The incidence of chronic wounds is increased among older adults, and the impact of chronic wounds on quality of life is particularly profound in this population. It is well established that wound healing slows with age. However, the basic biology underlying chronic wounds and the influence of age-associated changes on wound healing are poorly understood. Most studies have used in vitro approaches and various animal models, but observed changes translate poorly to human healing conditions. The impact of age and accompanying multi-morbidity on the effectiveness of existing and emerging treatment approaches for chronic wounds is also unknown, and older adults tend to be excluded from randomized clinical trials. Poorly defined outcomes and variables, lack of standardization in data collection, and variations in the definition, measurement, and treatment of wounds also hamper clinical studies. The Association of Specialty Professors, in conjunction with the National Institute on Aging and the Wound Healing Society, held a workshop, summarized in this paper, to explore the current state of knowledge and research challenges, engage investigators across disciplines, and identify key research questions to guide future study of age-associated changes in chronic wound healing.

Beneficial short-term effects of aquatic exercise were found in adults with osteoarthritis of the hip or knee. Although the programme may not offer pain relief or self-reported improvements in physical functioning, results suggest that aquatic exercise does not worsen the joint condition or result in injury. Nurses engaging in disease management and health promotion for these patients should consider recommending or implementing aquatic classes for patients.

Background Hospital-acquired pressure injuries are a serious problem among critical care patients. Some can be prevented by using measures such as specialty beds, which are not feasible for every patient because of costs. However, decisions about which patient would benefit most from a specialty bed are difficult because results of existing tools to determine risk for pressure injury indicate that most critical care patients are at high risk. Objective To develop a model for predicting development of pressure injuries among surgical critical care patients. Methods Data from electronic health records were divided into training (67%) and testing (33%) data sets, and a model was developed by using a random forest algorithm via the R package “randomforest.” Results Among a sample of 6376 patients, hospital-acquired pressure injuries of stage 1 or greater (outcome variable 1) developed in 516 patients (8.1%) and injuries of stage 2 or greater (outcome variable 2) developed in 257 (4.0%). Random forest models were developed to predict stage 1 and greater and stage 2 and greater injuries by using the testing set to evaluate classifier performance. The area under the receiver operating characteristic curve for both models was 0.79. Conclusion This machine-learning approach differs from other available models because it does not require clinicians to input information into a tool (eg, the Braden Scale). Rather, it uses information readily available in electronic health records. Next steps include testing in an independent sample and then calibration to optimize specificity. (American Journal of Critical Care. 2018; 27:461–468)