SAA、hs-CRP、IL-6联合检测在儿童感染性疾病中的诊断价值

目的:分析SAA、hs-CRP、IL-6联合检测在儿童感染性疾病中的诊断价值。方法:选择2019年1月~2020年10月某院收治的72例感染性疾病患儿开展研究,根据患儿的病原体检测结果划分为病毒感染组和细菌感染组各36例,另选择同期体检的36名健康儿童作为研究的参照组,分别比较3组的SAA、hs-CRP、IL-6等指标水平的差异。结果:细菌感染组的SAA、hs-CRP、IL-6等指标水平及阳性率均高于病毒感染组、参照组,同时病毒感染组的SAA、hs-CRP、IL-6等指标水平及阳性率高于参照组(P<0.05);SAA、hs-CRP、IL-6联合诊断的敏感度、准确度、阳性预测值、阴性预测值均高于SAA、hs-CRP、IL-6三个指标单独检测的敏感度、准确度、阳性预测值、阴性预测值,差异有统计学意义(P<0.05);联合检测的特异度与单独检测特异度对比无统计学意义(P>0.05)。结论:SAA、hs-CRP、IL-6联合诊断在儿童感染性疾病中具备较高的诊断价值,临床可将SAA、hs-CRP、IL-6作为该病的诊断辅助指标,有效提高疾病的诊断准确性。     

EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

EZH2对弥漫大B细胞淋巴瘤RCHOP方案治疗效果的预测价值

目的:探讨Zeste基因增强子(enhancer of zeste homolog 2,EZH2)对弥漫大B细胞淋巴瘤(diffuse large B-cell lymphoma,DLBCL)RCHOP方案治疗的效果的预测价值。方法:纳入2017年1月至2018年5月南华大学附属第二医院80例接受RCHOP方案治疗的DLBCL患者,分析患者EZH2表达情况与治疗效果的关系,绘制EZH2预测治疗效果的ROC曲线,并对患者pCR与病理特征的关系进行讨论。结果:80例患者中EZH2高表达者49例,EZH2低表达者31例,DLBCL患者RCHOP治疗的pCR率为51.25%,其中EZH2高表达患者完全缓解(complete response,CR)、客观缓解率(objective response rate,ORR)均明显低于EZH2低表达患者(P<0.05);EZH2预测治疗效果的曲线下面积为0.874(P<0.05);pCR与性别、年龄、美国东部肿瘤协作组(Eastern Cooperative Oncology Group,ECOG)得分、淋巴瘤国际预后指数(International Prognostic Index,IPI)得分、乳酸脱氢酶(lactate dehydrogenase,LDH)因素无相关关系(P>0.05);与Hans分型、EZH2表达水平存在一定的相关性(P<0.05)。结论:DLBCL患者EZH2低表达是RCHOP治疗后高pCR率的预测因子,在临床上有助于为DLBCL患者临床治疗提供更好的指导。     

多排螺旋CT诊断腹内疝的临床价值

目的研究分析腹内疝患者采用多排螺旋CT进行诊断的临床价值。方法将本院接收的32例腹内疝患者作为此次研究之中的观察主体,均通过手术证实,临床资料完整,均进行多排螺旋CT检查,对其诊断结果进行分析,对比CT与手术证实的符合率。结果多排螺旋CT确诊率高达90.63%,与手术证实结果无差异(P> 0.05);同时,通过多排螺旋CT检查,可清晰的观察到腹内疝相关征象,与手术证实结果高度一致,无显著差异(P> 0.05)。结论多排螺旋CT诊断技术能够较好的诊断腹内疝,且CT征象清晰,为临床有效诊治腹内疝提供了可靠指导,值得在临床中普及。     

Diffusion-weighted MRI and PET/CT reproducibility in epithelial ovarian cancers during neoadjuvant chemotherapy

PurposeTo investigate the reproducibility of diffusion-weighted (DW) MRI and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG)-Positron emission tomography/CT (PET/CT) in monitoring response to neoadjuvant chemotherapy in epithelial ovarian cancer.Materials and methodsTen women (median age, 67 years; range: 41.8–77.3 years) with stage IIIC-IV epithelial ovarian cancers were included in this prospective trial (NCT02792959) between 2014 and 2016. All underwent initial laparoscopic staging, four cycles of carboplatine-paclitaxel-based chemotherapy and interval debulking surgery. PET/CT and DW-MRI were performed at baseline (C0), after one cycle (C1) and before surgery (C4). Two nuclear physicians and two radiologists assessed five anatomic sites for the presence of ≥ 1 lesion. Target lesions in each site were defined and their apparent diffusion coefficient (ADC), maximal standardized uptake value (SUV-max), SUV-mean, SUL-peak, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were monitored (i.e., 10 patients × 5 sites × 3 time-points). Their relative early and late changes were calculated. Intra/inter-observer reproducibilities of qualitative and quantitative analysis were estimated with Kappa and intra-class correlation coefficients (ICCs).ResultsFor both modalities, inter- and intra-observer agreement percentages were excellent for initial staging but declined later for DW-MRI, leading to lower Kappa values for inter- and intra-observer variability (0.949 and 1 at C0, vs. 0.633 and 0.643 at C4, respectively) while Kappa values remained > 0.8 for PET/CT. Inter- and intra-observer ICCs were > 0.75 for SUV-max, SUL-peak, SUV-mean and their change regardless the time-point. ADC showed lower ICCs (range: 0.013–0.811). ANOVA found significant influences of the evaluation time, the measurement used (ADC, SUV-max, SUV-mean, SUV-max, SUL-peak, MTV or TLG) and their interaction on ICC values (P = 0.0023, P< 0.0001 and P =0.0028, respectively).ConclusionWhile both modalities demonstrated high reproducibility at baseline, only SUV-max, SUL-peak, SUV-mean and their changes maintained high reproducibility during chemotherapy.     

糖化血红蛋白在糖尿病(DM)诊断中的应用价值

目的探究糖化血红蛋白在糖尿病(DM)诊断中的应用价值。方法选取该院收治的36例糖尿病(DM)患者作为观察组,时间区间为2019年10月—2020年10月,实施糖化血红蛋白展开筛查和诊断,同时选择36名无糖尿病的健康者为对照组,分析并发症发生率、血糖指标、生活质量、心理状态评分等情况。结果观察组的空腹血糖、糖化血红蛋白和餐后2 h血糖的指标均高于对照组,差异有统计学意义(P<0.05);观察组经糖化血红蛋白展开筛查和诊断后,发现其各项生活质量评分均高于筛查诊断前,差异有统计学意义(P<0.05)。结论针对糖尿病(DM)患者,采用糖化血红蛋白展开筛查和诊断,可有效反映患者血糖改变情况,进一步提升临床上患者疾病诊断准确性,改善其不良负性心理情绪,提供可靠的参考资料,同时显著改善患者的生活质量,安全有效,具有临床应用价值。     

Influence of coronary stenosis location on diagnostic performance of machine learning-based fractional flow reserve from CT angiography

BackgroundCompared with invasive fractional flow reserve (FFR), coronary CT angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based FFR (CT-FFR) is an approach to overcome this insufficiency by use of computational fluid dynamics. Applying recent innovations in computer science, a machine learning (ML) method for CT-FFR derivation was introduced and showed improved diagnostic performance compared to cCTA alone. We sought to investigate the influence of stenosis location in the coronary artery system on the performance of ML-CT-FFR in a large, multicenter cohort.MethodsThree hundred and thirty patients (75.2% male, median age 63 years) with 502 coronary artery stenoses were included in this substudy of the MACHINE (Machine Learning Based CT Angiography Derived FFR: A Multi-Center Registry) registry. Correlation of ML-CT-FFR with the invasive reference standard FFR was assessed and pooled diagnostic performance of ML-CT-FFR and cCTA was determined separately for the following stenosis locations: RCA, LAD, LCX, proximal, middle, and distal vessel segments.ResultsML-CT-FFR correlated well with invasive FFR across the different stenosis locations. Per-lesion analysis revealed improved diagnostic accuracy of ML-CT-FFR compared with conventional cCTA for stenoses in the RCA (71.8% [95% confidence interval, 63.0%–79.5%] vs. 54.8% [45.7%–63.8%]), LAD (79.3 [73.9–84.0] vs. 59.6 [53.5–65.6]), LCX (84.1 [76.0–90.3] vs. 63.7 [54.1–72.6]), proximal (81.5 [74.6–87.1] vs. 63.8 [55.9–71.2]), middle (81.2 [75.7–85.9] vs. 59.4 [53.0–65.6]) and distal stenosis location (67.4 [57.0–76.6] vs. 51.6 [41.1–62.0]).ConclusionIn a multicenter cohort with high disease prevalence, ML-CT-FFR offered improved diagnostic performance over cCTA for detecting hemodynamically relevant stenoses regardless of their location.