Abstract 276: Impact of Skin Color on Accuracy of Capillary Refill Time Measurement by Pulse Oximeter
Bibliographic record
Abstract
Capillary refill time(CRT) is a non-invasive method to assess tissue perfusion, routinely performed in pediatric practice. Current methods to measure CRT have limitations in objectivity and reproducibility. The measurement depends on clinician’s assessment. New analytic approach using pulse oximeter waveform has been developed. Hypothesis: CRT measured by pulse oximeter device and clinicians(critical care/anesthesiologist attending physicians) were different across skin color and finger thickness. Method: Children(1-12 yr) with different skin color tones (Fitzpatrick scale 1-2:fair, 3-4:medium, 5-6:dark) were recruited. Subjects were randomized to a pulse oximeter either on index/middle finger, and had a total 10 CRT measurements (5 with device, 5 with clinician’s visual assessment, alternating). Waveform analysis was performed with quick compression and release on the pulse oximetry device by clinician. The difference between device and clinician measured CRT was calculated. ANOVA for difference in CRT across 3 skin color categories and across 4 finger thickness. Result: 64 subjects(skin color fair 33, medium 16, dark 15) were recruited (median age 72 m, IQR 42-123m). Out of 640 CRT measurements, 300 pairs had measurable CRTs in both device and clinician. Based on clinician’s measurement, 114 CRTs were >2s and 26 CRTs > 4s. The overall CRT difference was mean 0.97±1.32s. The CRT difference by skin color was fair 0.86±1.35s, medium 0.90±1.31s, dark 1.26±1.22s, p=0.095. Pearson correlation coefficient was all 0.49 (fair 0.31, medium 0.67, and dark 0.41, all p<0.001). There was no significant difference in CRT difference among 4 finger thickness categories(thin to thick); 1.21±1.48s, 0.94±1.48s, 1.12±1.20s, 0.75±1.20s, p=0.108. Conclusion: The difference between device and clinician measured CRT did not vary across the different patient skin color or finger thickness. Device measured CRT may be a helpful indicator for peripheral perfusion.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".