Infrared thermography as an adjunctive tool for detection of femoral arterial thrombosis after cardiac catheterization: A prospective, pilot study
Bibliographic record
Abstract
OBJECTIVES: To assess the utility of infrared thermography (IRT), to map skin temperature, in the detection of femoral arterial (FA) thrombosis after cardiac catheterization. BACKGROUND: Ultrasound is a validated method for thrombus detection but is generally reserved as a confirmatory test for clinical suspicion due to various constraints. METHODS: Prospective study of infants and children undergoing cardiac catheterization via FA access, comparing IRT and pulse examination. The thermograms, displayed in a color map with each pixel representing a temperature, were examined by qualitative assessment of symmetry in thermal patterns and quantitative image analysis with abnormal thermographic asymmetry defined as a difference of >10% between limbs. RESULTS: In the 20 children enrolled, excellent agreement was found between the two methods with a Kappa value of 0.89. The median thermographic asymmetry in the nine children with pulse loss was 36 (13-76)%. Using receiver operating characteristic analysis, the asymmetrical pattern of ≥18% between limbs predicted the need for anticoagulation with a sensitivity of 100% and specificity of 89%. The area under the curve was 0.97 (95% confidence interval: 0.95-1). Children with absent pulse requiring anticoagulation showed a slower recovery in thermal asymmetry compared to those with a reduced pulse. By qualitative IRT assessment, all children with absent pulse requiring anticoagulation were correctly identified by 10 independent assessors. CONCLUSIONS: This pilot study showed that IRT is feasible and reliable as an adjunctive tool for thrombus detection postcatheterization and treatment monitoring. Specific advantages of IRT include portability, affordability, and contactless image acquisition.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".