Changteng Zhang, Ying Su, Xianzheng Zeng, Xiaoyu Zhu, Rui Gao, Wangyang Liu, Runzi Du, Chan Chen, Jin Liu
{"title":"Risk Factors and Diagnostic Model Construction of Chronic Pain with Cognitive Impairment.","authors":"Changteng Zhang, Ying Su, Xianzheng Zeng, Xiaoyu Zhu, Rui Gao, Wangyang Liu, Runzi Du, Chan Chen, Jin Liu","doi":"10.2147/JPR.S485000","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Cognitive impairment (CI) is frequently observed in patients with chronic pain (CP). CP progression increases the risk of dementia and accelerates Alzheimer's disease pathogenesis. However, risk diagnostic models and biomarkers for CP-related CI remain insufficient. Previous research has highlighted the relationships between several complete blood count parameters for CP or CI-related diseases, such as Alzheimer's disease, while the specific values of complete blood count parameters in CP-related CI patients remain unclear. This study aimed to explore the correlation between complete blood count parameters and CP-related CI to establish a risk diagnostic model for the early detection of CP-related CI.</p><p><strong>Methods: </strong>This cross-sectional study was conducted at West China Hospital, Sichuan University. The Montreal Cognitive Assessment (MoCA) was used to classify patients into either the CP with CI group or the CP without CI group. Univariate analysis and multivariate logistic regression analysis were used to screen the related factors of CP-related CI for constructing a risk diagnostic model, and the model was evaluated using receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>The study ultimately included 163 eligible patients. Based on analysis, age (OR, 1.037 [95% CI, 1.007-1.070]; <i>P</i>=0.018), duration of pain (OR, 2.546 [95% CI, 1.099-6.129]; <i>P</i>=0.032), VAS score (OR, 1.724 [95% CI, 0.819-3.672]; <i>P</i>=0.153), LMR (OR, 0.091 [95% CI, 0.024-0.275]; <i>P</i><0.001), absolute neutrophil value (OR, 0.306 [95% CI, 0.115-0.767]; <i>P</i>=0.014), and lymphocyte percentage (OR, 6.551 [95% CI, 2.143-25.039]; <i>P</i>=0.002) were identified as critical factors of CP-related CI. The diagnostic model was evaluated by the ROC curve, demonstrating good diagnostic value with an area under the curve (AUC) of 0.803, a sensitivity of 0.603 and a specificity of 0.871.</p><p><strong>Conclusion: </strong>The risk diagnostic model developed in this study for CP-related CI has significant value and enables clinicians to customize interventions based on each patient's needs.</p>","PeriodicalId":16661,"journal":{"name":"Journal of Pain Research","volume":"17 ","pages":"4331-4342"},"PeriodicalIF":2.5000,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662672/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Pain Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JPR.S485000","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Cognitive impairment (CI) is frequently observed in patients with chronic pain (CP). CP progression increases the risk of dementia and accelerates Alzheimer's disease pathogenesis. However, risk diagnostic models and biomarkers for CP-related CI remain insufficient. Previous research has highlighted the relationships between several complete blood count parameters for CP or CI-related diseases, such as Alzheimer's disease, while the specific values of complete blood count parameters in CP-related CI patients remain unclear. This study aimed to explore the correlation between complete blood count parameters and CP-related CI to establish a risk diagnostic model for the early detection of CP-related CI.
Methods: This cross-sectional study was conducted at West China Hospital, Sichuan University. The Montreal Cognitive Assessment (MoCA) was used to classify patients into either the CP with CI group or the CP without CI group. Univariate analysis and multivariate logistic regression analysis were used to screen the related factors of CP-related CI for constructing a risk diagnostic model, and the model was evaluated using receiver operating characteristic (ROC) curve analysis.
Results: The study ultimately included 163 eligible patients. Based on analysis, age (OR, 1.037 [95% CI, 1.007-1.070]; P=0.018), duration of pain (OR, 2.546 [95% CI, 1.099-6.129]; P=0.032), VAS score (OR, 1.724 [95% CI, 0.819-3.672]; P=0.153), LMR (OR, 0.091 [95% CI, 0.024-0.275]; P<0.001), absolute neutrophil value (OR, 0.306 [95% CI, 0.115-0.767]; P=0.014), and lymphocyte percentage (OR, 6.551 [95% CI, 2.143-25.039]; P=0.002) were identified as critical factors of CP-related CI. The diagnostic model was evaluated by the ROC curve, demonstrating good diagnostic value with an area under the curve (AUC) of 0.803, a sensitivity of 0.603 and a specificity of 0.871.
Conclusion: The risk diagnostic model developed in this study for CP-related CI has significant value and enables clinicians to customize interventions based on each patient's needs.
期刊介绍:
Journal of Pain Research is an international, peer-reviewed, open access journal that welcomes laboratory and clinical findings in the fields of pain research and the prevention and management of pain. Original research, reviews, symposium reports, hypothesis formation and commentaries are all considered for publication. Additionally, the journal now welcomes the submission of pain-policy-related editorials and commentaries, particularly in regard to ethical, regulatory, forensic, and other legal issues in pain medicine, and to the education of pain practitioners and researchers.