Evidence map›Paper›PMID 40952748›Full record

Observational studyJAMA2025

Individualized Prediction of Platelet Transfusion Outcomes in Preterm Infants With Severe Thrombocytopenia.

Hilde van der Staaij, Ilaria Prosepe, Camila Caram-Deelder, Ruth H Keogh, Emöke Deschmann, Christof Dame, Wes Onland, Sandra A Prins, Florian Cassel, Esther J d'Haens and 10 more

Abstract readMulticenter StudyObservational StudyValidation Study
In one paragraph

Observational study in JAMA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors.

Hilde van der StaaijDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Ilaria ProsepeDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
Camila Caram-DeelderDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Ruth H KeoghDepartment of Medical Statistics, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Emöke DeschmannDivision of Neonatology, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.
Christof DameDepartment of Neonatology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Wes OnlandDepartment of Neonatology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Sandra A PrinsDepartment of Neonatology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Florian CasselDepartment of Neonatal and Pediatric Intensive Care, Erasmus Medical Center Sophia, Rotterdam, the Netherlands.
Esther J d'HaensDepartment of Neonatology, Isala Klinieken, Zwolle, the Netherlands.
Elke van Westering-KroonDivision of Neonatology, Department of Pediatrics, MosaKids Children's Hospital, Maastricht University Medical Center, Maastricht, the Netherlands.
Peter AndriessenDepartment of Neonatology, Máxima Medical Center, Veldhoven, the Netherlands.
Sabine L VranckenDepartment of Neonatology, Amalia Children's Hospital, Radboud University Medical Center, Nijmegen, the Netherlands.
Christian V HulzebosDepartment of Neonatology, Beatrix Children's hospital, University Medical Center Groningen, Groningen, the Netherlands.
Daniel C VijlbriefDepartment of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, the Netherlands.
Suzanne F Fustolo-GunninkDepartment of Pediatrics, Division of Neonatology, Willem-Alexander Children's Hospital, Leiden University Medical Center, Leiden, the Netherlands.
Karin FijnvandraatSanquin Research & Lab Services, Sanquin Blood Supply Foundation, Amsterdam, the Netherlands.
Enrico LoprioreDepartment of Pediatrics, Division of Neonatology, Willem-Alexander Children's Hospital, Leiden University Medical Center, Leiden, the Netherlands.
Johanna G van der BomDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Nan van GelovenDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

importancePreterm infants with severe thrombocytopenia (platelet count <50 × 109/L) frequently receive platelet transfusions. However, it is unclear in what cases prophylactic transfusion truly reduces bleeding risk or whether it does more harm than good.

objectiveTo develop and validate a dynamic prediction model for major bleeding or mortality if prophylactic platelet transfusion were or were not to be given to infants with severe thrombocytopenia. DESIGN, SETTING, AND

participantsThe dynamic prediction model was developed in an international multicenter cohort (2017-2021) comprising 14 neonatal intensive care units in the Netherlands, Sweden, and Germany. Model evaluation was performed in a national multicenter cohort (2010-2014) including 7 Dutch neonatal intensive care units. The study population consisted of infants with severe thrombocytopenia less than 34 weeks' gestation. EXPOSURE: Two transfusion strategies were contrasted at each prediction point: receiving a platelet transfusion within 6 hours (prophylaxis) vs no platelet transfusion for 3 days (no prophylaxis). MAIN OUTCOMES AND MEASURES: The primary outcome was the 3-day risk of major bleeding or mortality, reestimated every 2 hours during the first week after severe thrombocytopenia onset. Predictors included gestational and postnatal age, small-for-gestational-age infant, necrotizing enterocolitis, sepsis, mechanical ventilation, vasoactive agents, platelet count, and prior platelet transfusion(s). Landmarking combined with the clone-censor-weight approach enabled dynamic prediction under the 2 transfusion strategies, accounting for time-varying confounding. Model performance was evaluated in the external validation cohort.

resultsIn both the development (n = 1042) and validation (n = 637) cohorts, the median gestational age was 28 weeks and median birth weight was 900 g; there were 613 (59%) and 370 (58%) males, respectively. Major bleeding or death occurred in 235 infants (23%) in the development cohort and 135 (21%) in the validation cohort. In the validation cohort, the time-dependent area under the receiver operating characteristic curve was 0.69 (95% CI, 0.60-0.76) for the prophylaxis strategy and 0.85 (95% CI, 0.76-0.92) for the no prophylaxis strategy, with calibration plots showing good calibration. Estimated risks under both strategies varied considerably depending on the infant's clinical condition at the time of prediction. CONCLUSIONS AND RELEVANCE: Among preterm infants with severe thrombocytopenia, this modeling study found substantial variation among individuals in predicted benefits and harms of prophylactic platelet transfusion based on their current clinical characteristics. The dynamic prediction model performed well in a validation cohort, and its value to support individualized decisions warrants evaluation in future studies.

Indexed as

HemorrhageInfant, Premature, DiseasesPlatelet TransfusionThrombocytopeniaFemaleGestational AgeHumansInfant, NewbornInfant, PrematureIntensive Care Units, NeonatalMaleModels, StatisticalPlatelet CountRisk AssessmentSeverity of Illness Index

Identifiers

PMID40952748
PMCPMC12439188

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.