Purpose: To use polymerase chain reaction (PCR) and Goldmann-Witmer coefficient (GWC) calculation to diagnose infectious uveitis.
Methods: Prospective cross-sectional study.
Results: Twenty-seven of 106 patients had positive PCR and/or GWC results on aqueous humor (AH) sampling and 15 of 27 (55.6%) were HIV-positive. Patients with non-anterior uveitis (NAU) were more likely to be HIV+ (p = 0.005). More than 1 possible pathogen was identified in 9 of 27 patients of whom 7 were HIV+. The final clinical diagnosis was discordant with AH findings in 9 of 27 cases. A positive EBV PCR result was associated with a discordant diagnosis (p = 0.001). All cases of herpetic anterior uveitis (42.9% HIV+) tested PCR-/GWC+ while all cases of herpetic NAU tested PCR+/GWC- (83.3% HIV+). All rubella virus cases were PCR+/GWC+.
Conclusion: PCR is useful to diagnose herpetic NAU in HIV+ patients while GWC is useful to diagnose herpetic anterior uveitis. 相似文献
PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10−3 mm2/s [range: (0.91 - 1.3) × 10−3 mm2/s] vs. [1.4 ± 0.2 (SD)] × 10−3 mm2/s [range: (1.1 - 1.6) × 10−3 mm2/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI. 相似文献
A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity. 相似文献
Study objectivesTo analyze the association between sleep-related symptoms and sleep length in parents and their children in relation to other risk factors in both generations.MethodThe participants were parents (n = 5,855, age 54.3 ± 6.5 years, 45.2% men) who participated in the community-based Respiratory Health in Northern Europe (RHINE) study and one random member of their adult offspring (n = 5,855, age 30.2 ± 7.7 years, 41.5% men) who participated in the Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) study. Both generations responded to identical questionnaires on sleep symptoms, including difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), early morning awakening (EMA), snoring, nocturnal sweating, nocturnal gastroesophageal reflux (nGER), sleep time and excessive daytime sleepiness (EDS). Insomnia was defined as either, or both, DIS and DMS in combination with EDS.ResultsAll sleep variables except nocturnal sweating were more common in offspring whose parents had reported the same symptom. After adjusting for age, gender, BMI, smoking, physical activity, education, center and parents' total number of children, there were independent associations between sleep symptoms in parents and offspring for DIS (adj. OR, 95% CI: 1.52, 1.20–1.93), DMS (1.34, 1.15–1.56), snoring (1.45, 1.15,1.83), nGER (1.65, 1.15–2.37), insomnia (1.39, 1.13–1.73), short sleep time (<6 h/night) (2.51, 1.72–3.68) and EDS (1.48, 1.26,1.72). There were no independent relationships between symptoms in parents and offspring for EMA, nocturnal sweating or long sleep time (>9 h/night).ConclusionThe familiar aggregation of many sleep disturbances was not explained by investigated lifestyle and environmental factors. This supports a heritable factor in sleep problems. 相似文献