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Record W4226147130

Optical thermography infrastructure to assess thermal distribution in critically ill children

2021· article· en· W4226147130 on OpenAlexaff
Monisha Shcherbakova

Bibliographic record

VenueEspace École de technologie supérieure (École de technologie supérieure) · 2021
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsÉcole de Technologie SupérieureCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsThermographyCritically illInterquartile rangeInfraredSkin temperatureMedicinePediatric intensive care unitIntensive care unitIntensive careMaterials scienceBiomedical engineeringSurgeryInternal medicinePediatricsIntensive care medicineOpticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.007
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.278
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

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