Dataset Information

Epilepsy and the risk of severe coronavirus disease 2019 outcomes: A systematic review, meta-analysis, and meta-regression.

ABSTRACT:

Background

Patients with epilepsy experience seizures, which have been reported to increase and worsen during the coronavirus disease (COVID-19) pandemic. However, the association between epilepsy and COVID-19 outcomes remains unclear. The aim of this study was to analyze whether patients with epilepsy have an increased risk of having poor COVID-19 outcomes.

Methods

We comprehensively evaluated potential articles extracted from the medRxiv, Europe PMC, and PubMed databases until June 30, 2021, using selected keywords. All published studies on epilepsy and COVID-19 were selected. We used the Review Manager 5.4 and Comprehensive Meta-Analysis 3 software for statistical analysis.

Results

Thirteen studies with 67,131 patients with COVID-19 were included in the analysis. Evaluation of the collated data revealed an association between epilepsy and increased severity of COVID-19 (OR, 1.69; 95%CI: 1.11-2.59; p = 0.010; I² = 29%; random-effect modeling) and mortality from COVID-19 (OR, 1.71; 95%CI: 1.14-2.56; p = 0.010; I² = 53%; random-effect modeling). The results also showed that the association between epilepsy and increased risk of developing severe COVID-19 is influenced by sex and neurodegenerative disease.

Conclusions

The findings of this study suggest that patients with epilepsy are at risk of having poor COVID-19 outcomes. Patients with epilepsy need special attention and should be prioritized for administration of the COVID-19 vaccine. Registration details: PROSPERO (CRD42021264979).

SUBMITTER: Siahaan YMT

PROVIDER: S-EPMC8590948 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Epilepsy and the risk of severe coronavirus disease 2019 outcomes: A systematic review, meta-analysis, and meta-regression.

Siahaan Yusak Mangara Tua YMT Ketaren Retno Jayantri RJ Hartoyo Vinson V Hariyanto Timotius Ivan TI

Epilepsy & behavior : E&B 20211115

<h4>Background</h4>Patients with epilepsy experience seizures, which have been reported to increase and worsen during the coronavirus disease (COVID-19) pandemic. However, the association between epilepsy and COVID-19 outcomes remains unclear. The aim of this study was to analyze whether patients with epilepsy have an increased risk of having poor COVID-19 outcomes.<h4>Methods</h4>We comprehensively evaluated potential articles extracted from the medRxiv, Europe PMC, and PubMed databases until J ...[more]

PMID: 34839246

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Project description:ObjectivesExisting findings regarding the relationship between comorbidities and the severity of coronavirus disease 2019 (COVID-19) are inconsistent and insufficient. The aim of this study was to evaluate the association between different comorbidities and the severity of COVID-19.MethodsThe PubMed, Embase, and Cochrane Library databases were searched to identify studies reporting the rates of comorbidities in COVID-19 patients with severe/fatal outcomes. Subgroup analyses were conducted according to disease severity and the country of residence. Odds ratios (OR) with 95% confidence intervals (CI) were pooled using random-effects models.ResultsA total of 34 eligible studies were identified. In patients with severe/fatal COVID-19, the most prevalent chronic comorbidities were obesity (42%, 95% CI 34-49%) and hypertension (40%, 95% CI 35-45%), followed by diabetes (17%, 95% CI 15-20%), cardiovascular disease (13%, 95% CI 11-15%), respiratory disease (8%, 95% CI 6-10%), cerebrovascular disease (6%, 95% CI 4-8%), malignancy (4%, 95% CI 3-6%), kidney disease (3%, 95% CI 2-4%), and liver disease (2%, 95% CI 1-3%). In order of the prediction, the pooled ORs of the comorbidities in patients with severe or fatal COVID-19 when compared to patients with non-severe/fatal COVID-19 were as follows: chronic respiratory disease, OR 3.56 (95% CI 2.87-4.41); hypertension, OR 3.17 (95% CI 2.46-4.08); cardiovascular disease, OR 3.13 (95% CI 2.65-3.70); kidney disease, OR 3.02 (95% CI 2.23-4.08); cerebrovascular disease, OR 2.74 (95% CI 1.59-4.74); malignancy, OR 2.73 (95% CI 1.73-4.21); diabetes, OR 2.63 (95% CI 2.08-3.33); and obesity, OR 1.72 (95% CI 1.04-2.85). No correlation was observed between liver disease and COVID-19 aggravation (OR 1.54, 95% CI 0.95-2.49).ConclusionsChronic comorbidities, including obesity, hypertension, diabetes, cardiovascular disease, cerebrovascular disease, respiratory disease, kidney disease, and malignancy are clinical risk factors for a severe or fatal outcome associated with COVID-19, with obesity being the most prevalent and respiratory disease being the most strongly predictive. Knowledge of these risk factors could help clinicians better identify and manage the high-risk populations.

Project description:Objective:Clinical and laboratory biomarkers to predict the severity of coronavirus disease 2019 (COVID-19) are essential in this pandemic situation of which resource allocation must be urgently prepared especially in the context of respiratory support readiness. Lymphocyte count has been a marker of interest since the first COVID-19 publication. We conducted a systematic review and meta-analysis in order to investigate the association of lymphocyte count on admission and the severity of COVID-19. We would also like to analyze whether patient characteristics such as age and comorbidities affect the relationship between lymphocyte count and COVID-19. Methods:Comprehensive and systematic literature search was performed from PubMed, SCOPUS, EuropePMC, ProQuest, Cochrane Central Databases, and Google Scholar. Research articles in adult patients diagnosed with COVID-19 with information on lymphocyte count and several outcomes of interest, including mortality, acute respiratory distress syndrome (ARDS), intensive care unit (ICU) care, and severe COVID-19, were included in the analysis. Inverse variance method was used to obtain mean differences and its standard deviations. Maentel-Haenszel formula was used to calculate dichotomous variables to obtain odds ratios (ORs) along with its 95% confidence intervals. Random-effect models were used for meta-analysis regardless of heterogeneity. Restricted-maximum likelihood random-effects meta-regression was performed for age, gender, cardiac comorbidity, hypertension, diabetes mellitus, COPD, and smoking. Results:There were a total of 3099 patients from 24 studies. Meta-analysis showed that patients with poor outcome have a lower lymphocyte count (mean difference - 361.06 μL [- 439.18, - 282.95], p < 0.001; I 2 84%) compared to those with good outcome. Subgroup analysis showed lower lymphocyte count in patients who died (mean difference - 395.35 μL [- 165.64, - 625.07], p < 0.001; I 2 87%), experienced ARDS (mean difference - 377.56 μL [- 271.89, - 483.22], p < 0.001; I 2 0%), received ICU care (mean difference - 376.53 μL [- 682.84, - 70.22], p = 0.02; I 2 89%), and have severe COVID-19 (mean difference - 353.34 μL [- 250.94, - 455.73], p < 0.001; I 2 85%). Lymphopenia was associated with severe COVID-19 (OR 3.70 [2.44, 5.63], p < 0.001; I 2 40%). Meta-regression showed that the association between lymphocyte count and composite poor outcome was affected by age (p = 0.034). Conclusion:This meta-analysis showed that lymphopenia on admission was associated with poor outcome in patients with COVID-19.

Project description:Introduction: The quantitative effect of underlying non-communicable diseases on acute kidney injury (AKI) incidence and the factors affecting the odds of death among coronavirus disease 2019 (COVID-19) AKI patients were unclear at population level. This study aimed to assess the association between AKI, mortality, underlying non-communicable diseases, and clinical risk factors. Methods: A systematic search of six databases was performed from January 1, 2020, until October 5, 2020. Peer-reviewed observational studies containing quantitative data on risk factors and incidence of renal manifestations of COVID-19 were included. Location, institution, and time period were matched to avoid duplicated data source. Incidence, prevalence, and odds ratio of outcomes were extracted and pooled by random-effects meta-analysis. History of renal replacement therapy (RRT) and age group were stratified for analysis. Univariable meta-regression models were built using AKI incidence as dependent variable, with underlying comorbidities and clinical presentations at admission as independent variables. Results: Global incidence rates of AKI and RRT in COVID-19 patients were 20.40% [95% confidence interval (CI) = 12.07-28.74] and 2.97% (95% CI = 1.91-4.04), respectively, among patients without RRT history. Patients who developed AKI during hospitalization were associated with 8 times (pooled OR = 9.03, 95% CI = 5.45-14.94) and 16.6 times (pooled OR = 17.58, 95% CI = 10.51-29.38) increased odds of death or being critical. At population level, each percentage increase in the underlying prevalence of diabetes, hypertension, chronic kidney disease, and tumor history was associated with 0.82% (95% CI = 0.40-1.24), 0.48% (95% CI = 0.18-0.78), 0.99% (95% CI = 0.18-1.79), and 2.85% (95% CI = 0.93-4.76) increased incidence of AKI across different settings, respectively. Although patients who had a kidney transplant presented with a higher incidence of AKI and RRT, their odds of mortality was lower. A positive trend of increased odds of death among AKI patients against the interval between symptom onset and hospital admission was observed. Conclusion: Underlying prevalence of non-communicable diseases partly explained the heterogeneity in the AKI incidence at population level. Delay in admission after symptom onset could be associated with higher mortality among patients who developed AKI and warrants further research.

Dataset Information

Epilepsy and the risk of severe coronavirus disease 2019 outcomes: A systematic review, meta-analysis, and meta-regression.

Background

Methods

Results

Conclusions

Publications

Epilepsy and the risk of severe coronavirus disease 2019 outcomes: A systematic review, meta-analysis, and meta-regression.

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