Menu
Not yet recruiting NCT07696676

PREDICT-DOLOR VE: Validation of a Structured Triage Protocol for Chronic Pain

Observational Chronic Pain Pain Management Neuropathic Pain

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: PREDICT-DOLOR VE.
Who it may be relevant to
Registry conditions: Chronic Pain, Pain Management, Neuropathic Pain. Basic parameters: 18 years — 100 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Center list to be confirmed — check the primary protocol.
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

PREDICT-DOLOR VE: Prospective Multicenter Diagnostic Accuracy Study for the Validation of a Rule-Based Clinical Decision Support Tool for Chronic Pain Triage in a Low-Resource Setting in Venezuela

Overview

PREDICT-DOLOR VE is a structured clinical triage protocol for chronic pain that uses five internationally validated pain assessment instruments to help healthcare providers determine the appropriate level of care for patients with chronic pain. The tool operates on a free mobile-friendly platform and generates a four-level recommendation: primary care management, referral to physiatry or neurology, priority specialist evaluation, or evaluation for neurosurgical intervention. This study will validate the diagnostic accuracy of the PREDICT-DOLOR VE algorithm by comparing its recommendations with the independent assessment of a panel of three specialists in adult patients with chronic pain (lasting 3 months or longer) across three referral centers in Venezuela. The study aims to determine whether this structured, low-cost approach can help connect patients with the right type of care more quickly and consistently.

Detailed description

Chronic pain affects a substantial proportion of the adult population in Venezuela and Latin America, yet patients often face long delays and inconsistent referral pathways before reaching the appropriate specialist. PREDICT-DOLOR VE addresses this gap through a structured, rule-based clinical decision support tool that integrates five validated instruments: the Numeric Rating Scale (NRS), the Douleur Neuropathique 4 (DN4; Neuropathic Pain Diagnostic Questionnaire) questionnaire, the Brief Pain Inventory (BPI), the Pain Catastrophizing Scale (PCS), and the Patient Health Questionnaire-9 (PHQ-9). Based on responses to these instruments, the tool generates one of four triage recommendations: Level 1 (management in primary care), Level 2 (referral to physiatry or neurology), Level 3 (priority specialist evaluation, including psychology referral when indicated), or Level 4 (evaluation for neurosurgical procedure by a multidisciplinary pain committee). The platform operates on Google Forms and Google Sheets at no cost to patients or healthcare facilities. This prospective multicenter diagnostic accuracy study will enroll 120 consecutive adult patients with chronic pain (duration of 3 months or longer) across three referral centers in Venezuela. Each participant will complete the PREDICT-DOLOR VE assessment. Independently, a panel of three specialists (neurosurgeon, neurologist, and physiatrist) blinded to the algorithm's recommendation will evaluate each patient using standard clinical assessment and reach a consensus triage classification. The primary outcome is the concordance, measured by Cohen's kappa coefficient, between the algorithm's recommendation and the specialist panel's consensus classification. Secondary outcomes include the time from first consultation to appropriate specialist evaluation, system usability among primary care physicians, and patient satisfaction with the triage process.

Interventions

  • Other PREDICT-DOLOR VE
    A structured, rule-based clinical decision support tool integrating five validated pain assessment instruments (Numeric Rating Scale, Douleur Neuropathique 4, Brief Pain Inventory, Pain Catastrophizing Scale, and Patient Health Questionnaire-9) to generate a four-level triage recommendation for chronic pain management, operating on a free digital platform with no implementation cost.

Primary outcome measures

  • At completion of each patient's assessment (single visit, approximately 15-20 minutes) [Time frame: At completion of each patient's assessment (single visit, approximately 15-20 minutes)]
  • Concordance between PREDICT-DOLOR VE algorithm and specialist panel consensus [Time frame: At completion of each patient's assessment (single visit, approximately 15-20 minutes)]

Eligibility criteria

Inclusion criteria

  • Inclusion Criteria:
  • Age 18 years or older
  • Chronic pain of any etiology with duration of 3 months or longer
  • Ability to complete the PREDICT-DOLOR VE digital assessment battery (with assistance if needed)
  • Attending one of the three participating referral centers during the recruitment period
  • Provision of written informed consent before any study procedure

Exclusion criteria

  • Acute pain with duration less than 3 months
  • Active oncological pain under chemotherapy or radiotherapy protocol (separate evaluation pathway required)
  • Cognitive impairment that prevents completion of self-report instruments, even with assistance
  • Active psychiatric emergency or suicidal ideation at time of assessment
  • Refusal to provide informed consent
  • Participation in another clinical trial that could influence triage outcomes

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT07696676 · PREDICT-DOLOR-VE-2026-001

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗