Biomarkers for the early detection of pressure ulcers in the intensive care setting: A comparison between sub-epidermal moisture measurements and interleukin-1α

Nomogram model for predicting pressure injury in COPD patients using SII: a Chinese clinical study

Objectives

This study aims to investigate the association between the Systemic Immune-Inflammation Index (SII) and the development of pressure injuries (PI) in patients with chronic obstructive pulmonary disease (COPD). Additionally, a nomogram model based on the SII will be constructed to predict the probability of pressure injury (PI) occurrence in patients with COPD.

Methods

A retrospective analysis was performed on the clinical data of 844 patients with COPD who were admitted to the Affiliated Hospital of Guangdong Medical University between June 2018 and December 2019. Logistic regression analysis was employed to identify risk factors associated with the development of PI, and the Wald chi-square test was used to select variables for constructing a predictive nomogram. The performance of the nomogram was assessed, followed by internal validation. Additionally, clinical data from 452 patients with COPD admitted to the Second Affiliated Hospital of Guangdong Medical University between January 2024 and December 2024 were prospectively collected for external validation.

Results

A total of 844 patients with COPD were included in this study, with 590 cases in the training group and 254 cases in the internal validation group. The predictors included in the nomogram model were age, respiratory rate [Breathe (R)], duration of COPD history, Serum albumin (ALB), SII, paralysis, edema, and activities of daily living (ADL). The nomogram demonstrated strong predictive performance and calibration. The area under the curve and 95% confidence intervals were 0.77 (0.72-0.82) for the training group, 0.77 (0.70-0.85) for the internal validation group, and 0.73 (0.66-0.81) for the external validation group.

Conclusion

This study identified the SII, age, respiratory rate, duration of COPD history, ALB, paralysis, and ADL as independent risk factors for the development of PI in patients with COPD. A nomogram model was successfully developed based on SII and validated through both internal and external testing. The findings suggest that SII is a reliable predictor of PI development in patients with COPD, and the model demonstrates strong predictive performance.

Integrating technologies to enhance risk assessment for the early detection and prevention of pressure ulcers

Pressure ulcers (PU) are a globally recognised healthcare concern, with their largely preventable development prompting the implementation of targeted preventive strategies. Risk assessment is the first step to planning individualised preventive measures. However, despite the long use of risk assessment, and the >70 risk assessment tools currently available, PUs remain a significant concern. Various technological advancements, including artificial intelligence, subepidermal moisture measurement, cytokine measurement, thermography and ultrasound are emerging as promising tools for PU detection, and subsequent prevention of more serious PU damage. Given the rise in availability of these technologies, this advances the question of whether our current approaches to PU prevention can be enhanced with the use of technology. This article delves into these technologies, suggesting that they could lead healthcare in the right direction, toward optimal assessment and adoption of focused prevention strategies.

Biomarkers of local inflammation at the skin's surface may predict both pressure and diabetic foot ulcers

This commentary considers the similarities which exist between pressure ulcers (PUs) and diabetic foot ulcers (DFUs). It aims to describe what is known to be shared-both in theory and practice-by these wound types. It goes on to detail the literature surrounding the role of inflammation in both wound types. PUs occur following prolonged exposure to pressure or pressure in conjunction with shear, either due to impaired mobility or medical devices. As a result, inflammation occurs, causing cell damage. While DFUs are not associated with immobility, they are associated with altered mobility occurring as a result of complications of diabetes. The incidence and prevalence of both types of lesions are increased in the presence of multimorbidity. The prediction of either type of ulceration is challenging. Current risk assessment practices are reported to be ineffective at predicting when ulceration will occur. While systemic inflammation is easily measured, the presence of local or subclinical inflammation is harder to discern. In patients at risk of either DFUs or PUs, clinical signs and symptoms of inflammation may be masked, and systemic biomarkers of inflammation may not be elevated sufficiently to predict imminent damage until ulceration appears. The current literature suggests that the use of local biomarkers of inflammation at the skin's surface, namely oedema and temperature, may identify early tissue damage.

Pressure ulcer risk assessment in the ICU. Is it time for a more objective measure?

BACKGROUND

The Braden scale, one of the most widely used risk assessment tools is often criticized when used in the Intensive Care Unit. Most patients in the Intensive Care Unit are at risk of pressure ulcer development meaning that the Braden score will usually indicate high risk for these patients. This study set out to determine the correlation between Sub-Epidermal Moisture measurements and Braden scores among Intensive Care Unit patients.

METHODS

This study employed an observational research design. Braden score was assessed on all study days (1-5), in addition to visual skin assessment and Sub-Epidermal Moisture measurements at the sacrum and heels. Sub-Epidermal Moisture measurements were categorised as low (<0.5), borderline abnormal (≥0.5), and high (≥0.8). Correlation was assessed between Sub-Epidermal Moisture levels and Braden scores.

RESULTS

A total of 53 participants were recruited. The median (interquartile range) baseline Braden score was 9 (9-10) and 81 % (n = 43) of participants were at very high/high risk of pressure ulcer development. Braden scores remained relatively constant over time with little fluctuation in scores. 19 % (n = 10) of patients had normal (<0.5) Sub-Epidermal Moisture delta measurements on enrolment, and all developed abnormal measurements by day 2. There were no significant correlations between Braden scores and Sub-Epidermal Moisture measurements.

CONCLUSION

Although this was not its original intention, a missing link with the Braden scale is that it does not provide information on how patients are responding to the adverse effects of pressure and shear forces. Furthermore, in patients who are critically unwell, most patients are classified as being "at risk" of pressure ulcer development. Therefore, an objective measure of how patients are responding to pressure and shear forces at different anatomical areas is needed.

IMPLICATIONS TO CLINICAL PRACTICE

Sub-Epidermal Moisture measurements can offer more information, not only on identifying those who are at risk, but also how those patients are tolerating this risk at different anatomical sites.

The use of a protein network analysis to explore the complexity of early skin inflammation after oronasal mask application- A pilot study

Medical devices, such as non-invasive ventilation masks, save lives in health care settings but can be a cause of tissue injuries due to the pressure and shear loads on skin and soft tissue. These pressure injuries could be painful for the individual and cause a significant economic impact on healthcare providers. In the etiology of device related pressure ulcers, inflammation plays an important role. However, the exact nature and timing of inflammatory biomarker upregulation is still unknown in the early stages of skin damage. This study aimed to explore the inflammatory profile of vulnerable skin sites following non-invasive mask application on a convenience sample of eleven hospital patients. Seventy-one inflammatory proteins were explored from sebum sampled at the skin surface after oronasal mask application. A multivariate analysis to investigate differences between loaded and control site was conducted, with a protein network analysis used to explore interactions in the early inflammation. The study revealed that 21 cytokines and chemokines were important for the separation between loaded and control site. These proteins were associated with remodeling of tissue, vascular wound healing and/or cell death.

The correlation between sub-epidermal moisture measurement and other early indicators of pressure ulcer development-A prospective cohort observational study. Part 1. The correlation between sub-epidermal moisture measurement and ultrasound

The correlation between sub-epidermal moisture (SEM) and other early indicators of pressure ulcer (PU) development is yet to be determined. This three-part series aims to bridge this knowledge gap, through investigating SEM and its correlation with evidence-based technologies and assessments. This article focuses on the correlation between SEM and ultrasound. A prospective cohort observational study was undertaken between February and November 2021. Patients undergoing three surgery types were consecutively enrolled to the study following informed consent. Assessments were performed prior to and following surgery for 3 days at the sacrum, both heels and a control site, using a SEM scanner and high-frequency ultrasound scanner (5-15 MHz). Spearman's rank (rs ) explored the correlation between SEM and ultrasound. A total of 60 participants were included; 50% were male with a mean age of 58 years (±13.46). A statistically significant low to moderately positive correlation was observed between SEM and ultrasound across all anatomical sites (rs range = 0.39-0.54, p < 0.05). The only exception was a correlation between SEM and ultrasound on day 0 at the right heel (rs  = 0.23, p = 0.09). These results indicate that SEM and ultrasound agreed in the presence of injury; however, SEM was able to identify abnormalities before ultrasound.

Differences of bioelectrical impedance in the development and healing phase of pressure ulcers and erythema in mouse model

Pressure ulcers (PUs) are economically burdensome medical conditions. Early changes in pressure ulcers are associated with erythema. In this study, bioelectrical impedance was used to measure the differences between PUs and blanchable erythema. We divided 21 ICR mice into three groups: control, 1000 mmHg-1h, and 1000 mmHg-6h. Healthy skin, blanchable erythema, and PUs were induced on the dorsal skin. The results indicated an immediate increase in impedance, resistance, and reactance values in the pressure group after release, followed by a subsequent decrease until two days after release. Compared with the control group, impedance and reactance significantly increased by 30.9% (p < 0.05) and 30.1% (p < 0.01), respectively, in the 6 h-loading group immediately after release. One and two days after release, the 1 h-loading and 6 h-loading groups exhibited significantly different degrees of decline. One day after release, impedance and resistance decreased by 30.2% (p < 0.05) and 19.8% (p < 0.05), respectively, in the 1 h-loading group; while impedance, resistance, and reactance decreased by 39.2% (p < 0.01), 26.8% (p < 0.01), and 45.7% (p < 0.05), respectively, in the 6 h-loading group. Two days after release, in the 1 h-loading group, impedance and resistance decreased by 28.3% (p < 0.05) and 21.7% (p < 0.05), respectively; while in the 6 h-loading group, impedance, resistance, and reactance decreased by 49.8% (p < 0.001), 34.2% (p < 0.001), and 59.8% (p < 0.01), respectively. One and two days after release the pressure group reductions were significantly greater than those in the control group. Additionally, we monitored changes during wound healing. Distinguishing early PUs from blanchable erythema by noninvasive bioelectrical impedance technology may have applications value in early assessment of PUs.

[Research advances on application of sub-epidermal moisture scanner in monitoring tissue viability of early pressure injuries]

Pressure injury (PI) not only reduces the quality of life of patients but also is expensive to manage, placing a heavy financial burden on patients and their families, and society. Despite the increasing diversity of methods used to identify early PI, there are still few methods that can truly and accurately predict early PI. The sub-epidermal moisture scanner is the first U.S. Food and Drug Administration-authorized PI management device that can predict the occurrence and development of PI by measuring the level of local tissue bio-capacitance and monitoring the tissue viability. As an emerging diagnostic instrument, the sub-epidermal moisture scanner has already shown great advantages in clinical practice, which can promote the informatization, digitization, and intelligent prevention and management of PI. This paper introduces the pathophysiological mechanism of PI, elucidates the working principle and parameter settings of the sub-epidermal moisture scanner, its clinical application in monitoring tissue viability in early PI, and its limitation, and looks forward to its future development.

Systematic Review for Risks of Pressure Injury and Prediction Models Using Machine Learning Algorithms

Pressure injuries are increasing worldwide, and there has been no significant improvement in preventing them. This study is aimed at reviewing and evaluating the studies related to the prediction model to identify the risks of pressure injuries in adult hospitalized patients using machine learning algorithms. In addition, it provides evidence that the prediction models identified the risks of pressure injuries earlier. The systematic review has been utilized to review the articles that discussed constructing a prediction model of pressure injuries using machine learning in hospitalized adult patients. The search was conducted in the databases Cumulative Index to Nursing and Allied Health Literature (CINAHIL), PubMed, Science Direct, the Institute of Electrical and Electronics Engineers (IEEE), Cochrane, and Google Scholar. The inclusion criteria included studies constructing a prediction model for adult hospitalized patients. Twenty-seven articles were included in the study. The defects in the current method of identifying risks of pressure injury led health scientists and nursing leaders to look for a new methodology that helps identify all risk factors and predict pressure injury earlier, before the skin changes or harms the patients. The paper critically analyzes the current prediction models and guides future directions and motivations.