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Record W4406882407 · doi:10.3389/fped.2024.1475623

Direct antiglobulin test for the prediction of neonatal hyperbilirubinemia needing an intervention: a systematic review and diagnostic test accuracy meta-analysis

2025· review· en· W4406882407 on OpenAlexaff
Vijay Kumar Krishnegowda, Viraraghavan Vadakkencherry Ramaswamy, Thangaraj Abiramalatha, Tapas Bandyopadhyay, Abdul K. Pullattayil, Prakash Kannan Loganathan

Bibliographic record

VenueFrontiers in Pediatrics · 2025
Typereview
Languageen
FieldMedicine
TopicNeonatal Health and Biochemistry
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineMeta-analysisMEDLINERandomized controlled trialConfidence intervalPediatricsInternal medicineCINAHLPsychological intervention

Abstract

fetched live from OpenAlex

Importance The direct antiglobulin test (DAT) is commonly used as a screening test for predicting significant neonatal hyperbilirubinemia requiring intervention. However, evidence for this approach is limited. Objective The aim of this study was to evaluate the diagnostic utility of DAT in predicting the need for phototherapy and double volume exchange transfusion (DVET) in neonates with ABO and Rhesus (Rh) incompatibility conditions. Methods MEDLINE, Embase, CENTRAL, CINAHL, and Web of Science were searched from inception until 1 February 2024. Randomized controlled trials (RCTs) and non-RCTs were eligible for inclusion. Two reviewers screened the titles and abstracts blinded to each other. A Bayesian bivariate random-effects model was employed for the diagnostic test accuracy meta-analyses. Risk of bias was assessed using Quality Assessment for Studies of Diagnostic Accuracy 2 and certainty of evidence (CoE) was adjudged according to the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) guidelines. Results In total, 53 studies were included in the systematic review and 28 were synthesized in the meta-analysis. For the need for phototherapy outcome, the pooled sensitivity [95% credible interval (CrI)] and specificity (95% CrI) of DAT in ABO incompatibility (18 studies, n = 10,110) were 56.1% (44.5%–67.8%) and 83.6% (71.6%–90.8%). For Rh incompatibility (three studies, n = 491), the sensitivity and specificity were 40.4% (12.2%–81.7%) and 89.9% (72.7%–94.6%). The CoE was predominantly low. For the need for DVET outcome, the pooled sensitivity and specificity of DAT in ABO incompatibility (three studies, n = 2,652) were 83.6% (35.8%–99.6%) and 74.5% (40.3%–92.7%). For Rh incompatibility (two studies, n = 240), the sensitivity and specificity were 80.3% (34.2%–97.3%) and 68.0% (25.3%–92.1%). The CoE was predominantly very low. Conclusion In ABO and Rh incompatibility, DAT probably has moderate specificity and low sensitivity for predicting the need for phototherapy. For DVET, though DAT is possibly a better predictor due to its acceptable sensitivity, the predictive interval was wide. Thus, we do not suggest the routine use of DAT screening to predict the need for phototherapy and DVET. However, it may be used as a second-tier investigation for risk stratification of high-risk neonates. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022297785 , PROSPERO (CRD42022297785).

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)0.029
metaresearch head score (Gemma)0.086
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.086
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0260.048
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.348
Teacher spread0.305 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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