Validation of Commercially Available Infrared Thermometers for Measuring Skin Surface Temperature Associated with Deep and Surrounding Wound Infection
Bibliographic record
Abstract
OBJECTIVE: Increased local skin temperature is a classic sign of wound infection, repetitive trauma, and deep inflammation. Noncontact infrared thermometers can help to detect increases in skin surface temperatures; however, most scientifically tested devices are far too expensive for everyday wound care providers to use in routine clinical practice. This noninferiority study was conducted in an attempt to determine whether 4 less expensive, commercially available noncontact infrared thermometers have a similar level of accuracy as the scientifically accepted Exergen DermaTemp 1001 (Exergen Products, Watertown, Massachusetts). DESIGN, SETTING, AND PARTICIPANTS: Using an observational study design, participants with open wounds were randomly selected from a chronic wound clinic (n = 108). Demographic data and wound location were documented for all participants. Skin temperatures were recorded using 5 noncontact infrared thermometers under consistent environmental conditions. The thermometer brands were as follows: Exergen DermaTemp, Mastercool MSC52224-A (Mastercool Inc, Randolph, New Jersey), ATD Tools 70001 Infrared Thermometer (ATD Tools Inc, Wentzville, Missouri), Mastercraft Digital Temperature Reader (Mastercraft Canada, Toronto, Ontario, Canada), and Pro Point Infrared Thermometer (Princess Auto, Winnipeg, Manitoba, Canada). Data analysis was based on the skin surface temperature difference (ΔT in degrees Fahrenheit) between the wound site and an equivalent contralateral control site. OUTCOME MEASURES: One-way analysis of variance was used to compare the mean ΔT values for all the 5 thermometers, followed by post hoc analysis. Demographic data were analyzed using descriptive statistics. Interrater reliability was assessed for consistency using the intraclass correlation coefficient. MAIN RESULTS: No statistical difference was reported between the ΔT values for the 5 different thermometers (F4,514 = 0.339, P = .852). Post hoc analysis showed no significant difference when the thermometers were compared with the Exergen DermaTemp 1001, and Mastercool MSC52224-A (P = .987), ATD Tools 70001 Infrared Thermometer (P = .985), Mastercraft Digital Temperature Reader (P = .972), and Pro Point Infrared Thermometer (P = .774). The results for intraclass correlation demonstrated a high reliability and agreement between raters, as the intraclass correlation coefficient values for all thermometers were greater than 0.95. CONCLUSIONS: The results of this study demonstrate that less expensive, industrial-grade noncontact infrared thermometers have reliable temperature readings to identify and quantify the temperature gradients that along with other signs may be associated with deep and surrounding wound infection or tissue injury due to repeated microtrauma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".