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Do we know when to treat neonatal thrombocytopaenia?

2013· review· en· W2112799265 on OpenAlexaboutno aff
Vidheya Venkatesh, Anna Curley, Paul Clarke, Timothy Watts, Simon Stanworth

Bibliographic record

VenueArchives of Disease in Childhood Fetal & Neonatal · 2013
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePlateletPlatelet transfusionMean platelet volumeNeonatologyTransfusion medicineIntensive carePediatricsComorbidityIntensive care medicineInternal medicineBlood transfusionPregnancy

Abstract

fetched live from OpenAlex

Thrombocytopaenia is highly prevalent in neonatology affecting around 25% (22–35%) of all neonates admitted to neonatal intensive care units.1 Clinical signs of bleeding are also commonly documented in preterm neonates. But the close temporal association commonly noted in sick babies between low platelet counts and the occurrence of bleeding does not establish cause and effect. Thrombocytopaenia is a risk factor for poorer neonatal outcomes, although it is unclear whether it is largely a marker of severity of illness and comorbidity.2 Platelet transfusion remains the only readily available specific treatment for this condition. Decisions about when to treat thrombocytopaenia are therefore linked to defining safe and effective platelet transfusion practices. Policies for neonatal platelet transfusion therapy vary widely between clinicians, institutions and countries, and are inevitably based on specified threshold counts of platelets, although platelet counts provide no information on changes in platelet function. Alternative criterion of the need for platelet transfusions, such as platelet mass (which is based on a sum of platelet count and platelet volume, based on the rationale that larger platelets may be more effective haemostatically), have been proposed, but larger studies to assess clinical outcomes have not been undertaken.3 A large web based survey of neonatologists in Canada and USA reported significant variation between neonates units and indicated that platelet transfusions were frequently administered to non-bleeding neonates with platelet counts >50×109/l.4 In the UK, a telephone survey of all tertiary level neonatal units demonstrated similar variation in practice but with the most common thresholds for transfusion in well or stable term and preterm infants being 25×109 and 30×109/l, respectively.5 It should be stressed that the safety and efficacy of these platelet count thresholds for prophylactic platelet transfusions have never been assessed in randomised trials.6 Murray …

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)0.004
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.010
Open science0.0030.001
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0160.007

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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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 designNot applicable
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

Citations11
Published2013
Admission routes1
Has abstractyes

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