Optical thermography infrastructure to assess thermal distribution in critically ill children
Bibliographic record
Abstract
Goal: The aim of this study is to explore and assess infrared thermography as a method to analyze temperature profiles of critically ill children. Methods: Critically ill patients admitted to the pediatric intensive care unit of Saint Justine Hospital with features of respiratory, hemodynamic or neurological failure were included prospectively in this study. A FLIR Lepton 3.5 infrared sensor was used to take images of the patients in real clinical condition, after obtaining informed consent. The temperatures of their core (either thorax or inner eye) and of their extremities (fingers or toes) were extracted. The gradient between the central and extremities temperature of the patients was calculated by taking their difference and the ratio was calculated by dividing the two values. Continuous temperature analysis along the body was also performed by taking the temperatures along a line joining the core to the extremities. Spearman correlation tests were performed to study any relation between the gradient and the clinical background of the patients. Results: In total, 36 patients were included. The median central temperature [interquartile range] extracted from the IR images of the subjects was 33.88°C [32.74-34.19], and the median temperature of the extremities was 30.21°C [28.89-33.13]. There was a good correlation between the central temperature extracted via thermography and the clinical axillary temperature (correlation factor of 0.39, p value= 0.016). There was also a very good correlation between the central and extremities temperature extracted via thermography (correlation factor of 0.66, p value = 1.2 e-05). The correlation tests with clinical markers did not give any statistically significant results. The temperatures extracted along the line joining the core to the limbs were plotted on a graph and gave insightful results into the artefacts present on the body. Conclusion: Thermography was found to be effective to estimate the temperature of the core and limbs of the patients included in this study. Correlation with specific clinical conditions such as shock or sepsis needs further study with a larger sample size.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| 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; both teacher heads agree on what is shown here.
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".