ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2019
Mapping the Shah-modified Barthel Index to the Health Utility Index Mark III by the Mean Rank Method.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mapping to estimate health state utility: a systematic review of development and limitations.Health and quality of life outcomes · 2025Pooled it
- Health State Utility Values in People With Stroke: A Systematic Review and Meta-Analysis.Journal of the American Heart Association · 2022Pooled it
- Mapping IWQOL-Lite onto EQ-5D-5L and SF-6Dv2 among overweight and obese population in China.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo map the Shah-modified Barthel Index (SBI) to the Health Utility Index Mark III (HUI-3) in stroke patients, and to compare the performance of a recently developed method called the Mean Rank Method (MRM) against a popular method, the Ordinary Least Squares (OLS) method.
methodsA cohort of 473 patients who had their first clinical stroke diagnosis and hospital admission and were assessed using the SBI and HUI-3 at 3 months and/or 12 months post-admission. Observations were split to form a training dataset (N = 473) and a validation dataset (N = 245).
resultsIn the training dataset, the MRM using SBI total score as the predictor produced a mapped utility distribution that closely resembled the observed utility distribution. It had almost no shrinkage of the standard deviation (P = 0.542), whereas the OLS using SBI total score and SBI item scores under-estimated the standard deviation by 28% and 26%, respectively (each P < 0.001). The MRM mapping gave better fit in terms of smaller mean absolute error and larger intra-class correlation than the two versions of OLS mapping, whereas the OLS gave smaller mean-squared errors than the MRM. Multivariate regression analysis showed that the use of OLS-mapped utilities tended to under-estimate both the mean utility of people who had no comorbidity and the utility-comorbidity association as compared to the observed utility-comorbidity pattern although the differences did not reach statistical significance (each P > 0.05). The MRM-mapped utility showed utility-comorbidity pattern more similar to the observed. Similar findings were obtained from the validation dataset.
conclusionsThe MRM performed well. Mapping functions are available to map the SBI to the HUI-3 Utility Index.
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Registered trials
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