Patterns of Comorbidity and In-Hospital Mortality in Older Patients With COVID-19 Infection
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Updated: Oct 18, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
Mona Mahmoud1,2, Luca Carmisciano3, Luca Tagliafico1,2
1Geriatrics Clinic, Department of Internal Medicine and Medical Specialties (DIMI), University of Genoa, Genoa, Italy.
Insights
Older adults with specific chronic conditions, particularly neurocognitive and metabolic-renal-cancer clusters, face higher COVID-19 mortality. Identifying these comorbidity patterns aids early risk assessment and intervention for frail patients.
Area of Science:
- Gerontology and Geriatric Medicine
- Infectious Diseases
- Epidemiology
Background:
- Older adults are disproportionately affected by severe COVID-19 and mortality.
- Multimorbidity and disability are known risk factors, but specific clinical features require identification for prognosis.
Purpose of the Study:
- To identify chronic clinical conditions and comorbidity clusters associated with in-hospital mortality in older COVID-19 patients.
- To aid in accurate prognosis and appropriate care planning for elderly COVID-19 patients.
Main Methods:
- Retrospective cohort study of 219 COVID-19 patients aged 70 years or older.
- Data collected included demographics, chronic medical conditions (multimorbidity), and in-hospital mortality.
- Comorbidity patterns were clustered into 'Metabolic-renal-cancer', 'Neurocognitive', and 'Unspecified' groups.
Main Results:
- In-hospital mortality risk was higher for males, older patients, and those with dementia or cerebrovascular disease.
- The 'Neurocognitive' and 'Metabolic-renal-cancer' comorbidity clusters showed significantly higher mortality.
- These associations were independent of chronological age and sex.
Conclusions:
- Specific comorbidity patterns, particularly neurocognitive and metabolic-renal-cancer clusters, identify older adults at higher risk of COVID-19 death.
- These findings, independent of age, can guide early risk assessment in frail COVID-19 patients.
- Timely interventions based on identified comorbidity clusters may improve prognosis.
Abstract:
Introduction: Older adults are more susceptible to severe COVID-19, with increased all-cause mortality. This has been attributed to their multimorbidity and disability. However, it remains to be established which clinical features of older adults are associated with severe COVID-19 and mortality. This information would aid in an accurate prognosis and appropriate care planning. Here, we aimed to identify the chronic clinical conditions and the comorbidity clusters associated with in-hospital mortality in a cohort of older COVID-19 patients who were admitted to the IRCCS Policlinico San Martino Hospital, Genoa, Italy, between January and April 2020. Methods: This was a retrospective cohort study including 219 consecutive patients aged 70 years or older and is part of the GECOVID-19 study group. During the study period, upon hospital admission, demographic information (age, sex) and underlying chronic medical conditions (multimorbidity) were recorded from the medical records at the time of COVID-19 diagnosis before any antiviral or antibiotic treatment was administered. The primary outcome measure was in-hospital mortality. Results: The vast majority of the patients (90%) were >80 years; the mean patient age was 83 ± 6.2 years, and 57.5% were men. Hypertension and cardiovascular disease, along with dementia, cerebrovascular diseases, and vascular diseases were the most prevalent clinical conditions. Multimorbidity was assessed with the Cumulative Illness Rating Scale. The risk of in-hospital mortality due to COVID-19 was higher for males, for older patients, and for patients with dementia or cerebral-vascular disease. We clustered patients into three groups based on their comorbidity pattern: the Metabolic-renal-cancer cluster, the Neurocognitive cluster and the Unspecified cluster. The Neurocognitive and Metabolic-renal-cancer clusters had a higher mortality compared with the Unspecified cluster, independent of age and sex. Conclusion: We defined patterns of comorbidity that accurately identified older adults who are at higher risk of death from COVID-19. These associations were independent of chronological age, and we suggest that the identification of comorbidity clusters that have a common pathophysiology may aid in the early assessment of COVID-19 patients with frailty to promote timely interventions that, in turn, may result in a significantly improved prognosis.
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