A Clinical Investigation into the Relationship between Increased Periwound Skin Temperature and Local Wound Infection in Patients with Chronic Leg Ulcers
Bibliographic record
Abstract
In Brief PURPOSE: To enhance the clinician's knowledge about the relationship between increased periwound skin temperature and local wound infection in patients with chronic leg ulcers. TARGET AUDIENCE: This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. OBJECTIVE: After participating in this educational activity, the participant should be better able to: Interpret research findings on chronic wound assessment including skin temperature assessments. Examine the study reported in this article for appropriate use of periwound skin temperature assessment. Analyze this study's findings regarding the relationship between skin temperature and chronic wound infection. OBJECTIVE: Increased local temperature is a classic sign of wound infection, and its quantitative measurement has the potential to assist with assessment and diagnosis of chronic deep wound and surrounding skin infection at the bedside. Evidence supporting such use in chronic wound care is very limited. This clinical pilot study was conducted in an attempt to quantify the relationship between increased periwound skin temperature and wound infection, as well as validate use of a handheld infrared thermometer for the wound care practitioner. DESIGN, SETTING, AND PARTICIPANTS: Using a cross-sectional design, 2 groups of participants were recruited from a chronic wound clinic: without wounds (n = 20) and with chronic leg ulcers (n = 40). Participant and wound characteristics were documented. All skin temperatures were documented using a handheld infrared thermometer under consistent environmental conditions within the clinic. Data analysis was based on the difference (Δ) in skin temperature (in degrees Fahrenheit) between a target or wound site and an equivalent contralateral control site. Wound infection was identified using the combination of a validated assessment tool and clinical judgment. Supplemental semiquantitative bacterial swabs were collected from all wounds. OUTCOME MEASURES: Descriptive statistics were analyzed using the chi-squared calculation. A Pearson r calculation of test-retest skin temperature data collected from nonwounded participants initially determined reliability of the infrared thermometer. Correlation of increased periwound skin temperature to wound infection was determined by calculation of a 1-way analysis of variance. MAIN RESULTS: The infrared thermometer was found to be reliable (r = 0.939, P = .000 at a 95% confidence interval). A statistically significant relationship between increased periwound skin temperature and wound infection was identified (F = 44.238, P = .000 at a 95% confidence interval). Neither patient nor wound characteristics were significantly different between the participants with noninfected or infected wounds. CONCLUSION: The results of this study demonstrate that incorporating quantitative skin temperature measurement into routine wound assessment provides a timely and reliable method for a wound care practitioner to quantify the heat associated with deep and surrounding skin infection and to monitor ongoing wound status. Study limitations may reduce transferability of these findings to wound types other than chronic leg ulcers. Further research is needed to support and strengthen these results. In this continuing education activity, the authors discuss the relationship between increased periwound skin temperature and wound infection, as well as validate use of a handheld infrared thermometer for the wound care practitioner.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".