[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"leadSponsorName\":\"juan jose valero quintero,MD\",\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:":53},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":19,"enrollmentInfo":20,"targetDuration":4,"studyType":23,"phases":4,"briefSummary":24,"conditions":25,"keywords":30,"overallStatus":41,"whyStopped":4,"lastUpdateSubmitDate":42,"lastUpdatePostDateStruct":43,"startDateStruct":46,"completionDateStruct":48,"leadSponsor":50,"locationsCount":5},"100646096","spine-risk-ve-multimodal-predictive-model-for-failed-back-surgery-syndrome-in-venezuelan-surgical-patients-100646096",false,"NCT07693517","SPINE-RISK VE: Multimodal Predictive Model for Failed Back Surgery Syndrome in Venezuelan Surgical Patients","SPINE-RISK VE: Development and Internal Validation of a Multimodal Preoperative Predictive Model for Failed Back Surgery Syndrome Using Inflammatory Biomarkers, Lumbar MRI Findings, and Psychosocial Factors in Venezuelan Surgical Patients","SPINE-RISK VE","Inclusion Criteria:- Age 18 years or older\n\n* Confirmed indication for elective lumbar spine surgery (discectomy, spinal fusion, or decompression) for degenerative lumbar disease\n* Availability of preoperative lumbar MRI (with and without gadolinium contrast) within 6 months before surgery\n* Availability of standard preoperative laboratory panel (CRP, CBC with differential, albumin, HbA1c, ESR) within 30 days before surgery\n* Ability to complete validated psychosocial instruments (PHQ-9, PCS) in Spanish\n* Provision of written informed consent prior to any study procedure\n* Attending one of the three participating Venezuelan referral centers during the recruitment period\n\nExclusion Criteria:- Emergency lumbar spine surgery\n\n* Active spinal infection or spinal tumor requiring oncological surgery\n* Traumatic spinal fracture as primary indication\n* Cognitive impairment preventing completion of self-report psychosocial instruments\n* Active psychiatric emergency at time of preoperative assessment\n* Prior participation in another clinical trial that could influence surgical or pain outcomes\n* Inability to complete 12-month postoperative follow-up (geographic inaccessibility, planned relocation, or terminal illness)\n* Age under 18 years","ALL","18 Years","100 Years",{"count":21,"type":22},150,"ESTIMATED","OBSERVATIONAL","SPINE-RISK VE is a prospective multicenter cohort study designed to develop and internally validate a multimodal preoperative predictive model for Failed Back Surgery Syndrome (FBSS), now classified as Persistent Spinal Pain Syndrome Type 2 (PSPS-T2) per ICD-11 (code MG30.51), in Venezuelan adults patients undergoing elective lumbar spine surgery.\n\nThe model integrates three variable domains obtainable from routine preoperative evaluation at zero additional cost to the patient: (1) inflammatory laboratory biomarkers (C-reactive protein \\[CRP\\], neutrophil-to-lymphocyte ratio \\[NLR\\], albumin, glycated hemoglobin \\[HbA1c\\], erythrocyte sedimentation rate \\[ESR\\]); (2) preoperative lumbar magnetic resonance imaging (MRI) findings (Modic changes, Pfirrmann disc degeneration grade, foraminal stenosis, number of surgical levels, spondylolisthesis); and (3) validated psychosocial instruments (Patient Health Questionnaire-9 \\[PHQ-9\\], Pain Catastrophizing Scale \\[PCS\\], smoking status, benzodiazepine use, prior lumbar surgery).\n\nAnalysis proceeds in two phases: Phase 1 applies multivariable logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) variable selection to generate a printable clinical nomogram; Phase 2 applies a random forest machine learning algorithm with 10-fold cross-validation. Model reporting follows Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis plus Artificial Intelligence (TRIPOD+AI) guidelines.\n\nSPINE-RISK VE aims to produce the first validated multimodal predictive model for PSPS-T2\u002FFBSS was developed in a Latin American surgical cohort, providing neurosurgeons with an evidence-based preoperative risk stratification tool applicable without Additional technological infrastructure.",[26,27,28,29],"Persistent Spinal Pain Syndrome Type 2 (PSPS-T) Lower Spine","Chronic Low Back Pain","Postoperative Pain","Lumbar Spine Surgery",[31,32,33,34,35,36,37,38,39,40],"predictive model","machine learning","random forest","LASSO regression","Modic changes","inflammatory biomarkers","pain catastrophizing","TRIPOD+AI","Venezuela","Latin America","NOT_YET_RECRUITING","2026-07-08",{"date":44,"type":45},"2026-07-10","ACTUAL",{"date":47,"type":22},"2026-09-04",{"date":49,"type":22},"2028-02-10",{"name":51,"class":52},"juan jose valero quintero,MD","OTHER",""]