Malnutrition is a collective term that includes both undernutrition and malnutrition. Malnutrition presents with and without inflammation, is reported in underweight, normal weight, and overweight individuals, and is associated with undesirable alterations in body composition, and diminished functional status. Older adults commonly experience dwindling nutritional status as evidenced by insidious weight loss, insufficient dietary intake, loss of muscle mass, quality, and strength, declining functional status, and other physical and emotional decline indicators. Sustained pressure, acute trauma, malnutrition, and inflammatory-driven chronic conditions increase the risk for skin integrity issues.

Pressure injuries are a common chronic wound in the older adult. Care of pressure injuries is an interprofessional effort and involves physicians, nurses, registered dieticians, rehabilitation therapists, and surgical subspecialties. Numerous treatment modalities exist but have varying evidence to substantiate their efficacy. All primary and other care providers, particularly geriatricians, need to be aware of current evidence-based prevention and treatment standards. When healing is not expected, palliative care should be considered to avoid futile procedures and preserve dignity and quality of life.

BACKGROUND: Nurses\' knowledge of pressure injuries causes and risk factors helps to prevent their occurrences and protect the patient.
OBJECTIVE: To assess the level of knowledge of medical device-related pressure injuries and to identify risk factors that affect the knowledge.
METHODS: A cross-sectional design was used in this study considering a convenience sample from critical care nurses. The nurses were invited to complete the Medical Device-Related Pressure Injuries Knowledge Questionnaire.
RESULTS: About 71 nurses participated in the study. The mean score of MDRPI_KQ was 23.28 ± 4.14 out of 36. Mann-Whitney Test did not show statistically significant relationships between the MDRPI_KQ mean score and related variables (p > 0.05). The regression results indicated that the three predictors explained 46.4% of the variance (R2 = 0.215, F(3, 6.114) = 3.75, p = 0.001). It was found that the Frequency of encountering a patient with MDRPIs significantly predicted MDRPI_KQ score, job position, and assuming the care responsibility for MDRPIs in the department.
CONCLUSIONS: Poor knowledge of pressure injuries can negatively affect patient care so training programs and policies should be developed based on the level of knowledge and practices of the staff to be more effective.

BACKGROUND: The association between underweight and pressure injuries (PIs) has been established in several studies. However, there is a lack of well-designed research investigating the connection between overweight and obesity with these injuries.
OBJECTIVE: This meta-analysis aims to investigate the dose-response relationship between body mass index (BMI) and the risk of PIs in adult hospitalized patients.
METHODS: PubMed, Web of Science, and MEDLINE Databases were searched from inception to May 2024. Observational articles with at least three BMI categories were included in the study. BMI was defined as underweight, normal weight, overweight, and morbid obesity for the meta-analysis. The non-linear relationship between BMI and the risk of PIs in hospitalized adults was investigated using restricted cubic spline models. Fractional polynomial modeling was used.
RESULTS: Eleven articles reporting at least 3 categories of BMI met the inclusion criteria, including 31,389 participants. Compared to patients with normal weight, those with underweight, obesity, and morbid obesity exhibited an increased risk of PIs, with odds ratios of 1.70 (95%CI:1.50-1.91), 1.12 (95%CI:1.02-1.24), 1.70 (95%CI:1.13-2.55), respectively. A J-shaped dose-response model was established for the relationship between PI risk and BMI (Pnon-linearity < 0.001, Plinearity = 0.745).
CONCLUSIONS: The J-shaped dose-response pattern revealed that underweight, obesity and morbid obesity heightened the risk of PIs in hospitalized adults. Lower and higher BMI values may signify an increased risk for PIs, particularly among the elderly with lower BMI, providing valuable guidance for medical staff.

BACKGROUND: Surveillance of hospital-acquired pressure injuries (HAPI) is often suboptimal when relying on administrative health data, as International Classification of Diseases (ICD) codes are known to have long delays and are undercoded. We leveraged natural language processing (NLP) applications on free-text notes, particularly the inpatient nursing notes, from electronic medical records (EMRs), to more accurately and timely identify HAPIs.
OBJECTIVE: This study aimed to show that EMR-based phenotyping algorithms are more fitted to detect HAPIs than ICD-10-CA algorithms alone, while the clinical logs are recorded with higher accuracy via NLP using nursing notes.
METHODS: Patients with HAPIs were identified from head-to-toe skin assessments in a local tertiary acute care hospital during a clinical trial that took place from 2015 to 2018 in Calgary, Alberta, Canada. Clinical notes documented during the trial were extracted from the EMR database after the linkage with the discharge abstract database. Different combinations of several types of clinical notes were processed by sequential forward selection during the model development. Text classification algorithms for HAPI detection were developed using random forest (RF), extreme gradient boosting (XGBoost), and deep learning models. The classification threshold was tuned to enable the model to achieve similar specificity to an ICD-based phenotyping study. Each model\'s performance was assessed, and comparisons were made between the metrics, including sensitivity, positive predictive value, negative predictive value, and F1-score.
RESULTS: Data from 280 eligible patients were used in this study, among whom 97 patients had HAPIs during the trial. RF was the optimal performing model with a sensitivity of 0.464 (95% CI 0.365-0.563), specificity of 0.984 (95% CI 0.965-1.000), and F1-score of 0.612 (95% CI of 0.473-0.751). The machine learning (ML) model reached higher sensitivity without sacrificing much specificity compared to the previously reported performance of ICD-based algorithms.
CONCLUSIONS: The EMR-based NLP phenotyping algorithms demonstrated improved performance in HAPI case detection over ICD-10-CA codes alone. Daily generated nursing notes in EMRs are a valuable data resource for ML models to accurately detect adverse events. The study contributes to enhancing automated health care quality and safety surveillance.

UNASSIGNED: Hard-shell toilet seats may compromise safety and hinder the participation of individuals at risk for pressure injuries (PIs) when using these facilities away from home in public, hotel, or family/friend restrooms. Moreover, people often add \"wash-cloths\" for additional padding for comfort, and to reduce the risk of PIs due to pressure or shearing on their wheelchairs surfaces. This study investigated the utilization of portable pads, initially designed for toilet use but adaptable to various places and contexts, while examining pad usability.
UNASSIGNED: A cross-sectional descriptive survey design.
UNASSIGNED: Inpatient care, outpatient care, and community setting.
UNASSIGNED: 45 individuals at risk of PIs.
UNASSIGNED: Participants extended the use of these pads beyond toilets, employing them as wheelchair armrest and leg rest pads in other settings. Feedback from a customized questionnaire indicated high levels of usefulness (8.5/10) and ease of use (9.1/10) attributed to the pads. Among the features, the top three favored were ease of use, comfort/cushioning, and function. Participants expressed a desire for a variety of sizes and colors to enable versatile usage and suggested incorporating a pocket for storing small items.
UNASSIGNED: Individuals at risk of PIs require cushioning not only on hard-shell toilet seats, but also for additional padding, protection and enhancing the use of wheelchairs. Rehabilitation professionals can play a crucial role in educating and training both clients and caregivers to understand PI prevention, enabling them to effectively leverage the pads in appropriate situations, thereby enhancing their comfort in their wheelchairs during social engagement.

Pressure injuries are a significant comorbidity and lead to increased overall healthcare costs. Several European and global studies have assessed the burden of pressure injuries; however, no comprehensive analysis has been completed in the United States. In this study, we investigated the trends in the burden of pressure injuries among hospitalised adults in the United States from 2009 to 2019, stratified by sociodemographic subgroups. The length of admission, total cost of hospitalisation, and sociodemographic data was extracted from the National Inpatient Sample provided by the Healthcare Cost and Utilisation Project, Agency for Healthcare Research and Quality. Overall, the annual prevalence of pressure injuries and annual mean hospitalisation cost increased ($69,499.29 to $102,939.14), while annual mean length of stay decreased (11.14-9.90 days). Among all races, minority groups had higher average cost and length of hospitalisation. Our findings suggest that while the length of hospitalisation is decreasing, hospital costs and prevalence are rising. In addition, differing trends among racial groups exist with decreasing prevalence in White patients. Further studies and targeted interventions are needed to address these differences, as well as discrepancies in racial groups.

BACKGROUND: The development of models using deep learning (DL) to assess pressure injuries from wound images has recently gained attention. Creating enough supervised data is important for improving performance but is time-consuming. Therefore, the development of models that can achieve high performance with limited supervised data is desirable.
METHODS: This retrospective observational study utilized DL and included patients who received medical examinations for sacral pressure injuries between February 2017 and December 2021. Images were labeled according to the DESIGN-R® classification. Three artificial intelligence (AI) models for assessing pressure injury depth were created with a convolutional neural network (Categorical, Binary, and Combined classification models) and performance was compared among the models.
RESULTS: A set of 414 pressure injury images in five depth stages (d0 to D4) were analyzed. The Combined classification model showed superior performance (F1-score, 0.868). The Categorical classification model frequently misclassified d1 and d2 as d0 (d0 Precision, 0.503), but showed high performance for D3 and D4 (F1-score, 0.986 and 0.966, respectively). The Binary classification model showed high performance in differentiating between d0 and d1-D4 (F1-score, 0.895); however, performance decreased with increasing number of evaluation steps.
CONCLUSIONS: The Combined classification model displayed superior performance without increasing the supervised data, which can be attributed to use of the high-performance Binary classification model for initial d0 evaluation and subsequent use of the Categorical classification model with fewer evaluation steps. Understanding the unique characteristics of classification methods and deploying them appropriately can enhance AI model performance.

Background In neurosurgical procedures where the park bench position is employed, the risk of perioperative pressure injuries is elevated due to the limited contact surface area, with the head and part of the upper torso extending beyond the surgical table. This study aimed to examine the effects of preventative measures against such injuries, proposing a potential standard for postural fixation in these surgeries. Methods Conducted at a medical center, from January 2017 to March 2023, this prospective cohort study involved participants aged 20 and above who underwent neurosurgical procedures in the park bench position under general anesthesia. The focus was on comparing the incidence of pressure injuries between intervention and control groups. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results Out of 65 patients enrolled, 28 were assigned to each of the intervention and control groups. The control group experienced 17 instances of postoperative pressure injuries and skin disorders in areas prone to pressure, such as the axillary and greater trochanter regions. Conversely, the intervention group reported no such incidents, underscoring the efficacy of meticulous surgical positioning and management of bodily pressure, temperature, humidity, and microclimate. Conclusion Implementing preventive measures in neurosurgical park bench procedures significantly reduces the incidence of postoperative pressure injuries and skin disorders. These findings advocate for the adoption of standardized postural fixation protocols in such surgeries, potentially influencing global clinical practices in neurosurgery.

Obesity rates in nursing homes (NHs) are increasing. Residents with obesity are at risk for poor outcomes such as pressure injuries (PIs) due to special care needs such as bariatric medical equipment and special protocols for skin care. PIs among resident populations is a sign of poor quality NH care. The purpose of this retrospective observational study was to identify characteristics of NHs with high rates of stage 2-4 PIs among their high-risk residents with obesity. Resident assessment data were aggregated to the NH level. NH structure and process of care and antecedent conditions of the residents and environment measures were used in bivariate comparisons and multivariate logistic regression models to identify associations with NHs having high rates of stage 2-4 PIs among high-risk residents with obesity. We identified three characteristics for which the effect on the odds was at least 10% for clinical significance - for-profit status, large facilities, and the hours of certified nursing assistants (CNAs) per patient day (HRPPD). This study identified several NH characteristics that are associated with higher risk for PIs, which can be targeted with evidence-based interventions to reduce the risk of these adverse safety events occurring.