Alejandro Aceituno Rodríguez

Dr. Alejandro Aceituno Rodríguez


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 September 2025 in Healthcare
Verified
Journal Article
Open access
PDF file
ARAlejandro Aceituno Rodríguez
Alejandro Aceituno Rodríguez
CBCarlos Bustamante
Carlos Bustamante
CRCarmen Rodríguez-Rivera
Carmen Rodríguez-Rivera
MMMiguel Molina-Alvarez
Miguel Molina-Alvarez
CRCarlos Rodríguez-Moro
Carlos Rodríguez-Moro
LGLuis Matesanz Garcia
Luis Matesanz Garcia
Introduction: Lumbar radiculopathies involving the entrapment of nerve roots in the lumbar spine are common neuropathic conditions. These conditions affect 40% to 70% of individuals in their lifetime and lead to significant medical costs. Objective: This study aims to identify clinical, psychological, and biomarker-based prognostic factors that predict functional outcomes following surgery for lumbar radiculopathy. Materials and Methods: This prospective cohort study, conducted at Hospital Central de la Defensa Gómez Ulla, Madrid (Spain), adheres to the STROBE guidelines. The study includes patients aged 18–75 with lumbar radiculopathy, confirmed by clinical diagnosis, imaging, and electromyography (EMG) findings. Exclusion criteria include previous lumbar spine surgeries and systemic diseases. The primary outcome is the Oswestry Low Back Pain Disability Questionnaire. Sample size calculations, based on a conservative effect size (f2 = 0.20), determined the need for 172 participants, accounting for a 15% dropout rate and 80% power. Procedure: Patients will undergo an initial assessment, including EMG tests, sociodemographic and psychological questionnaires, blood sample tests, and physical questionnaires. This process will be repeated six months post-intervention, except for the blood sample test, expectations questionnaire, and EMG, which will be performed only once. Statistical Analyses: Data will be analyzed using Python 3.12.3, employing a multivariate linear regression analysis. Assumptions of linearity, independence, homoscedasticity, normality, and no multicollinearity will be validated. Corrective measures will be applied if assumptions are violated. Ethics and Dissemination: The study follows the Declaration of Helsinki guidelines and has been approved by the Ethics Committee of Universidad Rey Juan Carlos (070220241052024). Potential risks will be minimized, and adverse events will be recorded and addressed. Findings will be published in high-impact journals and presented at conferences.