Risk factors and determinants of carotid intima-media thickness in children: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Carotid intima-media thickness (CIMT) is a surrogate marker of atherosclerosis that is measured in adults and children to better understand the natural history of cardiovascular disease (CVD). In adults, CIMT is predictive of myocardial infarction and stroke. In children and adolescents, CIMT is used to assess vascular changes in the presence of CVD risk factors (obesity, hypertension, smoking, etc) or clinical conditions associated with a high risk for premature CVD. However, there is no comprehensive overview, in a life-course epidemiology perspective, of the risk factors and determinants of CIMT in children. It is also important to evaluate between-study differences in CIMT measurement methods and take them into consideration when drawing conclusions. Our objective is to systematically review the evidence on the relationship between CIMT and prenatal and postnatal exposures or interventions in children, as well as documenting and discussing the CIMT measurement methods. METHODS AND ANALYSIS: Systematic searches of the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica (EMBASE)and Central Register of Controlled Trials (CENTRAL) databases will be conducted. The reference lists and other literatures sources will be browsed. Observational and experimental studies in children from birth up to 18 years will be included. Prenatal and postnatal exposures or interventions assessed in relationship with CIMT will be considered for inclusion. Examples might include gestational age, obesity, hypertension, tobacco exposure, specific at-risk conditions (chronic kidney disease, diabetes, etc) or statin treatment. The outcome will be CIMT assessed by ultrasonography. The setting, scanning and measurement methods for each included study will be described in detail. Results will be synthesised descriptively and, if appropriate, will be pooled across studies to perform meta-analyses. Separate meta-analyses for each exposure or intervention type will be conducted. ETHICS AND DISSEMINATION: This systematic review will be published in a peer-reviewed journal. A report will be prepared for clinicians and other healthcare decision-makers. PROSPERO REGISTRATION NUMBER: CRD42017075169.
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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 | 0.043 | 0.060 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.023 | 0.028 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.062 | 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".