title: Predicting the evolution of low back pain patients in routine clinical practice: results from a registry within the Spanish National Health Service.
abstract: BACKGROUND
  The Spanish National Health Service (SNHS) is a tax-funded public organization that provides free health care to every resident in Spain.
  
  
  OBJECTIVE
  To develop models for predicting the evolution of low back pain (LBP) in routine clinical practice within SNHS.
  
  
  METHODS
  Analysis of a prospective registry in routine clinical practice, in 17 centers across SNHS.
  
  
  METHODS
  Patient sample includes 4,477 acute and chronic LBP patients treated in primary and hospital care.
  
  
  METHODS
  Pain and disability, measured through validated instruments.
  
  
  METHODS
  Patients treated for LBP were assessed at baseline and 3 months later. Data gathered were the following: sex, age, employment status, duration of pain, severity of LBP, pain down to the leg (LP) and disability, history of lumbar surgery, diagnostic procedures undertaken, imaging findings, and treatments used throughout the study period. Three separate multivariate logistic regression models were developed for predicting a clinically relevant improvement in LBP, LP, and disability at 3 months.
  
  
  RESULTS
  In total, 4,261 patients (95.2%) attended follow-up. For all the models, calibration was reasonable and the area under the receiver operating characteristic curve was ≥0.640. For LBP, LP, and disability, factors associated with a higher probability of improvement at 3 months were the following: not having undergone lumbar surgery, higher baseline scores for the corresponding variable, lower ones for the rest, and being treated with neuroreflexotherapy. Additional factors were the following: for LBP, shorter pain duration; for LP, not undergoing electromyography; and for disability, shorter pain duration, not being diagnosed with disc degeneration, and being treated with muscle relaxants and not opioids.
  
  
  CONCLUSIONS
  A prospective registry can be used for developing predictive models to quantify the odds that a given LBP patient will experience a clinically relevant improvement. This may empower patients for an informed shared decision making.
authors.affiliation: Departamento Científico, Fundación Kovacs, Paseo de Mallorca 36, 07012 Palma de Mallorca, Spain. kovacs@kovacs.org
authors.forename: Francisco M
authors.initials: FM
authors.lastname: Kovacs
authors.forename: Jesús
authors.initials: J
authors.lastname: Seco
authors.forename: Ana
authors.initials: A
authors.lastname: Royuela
authors.forename: Josep
authors.initials: J
authors.lastname: Corcoll Reixach
authors.forename: Víctor
authors.initials: V
authors.lastname: Abraira
mesh_terms: D059787:Acute Pain; D059350:Chronic Pain; D004185:Disability Evaluation; D018450:Disease Progression; D005260:Female; D006801:Humans; D016015:Logistic Models; D017116:Low Back Pain / Q000175:diagnosis* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D009313:National Health Programs / Q000706:statistics & numerical data; D010147:Pain Measurement / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012042:Registries; D013030:Spain; D016896:Treatment Outcome