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躯体心力衰竭症状群对延迟寻求治疗的预测作用。

Physical Heart Failure Symptom Clusters Predictive of Delay in Seeking Treatment.

出版信息

Nurs Res. 2024;73(6):426-433. doi: 10.1097/NNR.0000000000000755. Epub 2024 Jun 25.

Abstract

BACKGROUND

Recent research has focused on the relationship between heart failure (HF) symptom clusters and outcomes, including mortality, hospitalization, functional status, and quality of life. No known studies to date have explored the role of physical HF symptom clusters and delays in seeking treatment.

OBJECTIVES

Describe physical symptom clusters in a population of HF patients and determine if a specific cluster is predictive of delay in seeking treatment for HF symptoms.

METHOD

We analyzed combined data from two studies ( n = 406) collected during acute HF hospitalization. The Heart Failure Somatic Awareness Scale quantified physical HF symptoms. Delay, measured in days, was collected from the medical record and confirmed by interview. Hierarchical agglomerative clustering techniques determined physical HF symptom clusters. Hierarchical multiple regression analysis was computed to explore predictors of delay.

RESULTS

Participants were primarily White, male sex older adults. Three physical HF symptom clusters were identified: discordant, edema-related, and dyspnea-related symptoms. Hierarchical multiple regression analysis revealed in Step 1 that age was a significant predictor of delay.

DISCUSSION

Our findings provide valuable insight into the role of physical symptom clusters on delay in persons with HF. Through agglomerative hierarchical clustering techniques, we found three physical HF symptom clusters that were then used to determine differences in cluster membership by demographic and clinical variables. Significant age differences were noted by cluster membership with youngest older adults in a discordant symptom cluster.

摘要

背景

最近的研究集中在心力衰竭(HF)症状群与包括死亡率、住院率、功能状态和生活质量在内的结局之间的关系。迄今为止,尚无已知的研究探讨身体 HF 症状群与寻求治疗的延迟之间的关系。

目的

描述 HF 患者人群中的身体症状群,并确定特定的症状群是否与 HF 症状寻求治疗的延迟有关。

方法

我们分析了急性 HF 住院期间两项研究(n=406)的合并数据。心力衰竭躯体感知量表量化了身体 HF 症状。延迟时间(以天为单位)从病历中收集,并通过访谈进行确认。层次凝聚聚类技术确定了身体 HF 症状群。采用分层多元回归分析来探讨延迟的预测因素。

结果

参与者主要为白人、男性、老年成年人。确定了三个身体 HF 症状群:不和谐、水肿相关和呼吸困难相关症状。分层多元回归分析显示,在第 1 步中,年龄是延迟的显著预测因素。

讨论

我们的研究结果提供了有关身体症状群对 HF 患者延迟的作用的有价值的见解。通过层次凝聚聚类技术,我们发现了三个身体 HF 症状群,然后根据人口统计学和临床变量确定了不同症状群的差异。通过聚类成员关系发现了显著的年龄差异,最年轻的老年成年人属于不和谐症状群。

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