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Record W3017036469 · doi:10.1186/s12887-020-02050-8

Study protocol: NeoCLEAR: Neonatal Champagne Lumbar punctures Every time – An RCT: a multicentre, randomised controlled 2 × 2 factorial trial to investigate techniques to increase lumbar puncture success

2020· article· en· W3017036469 on OpenAlexaff
Andrew S. J. Marshall, Manish Sadarangani, Alexandra Scrivens, R. Jordan Williams, Jean Yong, Ursula Bowler, Louise Linsell, Virginia Chiocchia, Jennifer Bell, Caz Stokes, Patricia Santhanadass, Eleri Adams, Edmund Juszczak, Charles Christoph Roehr

Bibliographic record

VenueBMC Pediatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersHealth Technology Assessment ProgrammeNational Institute for Health and Care Research
KeywordsMedicineStyletLumbar punctureSittingRandomized controlled trialGestational agePediatricsMeningitisLumbarSurgeryCerebrospinal fluidInternal medicinePregnancy

Abstract

fetched live from OpenAlex

BACKGROUND: The neonatal period carries the highest risk of bacterial meningitis (~ 1 in 5000 births), bearing high mortality (~ 10%) and morbidity (20-50%) rates. Lumbar puncture (LP) remains essential to the diagnosis of meningitis. Though LP is a common procedure in neonates, success rates are lower (50-60%) than in other patient populations. None of the currently-practised neonatal LP techniques are supported by evidence from adequately-powered, randomised controlled trials (RCTs). NeoCLEAR aims to compare two modifications to the traditional technique which are free, accessible, and commonly practised: sitting (as opposed to lying) position, and 'early' (as opposed to 'late') stylet removal. METHODS/DESIGN: on first LP procedure) in 1020 infants between the two positions, and between the two methods of stylet removal. Secondary outcomes relate to LP procedures, complications, diagnoses of meningitis, duration of antibiotics and hospital stay. A modified intention-to-treat analysis will be conducted. DISCUSSION: Two modifications to the traditional LP technique (sitting vs lying position; and early vs late stylet removal) will be simultaneously investigated in an efficient and appropriately-powered 2 × 2 factorial RCT design. Analysis will identify the optimal techniques (in terms of obtaining easily-interpretable cerebrospinal fluid), as well as the impact on infants, parents and healthcare systems whilst providing robust safety data. Using a pragmatic RCT design, all practitioners will be trained in all LP techniques, but there will inevitably be variation between unit practice guidelines and other aspects of individual care. An improved LP technique would result in: • Fewer uninterpretable samples, repeated attempts and procedures • Reduced distress for infants and families • Decreased antibiotic use and risk of antibiotic resistance • Reduced healthcare costs due to fewer procedures, reduced length of stay, shorter antibiotic courses, and minimised antibiotic-associated complications TRIAL REGISTRATION: ISRCTN14040914. Date assigned: 26/06/2018.

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)0.019
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.052
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.029
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0080.005
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0520.007

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 head0.023
GPT teacher head0.296
Teacher spread0.273 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations12
Published2020
Admission routes1
Has abstractyes

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