Evidence map›Paper›PMID 42173558›Full record

Observational studyBMJ paediatrics open2026

Optimising transfusion practices in preterm neonates using gestational age and birth weight-based prediction model: a retrospective cohort study from India.

Malavika Krishnakumar, Anjali Ajith, Georg Gutjahr, Sreerenjini Biju, Veena Shenoy, Dhanya A, Perraju Bendapudi

Abstract readObservational Study
In one paragraph

Observational study in BMJ paediatrics open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Malavika KrishnakumarDepartment of Health Sciences Research, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Sciences and Research Centre, Kochi, Kerala, India.ORCID http://orcid.org/0009-0006-6903-5836
Anjali AjithDepartment of Neonatology, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Sciences, Kochi, Kerala, India.
Georg GutjahrDepartment of Health Sciences Research, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Sciences and Research Centre, Kochi, Kerala, India.ORCID http://orcid.org/0000-0002-1925-8349
Sreerenjini BijuDepartment of Mathematics, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Kollam, Kerala, India.ORCID http://orcid.org/0009-0008-9398-5983
Veena ShenoyDepartment of Transfusion Medicine, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Sciences, Kochi, Kerala, India.
Dhanya ADepartment of Transfusion Medicine, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Sciences, Kochi, Kerala, India.
Perraju BendapudiDepartment of Neonatology, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Sciences, Kochi, Kerala, India perrajub@aims.amrita.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreterm neonates, particularly those with extremely low birth weight and gestational age, are at high risk of requiring multiple blood transfusions during their stay in the neonatal intensive care unit (NICU). Repeated transfusions result in multiple donor exposures, leading to increased risk of infections, alloimmunisation, worse neurodevelopmental outcomes and transfusion-related complications. Optimising transfusion practices through prediction-based strategies could enhance safety and resource efficiency, particularly in low- and middle-income countries.

objectiveThis study aims to evaluate transfusion patterns among preterm neonates and develop a predictive model based on birth weight and gestational age to reduce donor exposure and improve transfusion efficiency.

methodsThis retrospective observational study included inborn preterm neonates (gestational age 23+0 to 32+0 weeks) admitted to a tertiary care NICU in South India in 2023 who received at least one packed red blood cell (PRBC) transfusion. Outborn babies who were transferred to the NICU beyond 48 hours of life and babies needing surgery at any point during their NICU stay were excluded. Data on gestational age, birth weight, transfusion frequency, donor exposure, clinical outcomes and blood usage were analysed. Predictive models were developed using Bayesian ordinal regression to estimate transfusion requirements.

resultsWe analysed 422 PRBC transfusions administered to 118 neonates. Lower gestational age and birth weight were significantly associated with increased transfusion frequency and donor exposure. Predictive models using gestational age and birth weight reduced the need for multiple donors. This approach, if used, would have also improved blood resource planning and highlighted the potential for reduced wastage.

conclusionIndividualised transfusion strategies may reduce donor exposure and improve transfusion safety in preterm neonates, especially in resource-limited settings.

Indexed as

Birth WeightBlood TransfusionErythrocyte TransfusionGestational AgeInfant, PrematureFemaleHumansIndiaInfant, NewbornIntensive Care Units, NeonatalMaleRetrospective StudiesInfantLow and Middle Income CountriesNeonatology

Identifiers

PMID42173558
PMCPMC13202167

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