Investigating clinical indicators for neuroimaging abnormalities in acute headache cases: insights from a retrospective study.

Abstract

Purpose: Headache is common at emergency services and neuroimaging can help in timely diagnosis of life-threatening pathologies. We evaluated clinical indicators associated with abnormal neuroimaging in patients with acute headache, aiming to develop a scoring system with reliable diagnostic performance.

Methods: This analytical and retrospective study was conducted at a teaching tertiary care hospital in Cali, Colombia, from January 2011 to December 2019. Patients aged 18 years or older with non-traumatic headaches who attended the emergency department and underwent neuroimaging were included. Demographic and clinical data were recorded, including headache associated signs and symptoms, imaging diagnosis and disposition. Statistically significant variables and clinically relevant variables were selected. Data was analyzed using a combination of logistic regression and Receiver Operator Characteristic (ROC) curves, leading to the derivation of three models.

Results: 626 patients were included, 15.5% with abnormal neuroimaging. The variables with the highest odds ratio (OR) were: age > 40 years (OR 3.2 CI 1.86-5.56), motor deficit (OR 5.4 CI 2.62-11.18), visual deficit (OR 3.2 CI 1.56-6.63) and gait disturbance (OR 2.27 CI 0.87-5.96). Three abnormal neuroimaging prediction logistic regression models have been derived. The better scale is performed with model 1, which is validated internally and a cut-off point of 0.179, the Area Under the Curve (AUC) of 0.757 is obtained with a diagnostic accuracy of 0.79 (0.73-0.85).

Conclusion: Our straightforward scale incorporates clinical factors associated with abnormal neuroimaging, with the aim of improving diagnostic performance and predictive capacity to distinguish patients who require neuroimaging.