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Record W3093237809 · doi:10.1186/s12936-020-03428-w

Prevalence of and risk factors for Plasmodium spp. co-infection with hepatitis B virus: a systematic review and meta-analysis

2020· review· en· W3093237809 on OpenAlexaboutno aff
Kwuntida Uthaisar Kotepui, Manas Kotepui

Bibliographic record

VenueMalaria Journal · 2020
Typereview
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersWalailak University
KeywordsMeta-analysisOdds ratioPublication biasMedicineFunnel plotConfidence intervalDemographyObservational studyHepatitis BStudy heterogeneityMalariaHepatitis B virusInternal medicineImmunologyVirus

Abstract

fetched live from OpenAlex

Abstract Background Plasmodium spp. and hepatitis B virus (HBV) are among the most common infectious diseases in underdeveloped countries. This study aimed to determine the prevalence of Plasmodium spp. and HBV co-infection in people living in endemic areas of both diseases and to assess the risk factors related to this co-infection. Methods The PubMed, Web of Science, and Scopus databases were searched. Observational cross-sectional studies and retrospective studies assessing the prevalence of Plasmodium species and HBV co-infection were examined. The methodological quality of the included studies was assessed with the Newcastle-Ottawa Scale (NOS), a tool for assessing the quality of nonrandomized studies in meta-analyses, and heterogeneity among the included studies was assessed with Cochran's Q test and the I 2 (inconsistency) statistic. The pooled prevalence of the co-infection and its 95% confidence interval (CI) were estimated using the random-effects model, depending on the amount of heterogeneity there was among the included studies. The pooled odds ratio (OR) represented the difference in qualitative variables, whereas the pooled mean difference (MD) represented the difference in quantitative variables. Meta-analyses of the potential risk factors for Plasmodium spp. and HBV co-infection, including patient age and gender, were identified and represented as pooled odds ratios (OR) and 95% CIs. Publication bias among the included studies was assessed by visual inspection of a funnel plot to search for asymmetry. Results Twenty-two studies were included in the present systematic review and meta-analysis. Overall, the pooled prevalence estimate of Plasmodium spp. and HBV co-infection was 6% (95% CI 4–7%, Cochran's Q statistic < 0.001, I 2 : 95.8%), with prevalences of 10% in Gambia (95% CI: 8–12%, weight: 4.95%), 8% in Italy (95% CI 5–12%, weight: 3.8%), 7% in Nigeria (95% CI 4–10%, weight: 53.5%), and 4% in Brazil (95% CI 2–5%, weight: 19.9%). The pooled prevalence estimate of Plasmodium spp. and HBV co-infection was higher in studies published before 2015 (7%, 95% CI 4–9%, Cochran's Q statistic < 0.001, I 2 : 96%) than in those published since 2015 (3%, 95% CI 1–5%, Cochran's Q statistic < 0.001, I 2 : 81.3%). No difference in age and risk of Plasmodium spp. and HBV co-infection group was found between the Plasmodium spp. and HBV co-infection and the Plasmodium monoinfection group (p: 0.48, OR: 1.33, 95% CI 0.60–2.96). No difference in gender and risk of Plasmodium spp. and HBV co-infection group was found between the Plasmodium spp. and HBV co-infection and HBV co-infection group and the Plasmodium monoinfection group (p: 0.09, OR: 2.79, 95% CI 0.86–9.10). No differences in mean aspartate aminotransferase (AST), mean alanine aminotransferase (ALT), or mean total bilirubin levels were found (p > 0.05) between the Plasmodium spp. and HBV co-infection group and the Plasmodium monoinfection group. Conclusions The present study revealed the prevalence of Plasmodium spp. and HBV co-infection, which will help in understanding co-infection and designing treatment strategies. Future studies assessing the interaction between Plasmodium spp. and HBV are recommended.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.773
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.346
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations23
Published2020
Admission routes1
Has abstractyes

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