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Record W2995768694 · doi:10.1136/bmjopen-2019-033887

Doppler ultrasound values after liver transplantation in children and their association with graft outcomes: a protocol for a systematic review and meta-analysis

2019· review· en· W2995768694 on OpenAlexaff
M. Méndez Ruiz, Rashid Alobaidi, Michelle Noga, Robin Featherstone, James Shapiro, Ravi Bhargava

Bibliographic record

VenueBMJ Open · 2019
Typereview
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineData extractionLiver transplantationCochrane LibraryMEDLINEMeta-analysisProtocol (science)Systematic reviewPublication biasTransplantationStudy heterogeneitySurgeryInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Liver graft and patient survival in children have improved substantially over the years; nevertheless, graft-related complications persist as the most important risk factor for mortality and graft loss. Doppler ultrasound evaluation is routinely used after liver transplantation; however, there is no consensus defining normal values, timing or frequency of Doppler ultrasound postoperative evaluation. Identification of patients who require an intervention or change in postoperative management is therefore challenging. METHODS AND ANALYSIS: We will conduct a systematic review and meta-analysis to appraise and synthesise evidence describing Doppler ultrasound measurements and their association with graft complications in children who have received a liver transplant. We will search multiple databases: Ovid Medline, Embase, Wiley Cochrane Library, Web of Science-Science Citation Index Expanded, trial registry records and meeting abstracts using a combination of subject headings and keywords for liver transplantation, Doppler ultrasound and paediatric patients. All identified titles and abstracts of studies will be assessed for potential relevance. Selected studies will be retrieved and subjected to a second phase of screening, both selection phases will be done in duplicate by two independent reviewers, and discrepancies will be documented and resolved by a third reviewer. Data extraction will be done independently by two reviewers using a standardised data extraction form. Quality of evidence and risk of bias will be assessed, synthesised and pooled for meta-analysis if possible. We will perform a subgroup analysis if enough data are available. ETHICS AND DISSEMINATION: Strategies to disseminate our review include presenting in liver transplant review sessions, publishing in high-impact peer-reviewed medical journals, and presenting at national and international paediatric radiology and liver transplant meetings, conference presentations, events, courses and plain-language summaries. This knowledge will allow easier identification of patients with a higher risk of developing graft-related complications and could potentially improve patient and graft outcomes. We wish to disseminate our results to discover potential areas for future research and drive improved future practices and policies. Our target audience includes researchers, institutions, healthcare professionals, health system decision-makers, policy-makers and research funders community. TRIAL REGISTRATION NUMBER: CRD42019119986.

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)0.075
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.075
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.115
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0220.027
Bibliometrics0.0120.012
Science and technology studies0.0030.003
Scholarly communication0.0080.007
Open science0.0050.005
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0490.006

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.

Opus teacher head0.107
GPT teacher head0.443
Teacher spread0.336 · 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 designMeta-analysis
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

Citations1
Published2019
Admission routes1
Has abstractyes

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