Preclinical techniques for drug discovery in psoriasis.

Psoriasis is a chronic, inflammatory, papulosquamous, noncontagious disease characterized by scaly, demarcated erythematous plaque, affecting skin, nails, and scalp. The IL-23/Th17 axis is the main operator in the development of psoriasis. Psoriasis is affecting worldwide, and new treatment options are urgently needed. Various local and systemic treatments are available for psoriasis but they only provide symptomatic relief because of numerous unknown mechanisms. Clinical trials demand overwhelming resources; therefore, drug development predominantly depends on the in-vivo, in-vitro, and ex-vivo techniques. Immediate attention is required to develop experimental techniques that completely imitate human psoriasis to assist drug development. This review portrays the various in-vivo, in-vitro, and ex-vivo techniques used in psoriasis research. It describes these techniques' characteristics, pathological presentations, and mechanisms. The experimental techniques of psoriasis provide significant information on disease progression mechanisms and possible therapeutic targets. However, until now, it has been challenging to invent a timely, affordable model that precisely imitates a human disease. Only the xenotransplantation model is reckoned as the closer, that mimics the complete genetic, and immunopathogenic event. Imiquimod-induced psoriasis and HaCat cell lines are popular among researchers because of their convenience, ease of use, and cost-effectiveness. There need to further improve the experimental techniques to best serve the disease imitation and meet the research goal.

Phase 1 study of the iodine absorption, safety, and tolerability of a 0.5% povidone-iodine nasal spray (Nasodine).

KEY POINTS: PVP-I is a widely used antiseptic but only recently proposed for intranasal use. The extent of iodine absorption from available PVP-I nasal products is unknown. Iodine absorption from use of Nasodine (0.5% PVP-I nasal spray) is not clinically significant.

Determinants of users' unverified information sharing on social media platforms: A herding behavior perspective.

The proliferation of unverified or false information by irresponsible users can significantly amplify the spread of misinformation or fake news. Despite growing research on unverified information sharing, a comprehensive understanding of the varying influences of different factors and strategies to mitigate this issue remains under investigation. To address this research gap, this study, rooted in the theory of herd behavior, develops, and tests a model theorizing the reasons behind social media users' unverified information sharing. Data was collected from 510 respondents across six regions of China using a convenience sampling method. The collected data was analyzed using Mplus. The results from this study indicated that perceived severity, state uncertainty, and herding have a significant positive influence on unverified information sharing. These results enrich the understanding of unverified information-sharing behavior among Chinese social media users. Drawing from these results, we suggest platform administrators and policymakers mitigate herd behavior tendencies and stem the spread of misinformation by disseminating timely, accurate, and authoritative information. Since this action will reduce users' perceptions of severity and uncertainty. Social media users are also advised to stay vigilant over the implications of herd behavior and foster a more critical attitude towards information sharing.

Time trend analysis of Injury Severity score of adult trauma patients with emergent CT examination.

PURPOSE: Controversy exists about whole-body computed tomography (CT) as a primary screening modality for suspected multiple trauma patients. Therefore, the aim of this study was to analyze time trends of CT examinations for trauma patients in relation to the Injury Severity Score (ISS). METHODS: We retrospectively analyzed 561 adult trauma patients (mean age = 54 years) who were admitted to the trauma room of our hospital, immediately followed by a CT examination, in 2009, 2013 und 2017. Review of electronic patient charts was performed to determine the cause of injury. ISS was either calculated upon hospital charts and CT imaging reports or documented in the TraumaRegister DGU® for trauma patients with ICU treatment or ISS ≥ 16. RESULTS: An increasing number of CT examinations of acute trauma patients were performed at our hospital with 117 patients in 2009 compared to 192 in 2013 and 252 in 2017. Their mean age increased (50 years in 2009, 54 in 2013 and 55 in 2017;p = 0.046), whereas their mean ISS decreased over time (15.2 in 2009 compared to 12.1 in 2013 and 10.6 in 2017;p = 0.001), especially in women (15.1 in 2009, 11.8 in 2013 and 7.4 in 2017;p = 0.001 both), younger age groups (18 to 24 years:15.6 in 2009, 6.5 in 2013 and 8.9 in 2017; p = 0.033 and 25 to 49 years:15.0 in 2009, 11.2 in 2013 and 8.3 in 2017;p = 0.001) as well as motor vehicle collision (MVC) victims (16.2 in 2009, 11.8 in 2013 and 6.1 in 2017; p < 0.001). Trauma patients with a high ISS were especially more likely of older age (OR 1.02,p < 0.001) and with the type of incident being a fall (< 3 m: OR3.84,p < 0.001;>3 m: OR6.22,p < 0.001) compared to MVC. CONCLUSION: Previous studies suggesting a benefit of primary whole-body CT for trauma patients might not reflect the current patient population with decreasing ISS. Especially females, younger age groups and MVC patients might benefit from stricter selection criteria for receiving whole-body CT. Our results also emphasize the importance of prevention of fall or tumble for elderly people.

The impact of hyperkalemia on ICU admission and mortality: a retrospective study of Chinese emergency department data.

OBJECTIVE: This study assesses the influence of hyperkalemia on both disease severity and the risk of mortality among patients admitted to the emergency room. METHODS: This retrospective observational study utilized data from the Chinese Emergency Triage Assessment and Treatment database (CETAT, version 2.0), which was designed to evaluate and optimize management strategies for emergency room (ER) patients. Patients were systematically categorized based on serum potassium levels. Relationships between serum potassium levels, risk of mortality, and the severity of illness were then analyzed using multifactorial logistic regression and through Receiver Operating Characteristic (ROC) analysis. The effectiveness of various treatments at lowering potassium levels was also investigated. RESULTS: 12,799 emergency patients were enrolled, of whom 20.1% (n = 2,577) were hypokalemic and 2.98% (n = 381) were hyperkalemic. Among hyperkalemic patients, the leading reasons for visiting the ER were altered consciousness 23.88% (n = 91), cardiovascular symptoms 22.31% (n = 85), and gastrointestinal symptoms 20.47% (n = 78). Comparative analysis with patients exhibiting normal potassium levels revealed hyperkalemia as an independent factor associated with mortality in the ER. Mortality risk appears to positively correlate with increasing potassium levels, reaching peaks when blood potassium levels ranged between 6.5 and 7.0. Hyperkalemia emerged as a strong predictor of death in the ER, with an Area Under the Curve (AUC) of 0.89. The most frequently prescribed treatment for hyperkalemia patients was diuretics (57.32%, n = 188), followed by intravenous sodium bicarbonate (50.91%, n = 167), IV calcium (37.2%, n = 122), insulin combined with high glucose (27.74%, n = 91), and Continuous Renal Replacement Therapy (CRRT) for 19.82% (n = 65). Among these, CRRT appeared to be the most efficacious at reducing potassium levels. Diuretics appeared relatively ineffective, while high-glucose insulin, sodium bicarbonate, and calcium preparations having no significant effect on the rate of potassium decline. CONCLUSION: Hyperkalemia is common in emergency situations, especially among patients with altered consciousness. There is a strong positive correlation between the severity of hyperkalemia and mortality risk. CRRT appears to be the most effective potassium reducting strategy, while the use of diuretics should be approached with caution.

Association of plasma lactoferrin levels with disease severity in glaucoma patients.

Objective: To explore the relationship between plasma lactoferrin (Lf) and glaucoma, assessing the clinical utility of Lf in glaucoma. Methods: A cross-sectional study involved 161 glaucoma patients and 115 healthy controls, with a follow-up of 14 subjects after approximately 2 years. Plasma Lf markers were quantified using ELISA, comparing levels between glaucoma patients and healthy controls, and analyzing plasma Lf across different glaucoma severity grades. Results: Glaucoma patients had significantly elevated plasma Lf levels compared to healthy controls (p < 0.001). Higher plasma Lf levels correlated with more severe disease stages (HPA grades showed ρ = 0.435, p < 0.001; AGIS grades showed ρ = 0.436, p < 0.001) and reduced retinal nerve fiber layer (RNFL) thickness (RNFL thickness showed ρ = -0.204, p = 0.024). ROC curve analysis demonstrated the efficacy of glaucoma markers in differentiating early-stage from advanced glaucoma. Conclusion: Plasma Lf levels are significantly associated with glaucoma severity and may be involved in the pathogenic progression of the disease.

Causal effects of dietary composition on multiple sclerosis risk and severity: a Mendelian randomization study.

Objectives: Observational studies have found potential associations between dietary intake and multiple sclerosis (MS). However, these associations are inconsistent, and the causal relationship remains unclear. In this study, we aim to examine the causal relationship between genetically predicted dietary composition and the risk and severity of MS using two-sample Mendelian randomization. Method: Genetic instruments for 30 different dietary compositions were extracted from large-scale genome-wide association studies (GWAS), mainly from the UK Biobank dataset. The GWAS data for MS risk and severity were obtained from the International Multiple Sclerosis Genetics Consortium. The primary analysis employed either the inverse variance weighted method or the Wald ratio method to evaluate the causal association. Several sensitivity analyses were also performed. Results: Genetically predicted higher pork intake was causally associated with an increased risk of MS (odds ratio [OR] = 6.76; p = 0.005), while genetically driven higher cereal intake (OR = 0.43, p = 0.016), vitamin C supplement (OR < 0.01; p = 4.34 × 10-5), folic acid supplement (OR < 0.01; p = 4.91 × 10-71), and fish oil supplement (OR = 0.04; p = 0.017) were causally linked to a decreased risk of MS. In addition, genetically predicted higher alcoholic intake (OR = 1.17; p = 0.041) was causally associated with an increase in MS severity, while folic acid supplement (OR < 0.01; p = 0.015) was causally linked to a decrease in MS severity. Interpretation: This study found that increased consumption of cereal, vitamin C, folic acid, and fish oil, coupled with reduced pork and alcohol intake, may potentially decrease the risk and severity of MS. These findings inform the development of dietary-based strategies for MS prevention and treatment.

Causal relationship between blood traits and severe influenza A(H1N1)pdm09 infection in East Asian: A Mendelian randomization study.

Although a range of blood traits have been reported to be associated with influenza A(H1N1)pdm09 (H1N1pdm09) disease severity, their underlying causal relationships and biological mechanisms have remained unclear. This study aimed to investigate the causal relationship between blood traits and H1N1pdm09 using a two-sample Mendelian randomization analysis. Based on the data from our in-house genome-wide association study (GWAS) on H1N1pdm09 disease severity (Ncase [severe] = 70, Ncontrol [mild] = 95) and GWAS summaries of 44 blood traits from Biobank Japan (N = 12 303-143 658), we identified the potential causal effect of blood traits on severe H1N1pdm09. The inverse variance weighted method analysis revealed significant causal effects of lower aspartate aminotransferase (AST, ß = -3.212, p = 0.019), low-density-lipoprotein cholesterol (LDL-C, ß = -1.372, p = 0.045), and basophil counts (Baso, ß = -1.638, p = 0.047) on severe H1N1pdm09 disease. Additionally, polygenic risk score analysis further confirmed genetic overlap between these blood traits and severe H1N1pdm09 disease. This study provided evidence linking the lower level of AST, LDL-C, and lower count of Baso with severe H1N1pdm09 disease, potentially identifying new therapeutic targets for patients with severe influenza.

Exploring the interplay of atopic dermatitis severity with sleep and mental health: a case-control study in adult patients.

OBJECTIVES: Atopic dermatitis (AD) is a chronic inflammatory skin disease often associated with non-atopic comorbidities. Recently, a severity-dependent relationship between AD and sleep/mental health diseases has been proposed. However, few studies investigated these comorbidities and their association with AD severity through validated questionnaires. This study aimed to use a set of validated instruments to assess the impact of AD on sleep and psychological disorders and estimate the association of itch and AD severity with sleep disorders and psychological symptoms, distinguishing between clinical-oriented and patient-oriented measures. METHODS: We conducted a case-control study, recruiting 57 adult AD patients (mean age ± std. dev. 34.28 years ± 13.07; 27 males) matched for age and sex with 57 healthy adults (34.39 years ± 13.09; 27 males). To investigate the differences in sleep quality, insomnia, depression, and anxiety between the two groups, we performed independent sample t-Tests. Moreover, we conducted univariate linear regression analyses to examine the relationship between itch and objective/subjective severity of AD and sleep quality, insomnia, and psychological symptoms. RESULTS: AD patients reported lower sleep quality (p = 0.002), more severe insomnia (p = 0.006) and depression (p = 0.013), and higher stress levels than healthy adults (p = 0.049). Itch intensity was linked to sleep disturbances and psychological symptoms (R2range = 0.13-0.19, prange = 0.02-<0.001). Objective and subjective AD severity were similarly associated with worse sleep quality (R2 = 0.26, p < 0.001; R2 = 0.24, p < 0.001; respectively), anxiety (R2 = 0.15, p = 0.04; R2 = 0.17, p = 0.001; respectively), and self-perceived stress (R2 = 0.10, p = 0.02; R2 = 0.07, p = 0.049; respectively). However, subjective AD severity was more strongly associated with insomnia (R2 = 0.31, p < 0.001) and depression (R2 = 0.20, p < 0.001) than clinical-oriented AD severity (R2 = 0.19, p < 0.001; R2 = 0.05, p = 0.098; respectively). CONCLUSIONS: The study demonstrated poor sleep quality and high levels of insomnia, depression, and stress in AD patients, with an aggravated psychological status for adults with more severe skin disease. We suggest implementing a multidisciplinary approach to AD management/treatment that considers objective and subjective measures of disease severity.

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

BACKGROUND: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. METHODS: AEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. RESULTS: Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. CONCLUSIONS: To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Next-gen regional fire risk mapping: Integrating hyperspectral imagery and National Forest Inventory data to identify hot-spot wildland-urban interfaces.

The increasing threat of high-severity wildfires in Mediterranean Wildland-Urban Interface (WUI) areas demands to develop effective fire risk assessment and management strategies. Simultaneously, the newfound accessibility of spaceborne hyperspectral data represents a significant potential for generating fire severity assessments, whereas National Forest Inventories (NFI) offer a vast dataset related to vegetation and fuel loads, which is essential for shaping the planning and strategies of forest services. This research work aims to advance the state-of-the-art in WUI fire risk mapping in the western Mediterranean Basin by combining PRISMA spaceborne hyperspectral data and Spanish NFI data. The proposed methodology had three main stages: (i) fire severity assessment at local scale (a wildfire) by using PRISMA hyperspectral data and Multi-Endmember Spectral Mixture Analysis (MESMA) leveraging field-based measurements of the Composite Burn Index (70 plots); (ii) development of a high fire severity probability map at regional scale from the extrapolation of a Random Forest predictive model calibrated from fire severity estimates, NFI data and topo-climatic variables at local scale (overall accuracy = 92 %; Kappa = 0.8); and (iii) identification and characterization of zones that concentrate WUIs with high probability of high fire severity if a fire event occurs (hot-spot WUIs) by crossing the information from the previous regional high fire severity probability map and a WUI cartography developed at regional scale. Study area was Castilla y León Autonomous Region (larger Spanish region, 94,226 km2), where the second-largest extreme Spanish wildfire event (28,000 ha) occurred. We identified hot-spot WUIs so that stakeholders and decision-makers could (i) prioritize resources and interventions for effective fire management and mitigation, (ii) allocate resources for prevention, and (iii) plan evacuation measures to safeguard lives and property. This study contributes to the development of next-generation fire risk assessment methods that combine remote sensing technologies with comprehensive ground-level datasets.

Analysis of Risk Factors for Severe Acute Pancreatitis in the Early Period (<24 h) After Admission.

BACKGROUND: Severe acute pancreatitis (SAP) has high mortality. Early identification of high-risk factors that may progress to SAP and active intervention measures may improve the prognosis of SAP patients. OBJECTIVE: Clinical data within 24 h after admission were retrospectively analyzed to provide an evidence for early screening of high-risk factors in patients with SAP. METHODS: A review of clinical data of acute pancreatitis patients from January 1, 2018, to December 31, 2022, was conducted. We compared the clinical data of SAP and non-SAP patients, and a multivariable logistic regression model was used to identify the independent predictors of SAP. The receiver operating characteristic (ROC) curve of SAP was drawn for continuous numerical variables to calculate the optimal clinical cutoff value of each variable, and the predictive value of each variable was compared by the area under the ROC curve. RESULTS: Based on the multivariate logistic regression analysis of Age (odds ratio (OR), 1.032;95% confident interval (CI),1.018-1.046, p < 0.001), body mass index (BMI) (OR, 1.181; 95% CI,1.083-1.288, p < 0.001), Non-HTGAP (nonhypertriglyceridemic acute pancreatitis) (OR, 2.098; 95% CI,1.276-3.45, p = 0.003), white blood cell count (WBC) (OR,1.072; 95% CI,1.034-1.111, p < 0.001), procalcitonin (PCT) (OR, 1.060; 95% CI, 1.027-1.095, p < 0.001), serum calcium (Ca) (OR,0.121; 95% CI, 0.050-0.292, p < 0.001), computed tomography severity index (CTSI) ≥4 (OR,12.942;95% CI,7.267-23.049, p < 0.001) were identified as independent risk factors for SAP. The area under the ROC curve (AUC) and optimal CUT-OFF values of continuous numerical variables for predicting SAP were Age (0.6079,51.5), BMI (0.6,23.25), WBC (0.6701,14.565), PCT (0.7086, 0.5175), Ca (0.7787,1.965), respectively. CONCLUSION: Age, BMI, non-HTGAP, WBC, PCT, serum Ca and CTSI≥4 have good predictive value for SAP.

Analyzing injury severity of three-wheeler motorized rickshaws: A correlated random parameters approach with heterogeneity in means.

Traffic crashes involving three-wheeler motorized rickshaw (3-WMR) are alarming public health and socioeconomic concerns in developing countries. While most of the earlier studies have dealt with safety analysis of four- and two-wheelers, there is a noticeable gap in understanding the safety dynamics, especially the risk factors affecting the crashes involving 3-WMR. The present study aims to address this gap by exploring potential risk factors influencing 3-WMR crashes, utilizing a correlated random parameters multinomial logit model with heterogeneity in means (CRPMNLMHM). This modeling framework advances the classic random parameters model by capturing associations among random parameters, providing a more comprehensive understanding of crash risks associated with 3-WMR. The empirical analysis draws on three years of traffic crash records (2017-2019) maintained by RESCUE 1122 in Rawalpindi city, Pakistan. A comparative assessment between the modeling frameworks demonstrated that CRPMNLMHM outperformed its counterparts. Model assessment for heterogeneity in the means identifies two significant variables, i.e., young age and nighttime, which yield statistically significant random parameters. In addition, the model's results suggest that fatal and severe injury outcomes in 3-WMR crashes are affected by several attributes related to temporal characteristics (weekend, nighttime, and off-peak indicators), driver profiles (young, older aged, and speeding), posted speed limits (>70 kmph), weather conditions (raining), and crash characteristics (collision with pedestrians, trucks, or 3-WMR overturning). The present study's findings offer invaluable insights, emphasizing the significance of considering for unobserved heterogeneity in variables contributing to the injury severity of 3-WMR crashes. Moreover, in light of the findings, a set of policy implications are suggested, which will guide safety practitioners to develop more effective countermeasures to address safety issues associated with 3-WMRs.

Classification of autonomous vehicle crash severity: Solving the problems of imbalanced datasets and small sample size.

Only a few researchers have shown how environmental factors and road features relate to Autonomous Vehicle (AV) crash severity levels, and none have focused on the data limitation problems, such as small sample sizes, imbalanced datasets, and high dimensional features. To address these problems, we analyzed an AV crash dataset (2019 to 2021) from the California Department of Motor Vehicles (CA DMV), which included 266 collision reports (51 of those causing injuries). We included external environmental variables by collecting various points of interest (POIs) and roadway features from Open Street Map (OSM) and Data San Francisco (SF). Random Over-Sampling Examples (ROSE) and the Synthetic Minority Over-Sampling Technique (SMOTE) methods were used to balance the dataset and increase the sample size. These two balancing methods were used to expand the dataset and solve the small sample size problem simultaneously. Mutual information, random forest, and XGboost were utilized to address the high dimensional feature and the selection problem caused by including a variety of types of POIs as predictive variables. Because existing studies do not use consistent procedures, we compared the effectiveness of using the feature-selection preprocessing method as the first process to employing the data-balance technique as the first process. Our results showed that AV crash severity levels are related to vehicle manufacturers, vehicle damage level, collision type, vehicle movement, the parties involved in the crash, speed limit, and some types of POIs (areas near transportation, entertainment venues, public places, schools, and medical facilities). Both resampling methods and three data preprocessing methods improved model performance, and the model that used SMOTE and data-balancing first was the best. The results suggest that over-sampling and the feature selection method can improve model prediction performance and define new factors related to AV crash severity levels.

Influenza and pneumococcal vaccination in patients with COPD from 3 French cohorts: Insufficient coverage and associated factors.

BACKGROUND: Low vaccination rates against influenza and Streptococcus (S.) pneumoniae infections in COPD could impair outcomes. Understanding underlying factors could help improving implementation. OBJECTIVES: To describe vaccination rates at inclusion in COPD cohorts and analyze associated factors. METHODS: Between 2012 and 2018, 5927 patients with sufficient data available were recruited in 3 French COPD cohorts (2566 in COLIBRI-COPD, 2653 in PALOMB and 708 in Initiatives BPCO). Data at inclusion were pooled to describe vaccination rates and analyze associated factors. RESULTS: Mean age was 66 years, 34 % were women, 35 % were current smokers, mean FEV1 was 58 % predicted, 22 % reported ≥2 exacerbations in the year prior to inclusion, mMRC dyspnea grade was ≥2 in 59 %, 52 % had cardiovascular comorbidities and 9 % a history of asthma. Vaccinations rates in the year prior to study entry were 34.4 % for influenza + S. pneumoniae, 17.5 % for influenza alone and 8.9 % for S. pneumoniae alone. In multivariate analyses, influenza vaccination rate was greater in older age, smoking status, low FEV1, exacerbation history, mMRC dyspnea>2, asthma history, hypertension, diabetes mellitus, and the year of inclusion. SP vaccination was associated with type of practice of the respiratory physician, age, smoking status, FEV1, exacerbation history, dyspnea grade, asthma history and the year of inclusion. CONCLUSION: Rates of vaccination against influenza and S. pneumoniae infection at inclusion in COPD cohorts remain insufficient and vaccination appears restricted to patients with specific features especially regarding severity and comorbidities, which is not consistent with current recommendations.

Topical corticosteroids for hives and itch (urticaria): systematic review and Bayesian meta-analysis of randomized trials.

BACKGROUND: Topical corticosteroids are widely used as a treatment for itch and wheals (urticaria), but their benefits and harms are unclear. OBJECTIVE: To systematically synthesize the benefits and harms of topical corticosteroids for the treatment of urticaria. METHODS: We searched MEDLINE, EMBASE, and CENTRAL from database inception to March 23, 2024, for randomized trials addressing comparing topical corticosteroid to placebo for patients with urticaria (either chronic spontaneous or inducible urticaria or acute urticaria elicited from skin/intradermal allergy testing). Paired reviewers independently screened records, extracted data, and assessed risk of bias. Random-effects meta-analyses addressed urticaria severity, itch severity (numeric rating scale; range 0-10; higher is worse), and adverse events. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach informed certainty of evidence ratings. PROSPERO registration: CRD42023455182. RESULTS: Nineteen RCTs enrolled 379 participants with a median of mean age of 30.1 years (range 21.1 to 44.0). Compared to placebo, topical corticosteroids may reduce wheal size (ratio of means 0.47, 95%CI 0.38 to 0.59; low certainty) and itch severity (mean difference -1.30, 95%CI -5.07 to 2.46; very low certainty). Topical corticosteroids result in little to no difference in overall adverse events (94 fewer patients per 1000, 95%CrI 172 fewer to 12 more; high certainty). CONCLUSION: Compared to placebo, topical corticosteroids may result in a reduction of wheal size, and result in little to no difference in overall adverse events. Topical corticosteroids may reduce itch severity, but the evidence is very uncertain. Future large, randomized trials addressing the use of topical corticosteroids would further support optimal urticaria management.

Synergistic impact of innate immunity hyper-activation and endothelial dysfunction on the magnitude of organ failure in the infection-sepsis continuum.

OBJECTIVES: identifying host response biomarkers implicated in the emergence of organ failure during infection is key to improving early detection of this complication. METHODS: twenty biomarkers of innate immunity, T-cell response, endothelial dysfunction, coagulation and immunosuppression were profiled in 180 surgical patients with infections of diverse severity (IDS) and 53 with no infection (nIDS). Those better differentiating IDS/nIDS in the area under the curve (AUC) were combined to test their association with the Sequential Organ Failure Assessment (SOFA) score by linear regression analysis in IDS. Results were validated in another IDS cohort of 174 patients. RESULTS: C-reactive protein, procalcitonin, pentraxin-3, lipocalin-2, TNF-α, angiopoietin-2, TREM-1 and IL-15 yielded AUCs ≥ 0.75 to differentiate IDS from nIDS. The combination of lipocalin-2, IL-15, TREM-1, angiopoietin-2 (Dys-4) showed the strongest association with SOFA in IDS (adjusted regression coefficient; standard error; p): Dys-4 (3.55;0.44; <0.001), Lipocalin-2 (2.24; 0.28; <0.001), angiopoietin-2 (1.92; 0.33; <0.001), IL-15 (1.78; 0.40; <0.001), TREM-1(1.74; 0.46; <0.001), TNF-α (1.60; 0.31; <0.001), pentraxin-3 (1.12; 0.18; <0.001), procalcitonin (0.85; 0.12; <0.001). Dys-4 provided similar results in the validation cohort. CONCLUSIONS: there is a synergistic impact of innate immunity hyper-activation (lipocalin-2, IL-15, TREM-1) and endothelial dysfunction (angiopoietin-2) on the magnitude of organ failure during infection.