Conservative and surgical modalities in the management of paediatric parapneumonic effusion and empyema: a protocol for a living systematic review and network meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Parapneumonic effusion and empyema are common complications of paediatric pneumonia. Acceptable treatment modalities for large parapneumonic effusions include antibiotics alone or in conjunction with surgical interventions. Clear guidelines on the best treatment approach are lacking and mostly based on evidence prior to widespread pneumococcal conjugate 13-valent vaccination (PCV-13). METHODS AND ANALYSIS: A living systematic review and network meta-analysis will be performed comparing the five treatment modalities: (1) antibiotics alone; (2) chest tube drainage without fibrinolytics; (3) chest tube drainage with fibrinolytics; (4) video-assisted thoracoscopic surgery and (5) open thoracotomy. The review protocol is reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. Eligible studies are randomised controlled trials comparing any pair of interventions in paediatric patients with empyema or parapneumonic effusion. The following databases will be searched: Ovid MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, LILACS and Google Scholar. Citation screening and data extraction will be completed using a validated crowdsourcing methodology using InsightScope. To assess the risk of bias, we will use the revised Cochrane risk of bias tool for randomised trials. The primary outcome of the study is the length of stay. Secondary outcomes are (1) periprocedural complications and (2) need for re-intervention. A frequentist network meta-analysis design will be implemented with a random-effects model comparing different interventions. In a subgroup analysis, studies and patients will be stratified by the size of pleural effusion and the date of trial (pre/post-PCV-13). Eligible citations and available results will be uploaded to an online database, hosted on Open Science Framework. The database will be updated at least every 4 months with any newly published research. ETHICS AND DISSEMINATION: No ethics review is required for this study. Results will be published in a peer-reviewed journal. Data will be available as part of an online database summarising the evidence of this living systematic review. PROSPERO REGISTRATION: Pending peer review.
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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 | 0.072 | 0.121 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.022 | 0.033 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.005 |
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".