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Transforming self-r...
Transforming self-reported outcomes from a stroke register to the modified Rankin Scale: a cross-sectional, explorative study
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- Abzhandadze, Tamar, 1980 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för hälsa och rehabilitering,Institute of Neuroscience and Physiology, Department of Health and Rehabilitation
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- Reinholdsson, Malin (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för hälsa och rehabilitering,Institute of Neuroscience and Physiology, Department of Health and Rehabilitation
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- Palstam, Annie, 1981 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för hälsa och rehabilitering,Institute of Neuroscience and Physiology, Department of Health and Rehabilitation,Institute of Neuroscience and Physiology, Rehabilitation Medicine, University of Gothenburg
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- Eriksson, Marie, Professor (författare)
- Umeå universitet,Statistik,Stat4Reg
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- Stibrant Sunnerhagen, Katharina, 1957 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för hälsa och rehabilitering,Institute of Neuroscience and Physiology, Department of Health and Rehabilitation
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(creator_code:org_t)
- 2020-10-14
- 2020
- Engelska.
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
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Abstract
Ämnesord
Stäng
- The aim was to create an algorithm to transform self-reported outcomes from a stroke register to the modified Rankin Scale (mRS). Two stroke registers were used: the Vaststroke, a local register in Gothenburg, Sweden, and the Riksstroke, a Swedish national register. The reference variable, mRS (from Vaststroke), was mapped with seven self-reported questions from Riksstroke. The transformation algorithm was created as a result of manual mapping performed by healthcare professionals. A supervised machine learning method-decision tree-was used to further evaluate the transformation algorithm. Of 1145 patients, 54% were male, the mean age was 71 y. The mRS grades 0, 1 and 2 could not be distinguished as a result of manual mapping or by using the decision tree analysis. Thus, these grades were merged. With manual mapping, 78% of the patients were correctly classified, and the level of agreement was almost perfect, weighted Kappa (K-w) was 0.81. With the decision tree, 80% of the patients were correctly classified, and substantial agreement was achieved, K-w=0.67. The self-reported outcomes from a stroke register can be transformed to the mRS. A mRS algorithm based on manual mapping might be useful for researchers using self-reported questionnaire data.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Neurosciences (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Neurologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Neurology (hsv//eng)
Nyckelord
- weighted kappa
- interrater reliability
- agreement
- coefficient
- trials
- Science & Technology - Other Topics
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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