Objective To characterize the phenotype, headache-related disability, medical co-morbidities, use of symptomatic headache medications, and headache response to study interventions in the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT). Methods Patients with untreated IIH and mild vision loss enrolled in the IIHTT and randomized to acetazolamide (ACZ) and weight loss or placebo (PLB) and weight loss had prospective assessment of headache disability using the Headache Impact Test 6 (HIT-6) questionnaire. Subjects with headache at the baseline visit were assigned a headache phenotype using the International Classification for Headache Disorders version 3 beta (ICHD-3b). Medication overuse was determined using the participants’ reported medication use for the preceding month and ICHD-3b thresholds for diagnosing medication overuse headache. We investigated relationships between headache disability and various other clinical characteristics at baseline and at six months. Results Headache was present in 139 (84%) of the 165 enrollees at baseline. The most common headache phenotypes were migraine (52%), tension type headache (22%), probable migraine (16%), and probable tension type headache (4%). Fifty-one (37%) participants overused symptomatic medications at baseline, most frequently simple analgesics. A similar amount of improvement in the adjusted mean (± standard error) HIT-6 score occurred in the ACZ (−9.56 ± 1.05) and PLB groups (−9.11 ± 1.14) at six months (group difference −0.45, 95% CI −3.50 to 2.60, p=0.77). Headache disability did not correlate with any of the studies headache parameters, which included: the lumbar puncture opening pressure at baseline or at six months, body mass index, the amount of weight lost, papilledema grade, perimetric mean deviation, or the use of hormonal contraception. Headache disability was significantly associated with patient-reported quality of life in the physical, mental, and visual domains. Conclusions Headache was common, of varied character, disabling, and associated with poorer quality of life in our cohort of patients with mild visual impairment. The lack of correlation between headache disability and cerebrospinal fluid (CSF) pressure at baseline and at the end of the randomized phase of the study implies that headache in IIH may be related to factors other than intracranial hypertension, and that specific headache treatment is needed in addition to therapies directed at lowering CSF pressure.

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Patients with IIH recurrence had significant increases in BMI compared to patients without recurrence in this cohort. Patients with resolved IIH should be advised that weight gain may be a risk factor for IIH recurrence.

Recent studies in mice have demonstrated that the protein tyrosine phosphatase SHP-1 is a crucial negative regulator of cytokine signaling, inflammatory gene expression, and demyelination in central nervous system. The present study investigates a possible similar role for SHP-1 in the human disease multiple sclerosis (MS). The levels of SHP-1 protein and mRNA in PBMCs of MS patients were significantly lower compared to normal subjects. Moreover, promoter II transcripts, expressed from one of two known promoters, were selectively deficient in MS patients. To examine functional consequences of the lower SHP-1 in PBMCs of MS patients, we measured the intracellular levels of phosphorylated STAT6 (pSTAT6). As expected, MS patients had significantly higher levels of pSTAT6. Accordingly, siRNA to SHP-1 effectively increased the levels of pSTAT6 in PBMCs of controls to levels equal to MS patients. Additionally, transduction of PBMCs with a lentiviral vector expressing SHP-1 lowered pSTAT6 levels. Finally, multiple STAT6-responsive inflammatory genes were increased in PBMCs of MS patients relative to PBMCs of normal subjects. Thus, PBMCs of MS patients display a stable deficiency of SHP-1 expression, heightened STAT6 phosphorylation, and an enhanced state of activation relevant to the mechanisms of inflammatory demyelination.

and for the BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) Study Group Objective: To compare the diagnostic performance of an artificial intelligence deep learning system with that of expert neuro-ophthalmologists in classifying optic disc appearance. Methods: The deep learning system was previously trained and validated on 14,341 ocular fundus photographs from 19 international centers. The performance of the system was evaluated on 800 new fundus photographs (400 normal optic discs, 201 papilledema [disc edema from elevated intracranial pressure], 199 other optic disc abnormalities) and compared with that of 2 expert neuro-ophthalmologists who independently reviewed the same randomly presented images without clinical information. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were calculated. Results: The system correctly classified 678 of 800 (84.7%) photographs, compared with 675 of 800 (84.4%) for Expert 1 and 641 of 800 (80.1%) for Expert 2. The system yielded areas under the receiver operating characteristic curve of 0.97 (95% confidence interval [CI] = 0.96-0.98), 0.96 (95% CI = 0.94-0.97), and 0.89 (95% CI = 0.87-0.92) for the detection of normal discs, papilledema, and other disc abnormalities, respectively. The accuracy, sensitivity, and specificity of the system's classification of optic discs were similar to or better than the 2 experts. Intergrader agreement at the eye level was 0.71 (95% CI = 0.67-0.76) between Expert 1 and Expert 2, 0.72 (95% CI = 0.68-0.76) between the system and Expert 1, and 0.65 (95% CI = 0.61-0.70) between the system and Expert 2. Interpretation: The performance of this deep learning system at classifying optic disc abnormalities was at least as good as 2 expert neuro-ophthalmologists. Future prospective studies are needed to validate this system as a diagnostic aid in relevant clinical settings.