大承气汤加减治疗脑病医案3则

通过病案举例,介绍大承气汤在中医脑病治疗中的使用技巧,说明大承气汤可以运用于出血性中风头痛、癫痫、失眠等多种脑病的治疗,疗效显著。大承气汤具有通腑泄热、祛邪外出的作用。对于六经辨证属阳明腑实证者,无论病种,皆可用大承气汤加味化裁。     

医用退热贴冷敷治疗产后生理性乳房胀痛的效果观察

目的 比较医用退热贴冷敷及卷心菜叶外敷2种方法对缓解产后生理性乳房胀痛的疗效。方法 选取2018年3-12月在产科住院的产后生理性乳房胀痛的患者100例为研究对象,将其随机分为对照组和观察组,各50例。对照组采用卷心菜叶外敷,观察组采用医用退热贴冷敷。结果 观察组产后生理性胀痛乳房评分低于对照组(Z=-2.568,P=0.010),乳房硬度优于对照组(Z=-4.361,P<0.001),使用维持时间长于对照组(t=19.804,P＜0.001)。结论 医用退热贴冷敷用于产后生理性乳房胀痛效果理想,操作方法简单易行,实施方便,易被产妇接受,值得临床推广应用。     

Braden scale for pressure ulcer risk predicts rehabilitation placement after pancreatic resection

BackgroundPatients undergoing pancreatic resection frequently require rehabilitation facilities after hospital discharge. We evaluated the predictive role of validated markers of frailty on rehabilitation facility placement to identify patients who may require this service.MethodsSingle-center retrospective cohort study of patients who underwent pancreatic resection from 2010 to 2015. 90-day morbidity and mortality were calculated. Postoperative validated markers of frailty (Activities of Daily Living scale, Braden scale [assesses pressure ulcer risk, lower scores = higher risk] and Morse fall scale) were evaluated via multivariate regression to identify predictors of discharge to rehabilitation facility.Results470 patients with complete data were included. Mean age was 62 and 49.2% were male. Postoperative median length of stay (LOS) was 8 (IQR 7–10). 92 (19.66%) patients were discharged to rehabilitation facilities and 138 (29.49%) patients were readmitted within 90 days. On multivariate analysis, age, sex, LOS > 8 days, inpatient Comprehensive Complication Index (CCI) and initial Braden scale were predictive of rehabilitation placement.ConclusionA marker of frailty routinely collected daily by nursing staff, the Braden scale, is available to help surgeons predict the need for postoperative rehabilitation placement after pancreatic resection. Engaging discharge planning services for at-risk patients may help prevent delayed hospital discharge and should be further evaluated.     

Study of Haralick’s and GLCM texture analysis on 3D medical images

Purpose of the study: Medical field has highly evolved with advancements in the technologies which prove to be beneficial for radiologists and patients for better diagnosis. The era of medical science provides best healthcare solutions with the help of medical images. Till now, 2D MRIs played a prominent role in early detection of disease but with latest technologies taking over the charge, 3D MRIs are highly effective and great in demand nowadays. With the aid of advanced techniques such as edge detection, segmentation and texture analysis on these images, the disease detection may become much easier.

Materials and Methods: Texture of any image is recognized by distribution of gray levels in the neighborhood. The Texture Analysis plays an important role in study of medical images. It identifies the prominent features of an image and highlights the same using different feature extraction technique. In this paper, 3D MRI of human brain is considered and texture analysis based on Haralick's and GLCM texture features is performed. Haralick's feature explains the image intensities of each pixel and their relationship with neighborhood pixels. The entire data set consists of 40 brain tumor patients, out of which a sample has been depicted.

Results: The analysis of different features such as Contrast, Correlation, Energy, Homogeneity and Entropy is carried out. Conclusion: Further, the study highlights about the highly useful features for early detection of brain tumor disease.