A rare presentation of Rosai-Dorfman-Destombes disease with central nervous system involvement and cutaneous wounds.

OBJECTIVE: The aim of this case report is to investigate an uncommon presentation of Rosai-Dorfman-Destombes (RDD) disease, and discuss possible differential diagnoses and treatment options for this pathology. RDD is a rare disorder of histiocytes that typically presents in patients as painless cervical lymphadenopathy. However, this case involves a patient with the central nervous system (CNS) type of RDD who later developed cutaneous lesions. METHOD: Several differential diagnoses were examined, including hidradenitis suppurativa, pilonidal cyst and pressure ulcers. It is important to be able to exclude these diagnoses based on the presentation, patient demographic and wound location. RESULTS: Biopsies verified the presence of RDD in the patient's suprasellar hypothalamic mass and skin lesions, confirming the patient had both CNS-RDD and cutaneous-RDD in the absence of lymphadenopathy. CONCLUSION: Recognising the unique manifestations of rare diseases such as RDD prevents delay of proper intervention and treatment.

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.

Detecting Patient Position Using Bed-Reaction Forces for Pressure Injury Prevention and Management.

A key best practice to prevent and treat pressure injuries (PIs) is to ensure at-risk individuals are repositioned regularly. Our team designed a non-contact position detection system that predicts an individual's position in bed using data from load cells under the bed legs. The system was originally designed to predict the individual's position as left-side lying, right-side lying, or supine. Our previous work suggested that a higher precision for detecting position (classifying more than three positions) may be needed to determine whether key bony prominences on the pelvis at high risk of PIs have been off-loaded. The objective of this study was to determine the impact of categorizing participant position with higher precision using the system prediction F1 score. Data from 18 participants was collected from four load cells placed under the bed legs and a pelvis-mounted inertial measurement unit while the participants assumed 21 positions. The data was used to train classifiers to predict the participants' transverse pelvic angle using three different position bin sizes (45°, ~30°, and 15°). A leave-one-participant-out cross validation approach was used to evaluate classifier performance for each bin size. Results indicated that our prediction F1 score dropped as the position category precision was increased.

Validity and reliability of the Waterlow scale for assessing pressure injury risk in critical adult patients: A multi-centre cohort study.

AIM: To evaluate the predictive validity and reliability of the Waterlow scale in critically adult hospitalised patients. DESIGN: A multi-centre cohort study. METHODS: This study was conducted in 72 intensive care units (ICUs) in 38 tertiary hospitals in Gansu Province, China. All adults admitted to the ICU for greater than or equal to 24 h without pressure injury (PI) on admission were screened by the Waterlow scale on admission, during ICU stay and ICU discharge from April 2021 to February 2023. Receiver operating characteristic (ROC) curves were used to determine a potential cut-off value for critical adult hospitalised patients. Cut-off values were then determined using Youden's index, and sensitivity, specificity, positive predictive value, negative predictive value and accuracy were calculated based on these cut-off values. Test-retest reliability was used to evaluate inter-rater reliability. RESULTS: A total of 5874 critical patients on admission were included, and 5125 of them were assessed regularly. The area under curve (AUC) was 0.623 (95% CI, 0.574-0.690), with a cut-off score of 19 showing the best balance among sensitivity of 62.7%, specificity of 57.4%, positive predictive value of 2.07% and negative predictive value of 99.08%. The test-retest reliability between the first assessment and the regular assessment was 0.447. CONCLUSIONS: The Waterlow scale shows insufficient predictive validity and reliability in discriminating critical adults at risk of PI development. To further modify the items of the Waterlow scale, exploring specific risk factors for PI in the ICU and clarifying their impact degree was necessary. Risk predictive models or better tools are inevitable in the future. PATIENT OR PUBLIC CONTRIBUTION: Patients or family members supported nurses with PI risk assessment, skin examination and other activities during the inquiry.

Comparison of the predictive validity of the Braden and Waterlow scales in intensive care unit patients: A multicentre study.

BACKGROUND: The first step in preventing pressure injuries (PIs), which represent a significant burden on intensive care unit (ICU) patients and the health care system, is to assess the risk for developing PIs. A valid risk assessment scale is essential to evaluate the risk and avoid PIs. OBJECTIVES: To compare the predictive validity of the Braden scale and Waterlow scale in ICUs. DESIGN: A multicentre, prospective and cross-sectional study. METHODS: We conducted this study among 6416 patients admitted to ICUs in Gansu province of China from April 2021 to October 2022. The incidence and characteristics of PIs were collected. The risk assessment of PIs was determined using the Braden and Waterlow scale. The sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve of the two scales were compared. RESULTS: Out of 5903 patients, 72 (1.2%) developed PIs. The sensitivity, specificity, positive and negative predictive, and the area under the curve of the Braden scale were 77.8%, 50.9%, 0.014 and 0.996, and 0.689, respectively. These values for the Waterlow scale were 54.2%, 71.1%, 0.017, 0.994 and 0.651. CONCLUSIONS: Both scales could be used for risk assessment of PIs in ICU patients. However, the accuracy of visual inspection for assessment of skin colour, nursing preventive measures for patients and scales inter-rater inconsistency may limited the predictive validity statistics. RELEVANCE TO CLINICAL PRACTICE: Both scales could be used for PIs risk assessment. The low specificity of the Braden scale and low sensitivity of the Waterlow scale remind medical staff to use them in combination with clinical judgement and other objective indicators. PATIENT OR PUBLIC CONTRIBUTION: This study was designed to enhance the management of PIs. Patients and the general public were not involved in the study design, analysis, and interpretation of the data or manuscript preparation.

Applying Object Detection and Large Language Model to Establish a Smart Telemedicine Diagnosis System with Chatbot: A Case Study of Pressure Injuries Diagnosis System.

Background: The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical examination. Evaluating pressure injuries is time consuming, energy intensive, and inconsistent. Most of today's telemedicine platforms utilize graphical user interfaces with complex operational procedures and limited channels for information dissemination. The study aims to establish a smart telemedicine diagnosis system based on YOLOv7 and large language model. Methods: The YOLOv7 model is trained using a clinical data set, with data augmentation techniques employed to enhance the data set to identify six types of pressure injury images. The established system features a front-end interface that includes responsive web design and a chatbot with ChatGPT, and it is integrated with a database for personal information management. Results: This research provides a practical pressure injury staging classification model with an average F1 score of 0.9238. The system remotely provides real-time accurate diagnoses and prescriptions, guiding patients to seek various medical help levels based on symptom severity. Conclusions: This study establishes a smart telemedicine auxiliary diagnosis system based on the YOLOv7 model, which possesses capabilities for classification and real-time detection. During teleconsultations, it provides immediate and accurate diagnostic information and prescription recommendations and seeks various medical assistance based on the severity of symptoms. Through the setup of a chatbot with ChatGPT, different users can quickly achieve their respective objectives.

Evaluating Natural Language Processing Packages for Predicting Hospital-Acquired Pressure Injuries From Clinical Notes.

Incidence of hospital-acquired pressure injury, a key indicator of nursing quality, is directly proportional to adverse outcomes, increased hospital stays, and economic burdens on patients, caregivers, and society. Thus, predicting hospital-acquired pressure injury is important. Prediction models use structured data more often than unstructured notes, although the latter often contain useful patient information. We hypothesize that unstructured notes, such as nursing notes, can predict hospital-acquired pressure injury. We evaluate the impact of using various natural language processing packages to identify salient patient information from unstructured text. We use named entity recognition to identify keywords, which comprise the feature space of our classifier for hospital-acquired pressure injury prediction. We compare scispaCy and Stanza, two different named entity recognition models, using unstructured notes in Medical Information Mart for Intensive Care III, a publicly available ICU data set. To assess the impact of vocabulary size reduction, we compare the use of all clinical notes with only nursing notes. Our results suggest that named entity recognition extraction using nursing notes can yield accurate models. Moreover, the extracted keywords play a significant role in the prediction of hospital-acquired pressure injury.

Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection.

OBJECTIVE: To establish a risk assessment model to predict postoperative National Pressure Injury Advisory Panel stage 2 or higher pressure injury (PI) risk in patients undergoing acute type A aortic dissection surgery. METHODS: This retrospective assessment included consecutive patients undergoing acute type A aortic dissection surgery in the authors' hospital from September 2017 to June 2021. The authors used LASSO (logistic least absolute shrinkage and selection operator) regression analysis to identify the most relevant variables associated with PI by running cyclic coordinate descent with 10-times cross-validation. The variables selected by LASSO regression analysis were subjected to multivariate logistic analysis. A calibration plot, receiver operating characteristic curve, and decision curve analysis were used to validate the model. RESULTS: There were 469 patients in the study, including 94 (27.5%) with postoperative PI. Ten variables were selected from LASSO regression: body mass index, diabetes, Marfan syndrome, stroke, preoperative skin moisture, hemoglobin, albumin, serum creatinine, platelet, and d-dimer. Four risk factors emerged after multivariate logistic regression: Marfan syndrome, preoperative skin moisture, albumin, and serum creatinine. The area under the receiver operating characteristic curve of the model was 0.765. The calibration plot and the decision curve analysis both suggested that the model was suitable for predicting postoperative PI. CONCLUSIONS: This study built an efficient predictive model that could help identify high-risk patients.

Improving Wound Healing and Infection Control in Long-term Care with Bacterial Fluorescence Imaging.

BACKGROUND: High bacterial burden stalls wound healing and can quickly progress to infection and sepsis in complex, older-adult patients in long-term care (LTC) or skilled nursing facilities (SNFs). OBJECTIVE: To investigate the outcomes of point-of-care fluorescence (FL) imaging (MolecuLight i:X) of bacterial loads, which are frequently asymptomatic, to inform customized wound treatment plans for patients in LTC/SNFs. METHODS: In this retrospective pre/postinterventional cohort study, the authors compared the healing and infection-associated outcomes of 167 pressure injuries from 100 Medicare beneficiaries before and after implementation of FL imaging. RESULTS: Most patient demographics and wound characteristics did not differ significantly between the standard-of-care (SOC; n = 71 wounds) and FL (n = 96 wounds) cohorts. Significantly more wounds (+71.0%) healed by 12 weeks in the FL cohort (38.5%) versus the SoC cohort (22.5%). Wounds in the FL cohort also healed 27.7% faster (-4.8 weeks), on average, and were 1.4 times more likely to heal per Kaplan-Meier survival analysis (hazard ratio = 1.40; 95% CI, 0.90-2.12). Infection-related complications decreased by 75.3% in the FL cohort, and a significant shift from largely systemic to topical antibiotic prescribing was evidenced. CONCLUSIONS: Fluorescence-imaging-guided management of wounds significantly improved healing and infection outcomes in highly complex and multimorbid patients in LTC/SNFs. Proactive bacterial infection management via local treatments was enabled by earlier, objective detection. These reported outcome improvements are comparable to randomized controlled trials and cohort studies from less compromised, selectively controlled outpatient populations. Fluorescence imaging supports proactive monitoring and management of planktonic and biofilm-encased bacteria, improving patient care in a complex, real-world setting.

Overlooked Pain Assessment Records in Patients with Pressure Injuries During the COVID-19 Pandemic: A Retrospective Data Analysis.

BACKGROUND: During the COVID-19 pandemic, healthcare professionals focused on identifying the cause of hemodynamic instability in patients and may have neglected to assess pressure injury (PI)-related pain. Although pain is an early indicator of PI development, there has been no systematic evaluation of PI-related pain in patients. OBJECTIVE: To review nurses' records of PI-related pain in patients who developed PIs during the COVID-19 pandemic. METHODS: This retrospective, descriptive study included data from 510 patients at one hospital. Collected data included patient demographics (age, sex, diagnosis, and comorbidities), PI classification, and assessment of PI-related pain. Assessment data regarding PI-related pain included the characteristics of the pain, the type of analgesia (pharmacologic/nonpharmacologic) administered before and after PI management (debridement, dressing change, etc), the route of administration, and the frequency of pain assessment before and after analgesia. RESULTS: The mean age of the patients (60.4% men) was 28.96 (SD, 5.82) years, and the mean length of hospital stay was 26.15 (SD, 16.1) days. Overall, 43.1% of the patients were treated in the ICU, 68.0% were conscious, and 18.6% tested positive for COVID-19. Deep-tissue injuries occurred in 57.5% of patients, with 48.6% developing stage 2 PI. The sacral region was the most common area for PI development (44.8%). The mean duration of repositioning in patients with PI was 23.03 (SD, 5.4) hours. Only 0.40% of patients (n = 2) were evaluated for pain, and only one patient was assessed for pain before and after analgesia was administered. CONCLUSIONS: The findings suggest a lack of comprehensive evaluation and records concerning PI-related pain in patients with COVID-19.

Sacral Ulcer Development Risk Among Older Adult Patients in North Texas Rehabilitation Hospitals: Role of Comorbidities, Lifestyle, and Personal Factors.

PURPOSE: Sacral ulcers are a serious mortality risk for older adults; thus, we aimed to determine sacral ulcer risk factors among older adults who were recently admitted to rehabilitation hospitals. METHOD: We conducted a retrospective cohort study using the Texas Inpatient Discharge database (2021). The study included 1,290 rehabilitation hospital patients aged ≥60 years diagnosed with sacral ulcers. The control group comprised 37,626 rehabilitation hospital patients aged ≥60 years without sacral ulcers. Binary logistic regression was used to identify risks for sacral ulcer development adjusting for patient demographics, insurance type, and lifestyle. RESULTS: Comorbidities of dementia, Parkinson's disease, type 2 diabetes, and cardiac dysrhythmias were significantly associated with increased risk of sacral ulcers. Longer length of stay, Medicare, and Medicare HMO were also associated with sacral ulcers. Demographically, older age, male sex, identifying as African American, and having malnutrition all had a 50% increased prevalence of sacral ulcers. CONCLUSION: Findings indicate a need to proactively treat chronic comorbidities in vulnerable populations to reduce their possible risk for hospital-acquired infections and excess mortality from sacral ulcers. [Journal of Gerontological Nursing, 50(2), 32-41.].

Detecting Early-Stage Pressure Injury in Patients With Dark Skin Tones Using an Enhanced Physical Assessment Technique and Halogen Lighting.

PURPOSE: The purpose of this quality improvement project was to identify stage 1 pressure injuries (PIs) in patients with darker skin tones using an enhanced skin assessment (Skin Assessment for Dark Skin, SADS) and halogen lighting. PARTICIPANTS AND SETTING: This quality improvement project was conducted on 3 units at a large university teaching hospital in Southeast Michigan. The project was originally designed so that participating patients were identified by bedside nurses as having sufficient melanin to obscure blanching on the hand/forearm using regular lighting, but this goal was not met. Data analysis is based on patients who self-identified as African American or Black, Native Hawaiian or Pacific Islander, Asian, American Indian, and Native Alaskan. Bedside nurses participating in this project were also asked to complete a questionnaire describing their knowledge and experiences with this project and assessment of early-stage PI in patients with darker skin tones. APPROACH: The Iowa Model of Evidence-Based Practice was used to guide this quality improvement initiative. Following a trigger event, we reviewed pertinent literature and developed an enhanced technique for assessing patients with darker skin tones that involved use of halogen lighting (SADS) and documentation of findings. We selected units from our facility and taught nurses to apply the SADS approach. Data from the electronic medical record and a survey of participating nurses were used to compare findings before and after project implementation. Comparisons were based on descriptive data analysis. OUTCOMES: Following implementation of the enhanced physical assessment, the participating units experienced a 6% decrease in the total number of facility-acquired PIs during the implementation period. IMPLICATIONS FOR PRACTICE: The enhanced physical assessment, when paired with halogen lighting, enhanced identification of stage 1 PI in persons with dark skin. The assessment method was easy to teach, learn, and can be performed at the bedside as part of a shift assessment which routinely includes inspection of skin.

Fluctuations in Detection Indicators and Their Significance for the Diagnosis of Early Pressure Injury in Rat Models.

PURPOSE: The aim of this study was to identify the most meaningful diagnostic indicator for distinguishing blanchable erythema (BE) and stage 1 pressure injury (early PI) in an in vivo (rat) model. DESIGN: A prospective case-control design was used to complete a horizontal and vertical comparison of detection indicators during the process of fading of BE or the deterioration of early PI into ulcer in rat models. MATERIALS AND SETTING: The sample comprised 5 hairless rats with 20 injuries, of which 10 were BE and the other 10 were early PI. Data were collected at Nagano College of Nursing in 2020 in Nagano, Japan. METHODS: The BE and PI rat models were established by subjecting the dorsal skin of a hairless rat to compression between 2 neodymium magnets for 45 minutes and 3.45 hours, respectively. The affected skin was observed based on the following: (1) photography, (2) hardness, (3) temperature, (4) moisture, and (5) spectrophotometric (a* value and ultraviolet [UV] reflectance) measurements. All measurements of BE were performed at the beginning to 60 minutes after decompression, and those for early PI were performed until 48 hours after decompression. RESULTS: Multiple BE factors, such as the degree of erythema (macroscopy and a* value), hardness, temperature, and moisture, were found to have unstable fluctuations. Only UV reflectance gradually decreased from 6 hours and decreased significantly at 48 hours after decompression (P = .001 vs 1 hour). In contrast to early PI, erythema in BE obviously faded within 10 minutes. CONCLUSIONS: Study findings indicate that a continuous decrease in UV reflectance can reflect the worsening of hemorrhage in early (stage 1) PI. In contrast, other indicators including photography, skin hardness, temperature, and moisture fluctuated and did not prove predictive for PI progression. The obvious fading of erythema in BE a short time after decompression can be used for clinical observations.

The correlation between sub-epidermal moisture assessment and other early indicators of pressure ulcer development: A prospective cohort observational study. Part 2. The correlation between sub-epidermal moisture assessment, temperature, epidermal hydration and pain.

There is growing interest in the roles of temperature, epidermal hydration (EH) and pain in pressure ulcer (PU) development. Investigating correlations between these measures and sub-epidermal moisture (SEM) will address this knowledge deficit. A prospective observational study enrolled 60 surgical patients from February to November 2021. SEM, temperature, EH and pain were assessed using a SEM scanner, thermography imaging, skin hydration device and numeric pain intensity scale, respectively. Measurements were taken at the sacrum, both heels and a control site, before and after surgery for 3 days. Data were analysed using Pearson or Spearman's correlation. Of the participants, 50% were male with a mean age of 58 years (±13.46). Low positive/negative correlations between SEM and temperature were found at the sacrum. However, after removing outliers, these results were not statistically significant. Other sites and follow-up days showed negligible correlations. No evidence of a correlation, to low correlations between SEM and EH were observed, but unreliable due to little variation in EH at the heels. Pain showed negligible correlations with SEM. This study did not find consistent evidence of a correlation between SEM, temperature, EH and pain, highlighting the unreliability of temperature and EH for early PU detection. Post-operative pain may also confound accurate pain assessments.

Traditional Chinese-version reliability test of the Pieper-Zulkowski pressure ulcer knowledge: Psychometric and assessment.

This study was to translate the Pieper-Zulkowski pressure ulcer knowledge test (PZ-PUKT) into Traditional Chinese and evaluate its psychometric properties as well as identify the predictors of knowledge on pressure injury. The PZ-PUKT was translated into Traditional Chinese (TC-PZ-PUKT), and its content validity was evaluated. A total of 296 nurses participated in this study and completed the 72-item TC-PZ-PUKT online. The reliability of the TC-PZ-PUKT was analysed by evaluating its internal consistency and test-retest reliability. Hierarchical regression was used to determine factors associated with TC-PZ-PUKT scores. Content validity was achieved with a score of 0.986. Internal consistency was observed to be reliable, with a Cronbach's alpha of 0.858. The mean knowledge score on the TC-PZ-PUKT was 72.5%, with a 1-week test-retest reliability of r = 0.849. Education level, certification as a wound specialist and self-learning through reading articles, books or guidelines on pressure injury were significantly associated with TC-PZ-PUKT scores. The TC-PZ-PUKT is a valid and reliable tool. Education level, certification as a wound specialist and self-learning regarding pressure injury are related to knowledge of pressure injury.

Pressure ulcers: aSSKINg framework study.

Pressure ulcers (PUs) represent a burden to the health economy and patients alike. Despite national and international guidelines regarding the management of risk, the incidence and prevalence across England remains high. Detecting early the risk of PUs is paramount, and requires using a valid risk assessment tool alongside clinical judgement and management of associated risk factors. There is a need to implement prevention strategies. Introducing care bundles for pressure ulcers, for example SKIN, SSKIN and most recently aSSKINg, is designed to guide clinicians and reduce variations in care. This article presents a review of the evidence on compliance with guidelines, frameworks, pathways or care bundles within primary and secondary care settings. This article focuses on the literature review that was conducted to inform a subsequent clinical audit of compliance with the aSSKINg framework in a Community NHS Foundation Trust in the South East of England.

Machine learning to develop a predictive model of pressure injury in persons with spinal cord injury.

STUDY DESIGN: A 5-year longitudinal, retrospective, cohort study. OBJECTIVES: Develop a prediction model based on electronic health record (EHR) data to identify veterans with spinal cord injury/diseases (SCI/D) at highest risk for new pressure injuries (PIs). SETTING: Structured (coded) and text EHR data, for veterans with SCI/D treated in a VHA SCI/D Center between October 1, 2008, and September 30, 2013. METHODS: A total of 4709 veterans were available for analysis after randomly selecting 175 to act as a validation (gold standard) sample. Machine learning models were created using ten-fold cross validation and three techniques: (1) two-step logistic regression; (2) regression model employing adaptive LASSO; (3) and gradient boosting. Models based on each method were compared using area under the receiver-operating curve (AUC) analysis. RESULTS: The AUC value for the gradient boosting model was 0.62 (95% CI = 0.54-0.70), for the logistic regression model it was 0.67 (95% CI = 0.59-0.75), and for the adaptive LASSO model it was 0.72 (95% CI = 0.65-80). Based on these results, the adaptive LASSO model was chosen for interpretation. The strongest predictors of new PI cases were having fewer total days in the hospital in the year before the annual exam, higher vs. lower weight and most severe vs. less severe grade of injury based on the American Spinal Cord Injury Association (ASIA) Impairment Scale. CONCLUSIONS: While the analyses resulted in a potentially useful predictive model, clinical implications were limited because modifiable risk factors were absent in the models.

Pressure Injuries: Prevention, Evaluation, and Management.

Pressure injuries are localized damage to skin or soft tissue. They commonly occur over bony prominences and often present as an intact or open wound. Pressure injuries are common and costly, and they significantly impact patient quality of life. Comprehensive skin assessments are crucial for evaluating pressure injuries. Staging of pressure injuries should follow the updated staging system of the National Pressure Injury Advisory Panel. Risk assessments allow for appropriate prevention and care planning, and physicians should use a structured, repeatable approach. Prevention of pressure injuries focuses on assessing and optimizing nutritional status, repositioning the patient, and providing appropriate support surfaces. Treatment involves pressure off-loading, nutritional optimization, appropriate bandage selection, and wound site management. Pressure injuries and surrounding areas should be cleaned, with additional debridement of devitalized tissue and biofilm if necessary. All injuries should be monitored for local infection, biofilms, and osteomyelitis. Appropriate wound dressings should be selected based on injury stage and the quality and volume of exudate.

Differential diagnosis of stage 2, 3 and 4 pressure injuries of the pelvis and lower extremity: a case series.

Constant, unrelieved pressure of local tissue, particularly over bony prominences, may provoke damage that progresses to necrosis and pressure injury (PI). Differentiating PIs from conditions of similar appearance is imperative to minimising complications and implementing prompt treatment. This case series describes several conditions that may be mistaken for a PI. Outlined are the key differences in patient history, presentation and clinical cues that assist in correctly identifying the true pathology behind these conditions. Conditions reviewed included: pyoderma gangrenosum; necrotising fasciitis; genital herpes; Marjolin ulcer, Rosai-Dorfman disease; vascular disease; coagulopathies; calciphylaxis; trauma and surgical wounds; pilonidal cysts; graft-versus-host disease; hidradenitis suppurativa; Stevens-Johnson syndrome; epidermolysis bullosa; radiation wounds; spider bites; and end-of-life skin failure pressure ulcers (also known as Kennedy ulcers). Although commonly recognised and diagnosed, stage 2, 3 and 4 PIs occasionally prove to be difficult to pinpoint, with undefined characteristics and similarities in presentation to several other conditions. Therefore, it is clinically vital to be aware of their appearance, risk factors and aetiology in order to make an appropriate patient assessment and avoid misdiagnosis.