Epidemiologic features and therapeutic strategies of kerion: A nationwide multicentre study.

BACKGROUND: Kerion is a severe type of tinea capitis that is difficult to treat and remains a public health problem. OBJECTIVES: To evaluate the epidemiologic features and efficacy of different treatment schemes from real-world experience. METHODS: From 2019 to 2021, 316 patients diagnosed with kerion at 32 tertiary Chinese hospitals were enrolled. We analysed the data of each patient, including clinical characteristics, causative pathogens, treatments and outcomes. RESULTS: Preschool children were predominantly affected and were more likely to have zoophilic infection. The most common pathogen in China was Microsporum canis. Atopic dermatitis (AD), animal contact, endothrix infection and geophilic pathogens were linked with kerion occurrence. In terms of treatment, itraconazole was the most applied antifungal agent and reduced the time to mycological cure. A total of 22.5% of patients received systemic glucocorticoids simultaneously, which reduced the time to complete symptom relief. Furthermore, glucocorticoids combined with itraconazole had better treatment efficacy, with a higher rate and shorter time to achieving mycological cure. CONCLUSIONS: Kerion often affects preschoolers and leads to serious sequelae, with AD, animal contact, and endothrix infection as potential risk factors. Glucocorticoids, especially those combined with itraconazole, had better treatment efficacy.

A Destructive Midfacial Mass in a Middle-Aged Man.

A 43-year-old man presented with a destructive mass on the nose, with multiple areas of erosion, ulcers, and exudate covering the mass. Histological examination showed polymorphous lymphocytic infiltration in the full-thickness dermis. What is your diagnosis?

Dermatophyte infection: from fungal pathogenicity to host immune responses.

Dermatophytosis is a common superficial infection caused by dermatophytes, a group of pathogenic keratinophilic fungi. Apart from invasion against skin barrier, host immune responses to dermatophytes could also lead to pathologic inflammation and tissue damage to some extent. Therefore, it is of great help to understand the pathogenesis of dermatophytes, including fungal virulence factors and anti-pathogen immune responses. This review aims to summarize the recent advances in host-fungal interactions, focusing on the mechanisms of anti-fungal immunity and the relationship between immune deficiency and chronic dermatophytosis, in order to facilitate novel diagnostic and therapeutic approaches to improve the outcomes of these patients.

Asymptomatic Candida glabrata urinary tract infection in an immunocompetent young female: A case report.

INTRODUCTION: Fungal urinary tract infections (UTIs) are becoming increasingly common in hospitalized patients and Candida species are the most prevalent organisms. However, recurrent candiduria in young healthy outpatients is rare thus require further examination to find the etiologic factors. CASE PRESENTATION: We described a case of recurrent asymptomatic c caused by azole-resistant C. glabrata in a healthy young female who only had previous use of antibiotics without other risk factors. However, after removal of the predisposing factor and the use of sensitive antifungal agents, the patient's urine cultures remained positive. This phenomenon indicated to us that the patient might have an immune-related genetic deficiency. We found a novel caspase-associated recruitment domain-containing protein 9 (CARD9) gene mutation (c.808-11G > T) which might be the cause of recurrent asymptomatic candiduria in this immune-competent young female without any underlying diseases. CONCLUSIONS: We report a case of recurrent asymptomatic candiduria caused by azole-resistant Candida glabrata in a young healthy female with a novel CARD9 mutation. A functional study of this mutation should be performed in the future to determine its effect on asymptomatic fungal UTIs.

Cutaneous granuloma annulare in an adult patient with macrophage activation syndrome.

Macrophage activation syndrome (MAS) is a rare but life-threatening disorder that is associated with multiple organ involvement. Here, we described cutaneous granuloma annulare in MAS. This novel histological finding is a reminder to explore the underlying mechanisms of skin involvement in MAS, which may reveal its pathogenesis.

Machine learning algorithm as a prognostic tool for venous thromboembolism in allogeneic transplant patients.

As a serious complication after allogenic hematopoietic stem cell transplantation (allo-HSCT), venous thromboembolism (VTE) is significantly related to increased nonrelapse mortality. Therefore distinguishing patients at high risk of death who should receive specific therapeutic management is key to improving survival. This study aimed to establish a machine learning-based prognostic model for the identification of post-transplantation VTE patients who have a high risk of death. We retrospectively evaluated 256 consecutive VTE patients who underwent allo-HSCT at our center between 2008 and 2019. These patients were further randomly divided into (1) a derivation (80%) cohort of 205 patients and (2) a test (20%) cohort of 51 patients. The least absolute shrinkage and selection operator (LASSO) approach was used to choose the potential predictors from the primary dataset. Eight machine learning classifiers were used to produce 8 candidate models. A 10-fold cross-validation procedure was used to internally evaluate the models and to select the best-performing model for external assessment using the test cohort. In total, 256 of 7238 patients were diagnosed with VTE after transplantation. Among them, 118 patients (46.1%) had catheter-related venous thrombosis, 107 (41.8%) had isolated deep-vein thrombosis (DVT), 20 (7.8%) had isolated pulmonary embolism (PE), and 11 (4.3%) had concomitant DVT and PE. The 2-year overall survival (OS) rate of patients with VTE was 68.8%. Using LASSO regression, 8 potential features were selected from the 54 candidate variables. The best-performing algorithm based on the 10-fold cross-validation runs was a logistic regression classifier. Therefore a prognostic model named BRIDGE was then established to predict the 2-year OS rate. The areas under the curves of the BRIDGE model were 0.883, 0.871, and 0.858 for the training, validation, and test cohorts, respectively. The Hosmer-Lemeshow goodness-of-fit test showed a high agreement between the predicted and observed outcomes. Decision curve analysis indicated that VTE patients could benefit from the clinical application of the prognostic model. A BRIDGE risk score calculator for predicting the study result is available online (47.94.162.105:8080/bridge/). We established the BRIDGE model to precisely predict the risk for all-cause death in VTE patients after allo-HSCT. Identifying VTE patients who have a high risk of death can help physicians treat these patients in advance, which will improve patient survival.

A prognostic model (BATAP) with external validation for patients with transplant-associated thrombotic microangiopathy.

Transplant-associated thrombotic microangiopathy (TA-TMA) is a potentially life-threatening complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT). Information on markers for early prognostication remains limited, and no predictive tools for TA-TMA are available. We attempted to develop and validate a prognostic model for TA-TMA. A total of 507 patients who developed TA-TMA following allo-HSCT were retrospectively identified and separated into a derivation cohort and a validation cohort, according to the time of transplantation, to perform external temporal validation. Patient age (odds ratio [OR], 2.371; 95% confidence interval [CI], 1.264-4.445), anemia (OR, 2.836; 95% CI, 1.566-5.138), severe thrombocytopenia (OR, 3.871; 95% CI, 2.156-6.950), elevated total bilirubin (OR, 2.716; 95% CI, 1.489-4.955), and proteinuria (OR, 2.289; 95% CI, 1.257-4.168) were identified as independent prognostic factors for the 6-month outcome of TA-TMA. A risk score model termed BATAP (Bilirubin, Age, Thrombocytopenia, Anemia, Proteinuria) was constructed according to the regression coefficients. The validated c-statistic was 0.816 (95%, CI, 0.766-0.867) and 0.756 (95% CI, 0.696-0.817) for the internal and external validation, respectively. Calibration plots indicated that the model-predicted probabilities correlated well with the actual observed frequencies. This predictive model may facilitate the prognostication of TA-TMA and contribute to the early identification of high-risk patients.

Clinical risk factors and prognostic model for idiopathic inflammatory demyelinating diseases after haploidentical hematopoietic stem cell transplantation in patients with hematological malignancies.

Idiopathic inflammatory demyelinating diseases (IIDDs) of the central nervous system (CNS) are rare but serious neurological complications of haploidentical hematopoietic stem cell transplantation (haplo-HSCT). However, the risk factors and a method to predict the prognosis of post-transplantation CNS IIDDs are not available. This retrospective study first reviewed data from 4532 patients who received haplo-HSCT during 2008-2019 in our center, and 184 patients (4.1%) with IIDDs after haplo-HSCT were identified. Grades II to IV acute graft-versus-host disease (aGVHD) (p < 0.001) and chronic GVHD (cGVHD) (p = 0.009) were identified as risk factors for developing IIDDs after haplo-HSCT. We then divided the 184 IIDD patients into a derivation cohort and validation cohort due to transplantation time to develop and validate a model for predicting the prognosis of IIDDs. In the multivariate analysis of the derivation cohort, four candidate predictors were entered into the final prognostic model: cytomegalovirus (CMV) infection, Epstein-Barr virus (EBV) infection, IgG synthesis (IgG-syn) and spinal cord lesions. The prognostic model had an area under the receiver operating characteristic curve of 0.864 (95% CI: 0.803-0.925) in the internal validation cohort and 0.871 (95% CI: 0.806-0.931) in the external validation cohort. The calibration plots showed a high agreement between the predicted and observed outcomes. Decision curve analysis indicated that IIDD patients could benefit from the clinical application of the prognostic model. The identification of IIDD patients after allo-HSCT who have a poor prognosis might allow timely treatment and improve patient survival and outcomes.