Proven Intra and Interobserver Reliability in the Echographic Assessments of Body Fat Changes Related to HIV Associated Adipose Redistribution Syndrome (HARS)
Bibliographic record
Abstract
OBJECTIVE: To prove intra- and inter-observer's reliability of ultrasound (US) in the assessment of lipoatrophic findings related to the HIV associated Adipose Redistribution Syndrome (HARS). PATIENTS AND METHODS: In two separated sessions, 2 consecutive measurements of subcutaneous fat thickness (SFT) were performed by each observer at the deepest point of Bichat pad, the dorsal face of arm and the mid thigh for the assessment of facial, brachial and crural lipoatrophy, respectively. We enrolled 20 HIV patients, rotating an experienced and untrained sonologist. The assessments were performed avoiding any stand off pads in the skin and excluding artefacts due to the too abundant quantity of gel to obtaining, with minimal transducer pressure, the best resolution of the reference points. RESULTS: Means of facial, brachial and crural SFT showed no significant differences between the workers. Coefficients of variability (SD/mean x100) were similar for facial (ranges: 4.7-5.2% vs 4.9-5.6%, respectively), brachial (ranges: 5.8-8.4% vs 9.7-11.2%) and crural SFTs (ranges: 5.9-6% vs 6.2-8.7%). There was greater consistency in the measurements performed by the experienced vs the untrained worker. Inter-observer agreement, assessed through kappa statistic (k) analysis, confirmed increased measurement's agreement in the facial (k ranged from 0.40 to 0.60), brachial (k: 0.23-0.63) and crural SFT assessments (k: 0.58-0.70) from the 1(st) to 2(nd) session. CONCLUSIONS: US shows low intra observer variability and good inter observer reliability in the assessment of body fat changes related to the HARS. The different degree of consistency by the workers and the improvement of interobserver agreement, suggest to stating a well defined period of training to obtain better US reliability.
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 | 0.028 | 0.058 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".