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A few studies have examined post‐traumatic growth (PTG) after burns, a relatively new area of research. To understand how to promote PTG in burn survivors, we need to know how PTG and coping are presented, how they change over time, and the components that influence development. Based on the criteria of the PRISMA statement, we conducted our initial search on 1 February 2023. This study systematically reviewed relevant studies in five PubMed, Web of Science, Google Scholar, Scopus and Science Direct search databases. The search used the following keywords: Post‐traumatic Growth, Psychological Growth, Post‐traumatic Growth, Psychological, PTG, Burns and Burn. The two researchers evaluated the quality of the included studies using a 20‐item tool called the appraisal tool for cross‐sectional studies (AXIS tool). A total of 1396 burn patients participated in 12 studies. Among the studies included in this systematic review, seven were cross‐sectional, and five were cohort. The average age of the patients in this study was 35.77 (SD = 10.19). Among the participants, 52.4% were men. The total body surface area (TBSA) percentage in these patients was 32.77 (SD = 16.42). The mean of PTG inventory (PTGI) was 54.08 (SD = 20.46) out of 105, which is a moderate level. Factors such as coping strategies, perceived social support, TBSA, religion/spirituality and severity of burn are positive factors for PTG in burn survivors. Also, factors such as depression, post‐traumatic stress disorder and physical and mental recovery are negative factors for PTG in burn survivors. These factors can be improved through targeted intervention strategies, including overall function, quality of life, social support, optimism, hope and new opportunities. There is a need for further research in several areas related to growth, intervention and measurement. [ABSTRACT FROM AUTHOR]

Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in intensive care units (ICUs) were frequently reported to suffer PIs, with a heavy burden on their life and expenditures. Machine learning (ML) is a Section of artificial intelligence (AI) that has emerged in nursing practice and is increasingly used for diagnosis, complications, prognosis, and recurrence prediction. This study aims to investigate hospital‐acquired PI (HAPI) risk predictions in ICU based on a ML algorithm by R programming language analysis. The former evidence was gathered through PRISMA guidelines. The logical analysis was applied via an R programming language. ML algorithms based on usage rate included logistic regression (LR), Random Forest (RF), Distributed tree (DT), Artificial neural networks (ANN), SVM (Support Vector Machine), Batch normalisation (BN), GB (Gradient Boosting), expectation–maximisation (EM), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost). Six cases were related to risk predictions of HAPI in the ICU based on an ML algorithm from seven obtained studies, and one study was associated with the Detection of PI risk. Also, the most estimated risksSerum Albumin, Lack of Activity, mechanical ventilation (MV), partial pressure of oxygen (PaO2), Surgery, Cardiovascular adequacy, ICU stay, Vasopressor, Consciousness, Skin integrity, Recovery Unit, insulin and oral antidiabetic (INS&OAD), Complete blood count (CBC), acute physiology and chronic health evaluation (APACHE) II score, Spontaneous bacterial peritonitis (SBP), Steroid, Demineralized Bone Matrix (DBM), Braden score, Faecal incontinence, Serum Creatinine (SCr) and age. In sum, HAPI prediction and PI risk detection are two significant areas for using ML in PI analysis. Also, the current data showed that the ML algorithm, including LR and RF, could be regarded as the practical platform for developing AI tools for diagnosing, prognosis, and treating PI in hospital units, especially ICU. [ABSTRACT FROM AUTHOR]

Introduction: This systematic review and meta-analysis aimed to summarize the evidence regarding the impact of needle direction and distance of arteriovenous fistula (AVF) cannulation on KT/V (where k is the dialyzer urea clearance, t, the duration of dialysis, and V, the volume of distribution of urea) and access recirculation (AR) as hemodialysis (HD) adequacy criteria., Methods: A comprehensive systematic search was performed on international and domestic electronic databases from the earliest to June 4, 2022 using keywords. Analysis was performed in STATA software v.14., Results: Three randomized control trials (RCTs) and four non-RCT articles were included in the final review. Six studies reported the effects of direction, while four mentioned the effects of distances of AVF cannulation on outcomes of HD adequacy based on KT/V or AR. Results of three non-RCT studies showed that retrograde direction decreased KT/V more than antegrade direction (ES: 0.44, 95% CI: -0.38 to 1.27). Two non-RCT studies showed that antegrade decreased AR compared to the retrograde direction (ES: -0.64, 95%CI: -1.94 to 0.67). However, the results of two RCTs indicated uncertainty about this issue. Two of the four studies suggested that a distance of 5 cm or more in arterial and venous needles had greater adequacy than a distance of less than 5 cm. However, other studies did not confirm this finding., Conclusion: Overall comparison of the results qualitatively and quantitatively indicated uncertainty about the effects of direction and distance of AVF cannulation on HD adequacy outcomes. More studies with high-quality designs, such as RCTs, are required to better understand and adjudicate the effects of needle direction and distance of AVF cannulation on HD adequacy outcomes., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.