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Updated: Apr 14, 2026
Computerized Adaptive Testing System of Functional Assessment of Stroke
Published on: January 7, 2019
Determining optimal Barthel Index cutoff scores for predicting Longshi Scale grades across age groups in stroke
Jing Zhang1, Mingchao Zhou1, Ankang Liu2
1Department of Rehabilitation, Shenzhen Second People's Hospital, First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China.
Background:
The Barthel Index (BI) is a standard, widely used measure of dependence in activities of daily living (ADL), particularly in stroke care. The Longshi Scale (LS) offers a simpler, more user-friendly alternative; however, it lacks a validated, age-stratified mapping to BI scores. This gap limits consistent outcome interpretation and application.
Objective:
This study aims to establish and validate a standardized, age-stratified concordance between BI scores and LS grades, thereby providing a practical conversion tool for clinical and research settings.
Method:
In a multi-center study of 16,412 stroke inpatients (3 months post-stroke), BI scores and LS grades were analyzed across age groups: <60 years (n = 12,662), 60-79 years (n = 2,596), and ≥80 years (n = 1,154). Sensitivity (correct identification) and specificity (correct exclusion), along with receiver operating characteristic (ROC) curves were used to determine optimal BI cutoff points for each LS grade. Spearman correlation and the Kruskal-Wallis test were applied across age groups.
Results:
Key BI cutoffs were identified for LS grades: ≥75 for LS ≥ 2, ≥45 for LS ≥ 4, and <5 for LS = 6. These cutoff values were consistent across age groups. The BI scores were negatively correlated with LS disability level (e.g., r = -0.879 in patients aged ≥80 years, p < 0.001). Correlations remained strongest at severe disability levels (LS grades 5-6) across age groups (r = -0.60 to -0.65). AUC analysis demonstrated excellent discriminative ability, particularly for the mildest (LS 1) and most severe (LS 6) disability levels (AUC >0.95).
Conclusion:
The study provides age-stratified BI cutoff values to guide resource allocation, emphasizing the need to prioritize care for individuals aged ≥80 years with BI scores below 5.
