Neuropsychiatric disorders among Syrian and Iraqi refugees in Jordan: A retrospective cohort study 2012-2013

Background: The burden of neuropsychiatric disorders in refugees is likely high, but little has been reported on the neuropsychiatric disorders that affect Syrian and Iraqi refugees in a country of first asylum. This analysis aimed to study the cost and burden of neuropsychiatric disorders among refugees from Syria and Iraq requiring exceptional, United Nations-funded care in a country of first asylum. Methods: The United Nations High Commissioner for Refugees works with multi-disciplinary, in-country exceptional care committees to review refugees’ applications for emergency or exceptional medical care. Neuropsychiatric diagnoses among refugee applicants were identified through a retrospective review of applications to the Jordanian Exceptional Care Committee (2012-2013). Diagnoses were made using International Classification of Disease-10th edition codes rendered by treating physicians.Other Research Uni

Titles versus titles and abstracts for initial screening of articles for systematic reviews

PMC3933432BACKGROUND: There is no consensus on whether screening titles alone or titles and abstracts together is the preferable strategy for inclusion of articles in a systematic review. METHODS: TWO METHODS OF SCREENING ARTICLES FOR INCLUSION IN A SYSTEMATIC REVIEW WERE COMPARED: titles first versus titles and abstracts simultaneously. Each citation found in MEDLINE or Embase was reviewed by two physician reviewers for prespecified criteria: the citation included (1) primary data; (2) the exposure of interest; and (3) the outcome of interest. RESULTS: There were 2965 unique citations. The titles first strategy resulted in an immediate rejection of 2558 (86%) of the records after reading the title alone, requiring review of 239 titles and abstracts, and subsequently 176 full text articles. The simultaneous titles and abstracts review led to rejection of 2782 citations (94%) and review of 183 full text articles. Interreviewer agreement to include an article for full text review using the titles-first screening strategy was 89%-94% (kappa = 0.54) and 96%-97% (kappa = 0.56) for titles and abstracts combined. The final systematic review included 13 articles, all of which were identified by both screening strategies (yield 100%, burden 114%). Precision was higher in the titles and abstracts method (7.1% versus 3.2%) but recall was the same (100% versus 100%), leading to a higher F-measure for the titles and abstracts approach (0.1327 versus 0.0619). CONCLUSION: Screening via a titles-first approach may be more efficient than screening titles and abstracts together.JH Libraries Open Access Fun

Normalization Techniques for Statistical Inference from Magnetic Resonance Imaging

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature on intensity normalization has focused on histogram matching and other histogram mapping techniques, with little emphasis on normalizing images to have biologically interpretable units. Furthermore, there are no formalized principles or goals for the crucial comparability of image intensities within and across subjects. To address this, we propose a set of criteria necessary for the normalization of images. We further propose simple and robust biologically motivated normalization techniques for multisequence brain imaging that have the same interpretation across acquisitions and satisfy the proposed criteria. We compare the performance of different normalization methods in thousands of images of patients with Alzheimer\u27s Disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers

Statistical normalization techniques for magnetic resonance imaging☆☆☆

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature on intensity normalization has focused on histogram matching and other histogram mapping techniques, with little emphasis on normalizing images to have biologically interpretable units. Furthermore, there are no formalized principles or goals for the crucial comparability of image intensities within and across subjects. To address this, we propose a set of criteria necessary for the normalization of images. We further propose simple and robust biologically motivated normalization techniques for multisequence brain imaging that have the same interpretation across acquisitions and satisfy the proposed criteria. We compare the performance of different normalization methods in thousands of images of patients with Alzheimer's disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers

OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI☆

Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1% and below of 0.59% (95% CI; [0.50%, 0.67%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74% (95% CI: [65%, 82%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77% (95% CI: [71%, 83%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76% (95% CI: [64%, 88%]) of cases, the neurologist 66% (95% CI: [52%, 78%]) and the radiologist 52% (95% CI: [38%, 66%]). OASIS obtains the estimated probability for each voxel to be part of a lesion by weighting each imaging modality with coefficient weights. These coefficients are explicit, obtained using standard model fitting techniques, and can be reused in other imaging studies. This fully automated method allows sensitive and specific detection of lesion presence and may be rapidly applied to large collections of images

Spinal intradural extraosseous Ewing's sarcoma

Extraosseous Ewing's sarcoma (EES) involving the central nervous system is rare, but can be diagnosed and distinguished from other primitive neuroectodermal tumors (PNET) by identification of the chromosomal translocation (11;22)(q24;q12). We report EES arising from the spinal intradural extramedullary space, based on imaging, histopathological, and molecular data in two men, ages 50 and 60 years old and a review of the literature using PubMed (1970–2009). Reverse transcriptase polymerase chain reaction (RT-PCR) identified the fusion product FL1-EWS. Multimodal therapy, including radiation and alternating chemotherapy including vincristine, cyclophosphamide, doxorubicin and ifosfamide and etoposide led to local tumor control and an initial, favorable therapeutic response. No systemic involvement was seen from the time of diagnosis to the time of last follow-up (26 months) or death (4 years). This report confirms that EES is not confined to the earliest decades of life, and like its rare occurrence as an extra-axial meningeal based mass intracranially, can occasionally present as an intradural mass in the spinal canal without evidence of systemic tumor. Gross total resection followed by multimodal therapy may provide for extended progression free and overall survival

Clinically relevant increases in serum neurofilament light chain and glial fibrillary acidic protein in patients with Susac syndrome

Background and purpose: Serum levels of neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) are promising neuro-axonal damage and astrocytic activation biomarkers. Susac syndrome (SS) is an increasingly recognized neurological condition and biomarkers that can help assess and monitor disease evolution are highly needed for the adequate management of these patients. sNfL and sGFAP levels were evaluated in patients with SS and their clinical relevance in the relapse and remission phase of the disease was assessed. Methods: As part of a multicentre study that enrolled patients diagnosed with SS from six international centres, sNfL and sGFAP levels were assessed in 22 SS patients (nine during a relapse and 13 in remission) and 59 age- and sex-matched healthy controls using SimoaTM assay Neurology 2-Plex B Kit. Results: Serum NfL levels were higher than those of healthy controls (p < 0.001) in SS patients and in both subgroups of patients in relapse and in remission (p < 0.001 for both), with significantly higher levels in relapse than in remission (p = 0.008). sNfL levels showed a negative correlation with time from the last relapse (r = -0.663; p = 0.001). sGFAP levels were slightly higher in the whole group of patients than in healthy controls (p = 0.046) and were more pronounced in relapse than in remission (p = 0.013). Conclusion: In SS patients, both sNFL and sGFAP levels increased compared with healthy controls. Both biomarkers had higher levels during clinical relapse and much lower levels in remission. sNFL was shown to be time sensitive to clinical changes and can be useful to monitor neuro-axonal damage in SS

Yield of Brain MRI in Clinically Diagnosed Epilepsy in the Kingdom of Bhutan: A Prospective Study

Background: People with epilepsy (PWE) in low- and middle-income countries may not access the health resources that are considered optimal for epilepsy diagnosis. The diagnostic yield of magnetic resonance imaging (MRI) has not been well studied in these settings. Objectives: To report the diagnostic yield of brain MRI and identify clinical associations of abnormal MRI findings among PWE in a neurocysticercosis-endemic, resource-limited setting and to identify the proportion and putative structural brain causes of drug-resistant epilepsy. Methods: PWE were prospectively enrolled at the Jigme Dorji Wangchuck National Referral Hospital in Bhutan (2014-2015). Each participant completed clinical questionnaires and a 1.5-Tesla brain MRI. Each MRI was reviewed by at least 1 radiologist and neurologist in Bhutan and the United States. A working definition of drug-resistant epilepsy for resource-limited settings was given as (a) seizures for >1 year, (b) at least 1 seizure in the prior year, and (c) presently taking 2 or more antiepileptic drugs (AEDs). Logistic regression models were constructed to test the cross-sectional association of an abnormal brain MRI with clinical variables. Findings: A total of 217 participants (125 [57%] female; 54 [25%] neurocysticercosis (n = 26, 12%, including 1 child) and congenital/perinatal abnormalities (n = 29, 14%, including 14 children). The number of AEDs (odds ratio = .59, 'P' = .03) and duration of epilepsy (odds ratio = 1.11, 'P' = .02) were significantly associated with an abnormal MRI. Seizure in the prior month was associated with the presence of mesial temporal sclerosis (odds ratio = .47, 'P' = .01). A total of 25 (12%) participants met our definition of drug-resistant epilepsy, with mesial temporal sclerosis (n = 10), congenital malformations (n = 5), and neurocysticercosis (n = 4) being the more common findings. Conclusions: The prevalence of abnormalities on brain MRI for PWE in resource-limited settings is high as a result of a diffuse range of etiologies, most commonly mesial temporal sclerosis. Drug-resistant epilepsy accounted for 12% of the referral population in a conservative estimation

Female hormonal exposures and neuromyelitis optica symptom onset in a multicenter study

Objective: To study the association between hormonal exposures and disease onset in a cohort of women with neuromyelitis optica spectrum disorder (NMOSD). Methods: Reproductive history and hormone use were assessed using a standardized reproductive survey administered to women with NMOSD (82% aquaporin-4 antibody positive) at 8 clinical centers. Using multivariable regression, we examined the association between reproductive exposures and age at first symptom onset (FS). Results: Among 217 respondents, the mean age at menarche was 12.8 years (SD 1.7). The mean number of pregnancies was 2.1 (SD 1.6), including 0.3 (SD 0.7) occurring after onset of NMOSD symptoms. In the 117 participants who were postmenopausal at the time of the questionnaire, 70% reported natural menopause (mean age: 48.9 years [SD 3.9]); fewer than 30% reported systemic hormone therapy (HT) use. Mean FS age was 40.1 years (SD 14.2). Ever-use of systemic hormonal contraceptives (HC) was marginally associated with earlier FS (39 vs 43 years, p = 0.05). Because HC use may decrease parity, when we included both variables in the model, the association between HC use and FS age became more significant (estimate = 2.7, p = 0.007). Among postmenopausal participants, 24% reported NMOSD onset within 2 years of (before or after) menopause. Among these participants, there was no association between age at menopause or HT use and age at NMOSD onset. Conclusions: Overall, age at NMOSD onset did not show a strong relationship with endogenous hormonal exposures. An earlier onset age did appear to be marginally associated with systemic HC exposure, an association that requires confirmation in future studies