Imaging the microvasculature using nailfold capillaroscopy in patients with coronavirus disease-2019; A cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: It is understood that microvascular dysfunction plays a key role in the pathogenesis of SARS-CoV-2 coronavirus disease (COVID-19). The aim of this study was to evaluate the usefulness of an automated, quantitative nailfold capillaroscopy system in identifying microvascular changes in those confirmed with or having had COVID-19. METHODS: Ninety-seven participants were enrolled into this study and grouped as follows: 52 participants with acute COVID-19 (further grouped by disease severity) and 45 participants with convalescent COVID-19 (further grouped into long COVID i.e. symptoms beyond 12 weeks, and fully recovered). Nailfold capillaroscopy images were obtained from the bilateral ring fingers using a Dino-Lite CapillaryScope 200 Pro, a small USB handheld microscope. Images were assessed quantitatively using bespoke automated measurement software and the number of haemorrhages noted for each participant. RESULTS: Capillaries were predominantly 'normal' in appearance with narrow capillary loops and evenly distributed, but with an increased number of haemorrhages (40 % in the convalescent group and 17 % in the acute group, p = 0.007). There was no statistically significant difference in the mean width of capillaries (20.9-21.8 μm) or vessel density (9.6-9.9 caps/mm; acute and convalescent group, respectively). CONCLUSIONS: This study has demonstrated the feasibility of nailfold capillaroscopy at the critical care bedside. Capillary structure appeared normal across all groups of individuals affected by COVID-19. Although the small differences in the microvasculature in recovered patients compared to in acutely unwell patients may suggest delayed structural change due to COVID-19, these differences are unlikely to be clinically relevant. Longitudinal studies would be required to explore this in more detail.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".