Association between pressure injury status and hospital discharge to home: a retrospective observational cohort study using a national inpatient database

Relationship between gene expression associated with cellular senescence in cells from discarded wound dressings and wound healing: A retrospective cohort study

AIM

Senescent cells, inducing a senescence-associated secretory phenotype (SASP), lead to chronic inflammation in hard-to-heal wound tissue. However, eliminating senescent cells may impede normal wound healing due to their important role in the wound healing mechanism. Accordingly, we focused on wound exudates in hard-to-heal wounds, which contain many inflammation biomarkers consistent with SASP. Therefore, we hypothesized that senescent cells might be present in the exudates and induce chronic inflammation. This study investigated the relationship between gene expression associated with cellular senescence in exudates from pressure injuries and wound healing status.

METHODS

This retrospective cohort study involved patients treated by a pressure injury team. We collected viable cells from wound dressings and analyzed gene expression. Pearson's correlation coefficient was calculated between cellular senescence and SASP expression. The relationship between the gene expression of cellular senescence and the wound area reduction rate by the following week was examined using a mixed-effects model.

RESULTS

CDKN1A-related to cellular senescence-was expressed in 96.3 % of 54 samples, and CDKN1A expression and SASPs positively correlated (PLAU: r = 0.68 and TNF: r = 0.34). Low CDKN1A expression was statistically associated with a large wound area reduction rate (β = 0.83, p < 0.01).

CONCLUSIONS

Gene expression of both cellular senescence and SASP factor in wound dressings suggests the presence of cellular senescence. Senescent cells in wound dressings could be associated with delayed wound healing in the following week.

Delayed discharges at a tertiary rehabilitation centre in Saudi Arabia: contributing factors and cost impact

There are various challenges in discharging hospitalized patients with disabilities. Discharge process for individuals with disabilities is multifactorial and can vary from one health system to another. The current study is aimed to explore the factors contributing to delayed discharges and to determine the number of exceeded bed days and subsequent cost impact at a government rehabilitation facility in Saudi Arabia. This retrospective cohort study was conducted at the Rehabilitation Hospital of King Fahad Medical City, Riyadh. All the 2285 discharges from inpatient rehabilitation from August 2011 to March 2017 were included in the study. Patients with delayed discharge were identified. Information about the diagnosis and reasons for delayed discharge was obtained from the rehabilitation hospital bed utilization data. The cost impact was calculated based on the number of days patients stayed beyond the estimated length of stay for each diagnosis. Of the 2285 discharges, 531 (23.3%) were delayed. The most common clinical conditions of patients with delayed discharge included spinal cord injury (n = 168, 31.6%) and traumatic brain injury (n = 145, 27.3%). The factors that led to delayed discharges were medical complications (n = 352, 66.7%), organizational factors (n = 83, 15.7%), family factors (n = 46, 8.7%), and external factors (n = 46, 8.7%). A total of 21 817 hospital bed days were exceeded, with an approximate estimated cost of 80 million Saudi Arabian Riyals. Early rehabilitation and enhancement of the discharge process may significantly decrease delayed discharge rates. Strategies need to be adapted to identify patients at risk of delayed discharge based on the factors highlighted in this study. Development of long-term care capacity, community services, and optimizing family and social support can promote timely discharge.

Relationship between healing status and microbial dissimilarity in wound and peri-wound skin in pressure injuries

AIM

Wound infection is the most serious cause of delayed healing for patients with pressure injuries. The wound microbiota, which plays a crucial role in delayed healing, forms by bacterial dissemination from the peri-wound skin. To manage the bioburden, wound and peri-wound skin care has been implemented; however, how the microbiota at these sites contribute to delayed healing is unclear. Therefore, we investigated the relationship between healing status and microbial dissimilarity in wound and peri-wound skin.

METHODS

A prospective cohort study was conducted at a long-term care hospital. The outcome was healing status assessed using the DESIGN-R® tool, a wound assessment tool to monitor the wound healing process. Bacterial DNA was extracted from the wound and peri-wound swabs, and microbiota composition was analyzed using 16S rRNA gene analysis. To evaluate microbial similarity, the weighted UniFrac dissimilarity index between wound and peri-wound microbiota was calculated.

RESULTS

Twenty-two pressure injuries (7 deep and 15 superficial wounds) were included in the study. For deep wounds, the predominant bacteria in wound and peri-wound skin were the same in the healing wounds, whereas they were different in all cases of hard-to-heal wounds. Analysis based on the weighted UniFrac dissimilarity index, there was no significant difference for healing wounds (p = 0.639), while a significant difference was found for hard-to-heal wounds (p = 0.047).

CONCLUSIONS

Delayed healing is possibly associated with formation of wound microbiota that is different in composition from that of the skin commensal microbiota. This study provides a new perspective for assessing wound bioburden.

Sensitivity and Specificity of Body Mass Index for Sarcopenic Dysphagia Diagnosis among Patients with Dysphagia: A Multi-Center Cross-Sectional Study

The accuracy of body mass index (BMI) for sarcopenic dysphagia diagnosis, which remains unknown, was evaluated in this study among patients with dysphagia. We conducted a 19-site cross-sectional study. We registered 467 dysphagic patients aged ≥ 20 years. Sarcopenic dysphagia was assessed using a reliable and validated diagnostic algorithm. BMI was assessed using the area under the curve (AUC) in the receiver operating characteristic analysis to determine diagnostic accuracy for sarcopenic dysphagia. The study included 460 patients (median age, 83.0 years (76.0−88.0); men, 49.8%). The median BMI was 19.9 (17.3−22.6) kg/m2. Two hundred eighty-four (61.7%) patients had sarcopenic dysphagia. The AUC for sarcopenic dysphagia was 0.60−0.62 in the overall patients, male, female, and patients aged ≥ 65 years The BMI cut-off value for sarcopenic dysphagia diagnosis was 20.1 kg/m2 in the overall patients (sensitivity, 58.1%; specificity, 60.2%) and patients aged ≥ 65 years (sensitivity, 59.8%; specificity, 61.8%). Conclusion: Although the AUC, sensitivity and specificity of BMI for sarcopenic dysphagia diagnosis was approximately 0.6, BMI < 20.0 kg/m2 might be a predictor for sarcopenic dysphagia. In clinical settings, if patients with dysphagia have a BMI < 20.0 kg/m2, then sarcopenic dysphagia should be suspected as early as possible after admission.

Supervised machine learning-based prediction for in-hospital pressure injury development using electronic health records: A retrospective observational cohort study in a university hospital in Japan

BACKGROUND

In hospitals, nurses are responsible for pressure injury risk assessment using several kinds of risk assessment scales. However, their predictive validity is insufficient to initiate targeted preventive strategy for each patient. The use of electronic health records with machine learning technique is a promising strategy to provide automated clinical decision-making aid.

OBJECTIVE

The purpose of this study was to construct a predictive model for pressure injury development which included feature variables that can be collected on the first day of hospitalization by nurses who routinely input the data to electronic health records.

DESIGN

Retrospective observational cohort study.

SETTING

This study was conducted at a university hospital in Japan.

PARTICIPANTS

This study used electronic health records, which include entry/discharge records, basic nursing records, and pressure injury management documents (N = 75,353).

METHODS

The outcome measure was the pressure injuries which developed outside of an operation theatre and frequently appeared on the specific body parts at high risk of pressure injury development. We utilized four major classifiers: logistic regression, random forest, linear support vector machine, and extreme gradient boosting (XGBoost) with 5-fold cross-validation technique. The area under the receiver operating characteristic curve (AUC) was used for evaluating predictive performance.

RESULTS

The proportion of hospital-acquired pressure injuries was 0.52%. The receiver operating characteristic curves revealed the best predictive performance for the XGBoost model, achieving the highest sensitivity of 0.78±0.03 and AUC of 0.80±0.02 amongst four types of classifiers. Variables related to difficulty in activities of daily living, anorexia, and respiratory or cardiac disorders were extracted as important features.

CONCLUSIONS

Our findings suggest that routinely collected health data by nurses on the first day of patient admission have the potential to help determine high-risk patients for pressure injury development. Tweetable abstract: Machine learning models on routinely collected electronic health records data successfully predict pressure injury development during hospitalization.

FUNDING

This work was supported by a JSPS KAKENHI Grant-in-Aid for Exploratory Research (16K15865).

Ultrasound assessment of deep tissue on the wound bed and periwound skin: A classification system using ultrasound images

AIMS

Given the utility of ultrasonography in assessing pressure injury, some ultrasonographic findings have already been used as indicators of deep tissue pressure injury. Despite reports showing that a cloud-like ultrasonographic pattern reflected the presence of deep tissue necrosis, identifying cloud-like patterns was difficult given the presence of similar findings, such as a cobblestone-like pattern. This case series reports patients with pressure injuries who presented with a cloud-like (five cases) and cobblestone-like (four cases) pattern during ultrasonography.

METHODS

This study was conducted at a Japanese university hospital. Participants included patients who underwent routine examination by an interdisciplinary pressure injury team. Pressure injury severity was assessed using the DESIGN-R® scoring system and the wound size were measured using ImageJ software based on the wound photograph.

RESULTS

Among the five cases showing a cloud-like pattern upon ultrasonography, all exhibited an increase in the total DESIGN-R® score, while three exhibited an increase in wound size. On the other hand, all four cases showing a cobblestone-like pattern displayed no increase in the total DESIGN-R® score and a decrease in wound size.

CONCLUSION

This study suggested that distinguishing between cloud-like and cobblestone-like ultrasonography patterns is necessary for determining the presence or absence of deep tissue pressure injury. In order to comprehensively assess pressure injuries with ultrasonography, future studies should be conducted in a large number of participants.