Circulating CCL20: A potential biomarker for active vitiligo together with the number of Th1/17 cells

Background

Vitiligo is an autoimmune disease with varying pathological features. Activation of the CCL20-CCR6 axis plays an important role in chronic inflammatory diseases. However, whether CCL20-CCR6 and Th1/17 cells are indicative of active vitiligo is unclear.

Artificial Intelligence–Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General Population

ObjectiveTo validate an artificial intelligence–augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort.MethodsWe identified a randomly selected community-based cohort of 2041 subjects age 45 years or older in Olmsted County, Minnesota. All participants underwent a study echocardiogram and ECG. We first assessed the performance of the AI-ECG to identify LVSD (ejection fraction ≤40%). After excluding participants with clinical heart failure, we further assessed the AI-ECG to detect preclinical LVSD among all patients (n=1996) and in a high-risk subgroup (n=1348). Next we modelled an imputed screening program for preclinical LVSD detection where a positive AI-ECG triggered an echocardiogram. Finally, we assessed the ability of the AI-ECG to predict future LVSD. Participants were enrolled between January 1, 1997, and September 30, 2000; and LVSD surveillance was performed for 10 years after enrollment.ResultsFor detection of LVSD in the total population (prevalence, 2.0%), the area under the receiver operating curve for AI-ECG was 0.97 (sensitivity, 90%; specificity, 92%); in the high-risk subgroup (prevalence 2.7%), the area under the curve was 0.97 (sensitivity, 92%; specificity, 93%). In an imputed screening program, identification of one preclinical LSVD case would require 88.3 AI-ECGs and 8.7 echocardiograms in the total population and 65.7 AI-ECGs and 5.5 echocardiograms in the high-risk subgroup. The unadjusted hazard ratio for a positive AI-ECG for incident LVSD over 10 years was 2.31 (95% CI, 1.32 to 4.05; P=.004).ConclusionArtificial intelligence–augmented ECG can identify preclinical LVSD in the community and warrants further study as a screening tool for preclinical LVSD.     

乡土特色的少年宫活动对中小学生积极心理品质的提升作用

目的探究乡土特色少年宫活动对学生积极心理品质的提升作用。方法采用实验组、对照组前后测实验设计,选取绵阳市某学校三年级到八年级学生共530名,随机分为实验组(n=265)和对照组(n=265)。实验组学生参与12次为期90天的乡土特色的少年宫活动,对照组处于常态。活动前后采用中国中小学生积极心理品质量表进行测量。结果①实验组和对照组在六个维度上的前测分数差异均无统计学意义(P均0.05)。②实验组在人际维度、公正维度、节制维度、超越维度上,后测分数均高于前测,差异有统计学意义(P0.05);而在认知维度和情感维度上,前、后测分数差异无统计学意义(P均0.05)。③对照组在六个维度上的前后测分数差异均无统计学意义(P均0.05)。④后测分数中,实验组在人际维度、公正维度、节制维度、超越维度上的得分均高于对照组,差异有统计学意义(P0.05);而两组在认知维度和情感维度上分数差异无统计学意义(P均0.05)。结论乡土特色的少年宫活动可能有利于提升中小学生人际、公正、节制和超越等积极心理品质。     

Nationwide survey of Arima syndrome: Revised diagnostic criteria from epidemiological analysis

Aim: We have never known any epidemiological study of Arima syndrome since it was first described in 1971. To investigate the number of Arima syndrome patients and clarify the clinical differences between Arima syndrome and Joubert syndrome, we performed the first nationwide survey of Arima syndrome, and herein report its results. Furthermore, we revised the diagnostic criteria for Arima syndrome. Methods: As a primary survey, we sent out self-administered questionnaires to most of the Japanese hospitals with a pediatric clinic, and facilities for persons with severe motor and intellectual disabilities, inquiring as to the number of patients having symptoms of Arima syndrome, including severe psychomotor delay, agenesis or hypoplasia of cerebellar vermis, renal dysfunction, visual dysfunction and with or without ptosis-like appearance. Next, as the second survey, we sent out detailed clinical questionnaires to the institutes having patients with two or more typical symptoms. Results: The response rate of the primary survey was 72.7% of hospitals with pediatric clinic, 63.5% of national hospitals and 66.7% of municipal and private facilities. The number of patients with 5 typical symptoms was 13 and that with 2–4 symptoms was 32. The response rate of the secondary survey was 52% (23 patients). After reviewing clinical features of 23 patients, we identified 7 Arima syndrome patients and 16 Joubert syndrome patients. Progressive renal dysfunction was noticed in all Arima syndrome patients, but in 33% of those with Joubert syndrome. Conclusion: It is sometimes difficult to distinguish Arima syndrome from Joubert syndrome. Some clinicians described a patient with Joubert syndrome and its complications of visual dysfunction and renal dysfunction, whose current diagnosis was Arima syndrome. Thus, the diagnosis of the two syndromes may be confused. Here, we revised the diagnostic criteria for Arima syndrome.     

Use of AUDIT-C as a tool to identify hazardous alcohol consumption in admitted trauma patients

Introduction

Alcohol use is an important contributor to injuries. Simple bedside tools to identify trauma patients with potentially harmful drinking may assist in brief intervention efforts in clinical practice. The objective of the study was to determine and compare the accuracy of alcohol use disorders identification test (AUDIT) and an abbreviated version of this test, in the detection of hazardous drinking.

Methods

A cross-sectional study of a convenience sample of admitted trauma patients at a single Australian major trauma centre. Eligible patients completed the AUDIT. AUDIT survey responses were scored in two ways, using the full form scale and secondly an abbreviated (AUDIT C) scale which uses only the first 3 questions. AUDIT and AUDIT-C scores were then evaluated with respect to the primary study measure; the detection of hazardous alcohol consumption based on a full alcohol consumption history. Sensitivities for each relevant score were calculated and receiver operator characteristic (ROC) curve analysis was used to determine test accuracy.

Results

During the study period, 523 trauma admissions were identified and of these 146 (28%) were screened. The optimum cut off scores for AUDIT and AUDIT-C were 8 and 5 respectively corresponding to sensitivities of 88% and 91% and both tests had excellent overall accuracy for the detection of hazardous alcohol consumption. There was no significant difference between AUDIT-C and AUDIT performance (p = 0.395) (AUDIT-C AUROC 0.96 95%CI 0.93, 0.99).

Conclusion

AUDIT-C appears to be a potentially useful screening tool for use trauma centres, but that further research with larger samples is required.