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Набор скоро начнётся NCT07696676

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

Наблюдательное Chronic Pain Pain Management Neuropathic Pain

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают
В протоколе указаны: PREDICT-DOLOR VE.
Кому может быть актуально
Состояния в реестре: Chronic Pain, Pain Management, Neuropathic Pain. Базовые параметры: 18 лет — 100 лет · Все.
Что важно проверить
Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится
Список центров уточняется — проверьте первичный протокол.
Следующий шаг
Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
Официальное название

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

Обзор

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.

Подробное описание

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.

Вмешательства

  • Другое 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.

Первичные конечные точки

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

Критерии участия

Критерии включения

  • 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

Критерии исключения

  • 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

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения
Когортное

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Идентификаторы

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

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗