Item reduction of the 39-item Rotterdam Diabetic Foot Study Test Battery using decision tree modelling

Autor: Mark J.W. van der Oest, J. Henk Coert, Willem D. Rinkel
Přispěvatelé: Plastic and Reconstructive Surgery and Hand Surgery
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Test battery
Endocrinology
Diabetes and Metabolism
Decision tree
Diagnostic Techniques
Neurological
030209 endocrinology & metabolism
030204 cardiovascular system & hematology
Spearman's rank correlation coefficient
Severity of Illness Index
decision making
Correlation
03 medical and health sciences
0302 clinical medicine
Endocrinology
Diabetic Neuropathies
SDG 3 - Good Health and Well-being
Statistics
Internal Medicine
medicine
Humans
Prospective Studies
RDF
Reliability (statistics)
Research Articles
Netherlands
business.industry
Decision Trees
decision tree analysis
Reproducibility of Results
risk assessment
sensory testing
computer.file_format
medicine.disease
Prognosis
Diabetic foot
Diabetic Foot
Tree (data structure)
Cross-Sectional Studies
Diabetes Mellitus
Type 1
Diabetes Mellitus
Type 2
item reduction
Case-Control Studies
Sensation Disorders
business
computer
Follow-Up Studies
Research Article
Zdroj: Diabetes-Metabolism Research and Reviews, 36(4):e3291. John Wiley & Sons Ltd.
Diabetes/Metabolism Research and Reviews
ISSN: 1520-7552
Popis: Aims Pedal sensory loss due to diabetes‐related neuropathy can be graded by testing static two‐point discrimination (S2PD), moving two‐point discrimination (M2PD), static one‐point discrimination (S1PD; eg, 10‐g monofilament), and vibration sense and is included in the Rotterdam Diabetic Foot (RDF) Study Test Battery. The aim of this study is to investigate if decision tree modelling is able to reduce the number of tests needed in estimating pedal sensation. Methods The 39‐item RDF Study Test Battery (RDF‐39) scores were collected from the prospective RDF study and included baseline (n = 416), first follow‐up (n = 364), and second follow‐up (n = 135) measurements, supplemented with cross‐sectional control data from a previous study (n = 196). Decision tree analysis was used to predict total RDF‐39 scores using individual test item data. The tree was developed using baseline RDF study data and validated in follow‐up and control data. Spearman correlation coefficients assessed the reliability between the decision tree and original RDF‐39. Results The tree reduced the number of items from 39 to 3 in estimating the RDF‐39 sum score. M2PD (hallux), S2PD (first dorsal web, fifth toe), vibration sense (interphalangeal joint), and S1PD (first dorsal web, fifth toe) measurements proved to be predictive. The correlation coefficients to original scores were high (0.76 to 0.91). Conclusions The decision tree was successful at reducing the number of RDF Test Battery items to only 3, with high correlation coefficients to the scores of the full test battery. The findings of this study aids medical decision making by time efficiently estimating pedal sensory status with fewer tests needed.
Databáze: OpenAIRE
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