健脾生血片治疗慢性心力衰竭伴贫血的临床效果

目的:探索健脾生血片治疗慢性心力衰竭伴贫血的疗效、安全性和作用机制。方法:选取2016年5月至2017年2月同济医院收治的慢性心力衰竭贫血患者144例,按照随机数字表法分为观察组和对照组,每组72例。观察组给予健脾生血片治疗,3片/次,3次/d,疗程3个月;对照组给予生血宝合剂治疗,15 m L/次,3次/d,3个月为1个疗程。比较2组患者治疗前与治疗后血红蛋白、红细胞计数、网织红细胞、血清铁、转铁蛋白饱和度、血清铁蛋白、血清铁调素(Hepcidin)、血清IL-1β、血清肿瘤坏死因子-α(TNF-α)、血清C反应蛋白(CRP)、左室射血分数(LVEF)、6 min步行距离、明尼苏达心力衰竭生命质量量表(MLHFQ)和不良事件。并随访2组心血管事件次数,住院次数与全因死亡率。结果:观察组72例患者完成了前3个月的治疗,随访期间脱失2例;对照组治疗期间1例患者退出研究,随访期间脱失4例。2组一般资料比较,差异无统计学意义(P 0. 05),具有可比性。观察组贫血有效率98. 6%,对照组有效率11. 3%,差异有统计学意义(P0. 05)。治疗后观察组红细胞计数和网织红细胞、均显著高于对照组(P 0. 05)。观察组血清铁、转铁蛋白饱和度水平均高于对照组,差异有统计学意义(P 0. 05),但血清铁调素水平显著低于对照组,差异有统计学意义(P 0. 05),血清铁蛋白水平2组差异无统计学意义(P 0. 05)。观察组IL-1β、血清TNF-α、血清CRP均显著低于对照组,差异有统计学意义(P 0. 05)。观察组LVEF、6 min步行距离、明尼苏达心力衰竭生命质量量表(MLHFQ)均显著高于对照组,差异有统计学意义(P 0. 05)。2组不良事件总发生率比较,差异无统计学意义(P 0. 05),但对照组4例患者出现血清肌酐、尿素氮水平异常,发生率高于观察组,差异有统计学意义(P 0. 05)。经1年随访,观察组心血管事件人均发生次数显著少于对照组(P 0. 05),但2组住院次数和全因死亡率比较,差异无统计学意义(P 0. 05)。结论:健脾生血片可有效治疗心力衰竭伴贫血,减少心血管发生次数,并且安全性良好,其作用机制与提供准确足量铁元素、抑制铁调素表达,抑制慢性炎性反应有关。     

良性前列腺增生与前列腺慢性炎症的相关性研究进展

良性前列腺增生（BPH）是老年男性常见的泌尿系统疾病，其发病与前列腺慢性炎症之间存在显著相关。感染因子、尿液返流、代谢综合征、衰老过程和自身免疫应答在内的几种刺激，通过相应分子途径引起前列腺免疫细胞的组织定位和组成成分发生广泛改变，从而导致免疫系统失调，之后引发的组织损伤和缓慢愈合，导致了BPH发生和进展。本文通过总结良性前列腺增生与前列腺慢性炎症的相关性的临床研究结果，前列腺免疫细胞在病理生理机制层面与前两者之间的内在联系，以及抗炎药物对BPH-LUTS的干预作用，以其为BPH-LUTS的药物研发提供参考。     

The interaction between pain and movement

Study DesignClinical commentary.Introduction/PurposePain and movement are universally relevant phenomena that influence human experiences in readily observable ways. Improved understanding of pain-movement relationships can guide medical and rehabilitative approaches to recovery and decrease risk of dysfunctional long-term consequences of otherwise normal neuromuscular responses. Therefore, the overall intent of this article is to elucidate the relationships between pain and movement as they relate to clinical decision making.ConclusionsMotor output is highly adaptable, can be influenced by multiple mechanisms at various levels along the nervous system, and may vary between individuals despite similar diagnoses. Therefore, interventions need to be individualized and consider both the types of motor response observed (ie, whether the response is protective or maladaptive), and the patient's acute physical activity tolerance when prescribing exercise/movement.     

Fractal dimension in CT low attenuation areas is predictive of long-term oxygen therapy initiation in COPD patients: Results from two observational cohort studies

BackgroundSome chronic obstructive pulmonary disease (COPD) patients develop hypoxemia with disease progression, with some even requiring long-term oxygen therapy (LTOT). Lung function, especially diffusing capacity, and the annual decline in PaO₂, are reported to be predictive factors of chronic respiratory failure. However, the association between lung morphometry evaluated using computed tomography (CT) images and LTOT initiation is unknown.MethodsWe retrospectively evaluated the relationship between clinical indices, including pulmonary function, body mass index (BMI), and CT parameters, at baseline and LTOT initiation in two prospective COPD cohorts. In the Nara Medical University cohort (n = 76), the low attenuation area (LAA) and its fractal dimension (fractal D) were adapted as the indices for parenchymal destruction in CT images. The association between these CT measurements and LTOT initiation was replicated in the Kyoto University cohort (n = 130).ResultsIn the Nara Medical University cohort, lower BMI (hazard ratio [HR]:0.70, p = 0.006), lower % diffusing capacity (%DLCO) (HR: 0.92, p = 0.006), lower %DLCO/VA (HR, 0.90, p = 0.008), higher RV/TLC (HR, 1.26, p = 0.012), higher LAA% (HR: 1.18, p = 0.001), and lower fractal D (HR: 3.27 × 10^?8, p < 0.001) were associated with LTOT initiation. Multivariate analysis in the Kyoto University cohort confirmed that lower %DLCO and lower fractal D were independently associated with LTOT initiation, whereas LAA% was not.ConclusionFractal D, which is the index for morphometric complexity of LAA in CT analysis, is predictive of LTOT initiation in COPD patients.     

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%.     

Electronic clinical records in primary care for estimating disease burden and management. An example of COPD

Chronic obstructive pulmonary disease (COPD) is a significant health problem in developed countries. We aimed to estimate the prevalence of COPD in a single Spanish healthcare area. We also aimed to assess if there are any differences in prevalence and spirometry use among primary care services by utilizing already registered information. We designed a cross-sectional study to determine the prevalence of COPD and the performance of spirometries in each primary care service. A total of 8,444 patients were diagnosed with COPD, with a prevalence of 2.6% for individuals older than 39 years. The prevalence increased with age and was much higher in men. Significant heterogeneity was found in the prevalence of COPD and spirometry use among primary care services. COPD was underdiagnosed and there was wide variability in spirometry use in our area. Greater efforts are needed to diagnose COPD in order to improve its clinical outcomes and to refine registries so that they can be used as reliable sources of information