The role of comorbidities and clinical predictors of severe disease in COVID-19: a systematic review and meta-analysis

AbstractBackgroundCOVID_19 is unpredictable due to non-specific symptoms and clinical course diversity in different individuals. We analyzed studies regarding the factors associated with severe status of the disease to identify unique findings in severely affected patients.MethodsWe systematically searched the electronic databases, including PubMed, Scopus, EMBASE, Web of Science, and Google Scholar from inception to 12th of March 2020. Cochrane’s Q and I-square statistics were used to assess the existence of heterogeneity between the included studies. We used the random-effects model to pool the odds ratios (ORs) at 95% confidence intervals (CIs).ResultsSeventeen articles out of 3009 citations were included. These contained 3189 patients, of whom 732 were severely affected (severe group) and 3189 were in non-severe group. Using the random-effects model, our meta-analyses showed that the odds of comorbidities, including COPD, DM, HTN, CVD, CKD, and symptoms, including dyspnea, dizziness, anorexia, and cough, were significantly higher among the severe group compared with the non-severe group. There were no significant changes in odds of CVA, liver disease, immunodeficiency/immunosuppression, fever, fatigue, myalgia, headache, diarrhea, sore throat, nasal congestion, sputum, nausea, vomiting, chest pain between the two groups.ConclusionsEarly recognition and intervention can be critical in management, and might stop progression to severe disease. Predictive symptoms and comorbidities can be used as a predictor in patients who are at risk of severe disease.

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Systematic Review of Second Primary Oropharyngeal Cancers in Patients With p16+ Oropharyngeal Cancer

Otolaryngology ◽

10.1177/0194599820951175 ◽

2020 ◽

pp. 019459982095117

Author(s):

Craig A. Bollig ◽

David S. Lee ◽

Angela L. Mazul ◽

Katelyn Stepan ◽

Sidharth V. Puram ◽

...

Keyword(s):

Surgical Treatment ◽

Random Effects ◽

Meta Analysis ◽

Second Primary ◽

Random Effects Model ◽

Treatment Information ◽

Pooled Prevalence ◽

Alive With Disease ◽

Medical Librarian ◽

Meta Analyses

Objective To systematically review the literature to determine the prevalence and clinical outcomes of second primary oropharyngeal squamous cell carcinoma (OPSCC). Data Sources Search strategies created with a medical librarian were implemented using multiple databases in October 2019. Review Methods The population of interest included adults age >18 years with a p16+ or human papillomavirus-positive OPSCC. The outcome was a synchronous or metachronous second primary OPSCC. Inclusion and exclusion criteria were designed to capture all study designs. In total, 685 records were identified by the search strategy. Two reviewers independently performed the review, extracted data, and performed a quality assessment. Primary Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A random-effects model was used for the meta-analysis. Results A total of 2470 patients with 35 second primary OPSCCs from 15 studies were identified. The pooled prevalence of second primary OPSCC was 1.4% (range, 0%-14.3%). In the random-effects model, the prevalence was estimated at 1.3% (95% CI, 0.7%-2.3%; P = .51, I2 = 52%). Of the 30 patients with treatment information, 26 (86.7%) received surgical treatment, while 4 (13.3%) underwent nonsurgical therapy. Of the 29 patients with available survival information, 22 (75.9%) had no evidence of disease at last follow-up, 5 (17.2%) ultimately died of disease, and 2 (6.9%) were alive with disease. Conclusion Overall, the rate of second primary OPSCC in patients with an index p16+ OPSCC is low, and most patients are successfully treated. Insufficient evidence currently exists to recommend routine elective tonsillectomy during surgical treatment of p16+ OPSCC.

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Bivariate Random-effects Meta-analysis of Sensitivity and Specificity with SAS PROC GLIMMIX

Methods of Information in Medicine ◽

10.3414/me09-01-0001 ◽

2010 ◽

Vol 49 (01) ◽

pp. 54-64 ◽

Cited By ~ 33

Author(s):

J. Menke

Keyword(s):

Sensitivity And Specificity ◽

Random Effects ◽

Mixed Model ◽

Linear Mixed Model ◽

Meta Analysis ◽

Empirical Evaluation ◽

Test Accuracy ◽

Random Effects Model ◽

Operating Characteristics ◽

Meta Analyses

Summary Objectives: Meta-analysis allows to summarize pooled sensitivities and specificities from several primary diagnostic test accuracy studies. Often these pooled estimates are indirectly obtained from a hierarchical summary receiver operating characteristics (HSROC) analysis. This article presents a generalized linear random-effects model with the new SAS PROC GLIMMIX that obtains the pooled estimates for sensitivity and specificity directly. Methods: Firstly, the formula of the bivariate random-effects model is presented in context with the literature. Then its implementation with the new SAS PROC GLIMMIX is empirically evaluated in comparison to the indirect HSROC approach, utilizing the published 2 x 2 count data of 50 meta-analyses. Results: According to the empirical evaluation the meta-analytic results from the bivariate GLIMMIX approach are nearly identical to the results from the indirect HSROC approach. Conclusions: A generalized linear mixed model with PROC GLIMMIX offers a straightforward method for bivariate random-effects meta-analysis of sensitivity and specificity.

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High burden of acute kidney injury in COVID-19 pandemic: systematic review and meta-analysis

Journal of Clinical Pathology ◽

10.1136/jclinpath-2020-207023 ◽

2020 ◽

pp. jclinpath-2020-207023

Author(s):

Camila Barbosa Oliveira ◽

Camilla Albertina Dantas Lima ◽

Gisele Vajgel ◽

Antonio Victor Campos Coelho ◽

Paula Sandrin-Garcia

Keyword(s):

Systematic Review ◽

Acute Kidney Injury ◽

Critically Ill ◽

Random Effects ◽

Meta Analysis ◽

Kidney Injury ◽

Random Effects Model ◽

Risk Of Death ◽

Meta Analyses ◽

The Impact

AimsHospitalised patients with COVID-19 have a variable incidence of acute kidney injury (AKI) according to studies from different nationalities. The present systematic review and meta-analysis describes the incidence of AKI, need for renal replacement therapy (RRT) and mortality among patients with COVID-19-associated AKI.MethodsWe systematically searched electronic database PubMed, SCOPUS and Web of Science to identify English articles published until 25 May 2020. In case of significant heterogeneity, the meta-analyses were conducted assuming a random-effects model.ResultsFrom 746 screened publications, we selected 21 observational studies with 15 536 patients with COVID-19 for random-effects model meta-analyses. The overall incidence of AKI was 12.3% (95% CI 7.3% to 20.0%) and 77% of patients with AKI were critically ill (95% CI 58.9% to 89.0%). The mortality among patients with AKI was 67% (95% CI 39.8% to 86.2%) and the risk of death was 13 times higher compared with patients without AKI (OR=13.3; 95% CI 6.1 to 29.2). Patients with COVID-19-associated AKI needed for RRT in 23.4% of cases (95% CI 12.6% to 39.4%) and those cases had high mortality (89%–100%).ConclusionThe present study evidenced an incidence of COVID-19-associated AKI higher than previous meta-analysis. The majority of patients affected by AKI were critically ill and mortality rate among AKI cases was high. Thus, it is extremely important for health systems to be aware about the impact of AKI on patients’ outcomes in order to establish proper screening, prevention of additional damage to the kidneys and adequate renal support when needed.

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Surgical Outcomes of Endoscopic Versus Open Resection for Primary Sinonasal Malignancy: A Meta-analysis

American Journal of Rhinology and Allergy ◽

10.1177/1945892419856976 ◽

2019 ◽

Vol 33 (5) ◽

pp. 608-616 ◽

Cited By ~ 2

Author(s):

Victor M. Lu ◽

Krishnan Ravindran ◽

Kevin Phan ◽

Jamie J. Van Gompel ◽

Timothy R. Smith ◽

...

Keyword(s):

Random Effects ◽

Surgical Outcomes ◽

Meta Analysis ◽

Random Effects Model ◽

Limited Evidence ◽

Open Resection ◽

Sinonasal Malignancies ◽

Meta Analyses ◽

Risk Ratios ◽

Indirect Comparisons

Background Endoscopic resection (ER) for uncommon sinonasal malignancies (SNMs) has been reported to confer superior surgical outcomes compared to open resection (OR) based on indirect comparisons of limited evidence. Objective The aim of this study was to pool all direct comparative studies in the literature to validate this potential superior association. Methods Systematic searches of 7 electronic databases from their inception to April 2019 were conducted following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. There were 1001 articles identified for screening. Outcomes of interest were pooled as risk ratios (RRs) and mean difference (MD) and analyzed using a random-effects model. Results There were 10 studies included in this meta-analysis, with 900 SNM patients in total where ER and OR were utilized in 399 (44%) and 501 (56%) cases, respectively. Compared to OR, random-effects (RE) modeling indicated ER resulted in statistically comparable complications (RR = 0.68; P-effect = .12) and recurrence (RR = 0.84; P-effect = .35). ER was associated with significantly shorter length of stay (LOS) compared to OR (MD = −2.9 days; P-effect <.01). Conclusions The use of ER to manage SNM was associated with significantly favorable reduction in LOS compared to OR. However, with respect to other surgical outcomes and recurrence, the current literature does not indicate either ER or OR as statistically superior. Therefore, until greater validation of these associations can be proven, expectations that ER for SNMs confers superior surgical outcomes compared to OR should be tempered.

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Efficacy of Corticosteroids in Patients with SARS, MERS and COVID-19: A Systematic Review and Meta-Analysis

Journal of Clinical Medicine ◽

10.3390/jcm9082392 ◽

2020 ◽

Vol 9 (8) ◽

pp. 2392 ◽

Cited By ~ 1

Author(s):

Keum Hwa Lee ◽

Sojung Yoon ◽

Gwang Hun Jeong ◽

Jong Yeob Kim ◽

Young Joo Han ◽

...

Keyword(s):

Systematic Review ◽

Random Effects ◽

Meta Analysis ◽

Random Effect Model ◽

Control Group ◽

Random Effects Model ◽

Number Of Patients ◽

Significant Difference ◽

Meta Analyses ◽

Coronavirus Infections

(1) Background: The use of corticosteroids in critical coronavirus infections, including severe acute respiratory syndrome (SARS), Middle East Respiratory Syndrome (MERS), or Coronavirus disease 2019 (COVID-19), has been controversial. However, a meta-analysis on the efficacy of steroids in treating these coronavirus infections is lacking. (2) Purpose: We assessed a methodological criticism on the quality of previous published meta-analyses and the risk of misleading conclusions with important therapeutic consequences. We also examined the evidence of the efficacy of corticosteroids in reducing mortality in SARS, MERS and COVID-19. (3) Methods: PubMed, MEDLINE, Embase, and Web of Science were used to identify studies published until 25 April 2020, that reported associations between steroid use and mortality in treating SARS/MERS/COVID-19. Two investigators screened and extracted data independently. Searches were restricted to studies on humans, and articles that did not report the exact number of patients in each group or data on mortality were excluded. We calculated odds ratios (ORs) or hazard ratios (HRs) under the fixed- and random-effect model. (4) Results: Eight articles (4051 patients) were eligible for inclusion. Among these selected studies, 3416 patients were diagnosed with SARS, 360 patients with MERS, and 275 with COVID-19; 60.3% patients were administered steroids. The meta-analyses including all studies showed no differences overall in terms of mortality (OR 1.152, 95% CI 0.631–2.101 in the random effects model, p = 0.645). However, this conclusion might be biased, because, in some studies, the patients in the steroid group had more severe symptoms than those in the control group. In contrast, when the meta-analysis was performed restricting only to studies that used appropriate adjustment (e.g., time, disease severity), there was a significant difference between the two groups (HR 0.378, 95% CI 0.221–0.646 in the random effects model, p < 0.0001). Although there was no difference in mortality when steroids were used in severe cases, there was a difference among the group with more underlying diseases (OR 3.133, 95% CI 1.670–5.877, p < 0.001). (5) Conclusions: To our knowledge, this study is the first comprehensive systematic review and meta-analysis providing the most accurate evidence on the effect of steroids in coronavirus infections. If not contraindicated, and in the absence of side effects, the use of steroids should be considered in coronavirus infection including COVID-19.

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Exploring the Relationships Between Problem Gambling and ADHD: A Meta-Analysis

Journal of Attention Disorders ◽

10.1177/1087054715626512 ◽

2016 ◽

Vol 23 (12) ◽

pp. 1427-1437 ◽

Cited By ~ 8

Author(s):

Jennifer Theule ◽

Kylee E. Hurl ◽

Kristene Cheung ◽

Michelle Ward ◽

Brenna Henrikson

Keyword(s):

Confidence Interval ◽

Problem Gambling ◽

Random Effects ◽

Meta Analysis ◽

Random Effects Model ◽

Adhd Symptoms ◽

Weighted Mean ◽

Problem Gamblers ◽

Gambling Severity ◽

Meta Analyses

Objective: At present, there are inconsistencies in the literature pertaining to the association between ADHD and problem gambling. This study utilized meta-analytic techniques to clarify the association between symptoms of problem gambling and symptoms of ADHD. Method: Several meta-analyses were conducted using a random effects model. PsycINFO, PubMed, ProQuest Dissertations & Theses, and Google Scholar were searched for relevant studies. Results: The weighted mean correlation between ADHD symptomology and gambling severity was r = .17, 95% confidence interval (CI) = [0.12, 0.22], p < .001. Mean age of the sample was the only moderator to approach significance, with greater age being linked to a stronger relationship between symptoms of ADHD and gambling severity. Conclusion: Clinicians needs to be cognizant of the greater risk of ADHD symptoms when working with problem gamblers and vice versa.

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A Meta-Analysis to Determine if Lower Extremity Muscle Strengthening Should Be Included in Military Knee Overuse Injury-Prevention Programs

Journal of Athletic Training ◽

10.4085/1062-6050-51.4.09 ◽

2016 ◽

Vol 51 (11) ◽

pp. 919-926 ◽

Cited By ~ 9

Author(s):

Roger O. Kollock ◽

Corey Andrews ◽

Ashlyn Johnston ◽

Teresa Elliott ◽

Alan E. Wilson ◽

...

Keyword(s):

Muscle Strength ◽

Lower Extremity ◽

Random Effects ◽

Overuse Injury ◽

Meta Analysis ◽

Overuse Injuries ◽

Random Effects Model ◽

Muscle Strengthening ◽

Meta Analyses ◽

External Rotator

Context: Knee overuse injuries are the most common musculoskeletal complaints in military trainees and are common in active-duty warfighters. Muscle strengthening is usually recommended; however, research is conflicting in this area, which makes it difficult to develop effective screening, prevention, and training interventions for warfighters. Objective: To determine if lower extremity muscular weakness contributes to knee overuse injuries and identify specific muscular involvement. Data Sources: We searched MEDLINE, PubMed, Web of Science, SPORTDiscus, CINAHL, and Military & Government Collection and reference lists of relevant articles published between January 1, 2000, and January 1, 2013. Study Selection: For inclusion, requirements were uninjured and injured groups; provision of the sample size, means, and standard deviations for all groups; identification of the specific muscles assessed; and clearly defined knee injury. Data Extraction: Sample size, sex, and muscle strength means and standard deviations. Data Synthesis: Twenty-five studies met these criteria. We used the Scottish Intercollegiate Guidelines Network algorithm to determine the appropriate tool for appraising article quality. Unweighted random-effects model meta-analyses were conducted. Separate meta-analyses were performed for the moderators of strength measurement scale (absolute or normalized muscle strength), muscle group, and sex. A weighted random-effects model with a Hedges g effect metric and 95% confidence intervals were used for comparison across studies. Conclusions: Our meta-analysis suggests that individuals with symptoms of a knee overuse injury have lower absolute and normalized hip muscle strength. Specifically, they had lower absolute hip external-rotator, knee-extensor, and knee-flexor strength, as well as lower normalized hip external-rotator, hip-extensor, and hip-abductor strength, compared with asymptomatic control participants. The findings suggest a possible link between lower hip and thigh strength and knee overuse injuries. Further research is needed to determine if weakness is a cause or a result of knee overuse injuries before screening and intervention can be developed for at-risk warfighters.

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An Exact Test for Meta-analysis with Binary Endpoints

Methods of Information in Medicine ◽

10.3414/me0422 ◽

2007 ◽

Vol 46 (06) ◽

pp. 662-668 ◽

Cited By ~ 6

Author(s):

C. Gromann ◽

O. Kuss

Keyword(s):

Random Effects ◽

Fixed Effects ◽

Meta Analysis ◽

Artery Bypass ◽

Sparse Data ◽

Random Effects Model ◽

Exact Test ◽

Standard Methods ◽

Meta Analyses ◽

Empirical Size

Summary Objectives : We reintroduce an exact Mantel-Haenszel (MH) procedure for meta-analysis with binary endpoints which is expected to workespeciallywell i sparse data, e.g., in meta-analyses of safety or adverse events. Methods : The performance of the exact MH procedure in terms of empirical size and power is compared to the asymptotic MH and to the two standard procedures (fixed effects and random effects model) in a simulation study. We illustrate the methods with a metaanalysis of postoperative stroke occurrence after offpump or on-pump surgery in coronary artery bypass grafting. Results : We find that in almost all situations the asymptotic MH procedure outperforms its competitors; especially the standard methods yield poor results in terms of power and size. Conclusions : There is no need to use the reintroduced exact MH procedure; the asymptotic MH procedure will be sufficient in most practical situations. The standard methods (fixed effects and random effects model) should not be used in the sparse data situation.

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An assessment of statistical methods for non-independent data in ecological meta-analyses: Comment

10.32942/osf.io/w96nv ◽

2021 ◽

Author(s):

Shinichi Nakagawa ◽

Alistair M Senior ◽

Wolfgang Viechtbauer ◽

Daniel W.A. Noble

Keyword(s):

Random Effects ◽

Effect Size ◽

Variance Estimation ◽

Meta Analysis ◽

Estimation Method ◽

Random Effects Model ◽

Step Method ◽

Robust Variance ◽

Robust Variance Estimation ◽

Meta Analyses

Recently, Song et al. (2020) conducted a simulation study using different methods to deal with non-independence resulting from effect sizes originating from the same paper – a common occurrence in ecological meta-analyses. The main methods that were of interest in their simulations were: 1) a standard random-effects model used in combination with a weighted average effect size for each paper (i.e., a two-step method), 2) a standard random-effects model after randomly choosing one effect size per paper, 3) a multilevel (hierarchical) meta-analysis model, modelling paper identity as a random factor, and 4) a meta-analysis making use of a robust variance estimation method. Based on their simulation results, they recommend that meta-analysts should either use the two-step method, which involves taking a weighted paper mean followed by analysis with a random-effects model, or the robust variance estimation method.

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Zero-cell corrections in random-effects meta-analyses

10.31219/osf.io/qjh5f ◽

2020 ◽

Author(s):

Frank Weber ◽

Guido Knapp ◽

Katja Ickstadt ◽

Günther Kundt ◽

Anne Glass

Keyword(s):

Random Effects ◽

Odds Ratio ◽

Meta Analysis ◽

Delta Method ◽

Random Effects Model ◽

Likelihood Estimator ◽

Log Odds ◽

The Individual ◽

Meta Analyses ◽

Zero Cell

The standard estimator for the log odds ratio (the unconditional maximum likelihood estimator) and the delta-method estimator for its standard error are not defined if the corresponding 2x2 table contains at least one "zero cell". This is also an issue when estimating the overall log odds ratio in a meta-analysis. It is well known that correcting for zero cells by adding a small increment should be avoided. Nevertheless, these zero-cell corrections continue to be used. With this article, we want to warn of a particularly bad zero-cell correction. For this, we conduct a simulation study comparing the following two zero-cell corrections under the ordinary random-effects model: (i) adding 1/2 to all cells of all the individual studies' 2x2 tables independently of any zero-cell occurrences and (ii) adding 1/2 to all cells of only those 2x2 tables containing at least one zero cell. The main finding is that correction (i) performs worse than correction (ii). Thus, we strongly discourage the use of correction (i).

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