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Establishment and Validation of Early-warning Model of Perioperative Pain for the Elders

Conditions
Pain Assessment
Elderly
Model
Postoperative Pain
Registration Number
NCT04228705
Lead Sponsor
Peking University People's Hospital
Brief Summary

This study will collect perioperative pain-related data of elderly patients in multi-centers. Analyzing these collected data to find the high-risk factors of postoperative pain in elderly patients and to establish an early-warning model of perioperative pain in elderly patients, so as to improve the ability of assessing the risks of postoperative pain in elderly patients and providing an early warning.

Detailed Description

This study will collect perioperative pain-related data of elderly patients in multi-centers, including: preoperative general data, intraoperative anesthesia and surgical data, clinical laboratory data, postoperative pain and intervention, postoperative complications and quality of life. Analyzing these collected data to find the high-risk factors of postoperative pain in elderly patients and to establish an early-warning model of perioperative pain in elderly patients, so as to improve the ability of assessing the risks of postoperative pain in elderly patients and providing an early warning.

Recruitment & Eligibility

Status
UNKNOWN
Sex
All
Target Recruitment
6000
Inclusion Criteria
  • 18 years or older
  • Undergoing general or regional anesthesia
  • Hospitalized for at least 24 hours after surgery
  • Able to give informed consent
  • Able to read and write
Exclusion Criteria
  • Existing diagnoses of psychiatric or neurologic pathology
  • A history of substance abuse
  • Admitted to ICU after surgery
  • Patients with advanced tumors who have received preoperative chemotherapy or who are expected to receive postoperative chemotherapy.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Pain trajectories after surgerywithin 6 months

The pain trajectory is the vector of mean pain severity domain score (from 0 to 10) measured with Brief Pain Inventory -Short Form (BPI-SF) within 6 months

Secondary Outcome Measures
NameTimeMethod
Postoperative duration of stay in hospital30 days postoperation

The duration when patients stay in hospital after surgery.

Complications within 30 days after surgeryUp to 30 days postoperation

Complications within 30 days after surgery will be classified using Clavien-Dindo Classification of Surgical Complications, ranging from Grade I(Any deviation from the normal postoperative course without the need for pharmacological treatment or surgical, endoscopic and radiological interventions) to Grade V(death of a patient).

Outcome of 6-mins-walking test1, 3, 7, 14, 21, 30, 60, 90, 120, 150 and180 days postoperation

Walking distance of 6 minutes

Number of readmission within 30 days after surgeryUp to 30 days postoperation

Readmission indicates unplanned readmission after hospital discharge.

The trajectories of health related quality of life(HRQoL)1, 3, 7, 14, 21, 30, 60, 90, 120, 150 and180 days postoperation

The trajectory of HRQoL is the vector of Utility values measured with EuroQol five-dimensional questionnaire(EQ-5D)taken over 6 months(days 1, 3, 7,14, 21, 30, 60, 90, 120, 150,180; Day 0 is the day of surgery). The EQ-5D measures health on five domains (mobility, self-care, usual activities, pain discomfort, and anxiety-depression), and the scores will be combined using Chinese general population weights to generate a single utility or index score. Utility values for the EQ-5D range from 1.00 to -0.391, where a score of 0 and 1 are regarded as equivalent to death and 'perfect health', respectively, and a score \< 0 is considered as health state that is 'worse than death'.

Ambulation timeUp to 30 days postoperation

The first time when patients can get off of bed and walk after surgery

Oral feeding timeUp to 30 days postoperation

The first time when patients begin oral feeding after surgery

Trial Locations

Locations (1)

Peking University People's Hospital

🇨🇳

Beijing, Beijing, China

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