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Record W3028654171 · doi:10.1186/s12889-020-08946-5

Another piece of the Zika puzzle: assessing the associated factors to microcephaly in a systematic review and meta-analysis

2020· review· en· W3028654171 on OpenAlexafffund
Luciana Guerra Gallo, Jorge Martínez-Cajas, Henry Maia Peixoto, Ana Carolina Esteves da Silva Pereira, Jillian E Carter, Sandra McKeown, Bruno Schaub, Camila V. Ventura, Giovanny Vinícius Araújo de França, Léo Pomar, Liana O. Ventura, Vivek R. Nerurkar, Wildo Navegantes de Araújo, Maria P. Vélez

Bibliographic record

VenueBMC Public Health · 2020
Typereview
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsQueen's University
FundersMinistério da EducaçãoQueen's University
KeywordsMicrocephalyZika virusMedicineMeta-analysisPregnancyPediatricsCINAHLIncidence (geometry)MEDLINERelative riskConfidence intervalSystematic reviewCochrane LibraryInternal medicineImmunologyPsychiatryVirusPsychological interventionBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Although it is known that Zika virus (ZIKV) infection during pregnancy may lead to microcephaly in the fetus, the prognostic factors associated with this tragic disorder remain unclear. We conducted a systematic review and meta-analysis to assess the prognostic factors associated with the incidence of microcephaly in congenital ZIKV infection. METHODS: We conducted a comprehensive search in Ovid MEDLINE, Ovid MEDLINE (R) Epub ahead of print, Embase, Embase Classic, Web of Science, CINAHL, Cochrane CENTRAL, LILACS, and various thesis databases to identify human studies reporting microcephaly associated with congenital ZIKV infection. We requested primary data from the authors of the included studies to calculate summary estimates and conduct the meta-analysis of the most prevalent factors. RESULTS: We screened 4106 titles and abstracts, and identified 12 studies for inclusion in the systematic review. The assessment of ZIKV infection and the definition of microcephaly varied among studies. A total of 6154 newborns/fetuses were enrolled; of those, 1120 (18.20%) had a diagnostic of ZIKV infection, of which 509 (45.45%) were diagnosed with microcephaly. Nine studies addressed the link between congenital ZIKV infection and neurological findings in newborns/fetuses. Half of the studies provided primary data. Three out of 11 factors of interest seem to be prognostic factors of microcephaly: infant's sex - males compared to females: Relative Risk (RR) 1.30, 95% Confidence Interval (95% CI) 1.14 to 1.49; the stage of pregnancy when infection occurred - infection in the first trimester of pregnancy compared to infection at other stages of pregnancy: RR 1.41, 95% CI 1.09 to 1.82; and asymptomatic infection compared to symptomatic infection during pregnancy: RR 0.68; 95% CI 0.60 to 0.77. CONCLUSION: Our findings support the female-biased resistance hypothesis and reinforce the risk associated with the stage of pregnancy when ZIKV infection occurs. Continued surveillance of ZIKV infection during pregnancy is needed to identify additional factors that could contribute to developing microcephaly in affected fetuses. PROTOCOL REGISTRATION: This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration no. CRD 42018088075.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.039
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.097
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.035
Bibliometrics0.0090.011
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.167
GPT teacher head0.420
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations21
Published2020
Admission routes2
Has abstractyes

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