19

López‐Bueno¹,

Torres‐Castro²,

Soto-Carmona³

et al. 2023

Aging and disease

View full text Add to dashboard Cite

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“…In the present study, the 90-day mortality rate was 49.5%. The post-discharge out-of-hospital mortality among patients with dementia with COVID-19 has been reported to be considerably higher than that among non-dementia patients (15). Patients with dementia are an older, more vulnerable population, having a higher CCI value than elderly patients without dementia (15).…”

Section: % CImentioning

confidence: 99%

“…The post-discharge out-of-hospital mortality among patients with dementia with COVID-19 has been reported to be considerably higher than that among non-dementia patients (15). Patients with dementia are an older, more vulnerable population, having a higher CCI value than elderly patients without dementia (15). As a result, patients with dementia will have a higher mortality rate, despite the fact that the majority did not meet the severity requirements at the time of admission.…”

Section: % CImentioning

confidence: 99%

Predictors of COVID‑19‑associated mortality among hospitalized elderly patients with dementia

et al. 2023

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The mortality of elderly patients with dementia hospitalized with coronavirus disease 2019 (COVID-19)-associated pneumonia is high. The mortality rate of these patients continues to be high following their discharge. However, data on the outcomes of these patients in all phases of the pandemic are limited. The aim of the present study was to examine the clinical characteristics and the in-hospital and 90-day mortality rates of elderly patients with dementia hospitalized due to COVID-19-associated pneumonia during all phases of the pandemic. During the time period between February 15, 2021 to July 15, 2022, 105 elderly patients (≥65 years old) with dementia of various etiologies were hospitalized due to COVID-19-associated pneumonia. The patient characteristics and in-hospital outcomes within 90 days of admission were recorded. The mean age of the patients was 84.03±7.61 years and 60 (57.1%) patients were females. A total of 52 (49.5%) patients were hospitalized during the omicron variant period, 27 (25.7%) were fully vaccinated (three doses) and 38 (36.2%) patients succumbed during their hospitalization. In total, 52 (49.5%) patients succumbed within the first 90 days of admission. According to the univariate regression analysis, the omicron variant [hazard ratio (HR), 2.126; 95% confidence interval (CI), 1.073-4.213; P=0.031] and the absence of full vaccination (HR, 6.231; 95% CI, 1.500-25.87; P=0.012) were associated with a higher in-hospital mortality. In the multivariate regression analysis, only the absence of complete vaccination was an independent predictor of mortality (HR, 5.182; 95% CI, 1.205-22.28; P=0.027). According to the univariate regression analysis, age (HR, 1.045; 95% CI, 1.006-1.085; P=0.023) and the lack of complete vaccination (HR, 3.254; 95% CI,; P=0.012) were associated with 90-day mortality; in addition, by multivariate regression analysis, age (HR, 1.047; 95% CI, 1.007-1.048; P=0.021) and the absence of full vaccination (HR, 3.286; 95% CI, 1.307-8.265; P=0.011) exhibited an independent association with the 90-day mortality rate. Based on the findings presented herein, the in-hospital and 90-day mortality rates of elderly patients with dementia and COVID-19-associated pneumonia is high. An older age and the lack of complete vaccination are independently associated with poor outcomes.

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“…www.nature.com/scientificreports/ Numerous prognostic models have been developed for COVID-19, using both traditional statistics and ML. Blood parameters, like ferritin 22 , troponin, and myoglobin [23][24][25][26] , demographic parameters, including Charlson comorbidity index score 27 , age and gender 28,29 , chest CT images 30 , routine chest X-rays 31 , age-related dementia 32 , cardiac auscultation 33 and other factors are suggested to predict severity or death in patients with COVID-19. However, all these studies were aimed at a single-time assessment of patients' prognosis, close to admission.…”

Section: Discussionmentioning

confidence: 99%

Developing and validating a machine learning prognostic model for alerting to imminent deterioration of hospitalized patients with COVID-19

Kogan

Robinson

Itelman

et al. 2022

Sci Rep

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Our study was aimed at developing and validating a new approach, embodied in a machine learning-based model, for sequentially monitoring hospitalized COVID-19 patients and directing professional attention to patients whose deterioration is imminent. Model development employed real-world patient data (598 prediction events for 210 patients), internal validation (315 prediction events for 97 patients), and external validation (1373 prediction events for 307 patients). Results show significant divergence in longitudinal values of eight routinely collected blood parameters appearing several days before deterioration. Our model uses these signals to predict the personal likelihood of transition from non-severe to severe status within well-specified short time windows. Internal validation of the model's prediction accuracy showed ROC AUC of 0.8 and 0.79 for prediction scopes of 48 or 96 h, respectively; external validation showed ROC AUC of 0.7 and 0.73 for the same prediction scopes. Results indicate the feasibility of predicting the forthcoming deterioration of non-severe COVID-19 patients by eight routinely collected blood parameters, including neutrophil, lymphocyte, monocyte, and platelets counts, neutrophil-to-lymphocyte ratio, CRP, LDH, and D-dimer. A prospective clinical study and an impact assessment will allow implementation of this model in the clinic to improve care, streamline resources and ease hospital burden by timely focusing the medical attention on potentially deteriorating patients.

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Elderly People with Dementia Admitted for COVID-19: How Different are They?

Cited by 13 publications

References 4 publications

Risk Factors for One-Year Mortality in Hospitalized Adults with Severe COVID-19

Risk Factors for One-Year Mortality in Hospitalized Adults with Severe COVID-19

Predictors of COVID‑19‑associated mortality among hospitalized elderly patients with dementia

Developing and validating a machine learning prognostic model for alerting to imminent deterioration of hospitalized patients with COVID-19

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