Dataset Information

Prevalence of Headache in Patients With Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Analysis of 14,275 Patients.

ABSTRACT: Background: Coronavirus disease 2019 (COVID-19) started to spread globally since December 2019 from Wuhan, China. Headache has been observed as one of the clinical manifestations in COVID-19 patients. We aimed to conduct a comprehensive systematic review and meta-analysis to estimate the overall pooled prevalence of headache in COVID-19 patients. Methods: PubMed, Scopus, ScienceDirect, and Google Scholar databases were searched to identify studies published between December 2019 and March 2020. Adult (?18 years) COVID-19 patients were considered eligible. We used random-effects model to estimate the pooled prevalence with 95% confidence intervals (CIs). Quality assessment was done using the Joanna Briggs Institute critical appraisal tools. This study is registered with PROSPERO (CRD42020182529). Results: We identified 2,055 studies, of which 86 studies (n = 14,275, 49.4% female) were included in the meta-analysis. Overall, the pooled prevalence of headache in COVID-19 patients was 10.1% [95% CI: 8.76-11.49]. There was no significant difference of headache prevalence in severe or critical vs. non-severe (RR: 1.05, p = 0.78), survived (recovered or discharged) vs. non-survived (RR: 1.36, p = 0.23), and ICU vs. non-ICU (RR: 1.06, p = 0.87) COVID-19 patients. We detected 64.0, 34.9, and 1.1% of the included studies as high, moderate, and low quality, respectively. Conclusions: From the first 4-month data of the outbreak, headache was detected in 10.1% of the adult COVID-19 patients.

SUBMITTER: Islam MA

PROVIDER: S-EPMC7728918 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prevalence of Headache in Patients With Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Analysis of 14,275 Patients.

Islam Md Asiful MA Alam Sayeda Sadia SS Kundu Shoumik S Hossan Tareq T Kamal Mohammad Amjad MA Cavestro Cinzia C

Frontiers in neurology 20201127

<b>Background:</b> Coronavirus disease 2019 (COVID-19) started to spread globally since December 2019 from Wuhan, China. Headache has been observed as one of the clinical manifestations in COVID-19 patients. We aimed to conduct a comprehensive systematic review and meta-analysis to estimate the overall pooled prevalence of headache in COVID-19 patients. <b>Methods:</b> PubMed, Scopus, ScienceDirect, and Google Scholar databases were searched to identify studies published between December 2019 an ...[more]

PMID: 33329305

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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:Importance: Coronavirus disease 2019 (COVID-19) is a newly emerging infectious disease that has caused a global pandemic. The presenting symptoms are mainly respiratory symptom, yet studies have reported nervous system involvement in the disease. A systematic review and meta-analysis of these studies are required to understanding the neurologic characteristic of the disease and help physicians with early diagnosis and management. Objective: To conduct a systematic review and meta-analysis on the neurologic characteristics in patients with COVID-19. Evidence Review: Authors conducted a literature search through PubMed from January 1st, 2020 to April 8th, 2020. Furthermore, the authors added additional sources by reviewing related references. Studies presenting the neurologic features of COVID-19 patients in their data were included. Case reports and case series were also included in this review. The quality of the studies was assessed based on the Oxford Center for Evidence-Based Medicine guidelines. Selected studies were included in the meta-analysis of proportion and the heterogeneity test. Finding: From 280 identified studies, 33 were eligible, with 7,559 participants included. Most of the included studies were from China (29 [88%]). Muscle injury or myalgia was the most common (19.2%, 95%CI 15.4-23.2%) neurologic symptom of COVID-19, followed by headache (10.9%, 95%CI 8.62-13.51%); dizziness (8.7%, 95%CI 5.02-13.43%); nausea with or without vomiting (4.6%, 95%CI 3.17-6.27%); concurrent cerebrovascular disease (4.4%, 95%CI 1.92-7.91%); and impaired consciousness (3.8%, 95%CI 0.16-12.04%). Underlying cerebrovascular disease was found in 8.5% (95%CI 4.5-13.5%) of the studies. Conclusion: Neurologic findings vary from non-specific to specific symptoms in COVID-19 patients. Some severe symptoms or diseases can present in the later stage of the disease. Physicians should be aware of the presence of neurologic signs and symptoms as a chief complaint of COVID-19, in order to improve management and prevent a worsening outcome of the patients.

Project description:BackgroundCoronavirus disease 2019 (COVID-19), a pandemic disease caused by the severe acute respiratory syndrome coronavirus 2 started to spread globally since December 2019 from Wuhan, China. Fever has been observed as one of the most common clinical manifestations, although the prevalence and characteristics of fever in adult and paediatric COVID-19 patients is inconclusive. We aimed to conduct a systematic review and meta-analysis to estimate the overall pooled prevalence of fever and chills in addition to fever characteristics (low, medium, and high temperature) in both adult and paediatric COVID-19 patients.MethodsThe protocol of this systematic review and meta-analysis was registered with PROSPERO (CRD42020176327). PubMed, Scopus, ScienceDirect and Google Scholar databases were searched between 1st December 2019 and 3rd April 2020 without language restrictions. Both adult (≥18 years) and paediatric (<18 years) COVID-19 patients were considered eligible. We used random-effects model for the meta-analysis to obtain the pooled prevalence and risk ratio (RR) with 95% confidence intervals (CIs). Quality assessment of included studies was performed using the Joanna Briggs Institute critical appraisal tools. Heterogeneity was assessed using the I² statistic and Cochran's Q test. Robustness of the pooled estimates was checked by different subgroups and sensitivity analyses.ResultsWe identified 2055 studies, of which 197 studies (n = 24266) were included in the systematic review and 167 studies with 17142 adults and 373 paediatrics were included in the meta-analysis. Overall, the pooled prevalence of fever in adult and paediatric COVID-19 patients were 79.43% [95% CI: 77.05-81.80, I2 = 95%] and 45.86% [95% CI: 35.24-56.48, I2 = 78%], respectively. Besides, 14.45% [95% CI: 10.59-18.32, I2 = 88%] of the adult COVID-19 patients were accompanied with chills. In adult COVID-19 patients, the prevalence of medium-grade fever (44.33%) was higher compared to low- (38.16%) and high-grade fever (14.71%). In addition, the risk of both low (RR: 2.34, 95% CI: 1.69-3.22, p<0.00001, I2 = 84%) and medium grade fever (RR: 2.79, 95% CI: 2.21-3.51, p<0.00001, I2 = 75%) were significantly higher compared to high-grade fever, however, there was no significant difference between low- and medium-grade fever (RR: 1.17, 95% CI: 0.94-1.44, p = 0.16, I2 = 87%). 88.8% of the included studies were of high-quality. The sensitivity analyses indicated that our findings of fever prevalence for both adult and paediatric patients are reliable and robust.ConclusionsThe prevalence of fever in adult COVID-19 patients was high, however, 54.14% of paediatric COVID-19 patients did not exhibit fever as an initial clinical feature. Prevalence and risk of low and medium-grade fevers were higher compared to high-grade fever.

Project description:BackgroundCoronavirus disease-2019 (COVID-19) is a global pandemic and high mortality rate among severe or critical COVID-19 is linked with SARS-CoV-2 infection-induced hyperinflammation of the innate and adaptive immune systems and the resulting cytokine storm. This paper attempts to conduct a systematic review and meta-analysis of published articles, to evaluate the association of inflammatory parameters with the severity and mortality in COVID-19 patients.MethodsA comprehensive systematic literature search of medical electronic databases including Pubmed/Medline, Europe PMC, and Google Scholar was performed for relevant data published from January 1, 2020 to June 26, 2020. Observational studies reporting clear extractable data on inflammatory parameters in laboratory-confirmed COVID-19 patients were included. Screening of articles, data extraction and quality assessment were carried out by two authors independently. Standardized mean difference (SMD)/mean difference (MD/WMD) and 95% confidence intervals (CIs) were calculated using random or fixed-effects models.ResultsA total of 83 studies were included in the meta-analysis. Of which, 54 studies were grouped by severity, 25 studies were grouped by mortality, and 04 studies were grouped by both severity and mortality. Random effect model results demonstrated that patients with severe COVID-19 group had significantly higher levels of C-reaction protein (CRP), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-2R (IL-2R), serum amyloid A (SAA) and neutrophil-to-lymphocyte ratio (NLR) compared to those in the non-severe group. Similarly, the fixed-effect model revealed significant higher ferritin level in the severe group when compared with the non-severe group. Furthermore, the random effect model results demonstrated that the non-survivor group had significantly higher levels of CRP, PCT, IL-6, ferritin, and NLR when compared with the survivor group.ConclusionIn conclusion, the measurement of these inflammatory parameters could help the physicians to rapidly identify severe COVID-19 patients, hence facilitating the early initiation of effective treatment.Prospero registration numberCRD42020193169.

Dataset Information

Prevalence of Headache in Patients With Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Analysis of 14,275 Patients.

Publications

Prevalence of Headache in Patients With Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Analysis of 14,275 Patients.

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