scholarly journals Correlation between gastrointestinal symptoms and disease severity in patients with COVID-19: a systematic review and meta-analysis

2020 ◽  
Vol 7 (1) ◽  
pp. e000437 ◽  
Author(s):  
Jing Liu ◽  
Min Cui ◽  
Tao Yang ◽  
Ping Yao
Keyword(s):  
Systematic Review ◽  
Publication Bias ◽  
Disease Severity ◽  
Meta Analysis ◽  
Severe Disease ◽  
Gastrointestinal Symptoms ◽  
Exclusion Criteria ◽  
Funnel Plot ◽  
Gi Symptoms ◽  
Significant Difference

ObjectiveTo study the correlation between gastrointestinal (GI) symptoms and disease severity in patients with COVID-19.DesignWe searched six databases including three Chinese and three English databases for all the published articles on COVID-19. Studies were screened according to inclusion and exclusion criteria. The relevant data were extracted and all the statistical analyses were performed using Revman5.3.ResultIn a meta-analysis of 9 studies, comprising 3022 patients, 479 patients (13.7%, 95% CI 0.125 to 0.149) had severe disease and 624 patients (14.7%, 95% CI 0.136 to 0.159) had GI symptoms. Of 624 patients with GI symptoms, 118 patients had severe disease (20.5%, 95% CI 0.133 to 0.276) and of 2397 cases without GI symptoms, 361 patients had severe disease (18.2%, 95% CI 0.129 to 0.235). Comparing disease severity of patients with and without GI symptoms, the results indicated: I²=62%, OR=1.21, 95% CI 0.94 to 1.56, p=0.13; there was no statistically significant difference between the two groups. The funnel plot was symmetrical with no publication bias.ConclusionCurrent results are not sufficient to demonstrate a significant correlation between GI symptoms and disease severity in patients with COVID-19.

scholarly journals Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis

2021 ◽  
Vol 8 (9) ◽  
Author(s):  
Vishal P Shah ◽  
Wigdan H Farah ◽  
James C Hill ◽  
Leslie C Hassett ◽  
Matthew J Binnicker ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Outcomes ◽  
Disease Severity ◽  
Meta Analysis ◽  
Severe Disease ◽  
Sample Type ◽  
Sample Collection ◽  
Cycle Threshold ◽  
Significant Difference ◽  
Polymerase Chain

Abstract Cycle threshold (CT) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, CT values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presently, the correlation between CT values and clinical outcomes is not well understood. We conducted a systematic review and meta-analysis of published studies through April 19, 2021, that reported an association between CT values and hospitalization, disease severity, and mortality in patients ≥18 years old with SARS-CoV-2. A meta-analysis of 7 studies showed no significant difference in mean CT values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with CT values <25 had a high risk of more severe disease and mortality than patients with CT values >30 (odds ratio [OR], 2.31; 95% CI, 1.70 to 3.13; and OR, 2.95; 95% CI, 2.19 to 3.96; respectively). The odds of increased disease severity and mortality were less pronounced in patients with CT values of 25–30 compared with >30.

scholarly journals Novelty in the gut: a systematic review and meta-analysis of the gastrointestinal manifestations of COVID-19

2020 ◽  
Vol 7 (1) ◽  
pp. e000417 ◽  
Author(s):  
Vishnu Charan Suresh Kumar ◽  
Samiran Mukherjee ◽  
Prateek Suresh Harne ◽  
Abinash Subedi ◽  
Muthu Kuzhali Ganapathy ◽  
...  
Keyword(s):  
Systematic Review ◽  
Abdominal Pain ◽  
Meta Analysis ◽  
Severe Disease ◽  
Clinical Feature ◽  
Severe Illness ◽  
Pooled Data ◽  
Reverse Transcription Pcr ◽  
Gi Symptoms ◽  
Significant Difference

BackgroundThe COVID-19 epidemic has affected over 2.6 million people across 210 countries. Recent studies have shown that patients with COVID-19 experience relevant gastrointestinal (GI) symptoms. We aimed to perform a systematic review and meta-analysis on the GI symptoms of COVID-19.MethodsA literature search was conducted via electronic databases, including PubMed, Embase, Scopus, and Google Scholar, from inception until 20 March 2020. Data were extracted from relevant studies. A systematic review of GI symptoms and a meta-analysis comparing symptoms in severe and non-severe patients was performed using RevMan V.5.3.ResultsPooled data from 2477 patients with a reverse transcription-PCR-positive COVID-19 infection across 17 studies were analysed. Our study revealed that diarrhoea (7.8%) followed by nausea and/or vomiting (5.5 %) were the most common GI symptoms. We performed a meta-analysis comparing the odds of having GI symptoms in severe versus non-severe COVID-19-positive patients. 4 studies for nausea and/or vomiting, 5 studies for diarrhoea and 3 studies for abdominal pain were used for the analyses. There was no significant difference in the incidence of diarrhoea (OR=1.32, 95% CI 0.8 to 2.18, Z=1.07, p=0.28, I2=17%) or nausea and/or vomiting (OR=0.96, 95% CI 0.42 to 2.19, Z=0.10, p=0.92, I2=55%) between either group. However, there was seven times higher odds of having abdominal pain in patients with severe illness when compared with non-severe patients (OR=7.17, 95% CI 1.95 to 26.34, Z=2.97, p=0.003, I2=0%).ConclusionOur study has reiterated that GI symptoms are an important clinical feature of COVID-19. Patients with severe disease are more likely to have abdominal pain as compared with patients with non-severe disease.

scholarly journals Serum albumin concentrations are associated with disease severity and outcomes in coronavirus 19 disease (COVID-19): a systematic review and meta-analysis

2021 ◽  
Author(s):  
Panagiotis Paliogiannis ◽  
Arduino Aleksander Mangoni ◽  
Michela Cangemi ◽  
Alessandro Giuseppe Fois ◽  
Ciriaco Carru ◽  
...  
Keyword(s):  
Systematic Review ◽  
Serum Albumin ◽  
Disease Severity ◽  
Meta Analysis ◽  
Severe Disease ◽  
Geographic Area ◽  
Adverse Outcomes ◽  
Poor Outcome ◽  
Standard Mean Difference ◽  
Meta Regression Analysis

AbstractCoronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the most threatening pandemic in modern history. The aim of this systematic review and meta-analysis was to investigate the associations between serum albumin concentrations and COVID-19 disease severity and adverse outcomes. A systematic literature search was conducted in PubMed, from inception to October 30, 2020. Sixty-seven studies in 19,760 COVID-19 patients (6141 with severe disease or poor outcome) were selected for analysis. Pooled results showed that serum albumin concentrations were significantly lower in patients with severe disease or poor outcome (standard mean difference, SMD: − 0.99 g/L; 95% CI, − 1.11 to − 0.88, p < 0.001). In multivariate meta-regression analysis, age (t =  − 2.13, p = 0.043), publication geographic area (t = 2.16, p = 0.040), white blood cell count (t =  − 2.77, p = 0.008) and C-reactive protein (t =  − 2.43, p = 0.019) were significant contributors of between-study variance. Therefore, lower serum albumin concentrations are significantly associated with disease severity and adverse outcomes in COVID-19 patients. The assessment of serum albumin concentrations might assist with early risk stratification and selection of appropriate care pathways in this group.

scholarly journals Clinical characteristics, treatment and outcomes of paediatric COVID-19: a systematic review and meta-analysis

2021 ◽  
pp. archdischild-2020-321385
Author(s):  
Omar Irfan ◽  
Fiona Muttalib ◽  
Kun Tang ◽  
Li Jiang ◽  
Zohra S Lassi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
World Bank ◽  
Low Income ◽  
Meta Analysis ◽  
Severe Disease ◽  
Income Level ◽  
Clinical Findings ◽  
Middle Income ◽  
Middle Income Countries

ObjectiveCompare paediatric COVID-19 disease characteristics, management and outcomes according to World Bank country income level and disease severity.DesignSystematic review and meta-analysis.SettingBetween 1 December 2019 and 8 January 2021, 3350 articles were identified. Two reviewers conducted study screening, data abstraction and quality assessment independently and in duplicate. Observational studies describing laboratory-confirmed paediatric (0–19 years old) COVID-19 were considered for inclusion.Main outcomes and measuresThe pooled proportions of clinical findings, treatment and outcomes were compared according to World Bank country income level and reported disease severity.Results129 studies were included from 31 countries comprising 10 251 children of which 57.4% were hospitalised. Mean age was 7.0 years (SD 3.6), and 27.1% had a comorbidity. Fever (63.3%) and cough (33.7%) were common. Of 3670 cases, 44.1% had radiographic abnormalities. The majority of cases recovered (88.9%); however, 96 hospitalised children died. Compared with high-income countries, in low-income and middle-income countries, a lower proportion of cases were admitted to intensive care units (ICUs) (9.9% vs 26.0%) yet pooled proportion of deaths among hospitalised children was higher (relative risk 2.14, 95% CI 1.43 to 3.20). Children with severe disease received antimicrobials, inotropes and anti-inflammatory agents more frequently than those with non-severe disease. Subgroup analyses showed that a higher proportion of children with multisystem inflammatory syndrome (MIS-C) were admitted to ICU (47.1% vs 22.9%) and a higher proportion of hospitalised children with MIS-C died (4.8% vs 3.6%) compared with the overall sample.ConclusionPaediatric COVID-19 has a favourable prognosis. Further severe disease characterisation in children is needed globally.

scholarly journals Factors Associated with Disease Severity and Mortality among Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Vignesh Chidambaram ◽  
Nyan Lynn Tun ◽  
Waqas Haque ◽  
Marie Gilbert Majella ◽  
Ranjith Kumar Sivakumar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
English Language ◽  
Clinical Decision Making ◽  
Clinical Laboratory ◽  
Data Extraction ◽  
Meta Analysis ◽  
Severe Disease ◽  
Factors Associated ◽  
Risk Of Mortality

Background: Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19. Methods: We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently. Results: Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45; 95%CI 1.23,1.71), dyspnea (RR 2.55; 95%CI 1.88,2.46), diabetes (RR 1.59; 95%CI 1.41,1.78), hypertension (RR 1.90; 95%CI 1.69,2.15). Congestive heart failure (OR 4.76; 95%CI 1.34,16.97), hilar lymphadenopathy (OR 8.34; 95%CI 2.57,27.08), bilateral lung involvement (OR 4.86; 95%CI 3.19,7.39) and reticular pattern (OR 5.54; 95%CI 1.24,24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality. Conclusion: Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.

scholarly journals Prevalence of pre-stroke depression and its association with post-stroke depression: a systematic review and meta-analysis

2018 ◽  
Vol 49 (4) ◽  
pp. 685-696 ◽  
Author(s):  
Martin Taylor-Rowan ◽  
Oyiza Momoh ◽  
Luis Ayerbe ◽  
Jonathan J. Evans ◽  
David J. Stott ◽  
...  
Keyword(s):  
Systematic Review ◽  
Publication Bias ◽  
Meta Analysis ◽  
Assessment Method ◽  
Self Report ◽  
Funnel Plot ◽  
Strength Of Evidence ◽  
Post Stroke ◽  
Depression Assessment ◽  
Post Stroke Depression

AbstractBackgroundDepression is a common post-stroke complication. Pre-stroke depression may be an important contributor, however the epidemiology of pre-stroke depression is poorly understood. Using systematic review and meta-analysis, we described the prevalence of pre-stroke depression and its association with post-stroke depression.MethodsWe searched multiple cross-disciplinary databases from inception to July 2017 and extracted data on the prevalence of pre-stroke depression and its association with post-stroke depression. We assessed the risk of bias (RoB) using validated tools. We described summary estimates of prevalence and summary odds ratio (OR) for association with post-stroke depression, using random-effects models. We performed subgroup analysis describing the effect of depression assessment method. We used a funnel plot to describe potential publication bias. The strength of evidence presented in this review was summarised via ‘GRADE’.ResultsOf 11 884 studies identified, 29 were included (total participantsn= 164 993). Pre-stroke depression pooled prevalence was 11.6% [95% confidence interval (CI) 9.2–14.7]; range: 0.4–24% (I295.8). Prevalence of pre-stroke depression varied by assessment method (p= 0.02) with clinical interview suggesting greater pre-stroke depression prevalence (~17%) than case-note review (9%) or self-report (11%). Pre-stroke depression was associated with increased odds of post-stroke depression; summary OR 3.0 (95% CI 2.3–4.0). All studies were judged to be at RoB: 59% of included studies had an uncertain RoB in stroke assessment; 83% had high or uncertain RoB for pre-stroke depression assessment. Funnel plot indicated no risk of publication bias. The strength of evidence based on GRADE was ‘very low’.ConclusionsOne in six stroke patients have had pre-stroke depression. Reported rates may be routinely underestimated due to limitations around assessment. Pre-stroke depression significantly increases odds of post-stroke depression.Protocol identifierPROSPERO identifier: CRD42017065544

scholarly journals Laboratory Tests and Outcome for Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 5 (5) ◽  
pp. 1038-1049 ◽  
Author(s):  
Anne Alnor ◽  
Maria B Sandberg ◽  
Charlotte Gils ◽  
Pernille J Vinholt
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
Laboratory Tests ◽  
Evidence Synthesis ◽  
Meta Analysis ◽  
Severe Disease ◽  
Risk Of Bias ◽  
Mean Difference ◽  
Routine Laboratory ◽  
Standard Mean Difference

Abstract Background Severe acute respiratory syndrome coronavirus 2 causes coronavirus disease 2019 (COVID-19) and poses substantial challenges for healthcare systems. With a vastly expanding number of publications on COVID-19, clinicians need evidence synthesis to produce guidance for handling patients with COVID-19. In this systematic review and meta-analysis, we examine which routine laboratory tests are associated with severe COVID-19 disease. Content PubMed (Medline), Scopus, and Web of Science were searched until March 22, 2020, for studies on COVID-19. Eligible studies were original articles reporting on laboratory tests and outcome of patients with COVID-19. Data were synthesized, and we conducted random-effects meta-analysis, and determined mean difference (MD) and standard mean difference at the biomarker level for disease severity. Risk of bias and applicability concerns were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2. Summary 45 studies were included, of which 21 publications were used for the meta-analysis. Studies were heterogeneous but had low risk of bias and applicability concern in terms of patient selection and reference standard. Severe disease was associated with higher white blood cell count (MD, 1.28 ×109/L), neutrophil count (MD, 1.49 ×109/L), C-reactive protein (MD, 49.2 mg/L), lactate dehydrogenase (MD, 196 U/L), D-dimer (standardized MD, 0.58), and aspartate aminotransferase (MD, 8.5 U/L); all p &lt; 0.001. Furthermore, low lymphocyte count (MD −0.32 × 109/L), platelet count (MD −22.4 × 109/L), and hemoglobin (MD, −4.1 g/L); all p &lt; 0.001 were also associated with severe disease. In conclusion, several routine laboratory tests are associated with disease severity in COVID-19.

scholarly journals Accuracy of Wristband Fitbit Models in Assessing Sleep: Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Shahab Haghayegh ◽  
Sepideh Khoshnevis ◽  
Michael H Smolensky ◽  
Kenneth R Diller ◽  
Richard J Castriotta
Keyword(s):  
Systematic Review ◽  
Effect Size ◽  
Meta Analysis ◽  
Body Movement ◽  
Sleep Onset ◽  
Sleep Stages ◽  
Sleep Staging ◽  
Exclusion Criteria ◽  
Significant Difference ◽  
Sleep Parameters

BACKGROUND Wearable sleep monitors are of high interest to consumers and researchers because of their ability to provide estimation of sleep patterns in free-living conditions in a cost-efficient way. OBJECTIVE We conducted a systematic review of publications reporting on the performance of wristband <italic>Fitbit</italic> models in assessing sleep parameters and stages. METHODS In adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we comprehensively searched the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane, Embase, MEDLINE, PubMed, PsycINFO, and Web of Science databases using the keyword <italic>Fitbit</italic> to identify relevant publications meeting predefined inclusion and exclusion criteria. RESULTS The search yielded 3085 candidate articles. After eliminating duplicates and in compliance with inclusion and exclusion criteria, 22 articles qualified for systematic review, with 8 providing quantitative data for meta-analysis. In reference to polysomnography (PSG), nonsleep-staging <italic>Fitbit</italic> models tended to overestimate total sleep time (TST; range from approximately 7 to 67 mins; effect size=-0.51, <italic>P</italic>&lt;.001; heterogenicity: I<sup>2</sup>=8.8%, <italic>P</italic>=.36) and sleep efficiency (SE; range from approximately 2% to 15%; effect size=-0.74, <italic>P</italic>&lt;.001; heterogenicity: I<sup>2</sup>=24.0%, <italic>P</italic>=.25), and underestimate wake after sleep onset (WASO; range from approximately 6 to 44 mins; effect size=0.60, <italic>P</italic>&lt;.001; heterogenicity: I<sup>2</sup>=0%, <italic>P</italic>=.92) and there was no significant difference in sleep onset latency (SOL; <italic>P</italic>=.37; heterogenicity: I<sup>2</sup>=0%, <italic>P</italic>=.92). In reference to PSG, nonsleep-staging <italic>Fitbit</italic> models correctly identified sleep epochs with accuracy values between 0.81 and 0.91, sensitivity values between 0.87 and 0.99, and specificity values between 0.10 and 0.52. Recent-generation <italic>Fitbit</italic> models that collectively utilize heart rate variability and body movement to assess sleep stages performed better than early-generation nonsleep-staging ones that utilize only body movement. Sleep-staging <italic>Fitbit</italic> models, in comparison to PSG, showed no significant difference in measured values of WASO (<italic>P</italic>=.25; heterogenicity: I<sup>2</sup>=0%, <italic>P</italic>=.92), TST (<italic>P</italic>=.29; heterogenicity: I<sup>2</sup>=0%, <italic>P</italic>=.98), and SE (<italic>P</italic>=.19) but they underestimated SOL (<italic>P</italic>=.03; heterogenicity: I<sup>2</sup>=0%, <italic>P</italic>=.66). Sleep-staging <italic>Fitbit</italic> models showed higher sensitivity (0.95-0.96) and specificity (0.58-0.69) values in detecting sleep epochs than nonsleep-staging models and those reported in the literature for regular wrist actigraphy. CONCLUSIONS Sleep-staging <italic>Fitbit</italic> models showed promising performance, especially in differentiating wake from sleep. However, although these models are a convenient and economical means for consumers to obtain gross estimates of sleep parameters and time spent in sleep stages, they are of limited specificity and are not a substitute for PSG.

scholarly journals Cardiovascular drugs and COVID-19 clinical outcomes: a living systematic review and meta-analysis

2020 ◽  
Author(s):  
Innocent G Asiimwe ◽  
Sudeep Pushpakom ◽  
Richard M Turner ◽  
Ruwanthi Kolamunnage-Dona ◽  
Andrea Jorgensen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Outcomes ◽  
Disease Severity ◽  
Meta Analysis ◽  
Severe Disease ◽  
Cardiovascular Drugs ◽  
Susceptibility To Infection ◽  
Drug Classes ◽  
All Cause Mortality ◽  
Length Of Hospitalization

ABSTRACTOBJECTIVETo continually evaluate the rapidly evolving evidence base on the role of cardiovascular drugs in COVID-19 clinical outcomes (susceptibility to infection, hospitalization, hospitalization length, disease severity, and all-cause mortality).DESIGNLiving systematic review and meta-analysis.DATA SOURCESEligible publications identified from >500 databases indexed through 31st July 2020 and additional studies from reference lists, with planned continual surveillance for at least two years.STUDY SELECTIONObservational and interventional studies that report on the association between cardiovascular drugs and COVID-19 clinical outcomes.DATA EXTRACTIONSingle-reviewer extraction and quality evaluation (using ROBINS-I), with half the records independently extracted and evaluated by a second reviewer.RESULTSOf 23,427 titles screened, 175 studies were included in the quantitative synthesis. The most reported drug classes were angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) with ACEI/ARB exposure being associated with higher odds of testing positive for COVID-19 (pooled unadjusted OR 1.15, 95% CI 1.02 to 1.30). Among patients with COVID-19, unadjusted estimates showed that ACEI/ARB exposure was associated with being hospitalized (OR 2.25, 1.70 to 2.98) and having severe disease (OR 1.50, 1.27 to 1.77) but not with the length of hospitalization (mean difference −0.45, −1.33 to 0.43 days) or all-cause mortality (OR 1.25, CI 0.98 to 1.58). However, after adjustment, ACEI/ARB exposure was not associated with testing positive for COVID-19 (pooled adjusted OR 1.01, 0.93 to 1.10), being hospitalized (OR 1.16, 0.80 to 1.68), having severe disease (1.04, 0.76 to 1.42), or all-cause mortality (0.86, 0.64 to 1.15). Similarly, subgroup analyses involving only hypertensive patients revealed that ACEI/ARB exposure was not associated with being hospitalized (OR 0.84, 0.58 to 1.22), disease severity (OR 0.88, 0.68 to 1.14) or all-cause mortality (OR 0.77, 0.54 to 1.12) while it decreased the length of hospitalization (mean difference −0.71, −1.11 to −0.30 days). After adjusting for relevant covariates, other cardiovascular drug classes were mostly not found to be associated with poor COVID-19 clinical outcomes. However, the validity of these findings is limited by a high level of heterogeneity in terms of effect sizes and a serious risk of bias, mainly due to confounding in the included studies.CONCLUSIONOur comprehensive review shows that ACEI/ARB exposure is associated with COVID-19 outcomes such as susceptibility to infection, severity, and hospitalization in unadjusted analyses. However, after adjusting for potential confounding factors, this association is not evident. Patients on cardiovascular drugs should continue taking their medications as currently recommended. Higher quality evidence in the form of randomized controlled trials will be needed to determine any adverse or beneficial effects of cardiovascular drugs.PRIMARY FUNDING SOURCENoneSYSTEMATIC REVIEW REGISTRATIONPROSPERO (CRD42020191283)

scholarly journals Vancomycin-Resistant Enterococci (VRE) in Nigeria: The First Systematic Review and Meta-Analysis

Antibiotics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 565
Author(s):  
Yusuf Wada ◽  
Azian Binti Harun ◽  
Chan Yean Yean ◽  
Abdul Rahman Zaidah
Keyword(s):  
Systematic Review ◽  
Publication Bias ◽  
Meta Analysis ◽  
Forest Plot ◽  
Funnel Plot ◽  
Vancomycin Resistant Enterococci ◽  
Pooled Prevalence ◽  
Vancomycin Resistant ◽  
Meta Regression ◽  
Leave One Out

Vancomycin-Resistant Enterococci (VRE) are on the rise worldwide. Here, we report the first prevalence of VRE in Nigeria using systematic review and meta-analysis. International databases MedLib, PubMed, International Scientific Indexing (ISI), Web of Science, Scopus, Google Scholar, and African journals online (AJOL) were searched. Information was extracted by two independent reviewers, and results were reviewed by the third. Two reviewers independently assessed the study quality using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist. OpenMeta analyst was used. The random effect was used, and publication bias was assessed using a funnel plot. Between-study heterogeneity was assessed, and the sources were analysed using the leave-one-out meta-analysis, subgroup analysis, and meta-regression. Nineteen studies met the eligibility criteria and were added to the final meta-analysis, and the study period was from 2009–2018. Of the 2552 isolates tested, 349 were VRE, and E. faecalis was reported the most. The pooled prevalence of VRE in Nigeria was estimated at 25.3% (95% CI; 19.8–30.8%; I2 = 96.26%; p < 0.001). Between-study variability was high (t2 = 0.011; heterogeneity I2 = 96.26% with heterogeneity chi-square (Q) = 480.667, degrees of freedom (df) = 18, and p = 0.001). The funnel plot showed no publication bias, and the leave-one-out forest plot did not affect the pooled prevalence. The South-East region had a moderate heterogeneity though not significant (I2 = 51.15%, p = 0.129). Meta-regression showed that all the variables listed contributed to the heterogeneity except for the animal isolate source (p = 0.188) and studies that were done in 2013 (p = 0.219). Adherence to proper and accurate antimicrobial usage, comprehensive testing, and continuous surveillance of VRE are required.

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