Seroprevalence and geographical distribution of parvovirus B19 antibodies in pregnant women: A-meta analysis
Bibliographic record
Abstract
Parvovirus B19 has been identified to infect pregnant women and cause anemia, spontaneous abortion, and fetal death. Given the significance of parvovirus B19 complications, this study aims to determine the seroprevalence and geographical distribution of parvovirus B19 antibodies in pregnant women to improve health control policies in the community. Online international databases and national Persian databases were used to define appropriate studies published between 2000 and January 2021. The quality of all papers was determined by a Newcastle-Ottawa Scale (NOS) checklist. The statistical analyses were performed using the Stata version 11 package (StataCorp, College Station, TX, USA) software. Heterogeneity among the primary studies was calculated using Cochran's Q-test and I2 index. The Egger test and the funnel plot chart with a significance level of less than 0.1 were used to evaluate the publishing bias. The seroprevalence of parvovirus B19 IgG antibodies among pregnant and non-pregnant women in Iran was assessed in 12 primary studies. Our finding showed that the seroprevalence of parvovirus B19 IgG antibodies among pregnant women varies from 21% to 76%. Combining the results of 5 primary studies based on the random effect model, the seroprevalence of parvovirus B19 IgG antibody among pregnant women in Iran was estimated to be 54% (95% CI:33-76). The seroprevalence of parvovirus B19 IgM antibodies has been reported in 9 studies. By combining the results of these studies using a random effect model, the seroprevalence of parvovirus B19 IgM antibody among pregnant women was estimated to be 3% (95% CI: 1-6). Generally, it is suggested that appropriate screening programs should be performed for the treatment and prevention of diseases. According to this point, the prevalence of parvovirus B19 is low among pregnant women, but it can cause serious manifestations such as hydrops fetalis and severe anemia, therefore, antibody determination using ELISA can be recommended for all pregnant women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".