Evaluation of predictive factors of idiopathic intracranial hypertension in different clinics
Abstract
PURPOSE: Idiopathic Intracranial Hypertension (IIH) is marked by elevated intracranial pressure without an identifiable cause. This study aimed to compare predictive factors between two IIH groups: those experiencing remission (single attack) and those developing migrainous headaches, in order to identify factors influencing the disease's progression.
METHODS: This retrospective study was conducted after obtaining ethics committee approval. It involved 118 patients diagnosed with IIH who were followed up in the Neuro-ophthalmology outpatient clinic between 2011 and 2023. Data on demographics, clinical history, comorbidities, habits, neurologic and neuro-ophthalmologic findings, cranial imaging features, lumbar puncture opening pressure, and current medical treatments were collected to assess the clinical course and predictive factors. The analyzed parameters were compared between two subgroups: one experiencing remission (single attack) and the other developing migrainous headaches. Statistically significant parameters were subjected to univariate and multivariate analysis.
RESULTS: Of the 118 patients, 87 (73.7 %) were in the single-attack group, while 31 (26.3 %) were in the migrainous headache group. Key predictive factors identified between the groups were the presence of allodynia (p 27.8 kg/m² (p = 0.002), and a history of migraine (p < 0.001).
CONCLUSIONS: Allodynia, neck and back pain, a history of migraine, and a BMI > 27.8 kg/m² were found to be predictive factors…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 118 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.