ArticleFolia parasitologica2022
Diagnostic accuracy of adjusted low IgG avidity index to predict acute Toxoplasma gondii infection in the first trimester of pregnancy.
Article in Folia parasitologica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Assessment of simultaneous IgM, IgG avidity, and IgA testing in diagnosis of acute toxoplasmosis in pregnant women: a systematic review and meta-analysis study.BMC pregnancy and childbirth · 2025Pooled it
- Evaluation of different cut-off points for IgG avidity and IgM in the diagnosis of acute toxoplasmosis in pregnant women participating in a congenital toxoplasmosis screening program.Revista do Instituto de Medicina Tropical de Sao Paulo · 2024Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Congenital toxoplasmosis is reportable disease in Europe. To prevent it antibody serological tests were introduced in several European countries as a part of screening programmes. Immunoglobulin G (IgG) avidity index testing is one of these tests for diagnosing acute infection with Toxoplasma gondii (Nicolle et Manceaux, 1908) in pregnant women. However, a low or moderate IgG avidity index can give inconclusive results for predicting woman's status. From June 2012 until the end of 2014, 17,990 women were included in the national screening program to prevent congenital toxoplasmosis. One hundred and twenty-six women were consecutively included in the study because they had low or moderate IgG avidity. Every woman with possible acute toxoplasmosis was followed up every month till delivery. Fifty-eight of 126 (46%) women got infected in months before current pregnancy, 39 women (31%) were infected early in pregnancy. Twenty-nine pregnant women of 126 (23%) got infected in the second/third trimester of pregnancy. New cut off for IgG avidity index was 0.11. With this cut off, we were able to exclude T. gondii acute infection in the first trimester with very good diagnostic accuracy (area under the curve (AUC) = 0.95, 95% confidence Interval (CI) 0.91-0.99, sensitivity 0.95, specificity 0.86). If an IgG avidity index above 0.11 is measured in a woman's serum and she is in the first trimester of pregnancy, then a odds ratio (OR) for acute infection with T. gondii is below 1 (OR 0.11, 95% CI 0.05-0.25, P < 0.0001). If we measure IgG avidity index that is ≥ 0.11 in the first trimester of pregnancy, we can exclude infection with T. gondii with good diagnostic accuracy in our cohort of women. With a new cut off we could reduce number of invasive procedures such as amniocentesis and put less pregnant women in distress.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.