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To evaluate the accuracy of different pressure injury risk assessment tools in paediatrics and identify risk assessment tools with the best predictive performance.
A systematic review and network meta-analysis.
Eight electronic databases, including PubMed, Embase, Web of Science, Cochrane Library, China Knowledge Resource Integrated Database, Weipu Database, Wanfang Database and Chinese Biomedical Database were comprehensively searched. The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines 2020. Two researchers independently conducted article screening, data extraction and quality assessment. Statistical analysis was performed using R 4.3.1 and Stata 14.0.
A total of 20 articles were included in this study, involving 4908 patients and 13 pressure injury risk assessment tools for children, of which 15 articles were included in the network meta-analysis. The results showed that the Paediatric Pressure Ulcer Prediction and Evaluation Tool (PPUPET) had the highest superiority index, with the relative sensitivity (0.7, 95% confidence interval, CI: 0.0–1.5) and the relative specificity (1.4, 95% CI: 0.7–1.8). The next was Braden-Q combined with the Glamorgan scale, with a superiority index of 7.08, a relative sensitivity of 1.1 (95% CI: 0.5–1.5) and a relative specificity of 1.3 (95% CI: 0.8–1.7).
This study suggested that the PPUPET can comprehensively evaluate medical device-related pressure injuries in children, the Braden-Q scale had a better predictive performance for children aged 21 days–8 years in general paediatric departments, and the Glamorgan scale was suitable in the Paediatric Intensive Care Unit.
This review highlights that clinical practitioners should select appropriate assessment tools based on different departments and the age of children to accurately assess the risk of pressure injuries in children.
No Patient or Public Contribution.
PROSPERO CRD42023470769. http://www.crd.york.ac.uk/PROSPERO/#recordDetails.
To evaluate the effectiveness of nurse-led care (NLC) in patients with rheumatoid arthritis on disease activity, physical function, fatigue, satisfaction, pain, and quality of life.
Rheumatoid arthritis is a chronic autoimmune disease, which may not respond to insufficient rheumatology care capacity and workforce shortage. NLC is a care delivery model that can help address this shortage and improve disease management.
Systematic review and meta-analysis.
Nine databases were independently searched by two reviewers for eligible studies. Randomised controlled studies evaluating the effects of NLC on disease activity, physical function, fatigue, satisfaction, and other outcomes were included. The cochrane risk of bias tool was used to assess the risk of bias.
A total of nine studies involving 1447 participants were included. The pooled results indicated that no significant difference in disease activity was found at 0.5 years of follow-up (SMD: −0.33, 95% CI [−0.70, 0.04]), and a significant difference was seen in favour of NLC at 1 year (SMD: −0.35, 95% CI [−0.48, −0.10]), and 2 years (SMD: −0.29, 95% CI [−0.48, −0.10]). Moreover, no significant difference was found in fatigue and satisfaction at 0.5 years of follow-up, whereas differences in favour of NLC were seen at 1 year. In addition, no significant difference was found in physical function, pain, and quality of life.
This review indicated that NLC was not inferior to other types of care, and even had a better positive impact on disease activity, fatigue, and satisfaction for patients with rheumatoid arthritis.
Our study demonstrates that NLC is an effective approach to managing rheumatoid arthritis and recommends medical practitioners be well-versed in its importance.
Patients or public members were not directly involved in this study.
ClinicalTrials.gov identifier: CRD42022355963
Pressure injuries (PIs) impose a significant burden on patients in the intensive care unit (ICU) and the healthcare system. Assessing the risk of developing PIs is crucial for prevention. However, it is unclear whether all subscales of the Waterlow scale can be used to assess PIs risk in ICU.
To assess whether all subscales of the Waterlow scale can predict PIs risk in ICU.
Multicentre prospective study.
A total of 18,503 patients from ICUs in 40 tertiary-level hospitals in Gansu province of China were enrolled from April 2021 to August 2023. The incidence and characteristics of PIs were recorded. Univariate Cox regression analyses were performed for each subscale as a predictor of PIs development, followed by multivariate Cox regression with covariates for each subscale separately.
Out of 17,720 patients included, the incidence of PIs was 1.1%. Multivariate analysis revealed skin type (HR: 1.468, 95% CI: 1.229, 1.758), sex (HR: 0.655, 95% CI: 0.472, 0.908), advanced age (HR: 1.263, 95% CI: 1.106, 1.442), continence (HR: 1.245, 95% CI: 1.052, 1.473), tissue malnutrition (HR: 1.070, 95% CI: 1.007, 1.136) and neurological deficit (HR: 1.153, 95% CI: 1.062, 1.251) were independently predictive of PIs development for all participants. Skin type (HR: 2.326, 95% CI: 1.153, 3.010) (HR: 2.217, 95% CI: 1.804, 2.573) independently predicted PIs occurrence for high-risk and very high-risk group, respectively, while sex (HR: 0.634, 95% CI: 0.431, 0.931) and age (HR: 1.269, 95% CI: 1.083, 1.487) predicted PIs development for very high-risk group.
This study found that not all subscales of the Waterlow scale are associated with the PIs development in patients in ICU, highlighting the importance of the skin type subscale in predicting PI risk across all patient groups.
Nurses need to focus on patient's skin and related (moisture, pain and pressure) conditions and take measures to promote skin health and avoid the occurrence of PI.
None.
The main aim of this study is to synthesize the prevalent predictive models for pressure injuries in hospitalized patients, with the goal of identifying common predictive factors linked to pressure injuries in hospitalized patients. This endeavour holds the potential to provide clinical nurses with a valuable reference for providing targeted care to high-risk patients.
Pressure injuries (PIs) are a frequently occurring health problem throughout the world. There are mounting studies about risk prediction model of PIs reported and published. However, the prediction performance of the models is still unclear.
Systematic review and meta-analysis: The Cochrane Library, PubMed, Embase, CINAHL, Web of Science and Chinese databases including CNKI (China National Knowledge Infrastructure), Wanfang Database, Weipu Database and CBM (China Biology Medicine).
This systematic review was conducted following PRISMA recommendations. The databases of Cochrane Library, PubMed, Embase, CINAHL, Web of Science, and CNKI, Weipu Database, Wanfang Database and CBM were searched for all studies published before September 2023. We included studies with cohort, case–control designs, reporting the development of risk model and have been validated externally and internally among the hospitalized patients. Two researchers selected the retrieved studies according to the inclusion and exclusion criteria, and critically evaluated the quality of studies based on the CHARMS checklist. The PRISMA guideline was used to report the systematic review and meta-analysis.
Sixty-two studies were included, which contained 99 pressure injuries risk prediction models. The AUC (area under ROC curve) of modelling in 32 prediction models were reported ranged from .70 to .99, while the AUC of verification in 38 models were reported ranged from .70 to .98. Gender (OR = 1.41, CI: .99 ~ 1.31), age (WMD = 8.81, CI: 8.11 ~ 9.57), diabetes mellitus (OR = 1.64, CI: 1.36 ~ 1.99), mechanical ventilation (OR = 2.71, CI: 2.05 ~ 3.57), length of hospital stay (WMD = 7.65, CI: 7.24 ~ 8.05) were the most common predictors of pressure injuries.
Studies of PIs risk prediction model in hospitalized patients had high research quality, and the risk prediction models also had good predictive performance. However, some of the included studies lacked of internal or external validation in modelling, which affected the stability and extendibility. The aged, male patient in ICU, albumin, haematocrit, low haemoglobin level, diabetes, mechanical ventilation and length of stay in hospital were high-risk factors for pressure injuries in hospitalized patients. In the future, it is recommended that clinical nurses, in practice, select predictive models with better performance to identify high-risk patients based on the actual situation and provide care targeting the high-risk factors to prevent the occurrence of diseases.
The risk prediction model is an effective tool for identifying patients at the risk of developing PIs. With the help of risk prediction tool, nurses can identify the high-risk patients and common predictive factors, predict the probability of developing PIs, then provide specific preventive measures to improve the outcomes of these patients.
CRD42023445258.
In 2015, the term ‘intrinsic capacity’ (IC) was proposed by the World Health Organisation to promote healthy aging. However, the factors associated with IC are still discrepant and uncertain.
We aim to synthesise the factors connected with IC.
This scoping review followed the five-stage framework of Arksey and O'Malley and was reported using PRISMA-ScR guidelines.
In all, 29 articles were included. IC of older adults is associated with demographic characteristics, socioeconomic factors, disease conditions, behavioural factors, and biomarkers. Age, sex, marital status, occupation status, education, income/wealth, chronic diseases, hypertension, diabetes, disability, smoking status, alcohol consumption, and physical activity were emerged as important factors related to the IC of older adults.
This review shows that IC is related to multiple factors. Understanding these factors can provide the healthcare personnel with the theoretical basis for intervening and managing IC in older adults.
The influencing factors identified in the review help to guide older adults to maintain their own intrinsic capacity, thereby promoting their health and well-being. The modifiable factors also provide evidence for healthcare personnel to develop targeted intervention strategies to delay IC decline.
As this is a scoping review, no patient or public contributions are required.
To investigate the preventive effect of different dressings on pressure injuries related to non-invasive ventilation equipment and to screen the efficacy of dressings. Systematic review and network meta-analysis. PubMed, the Cochrane Library, Web of Science, EMBASE, Cumulative Index to Nursing & Allied Health Literature (CINAHL), China Knowledge Resource Integrated Database (CNKI), Wanfang Database, Chinese Biomedical Database (CBM) and Weipu Database (VIP) were used for the search from the date of inception of each database to 15 October 2023. The quality of the data was assessed using the Cochrane Risk of Bias tool. Stata 16.0 Software was used to analysis and ranking of different types of dressings. A total of 23 randomized controlled trials on 7 interventions were included in the final analysis. The effectiveness of these in preventing the overall incidence of pressure injuries is ranked from best to worst as follows: hydrogel dressing > foam dressing > petroleum jelly gauze dressing > hydrocolloid dressing > film dressing > clean gauze dressing > sterile gauze. Sixteen studies reported the incidence of Stage I pressure injuries, the effectiveness in preventing the incidence of Stage I pressure injuries was ranked from best to least effective: foam dressing > hydrogel dressing > petroleum jelly gauze dressing > hydrocolloid dressing > film dressing > clean gauze dressing > sterile gauze dressing. Fourteen studies reported the incidence of Stages I/II pressure injuries, the effective in preventing the incidence of Stages I and II pressure injuries was ranked from best to least effective: foam dressing > hydrogel dressing > petroleum jelly gauze dressing > hydrocolloid dressing > clean gauze dressing > sterile gauze dressing. Considering the advantages and disadvantages of different dressings, both hydrogel and foam dressings are effective in preventing pressure injuries related to non-invasive ventilation equipment.
To compare the predictive properties of the Jackson/Cubbin scale and Waterlow scales in intensive care unit patients. A multi-centre study. This study was conducted between April 2021 and February 2023 in 72 intensive care units of 38 tertiary hospitals in Gansu Province, China. All adults admitted to the intensive care unit for 24 hours or more without pressure injury on admission were screened using the Waterlow scale and Jackson/Cubbin scales in intensive care. Additionally, the negative predictive value, positive predictive value, sensitivity, specificity and receiver operating characteristic curve with area under the curve of the Waterlow scale and Cubbin/Jackson scales were determined. The participant population for this study included 6203 patients. Predictive properties for the Jackson/Cubbin scales and Waterlow scales, respectively, were as follows: Cut-off scores, 28 versus 22; AUC, 0.859 versus 0.64; sensitivity, 92.4% versus 51.9%; specificity, 67.26% versus 71.46%; positive predictive value, 35% versus 23%; negative predictive value, 99.9% versus 99.1%. Both Waterlow scales and Jackson/Cubbin scales could predict pressure injury risk for patients in the intensive care unit. However, the Jackson/Cubbin scale demonstrated superior predictive properties than the Waterlow scale.
To evaluate the predictive validity and reliability of the Waterlow scale in critically adult hospitalised patients.
A multi-centre cohort study.
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.
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.
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.
Patients or family members supported nurses with PI risk assessment, skin examination and other activities during the inquiry.
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.
To compare the predictive validity of the Braden scale and Waterlow scale in ICUs.
A multicentre, prospective and cross-sectional study.
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.
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.
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.
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.
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.
Despite the fact that machine learning (ML) algorithms to construct predictive models for pressure injury development are widely reported, the performance of the model remains unknown. The goal of the review was to systematically appraise the performance of ML models in predicting pressure injury. PubMed, Embase, Cochrane Library, Web of Science, CINAHL, Grey literature and other databases were systematically searched. Original journal papers were included which met the inclusion criteria. The methodological quality was assessed independently by two reviewers using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was performed with Metadisc software, with the area under the receiver operating characteristic curve, sensitivity and specificity as effect measures. Chi-squared and I 2 tests were used to assess the heterogeneity. A total of 18 studies were included for the narrative review, and 14 of them were eligible for meta-analysis. The models achieved excellent pooled AUC of 0.94, sensitivity of 0.79 (95% CI [0.78–0.80]) and specificity of 0.87 (95% CI [0.88–0.87]). Meta-regressions did not provide evidence that model performance varied by data or model types. The present findings indicate that ML models show an outstanding performance in predicting pressure injury. However, good-quality studies should be conducted to verify our results and confirm the clinical value of ML in pressure injury development.
Deep tissue injuries (DTIs) are a serious type of pressure injuries that mainly occur at the bony prominences and can develop rapidly, making prevention and treatment more difficult. Although consistent research efforts have been made over the years, the cellular and molecular mechanisms contributing to the development of DTIs remain unclear. More recently, ferroptosis, a novel regulatory cell death (RCD) type, has been identified that is morphological, biochemical and genetic criteria distinct from apoptosis, autophagy and other known cell death pathways. Ferroptosis is characterized by iron overload, iron-dependent lipid peroxidation and shrunken mitochondria. We also note that some of the pathological features of DTI are known to be key features of the ferroptosis pathway. Numerous studies have confirmed that ferroptosis may be involved in chronic wounds, including DTIs. Here, we elaborate on the basic pathological features of ferroptosis. We also present the evidence that ferroptosis is involved in the pathology of DTIs and highlight a future perspective on this emerging field, desiring to provide more possibilities for the prevention and treatment of DTIs.
FreshRSS 