Diagnostic value of brain MR imaging and its correlation with clinical presentation and cognitive functions in idiopathic intracranial hypertension patients
Bibliographic record
Abstract
Abstract Background Idiopathic intracranial hypertension (IIH) is a neurological disorder of unknown etiology and ambiguous pathophysiology due to cerebrospinal fluid dysregulation. This study is designed to evaluate the role of brain magnetic resonance imaging (MRI) and magnetic resonance venography (MRV) in diagnosis of IIH, to clarify the nature and extent of cognitive deficits, and to detect if there is a correlation between radiology, clinical findings, and cognitive dysfunctions in those patients. Results The study included 34 patients and 34 age-, sex-, body mass index (BMI)-, and education-matched healthy control subjects. MR brain imaging and Montreal cognitive assessment (MoCA) test were used for both groups. MRI and MRV sensitivity for IIH diagnosis were 85.2% and 85.3% with 100% and 94.1% specificity respectively. 44.1% had cognitive impairment, memory was the most affected domain, followed by attention, abstraction, and orientation with statistically significantly lower total MoCA score (p < 0.005). Domain comparisons reveal a statistically significantly lower memory/delayed recall (p < 0.001) and abstract scores (p < 0.007) in IIH cases versus control subjects. In comparing patients with cognitive impairment (CI) versus those without CI, there were statistically significantly higher CI in low education level, presence of diplopia, hormonal contraceptive use, abnormal MRI brain, papilledema grades, BMI, and opening pressure. Conclusions Presence of more than or equal 3 MR imaging findings, bilateral transverse sinus stenosis, and less than or equal 4 combined conduit score increase the specificity and sensitivity of MRI and MRV for IIH diagnosis. IIH had detrimental effect on different cognitive domains especially when patient have low education level, diplopia, papilledema ≥ grade III, high OP ≥ 61.5 cm H2O, and BMI ≥ 34 Kg/m2 with abnormal MRI and MRV findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".