Neurological comorbidities and COVID-19-related case fatality: A cohort study

Romagnolo, Alberto; Imbalzano, Gabriele; Artusi, Carlo Alberto; Balestrino, Roberta; Ledda, Claudia; Rosa, Francesco Giuseppe De; Riccardini, Franco; Montanaro, Elisa; Bozzali, Marco; Rizzone, Mario Giorgio; Zibetti, Maurizio; Lopiano, Leonardo

doi:10.1016/j.jns.2021.117610

Cited by 10 publications

(8 citation statements)

References 31 publications

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“…Consistently with other reports, we found a COVID-19-associated crude case fatality rate of 31%, with a more than double risk of dying in dementia patients compared to the general population of the same age and gender [38,39]. Our analysis revealed a strong association between presence of symptoms at…”

supporting

confidence: 92%

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

Cascini¹,

Agabiti²,

Marino³

et al. 2022

JAD

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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.

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supporting

confidence: 92%

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

Cascini¹,

Agabiti²,

Marino³

et al. 2022

JAD

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“…Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been linked to abnormalities in the central nervous system such as the loss of smell and taste, cognitive decline, delirium, cerebrovascular accidents, neuronal autoimmune illnesses, and psychiatric disorders [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. However, the heterogeneity of symptoms remains puzzling [ 1 , 3 , 7 , 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, the heterogeneity of symptoms remains puzzling [ 1 , 3 , 7 , 8 , 9 , 10 ]. The development of these abnormalities often occurs within two days from the onset of symptoms [ 1 , 5 , 7 , 11 , 12 ]. In addition, an increasing number of survivors suffer from long-term neurological sequela [ 13 , 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Changes in Central and Peripheral Neuro-Injury vs. Neuroprotective Serum Markers in COVID-19 Are Modulated by Different Types of Anti-Viral Treatments but Do Not Affect the Incidence of Late and Early Strokes

et al. 2021

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The balance between neurodegeneration, neuroinflammation, neuroprotection, and COVID-19-directed therapy may underly the heterogeneity of SARS-CoV-2′s neurological outcomes. A total of 105 patients hospitalized with a diagnosis of COVID-19 had serum collected over a 6 month period to assess neuroinflammatory (MIF, CCL23, MCP-1), neuro-injury (NFL, NCAM-1), neurodegenerative (KLK6, τ, phospho τ, amyloids, TDP43, YKL40), and neuroprotective (clusterin, fetuin, TREM-2) proteins. These were compared to markers of nonspecific inflammatory responses (IL-6, D-dimer, CRP) and of the overall viral burden (spike protein). Data regarding treatment (steroids, convalescent plasma, remdasavir), pre-existing conditions, and incidences of strokes were collected. Amyloid β42, TDP43, NF-L, and KLK6 serum levels declined 2–3 days post-admission, yet recovered to admission baseline levels by 7 days. YKL-40 and NCAM-1 levels remained elevated over time, with clusters of differential responses identified among TREM-2, TDP43, and YKL40. Fetuin was elevated after the onset of COVID-19 while TREM-2 initially declined before significantly increasing over time. MIF serum level was increased 3–7 days after admission. Ferritin correlated with TDP-43 and KLK6. No treatment with remdesivir coincided with elevations in Amyloid-β40. A lack of convalescent plasma resulted in increased NCAM-1 and total tau, and steroidal treatments did not significantly affect any markers. A total of 11 incidences of stroke were registered up to six months after initial admission for COVID-19. Elevated D-dimer, platelet counts, IL-6, and leukopenia were observed. Variable MIF serum levels differentiated patients with CVA from those who did not have a stroke during the acute phase of COVID-19. This study demonstrated concomitant and opposite changes in neurodegenerative and neuroprotective markers persisting well into recovery.

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“…These results are also consistent with a recent study by Romagnolo et al, who stated that cerebrovascular disease and cognitive impairment are determinants of COVID-19 severity [ 36 ]. Another article by the same authors demonstrated that chronic neurological conditions, especially neurodegenerative diseases, increase lethality in COVID-19 cases [ 55 ]. In addition, Du et al reported a 2.4-fold increase in mortality risk in patients with cerebrovascular or cardiovascular disease, although they did not specify the distinction between these two conditions [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units

Chacón

García

Hernández

et al. 2022

Behavioral Sciences

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Purpose: To identify clinical phenotypes and biomarkers for best mortality prediction considering age, symptoms and comorbidities in COVID-19 patients with chronic neurological diseases in intensive care units (ICUs). Subjects and Methods: Data included 1252 COVID-19 patients admitted to ICUs in Cuba between January and August 2021. A k-means algorithm based on unsupervised learning was used to identify clinical patterns related to symptoms, comorbidities and age. The Stable Sparse Classifiers procedure (SSC) was employed for predicting mortality. The classification performance was assessed using the area under the receiver operating curve (AUC). Results: Six phenotypes using a modified v-fold cross validation for the k-means algorithm were identified: phenotype class 1, mean age 72.3 years (ys)—hypertension and coronary artery disease, alongside typical COVID-19 symptoms; class 2, mean age 63 ys—asthma, cough and fever; class 3, mean age 74.5 ys—hypertension, diabetes and cough; class 4, mean age 67.8 ys—hypertension and no symptoms; class 5, mean age 53 ys—cough and no comorbidities; class 6, mean age 60 ys—without symptoms or comorbidities. The chronic neurological disease (CND) percentage was distributed in the six phenotypes, predominantly in phenotypes of classes 3 (24.72%) and 4 (35,39%); χ² (5) 11.0129 p = 0.051134. The cerebrovascular disease was concentrated in classes 3 and 4; χ² (5) = 36.63, p = 0.000001. The mortality rate totaled 325 (25.79%), of which 56 (17.23%) had chronic neurological diseases. The highest in-hospital mortality rates were found in phenotypes 1 (37.22%) and 3 (33.98%). The SSC revealed that a neurological symptom (ageusia), together with two neurological diseases (cerebrovascular disease and Parkinson’s disease), and in addition to ICU days, age and specific symptoms (fever, cough, dyspnea and chilliness) as well as particular comorbidities (hypertension, diabetes and asthma) indicated the best prediction performance (AUC = 0.67). Conclusions: The identification of clinical phenotypes and mortality biomarkers using practical variables and robust statistical methodologies make several noteworthy contributions to basic and experimental investigations for distinguishing the COVID-19 clinical spectrum and predicting mortality.

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Neurological comorbidities and COVID-19-related case fatality: A cohort study

Cited by 10 publications

References 31 publications

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

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

Dynamic Changes in Central and Peripheral Neuro-Injury vs. Neuroprotective Serum Markers in COVID-19 Are Modulated by Different Types of Anti-Viral Treatments but Do Not Affect the Incidence of Late and Early Strokes

Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units

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