Strength of the association between Turner syndrome and coeliac disease: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Coeliac disease (CD) is a genetic autoimmune disorder characterised by a permanent sensitivity to the gluten contained in some grains. Certain patient groups are considered high risk for the development of CD, including, but not limited to, those with chromosomal disorders such as Turner syndrome (TS). Here, we present a protocol for a systematic review and meta-analysis that aims to comprehensively summarise the literature, and quantitatively estimate the weighted strength of the association between TS and CD. METHODS AND ANALYSIS: Our protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 guidelines. We will search PubMed, Scopus, Web of Science and Embase databases for relevant articles. Variant and broad search terms will be selected for identifying epidemiological studies reporting on the crude and/or adjusted association between TS and CD. Retrieved citations will be screened, and data from the eligible research reports against specific eligibility criteria will be extracted. We will then assess the risk of bias associated with the eligible studies using the Newcastle-Ottawa Scale. The overall weighted strength of the pooled association will be quantified using the random-effects model. ETHICS AND DISSEMINATION: This review will use data from published literature; hence, ethical approval will not be needed. The resulting review will be the first to produce a comprehensive synthesis of the strength of the association between TS and CD. The results will be disseminated through a peer-reviewed journal as well as in local and international conferences and symposiums. Results dissemination would help healthcare providers and policy-makers to make informed decisions regarding the diagnosis and management of CD in high-risk individuals. PROSPERO REGISTRATION NUMBER: CRD42019131881, dated 3 September 2019.
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 | 0.104 | 0.184 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.052 | 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".