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
Bibliographic record
Abstract
Abstract 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 Written parental informed consent permitting, infants in neonatal/maternity wards, of 27+ 0 to 44+ 0 weeks corrected gestational age and weighing ≥1000 g, who require an LP, will be randomly allocated to sitting or lying position, and to early or late stylet removal. The co-primary objectives are to compare success rates (the proportion of infants with cerebrospinal fluid red cell count < 10,000/mm3 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.053 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".