健康信念模式在吸毒致股动脉假性动脉瘤患者中的应用效果

目的：探讨健康信念模式在吸毒致股动脉假性动脉瘤患者中的应用效果。方法选取60例吸毒致股动脉假性动脉瘤患者随机分为研究组和对照组各30例。对照组给予常规护理，研究组在对照组的基础上给予健康信念模式进行干预，比较两组患者对疾病的认知、健康态度、焦虑及抑郁程度、住院时间。结果两组中以研究组对疾病的认知得分和健康态度得分较高，抑郁及焦虑得分较低，住院时间更短，各指标相比较，差异有统计学意义（ P＜0．01或P＜0．05）。结论健康信念模式能有效地提高吸毒致股动脉假性动脉瘤患者对疾病的认识，并改善其健康态度和不良心理状态，使患者临床恢复的时间也明显缩短。     

Description of Leprosy Classification at Baseline among Patients Enrolled at the Uniform Multidrug Therapy Clinical Trial for Leprosy Patients in Brazil

The uniform multidrug therapy clinical trial, Brazil (U-MDT/CT-BR), database was used to describe and report the performance of available tools to classify 830 leprosy patients as paucibacillary (PB) and multibacillary (MB) at baseline. In a modified Ridley and Jopling (R&J) classification, considering clinical features, histopathological results of skin biopsies and the slit-skin smear bacterial load results were used as the gold standard method for classification. Anti-phenolic glycolipid-I (PGL-I) serology by ML Flow test, the slit skin smear bacterial load, and the number of skin lesions were evaluated. Considering the R&J classification system as gold standard, ML Flow tests correctly allocated 70% patients in the PB group and 87% in the MB group. The classification based on counting the number of skin lesions correctly allocated 46% PB patients and 99% MB leprosy cases. Slit skin smears properly classified 91% and 97% of PB and MB patients, respectively. Based on U-MDT/CT-BR results, classification of leprosy patients for treatment purposes is unnecessary because it does not impact clinical and laboratories outcomes. In this context, the identification of new biomarkers to detect patients at a higher risk to develop leprosy reactions or relapse remains an important research challenge.     

Genome-wide haplotypic testing in a Finnish cohort identifies a novel association with low-density lipoprotein cholesterol

We performed genome-wide tests for association between haplotype clusters and each of 9 metabolic traits in a cohort of 5402 Northern Finnish individuals genotyped for 330 000 single-nucleotide polymorphisms. The metabolic traits were body mass index, C-reactive protein, diastolic blood pressure, glucose, high-density lipoprotein (HDL), insulin, low-density lipoprotein (LDL), systolic blood pressure, and triglycerides. Haplotype clusters were determined using Beagle. There were LDL-associated clusters in the chromosome 4q13.3-q21.1 region containing the albumin (ALB) and platelet factor 4 (PF4) genes. This region has not been associated with LDL in previous genome-wide association studies. The most significant haplotype cluster in this region was associated with 0.488 mmol/l higher LDL (95% CI: 0.361–0.615 mmol/l, P-value: 6.4 × 10⁻¹⁴). We also observed three previously reported associations: Chromosome 16q13 with HDL, chromosome 1p32.3-p32.2 with LDL and chromosome 19q13.31-q13.32 with LDL. The chromosome 1 and chromosome 4 LDL associations do not reach genome-wide significance in single-marker analyses of these data, illustrating the power of haplotypic association testing.