Inter and intra-reliability of ultrasonography for the measurement of abdominal subcutaneous & visceral adipose tissue thickness at 12 weeks gestation
Bibliographic record
Abstract
BACKGROUND: Excess abdominal adiposity cause metabolic disturbances, particularly in pregnancy. Methods of accurate measurement are limited in pregnancy due to risks associated with these procedures. This study outlines a non-invasive methodology for the measurement of adipose tissue in pregnancy and determines the intra- and inter-observer reliability of ultrasound (US) measurements of the two components of adipose tissue (subcutaneous (SAT) and visceral adipose tissue (VAT)) within a pregnant population. METHODS: Thirty pregnant women were recruited at the end of their first trimester, from routine antenatal clinic at the University Maternity Hospital Limerick, Ireland. Measurements of adipose tissue thickness were obtained using a GE Voluson E8 employing a 1-5 MHz curvilinear array transducer. Two observers, employing methodological rigour in US technique, measured thickness of adipose tissue three times, and segmented the US image systematically in order to define measurements of SAT and VAT using specifically pre-defined anatomical landmarks. RESULTS: Intra-observer and inter-observer precision was assessed using Coefficient of Variation (CV). Measurements of SAT and total adipose for both observers were < 5% CV and < 10% CV for VAT in measures by both observers. Inter-observer reliability was assessed by Limits of Agreement (LoA). LoA were determined to be - 0.45 to 0.46 cm for SAT and - 0.34 to 0.53 cm for VAT values. Systematic bias of SAT measurement was 0.01 cm and 0.10 cm for VAT. Inter-observer precision was also assessed by coefficient of variation (CV: SAT, 3.1%; VAT, 7.2%; Total adipose, 3.0%). CONCLUSION: Intra-observer precision was found to be acceptable for measures of SAT, VAT and total adipose according to anthropometric criterion, with higher precision reported in SAT values than in VAT. Inter-observer reliability assessed by Limits-Of-Agreement (LoA) confirm anthropometrically reliable to 0.5 cm. Systematic bias was minimal for both measures, falling within 95% confidence intervals. These results suggest that US can produce reliable, repeatable and accurate measures of SAT and VAT during pregnancy.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".