Evidence map›Paper›PMID 24014079›Full record

ArticleJournal of clinical immunology2013

Phenotypic parameters predict time to normalization in infants with hypogammaglobulinemia.

Robert C Van Winkle, Walter W Hauck, Stephen J McGeady

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Article in Journal of clinical immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Robert C Van WinkleThomas Jefferson University, Philadelphia, PA, USA.
Walter W Hauck
Stephen J McGeady
Alfred I. duPont Hospital for Children · USThomas Jefferson University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeInfants with recurrent infection may be found to have hypogammaglobulinemia without impaired specific antibody responses. Many will be diagnosed with transient hypogammaglobulinemia of infancy.

methodsThis study used a parametric survival analysis of 100 infants with hypogammaglobulinemia to predict time to normalization.

resultsAggregate initial immunoglobulins (IgG + IgA + IgM), as a percentage of age-adjusted normal, predicted time to resolution: median time to resolution for the infants in the lowest quartile of aggregate levels (≤81 % of age-adjusted lower limits) was greater than 5 years, with 34 % resolving in 3 years. For infants in the highest quartile (≥130 % of age-adjusted lower limits), the median was 9.9 months, with 77 % resolving in 3 years (P = 0.008). Initial IgG level, as a percentage of age-adjusted normal, also predicted resolution: the median time in the lowest quartile (≤78 % of age-adjusted lower limits) was greater than 5 years, with 36 % resolving in 3 years. In the highest quartile (≥128 %), the median time was 14.5 months, with 70 % resolving in 3 years (P = 0.010). Male sex was associated with more rapid resolution. The median time in males was 13 months, with 73 % resolution in 3 years. The median time in females was greater than 5 years, with 32 % resolution in 3 years.

conclusionsThese results suggest that if a term infant presents with hypogammaglobulinemia, protective specific antibody titers, and an absence of other known immune deficiency, initial immunoglobulin levels and sex may predict time to normalization.

Indexed as

AgammaglobulinemiaAge FactorsChild, PreschoolFemaleGenetic Predisposition to DiseaseHumansImmunoglobulinsImmunophenotypingInfantMalePredictive Value of TestsReference ValuesSex FactorsTime FactorsImmunoglobulins

Identifiers

PMID24014079
OpenAlexW2074446040

What OpenQuestion holds

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Registered trials

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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.