Concordance of three methods for palpebral fissure length measurement in the assessment of fetal alcohol spectrum disorder.
Bibliographic record
Abstract
BACKGROUND: The assessment of individuals at risk of fetal alcohol spectrum disorders (FASD) includes the assessment of the craniofacial features that can result from prenatal alcohol exposure. The characteristic facial features of fetal alcohol syndrome (FAS) consist of short palpebral fissures, smooth or flattened philtrum, and thin vermilion border of the upper lip. There are various methods for measuring palpebral fissure lengths (PFLs) and it can be challenging for clinicians to obtain reproducibly accurate measurements. The development of the FAS Facial Photographic Analysis Software by the University of Washington FAS Diagnostic and Prevention Network (DPN) is one such means of improving the accuracy and reproducibility in these measurements. OBJECTIVES: To assess concordance across three methods of PFL measurement: 1) a clear plastic handheld ruler, 2) blunt precision slide calipers, and 3) digital photometric photography (FAS Facial Photographic Analysis Software). METHODS: The PFLs of 50 children (referred to the Clinic for Alcohol and Drug Exposed Children, CADEC) at Children's Hospital in Winnipeg and 50 adults from the University of Manitoba Medical Class of 2008 were measured once by a single clinician, using each of the three methods. The frequency and magnitude of discordance was tabulated. No method served as a gold-standard. RESULTS: The PFLs ranged from 20 to 32 mm. The ruler and photometric measures were concordant in 42% of the subjects. When measures were discordant, half the ruler measures were larger and half were smaller. The caliper measure was concordant with the photometric and ruler measures on 18% and 24% of the subjects, respectively. When measures were discordant, the caliper measures were almost always larger than the photometric and ruler method (0.5 to 2.5 mm larger, 83% and 95% of the time, respectively). The presence of epicanthal folds did not appear to be a factor that contributed to discordance. CONCLUSION: This study demonstrates the challenge in measuring the PFL, even when a single trained clinician is involved. Factors that can contribute to error include the subject's willingness to cooperate, ability to tolerate placement of the tool close enough to the eye to obtain an accurate measure, and precision of the tool. When controlling for the clinician performing the measurements and the quality of the photographs, the ruler and photometric measures were most concordant. The caliper measures tended to measure larger than the ruler and photometric measures.
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 | 0.035 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".