{"title":"急性带状疱疹神经痛患者遵医嘱用药的临床预测因素","authors":"Hui Lyu, Ling-Yan Wang, Rui-Xia Wang, Han Sheng, Jian-Mei Xia, Jun-Ya Cheng","doi":"10.1016/j.pmn.2024.07.002","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Pain is one of the most common and harmful symptoms experienced by individuals with acute herpetic neuralgia (AHN). In this population, studies to determine the causes that affect patients taking medications compliance are rare. This study aimed to construct a predictive model for medication compliance of patients with AHN and to verify its performance.</p><p><strong>Design and methods: </strong>In this prospective study of 398 patients with AHN who were discharged from a tertiary hospital with medications from July 2020 to October 2022, we used logistic regression analysis to explore the predictive factors of medication compliance of patients with AHN and to construct a nomogram. The area under the curve was used to evaluate the predictive effect of the model.</p><p><strong>Results: </strong>A predictive model of drug compliance of patients with AHN was constructed based on the following four factors: disease duration, pain severity before treatment, medication beliefs, and comorbidity of chronic diseases. The area under the curve of the model was 0.766 (95% confidence interval [0.713, 0.819]), with a maximum Youden's index of 0.431, sensitivity of 0.776, and specificity of 0.655. A linear calibration curve was found with a slope close to 1.</p><p><strong>Conclusions: </strong>The prediction model constructed in this study had good predictive performance and provided a reference for early clinical screening of independent factors that affected the medication compliance of patients with AHN.</p>","PeriodicalId":19959,"journal":{"name":"Pain Management Nursing","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical Predictors of Medication Compliance in Patients With Acute Herpetic Neuralgia.\",\"authors\":\"Hui Lyu, Ling-Yan Wang, Rui-Xia Wang, Han Sheng, Jian-Mei Xia, Jun-Ya Cheng\",\"doi\":\"10.1016/j.pmn.2024.07.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Pain is one of the most common and harmful symptoms experienced by individuals with acute herpetic neuralgia (AHN). In this population, studies to determine the causes that affect patients taking medications compliance are rare. This study aimed to construct a predictive model for medication compliance of patients with AHN and to verify its performance.</p><p><strong>Design and methods: </strong>In this prospective study of 398 patients with AHN who were discharged from a tertiary hospital with medications from July 2020 to October 2022, we used logistic regression analysis to explore the predictive factors of medication compliance of patients with AHN and to construct a nomogram. The area under the curve was used to evaluate the predictive effect of the model.</p><p><strong>Results: </strong>A predictive model of drug compliance of patients with AHN was constructed based on the following four factors: disease duration, pain severity before treatment, medication beliefs, and comorbidity of chronic diseases. The area under the curve of the model was 0.766 (95% confidence interval [0.713, 0.819]), with a maximum Youden's index of 0.431, sensitivity of 0.776, and specificity of 0.655. A linear calibration curve was found with a slope close to 1.</p><p><strong>Conclusions: </strong>The prediction model constructed in this study had good predictive performance and provided a reference for early clinical screening of independent factors that affected the medication compliance of patients with AHN.</p>\",\"PeriodicalId\":19959,\"journal\":{\"name\":\"Pain Management Nursing\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pain Management Nursing\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.pmn.2024.07.002\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pain Management Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.pmn.2024.07.002","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
Clinical Predictors of Medication Compliance in Patients With Acute Herpetic Neuralgia.
Purpose: Pain is one of the most common and harmful symptoms experienced by individuals with acute herpetic neuralgia (AHN). In this population, studies to determine the causes that affect patients taking medications compliance are rare. This study aimed to construct a predictive model for medication compliance of patients with AHN and to verify its performance.
Design and methods: In this prospective study of 398 patients with AHN who were discharged from a tertiary hospital with medications from July 2020 to October 2022, we used logistic regression analysis to explore the predictive factors of medication compliance of patients with AHN and to construct a nomogram. The area under the curve was used to evaluate the predictive effect of the model.
Results: A predictive model of drug compliance of patients with AHN was constructed based on the following four factors: disease duration, pain severity before treatment, medication beliefs, and comorbidity of chronic diseases. The area under the curve of the model was 0.766 (95% confidence interval [0.713, 0.819]), with a maximum Youden's index of 0.431, sensitivity of 0.776, and specificity of 0.655. A linear calibration curve was found with a slope close to 1.
Conclusions: The prediction model constructed in this study had good predictive performance and provided a reference for early clinical screening of independent factors that affected the medication compliance of patients with AHN.
期刊介绍:
This peer-reviewed journal offers a unique focus on the realm of pain management as it applies to nursing. Original and review articles from experts in the field offer key insights in the areas of clinical practice, advocacy, education, administration, and research. Additional features include practice guidelines and pharmacology updates.