Reliability of widefield capillary microscopy to measure nailfold capillary density in systemic sclerosis.
Bibliographic record
Abstract
OBJECTIVES: To determine intra- and inter-observer reliability of widefield microscopy to measure nailfold capillary density in patients with systemic sclerosis (SSc). METHODS: Five SSc patients were examined with a STEMV-8 Zeiss biomicroscope with 50x magnification. The nailfold of the second, third, fourth and fifth fingers of both hands of each patient were photographed twice by each of two observers, once in the morning and again in the afternoon (total of 32 pictures). Two raters reviewed the photographs to produce capillary density readings. Intra- and inter-rater reliability of the readings were computed using intra-class correlations (ICC). Additional analyses were undertaken to determine the impact of other sources of variability in the data, namely patient, finger, technician and time. RESULTS: Intra-and inter-rater reliability were substantial (ICC 0.72-0.84) when raters were reading the same photographs or photographs taken at the same time of day. Agreement was only fair between morning and afternoon density readings (ICC 0.30-0.37). Patients, individual fingers and technician accounted for a large part of the variability in the data (combined variance component of 7.69 out of the total 12.23). The coefficient of variation of widefield microscopy was 24%. CONCLUSIONS: Although intra- and inter-rater reliability of nailfold capillary density measurements using widefield microscopy are good, proper standardisation of the conditions under which capillaroscopy is done and better imaging of nailfold capillary abnormalities should be considered if nailfold capillary density is to be used as an outcome measure in multi-centre clinical trials in SSc.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".