Neurosurgical Outcome Network

Aneurysms, Arteriovenous Malformations, Cavernomas, Chiari Malformation Type 1, Craniofacial Pain, Depression, Drug-resistant Epilepsy, Dural Fistulas, Dystonias, Extradural Hematoma, Hydrocephalus, Moyamoya Disease, Neuropathic Pain, Normal Pressure Hydrocephalus, Obsessive-compulsive Disorder, Parkinson&Amp;#39;s Disease, Skull Base Tumors, Spasticity, Subarachnoid Hemorrhage, Subdural Hematoma, Tremor, Trigeminal Neuralgia, Tumors of Peripheral Nerves

Neurosurgery Outcome Artificial Intelligence predictors

The evaluation of neurosurgical outcomes varies from center to center, and the predictive factors that determine these outcomes are not fully known or shared. This study aims to assess outcomes and their predictors using measures agreed upon by the participating centers. Standardizing the evaluation of outcomes and predictors improves the quality of research, allows for data comparison, and facilitates a "common language" in routine clinical practice. Most importantly, it influences therapeutic decisions in various neurosurgical conditions. Clinically, the identified predictors can also be used during preoperative assessments to provide more precise guidance to patients undergoing surgery.

The evaluation of outcome indicators, quality of life, and complexity in Neurosurgery has gained significant importance not only at a clinical and therapeutic level but also as a tool to assess the effectiveness and efficiency of the healthcare system. This study aims to evaluate neurosurgical outcomes and their predictors using measures shared among participating centers. Such evaluation varies from center to center, and the predictive factors are not entirely known or shared. Standardizing the evaluation of outcomes and predictors improves research quality, enables data comparison, and fosters a common language in everyday clinical practice. Most importantly, it influences therapeutic decisions in various neurosurgical pathologies. Primary Objective: Collect and describe the pre- and postoperative clinical, cognitive, and psychological status in various neurosurgical pathologies. Secondary Objectives: Identify outcome predictors. Primary Endpoint: Description of pre- and postoperative clinical, cognitive, and psychological data of patients undergoing neurosurgical intervention. Secondary Endpoints: Analyze the association between preoperative indicators collected and postoperative outcomes. Specific predictors and outcome measures for each neurosurgical pathology will be considered and reported in Appendix 1. Patient enrollment from Neurosurgery Departments; collection of clinical, cognitive, and psychological data before the intervention and during follow-up after the intervention (timing varies depending on the neurosurgical pathology); data analysis through AI. For all neurosurgical pathologies, the following data will be collected: sociodemographic, clinical (Charlson Comorbidity Index, heart disease, diabetes, Chronic Obstructive Pulmonary Disease, hypertension, Body Mass Index, smoking, psychiatric pathology, admission date, intervention date, discharge date, Modified Rankin Scale, American Society of Anesthesiologists, weight, height), anesthesiological (collected only by FINCB), and complication-related data (Novel Therapy-Disability-Neurology).

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