中药生产过程质量控制关键技术研究进展

中医药发展已上升到国家战略层面,在医药行业贯彻实施"中国制造2025"战略的新形势下,中药生产过程质量控制是中药工业需要加快突破的关键领域之一。对中药生产过程质量控制领域在工艺设计、分析检测、过程建模、制造装备等方面的关键共性问题进行解析,综述了中药生产过程质量控制体系中工艺过程理解、生产过程实时分析方法开发、过程控制策略建立3个方面的研究进展;并结合企业研究实践,介绍了质量源于设计(quality by design,Qb D)、过程分析技术(process analytical technology,PAT)、实验设计(design of experiment,DOE)、多变量统计分析等关键技术在上述3个研究方向中的应用进展,分析了实际工业应用的难点问题并对其应用前景进行展望,旨在为中药企业应用和提升生产过程质量控制技术提供参考。     

脑出血围手术期护理安全中细节管理的重要性分析

目的分析脑出血围手术期护理安全中细节管理的重要性。方法将于2018年6-10月在该院接受治疗的60例脑出血围术期患者作为该研究的常规组。将于2018年11月-2019年3月在该院接受治疗的60例脑出血围术期患者作为该研究的细节组。该院于2018年11月开始实施细节管理,以加强保障脑出血围术期患者的安全。对比两组患者的护理满意度、手术失败率、死亡率、住院时间及日常生活能力。结果细节组护理满意度明显高于常规组(P<0.05)。常规组的手术失败率、死亡率为均高于细节组,差异无统计学意义(P>0.05);细节组的住院时间明显短于常规组(P<0.05),ADL评分明显大于常规组(P<0.05)。结论细节管理在脑出血围手术期护理安全中具有相当重要性,可提升护理满意度,加快恢复速度,提升恢复效果。     

Simeprevir added to peginterferon and ribavirin lessens time with fatigue,depressive symptoms and functional limitations in patients with chronic hepatitis C compared with peginterferon and ribavirin: results from 1161 patients in the QUEST‐1, QUEST‐2 and PROMISE studies

The value of adding simeprevir (SMV) vs placebo (PBO) to peginterferon and ribavirin (PR) for treatment of chronic hepatitis C virus infection was examined using patient‐reported outcomes (PROs); further, concordance of PROs with virology endpoints and adverse events (AEs) was explored. Patients (n = 768 SMV/PR, n = 393 PBO/PR) rated fatigue (FSS), depressive symptoms (CES‐D) and functional impairment (WPAI: Hepatitis C Productivity, Daily Activity and Absenteeism) at baseline and throughout treatment in three randomised, double‐blind trials comparing the addition of SMV or PBO during initial 12 weeks of PR. PR was administered for 48 weeks (PBO group) and 24/48 weeks (SMV group) using a response‐guided therapy (RGT) approach. Mean PRO scores (except Absenteeism) worsened from baseline to Week 4 to the same extent in both groups but reverted after Week 24 for SMV/PR and only after Week 48 for PBO/PR. Accordingly, there was a significantly lower area under the curve (baseline–Week 60, AUC₆₀) and fewer weeks with clinically important worsening of scores in the SMV/PR group at any time point. Incidences of patients with fatigue and anaemia AEs were similar in both groups, but FSS scores showed that clinically important increases in fatigue lasted a mean of 6.9 weeks longer with PBO/PR (P < 0.001). PRO score subgroup analysis indicated better outcomes for patients who met the criteria for RGT or achieved sustained virological response 12 weeks post‐treatment (SVR12); differences in mean PRO scores associated with fibrosis level were only observed with PBO/PR. Greater efficacy of SMV/PR enabled reduced treatment duration and reduced time with PR‐related AEs without adding to AE severity.     

Prostatic Artery Embolization—Anatomic Predictors of Technical Outcomes

PurposeTo determine if cone-beam CT and digital subtraction angiography analysis of pelvic arterial anatomy has predictive value for radiation exposure and technical success of prostatic artery embolization (PAE).Materials and MethodsThis prospective, nonrandomized, single-center study included 104 consecutive patients with lower urinary tract symptoms secondary to benign prostatic hyperplasia. Cone-beam CT was performed in 160/208 (76.9%) hemipelves to determine prostatic artery (PA) origin. Classification of pelvic arterial tortuosity was possible in 73/104 (70.2%) patients. Learning curves of 2 interventionalists who performed 86.5% of PAEs were analyzed.ResultsTortuosity of pelvic arteries was classified as mild in 25 (34.2%) patients median age 64 years, moderate in 40 (54.8%) patients median age 69 years, and severe in 8 (11.0%) patients median age 70 years (mild vs moderate, P = .002; mild vs severe, P = .019); median fluoroscopy times were 24, 36, and 46 minutes (P = .008, P = .023); median contrast volumes were 105, 122.5, and 142 mL (P = .029, P = .064); and bilateral PAE rates were 84.0%, 77.5%, and 62.5% (P = .437), respectively. PA origin from superior vesical artery was most frequent (27.5%) and showed higher dose area product (median 402.4 vs 218 Gy ∙ cm², P = .033) and fluoroscopy time (median 42.5 vs 27 min, P = .01) compared with PA origin from obturator artery, which was least frequent. Interventionalist experience revealed significant impact on procedure times (median 159 vs 130 min, P = .006).ConclusionsTortuosity of pelvic arteries was more frequent in older patients and predicted worse technical outcomes of PAE. PA origin from obturator artery was associated with lower dose area product and fluoroscopy time, especially compared with PA origin from superior vesical artery. Interventionalist experience showed significant influence on technical outcome.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.