Evidence map›Paper›PMID 39974463›Full record

ArticleMaedica2024

Early Prediction of ABO HDN Using Immuno-Hematological and Biochemical Tests.

Dnyaneshwar Patale, Jayashree Sharma, Charusmita Modi, Swarupa Bhagwat

Abstract readEditorial
In one paragraph

Article in Maedica, 2024. 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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

4 authors.

Dnyaneshwar PataleAssistant Professor, Department of Transfusion Medicine, AIIMS Raebareli,Raebareli 229405, Uttarpradesh, India.
Jayashree SharmaProfessor and HOD, Department of Transfusion Medicine,Seth GS Medical College and KEM Hospital, Mumbai 400012, Maharashtra, India.
Charusmita ModiAdditional Professor, Department of Transfusion Medicine,Seth GS Medical College and KEM Hospital, Mumbai 400012, Maharashtra, India.
Swarupa BhagwatAssociate Professor, Department of Transfusion Medicine,Seth GS Medical College and KEM Hospital, Mumbai 400012, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveABO hemolytic disease of the newborn (ABO HDN) is the most common cause of neonatal jaundice due to feto-maternal incompatibility. The objective of this study is to evaluate early predictors of ABO HDN using immuno-hematological and biochemical tests. MATERIALS AND

methodsNewborns with blood group A/B born to group O mothers were prospectively enrolled in the present study. Direct antiglobulin test (DAT) and cord blood bilirubin (CBB) were performed. Total serum bilirubin (TSB) was measured at 72 hours of life. Serum anti-A/B IgG titers of maternal samples were measured. For the statistical analysis, Microsoft Excel 2013 (Microsoft Corporation, NY, USA) and SPSS statistical computer software (version 22) were used. To find the efficacy and cut-off values for various predictors of neonatal jaundice, receiver operating characteristic (ROC) curve analysis was performed. To evaluate the relative importance of predictors for phototherapy (PT), logistic regression was used.

resultsA total of 200 ABO incompatible mother-neonate pairs were included in the present study. The incidence of ABO HDN was 10% (n=20). The number of DAT positive cases was 38 (19%). Regression analysis showed a significant influence of antibody titre, CBB and DAT on probability of phototherapy. Antibody titers ≥512 predicted severe hyperbilirubinemia with 80% sensitivity and 83% specificity; CBB ≥2.75 mg/dL had 85% sensitivity and 83% specificity.

conclusionHigh risk ABO-incompatible neonates could be identified at birth using maternal antibody titers, DAT and CBB. Early diagnosis with enhanced surveillance will help in optimum utilization of healthcare.

Identifiers

PMID39974463
PMCPMC11834856

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