心内科患者Barthel评分与住院时间的相关性分析

Correlation Analysis of Barthel Score and Length of Hospital Stay in Cardiology Patients

摘要: 目的：探讨心内科住院患者入院时的Barthel指数(BI)评分与住院时间的相关性，分析BI评分对住院时间的独立预测价值。方法：采用单中心回顾性队列研究设计，连续纳入2022年1月至2025年8月于本院心内科住院的70例患者。收集患者基线资料、入院48小时内BI评分及住院时间等数据。采用Spearman相关性分析BI总分与住院时间的关系，采用单因素方差分析比较不同BI分级患者的住院时间差异，并运用多元线性回归分析BI评分对住院时间的独立影响。结果：患者平均BI评分为(73.50 ± 18.92)分，平均住院时间为(8.20 ± 3.45)天。相关性分析显示，BI总分与住院时间呈显著负相关(r = −0.63, P < 0.01)。不同BI分级组间的住院时间差异具有统计学意义(F = 18.47, P < 0.01)，完全依赖组住院时间最长[(14.33 ± 2.52)天]，完全独立组最短[(5.09 ± 1.22)天]。多元线性回归分析显示，在控制年龄、NYHA分级等混杂因素后，BI评分仍是住院时间的独立负向预测因素(β = −0.15, P < 0.01)，且其标准化回归系数(Beta = −0.68)绝对值最大。结论：心内科住院患者的Barthel指数与住院时间呈显著负相关，即自理能力越差，住院时间越长。BI评分是住院时间的独立预测因子，将其纳入入院评估有助于早期识别住院时间延长的高风险患者，为优化护理资源配置和制定个性化干预方案提供重要依据。

Abstract: Objective: To explore the correlation between the Barthel Index (BI) score of inpatients in the cardiology department at admission and the length of hospital stay, and to analyze the independent predictive value of the BI score for the length of hospital stay. Method: A single-center retrospective cohort study design was adopted. A total of 70 patients who were hospitalized in the Department of Cardiology of our hospital from January 2022 to August 2025 were consecutively included. Baseline data of patients, BI scores within 48 hours of admission, and length of hospital stay were collected. Spearman correlation analysis was used to analyze the relationship between the total BI score and the length of hospital stay. One-way analysis of variance was used to compare the differences in the length of hospital stay among patients with different BI grades. Multiple linear regression analysis was applied to analyze the independent effect of BI score on the length of hospital stay. Result: The average BI score of the patients was (73.50 ± 18.92) points, and the average length of hospital stay was (8.20 ± 3.45) days. Correlation analysis showed that the total BI score was significantly negatively correlated with the length of hospital stay (r = −0.63, P < 0.01). The differences in hospital stay among different BI classification groups were statistically significant (F = 18.47, P < 0.01). The complete dependence group had the longest hospital stay [(14.33 ± 2.52) days], while the complete independence group had the shortest [(5.09 ± 1.22) days). Multivariate linear regression analysis showed that after controlling for confounding factors such as age and NYHA classification, the BI score remained an independent negative predictor of hospital stay (β = −0.15, P < 0.01), and its standardized regression coefficient (Beta = −0.68) had the largest absolute value. Conclusion: The Barthel index of inpatients in the cardiology department is significantly negatively correlated with the length of hospital stay, that is, the poorer the self-care ability, the longer the hospital stay. The BI score is an independent predictor of hospital stay. Incorporating it into the admission assessment helps identify patients at high risk of prolonged hospital stay at an early stage, providing an important basis for optimizing the allocation of nursing resources and formulating personalized intervention plans.