Clinical Researches
Construction of risk prediction model for chronic pain in elderly patients
Wang Tingting, Zhu Tong, Ning Benxiang, Xu Jin
Published 2022-12-06
Cite as Chin J Mod Nurs, 2022, 28(34): 4773-4778. DOI: 10.3760/cma.j.cn115682-20220401-01564
Abstract
ObjectiveTo construct a risk prediction model for chronic pain in elderly patients and verify its predictive value.
MethodsFrom January 2020 to June 2021, 320 elderly patients admitted to the Pain Department of Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School were selected by convenience sampling. The general information of patients was collected, and patients were divided into chronic pain group (n=185) and non-chronic pain group (n=135) according to whether they had chronic pain. The patients were investigated with the Numerical Rating Scale (NRS) , Self-Rating Anxiety Scale (SAS) , Self-Rating Depression Scale (SDS) , Pittsburgh Sleep Quality Index (PSQI) , Morse Fall Scale, Constipation Symptom and Efficacy Scale, and bioelectrical impedance method. The binomial Logistic regression analysis was used to explore the risk factors of chronic pain in elderly patients and establish a risk prediction model. The predictive value of the risk prediction model was evaluated by the receiver operating characteristic (ROC) curve.
ResultsThe NRS score of 185 patients with chronic pain was (4.34±1.50) . Lower limbs, lumbosacral region and neck were the most common parts of chronic pain. Osteoarthritis and cervical spondylosis were the main diseases causing chronic pain. Binomial Logistic regression analysis showed that high SDS score, high Morse Fall Scale score, high constipation symptom score, high SAS score and low appendicular skeletal muscle mass index were independent risk factors for chronic pain in elderly patients (P<0.05) . The area under the ROC curve of the risk prediction model for chronic pain in elderly patients was 0.878, the sensitivity was 92.53%, and the specificity was 67.04%.
ConclusionsThe risk prediction model based on anxiety, depression, falls, myasthenia and constipation has good clinical value in predicting chronic pain in elderly patients, and can provide support for early identification and intervention of chronic pain in elderly patients.
Key words:
Aged; Predictive model; Chronic pain; Risk factors
Contributor Information
Wang Tingting
Pain Department, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
Zhu Tong
Pain Department, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
Ning Benxiang
Pain Department, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
Xu Jin
Pain Department, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
