Recalcitrant dermatophyte infections: identification and risk factors.

INTRODUCTION: Recalcitrant dermatophytosis is an emerging phenomenon that occurs worldwide, and Trichophyton indotineae is currently the prominent cause. MATERIALS AND METHODS: Skin specimens from patients with tinea infection were obtained by scrubbing and then sectioned into three fragments. Two fragments were subjected to direct microscopic examination and culture, while the third portion was utilized in the PCR method. RESULTS: Isolates were morphologically identified as Trichophyton mentagrophytes/interdigitale complex (n = 60 [83.33%]), Microsporum canis (n = 8 [11.11%]), Trichophyton rubrum (n = 3 [4.16%]), and Epidermophyton floccosum (n = 1 [1.38%]). Among 60 T. mentagrophytes complex isolates, 53 (88.33%) were classified as T. indotineae and seven as T. interdigitale genotype II. The disease duration was longer in the T. indotineae group (P = 0.035). Both Gradient PCR and skin-sampling methods yield similar results in terms of positive and negative cases (P = 1.0000). The time patients stopped their medication did not impact the positive case numbers (P = 0.803). Gender had no effects on the frequency (P = 0.699). Familial contamination, dermatologic disorder, and other underlying conditions did not differ in the two group infections (P > 0.05). Steroid usage is strongly associated with the emergence of tinea infection (P < 0.04). The duration of antifungal administration had a substantial effect on the emergence of resistant organisms (P = 0.05). CONCLUSIONS: Steroid usage, T. indotineae involvement, and prolonged exposure to antifungals were the solid and influential factors in recalcitrant involvement. Regarding quick and suitable diagnosis and treatment, which is essential in preventing recalcitrant cases, we suggest that direct skin sample PCR can meet the demands.

Prevalence of Delirium and Its Related Factors in Burn Patients; a Systematic Review and Meta-Analysis.

Introduction: Considering the importance of delirium disorder in burn patients and its complications, the present systematic review and meta-analysis aimed to determine the prevalence of delirium and its related factors in burn patients. Methods: A comprehensive, systematic search was performed in different international electronic databases, such as Scopus, PubMed, and Web of Science, as well as Persian electronic databases such as Iranmedex, and Scientific Information Database (SID) using keywords extracted from Medical Subject Headings such as "Prevalence", "Delirium", and "Burns" from the earliest to the 17th of July, 2023. Results: In total, 2,710 burn patients participated in ten original studies. Among the participants, 64.6% were male. In the ten studies, the reported pooled prevalence of delirium among burn patients was 20.5% (95% CI: 10.9% to 35.0%; I2=96.889%; P<0.001). Also, factors such as total body surface area, duration of hospitalization, mortality, days on ventilator, alcoholism, benzodiazepine dose, methadone dose, age, male gender, ICU days, operation days, wound care under anesthesia, and opioid dose had a significant correlation with the prevalence of delirium in burn patients. Conclusion: Health managers and policymakers can reduce the prevalence of delirium in burn patients by eliminating or reducing factors associated with it.

Risk predictions of hospital-acquired pressure injury in the intensive care unit based on a machine learning algorithm.

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.

A systematic review of caregivers' knowledge and related factors towards pressure ulcer prevention.

This systematic review aimed to examine the knowledge of caregivers regarding pressure ulcer (PU) prevention. A thorough, methodical search was conducted from the earliest date to February 1, 2023 using keywords extracted from Medical Subject Headings such as "Caregivers", "Knowledge", and "Pressure ulcer" in various international electronic databases such as Scopus, PubMed, Web of Science, and Persian electronic databases such as Iranmedex and Scientific Information Database. The quality of the studies included in this systematic review was evaluated using an appraisal tool for cross-sectional studies (AXIS tool). In total, 927 caregivers participated in the eight studies. The average age of the participants was 40.50 (SD = 12.67). Among the participants, 61.87% were women. The average caregiver's knowledge of PU prevention was 53.70 (SD = 14.09) out of 100, which suggests a moderate level of knowledge. Factors such as level of education, age, occupation, information about PUs, attitude, and practice had a significant positive relationship with caregivers' knowledge related to the prevention of PUs. Knowledge had a significantly negative relationship with age. In addition, marital status, type of relationship, age, gender, occupation, level of education, and inpatient wards had a significant relationship with caregivers' knowledge regarding PUs prevention. Therefore, managers and policymakers in the medical field can help increase caregivers' knowledge by providing an online or in-person educational platform relevant to PU prevention.

Recent advancements to engineer mesenchymal stem cells and their extracellular vesicles for targeting and destroying tumors.

Mesenchymal stem cells (MSCs) have the ability to migrate into tumor sites and release growth factors to modulate the tumor microenvironment. MSC therapy have shown a dual role in cancers, promoting or inhibiting. However, MSCs could be used as a carrier of anticancer agents for targeted tumor therapy. Recent technical improvements also allow engineering MSCs to improve tumor-targeting properties, protect anticancer agents, and decrease the cytotoxicity of drugs. While some of MSC functions are mediated through their secretome, MSCs-derived extracellular vesicles (EVs) are also proposed as a possible viechle for cancer therapy. EVs allow efficient loading of anticancer agents and have an intrinsic ability to target tumor cells, making them suitable for targeted therapy of tumors. In addition, the specificity and selectivity of EVs to the tumor sites could be enhanced by surface modification. In this review, we addressed the current approaches used for engineering MSCs and EVs to effectively target tumor sites and deliver anticancer agents.

Updates on Tinea Incognita: Literature review.

Background and Purpose: Tinea incognita (TI), or the other equivalent tinea atypica, is a term used to declare the atypical presentation of dermatophyte infections caused by the administration of steroids or other immunosuppressive medications which modulate the local and systemic immune response. It can mimic other dermatoses; hence making diagnostic challenges for dermatologists. Tina incognita may be misdiagnosed as many dermatoses. Based on previous studies, corticosteroids may cause different clinical manifestations of dermatophytes that might be very different from those that are commonly described. Materials and Methods: This narrative review was conducted using PubMed and Scopus databases. Search terms included "Tinea incognita" and "Atypical dermatophytosis". The search strategy included meta-analyses, randomized controlled trials, clinical trials, observational studies, reviews, and case reports. The search was restricted to articles written in the English language from 2006 to Feb 01, 2023. Moreover, duplicate articles and non-available full-text articles were excluded. The extracted data of the search results were retrieved in this study. The morphological patterns, prevalence, sight of infection, and causative agents were also described. Results: Prevalence of different patterns of TI were recorded as 50% (431 out of 862 cases) for eczema-like lesions followed by psoriasis-like and 6.61% (57 out of 862) for parapsoriasis-like pattern. Moreover, each of the rosacea-like and pyoderma-like lesions equally accounted for 4.98 % of cases (43 out of 862). In addition, the prevalence of causative agents was reported as follows: Trichophyton rubrum accounted for 247 isolates (40%) as the most prevalent, followed by Trichophyton mentagrophytes (n=152, 24%) and Microsporum canis (n=119, 19%). Conclusion: Tinea incognita is a great mimicker; hence, dermatologists should obtain a full medical history of the patients to make correct diagnoses. It is vital to encourage an exact identification of the etiological agent according to the internal transcribed spacer sequencing in some uncertain cases. This review highlights the importance of mycological tests and fast diagnosis of TI, especially in cases of atypical skin lesions, to choose appropriate treatment and avoid the spread of drug-resistant species.