Alan Castro Mejia , Philipp Gulde , Consuelo González Salinas
{"title":"骨关节炎步态质量模式的临床应用。","authors":"Alan Castro Mejia , Philipp Gulde , Consuelo González Salinas","doi":"10.1016/j.gaitpost.2024.10.011","DOIUrl":null,"url":null,"abstract":"<div><h3>Aim</h3><div>To investigate whether a smartphone-based gait analysis tool can reliably output gait quality parameters that can be cross-analyzed to establish individual & disease-based changes in gait quality patterns.</div></div><div><h3>Methods</h3><div>A cross-sectional study made up of a 48-patients undergoing disability certification at the “Dr. José Castro Villagrana” or the “Dr. David Fragoso Lizalde” Health Centers in Mexico City, Mexico. Their sensorimotor performance was evaluated through an in-house smartphone/IMU based digital tool. Gait was analyzed by means of frequency analysis of the acceleration of the body mass measured at the sternum. A composite gait quality score was determined through principal component analysis based primarily on the explainability and uniformity of gait. Quality independence against demographic variables (age & weight) was tested through ANCOVA. The association between gait quality and gait parameters was analyzed by using multiple linear regression.</div></div><div><h3>Results</h3><div>A multiple regression model developed with a limited set of gait quality parameters successfully predicted gait smoothness with a 97.05 % accuracy with a mean square error of 0.085 between predicted and actual quality scores. The model demonstrates different predictive capacities across disease groups, with Osteoarthrosis + Osteoporosis having the highest R<sup>2</sup> at 0.98 (p < 0.001) and Coxarthrosis having the lowest explained R<sup>2</sup> at 0.79 (p < 0.001).</div></div><div><h3>Conclusions</h3><div>The assessment of gait quality, in family medicine, with low-cost digital tools is an area of opportunity yet to be explored. This tool can potentially disrupt the current disability workflow between primary and specialty care to have an objective method of assessing gait within a clinical consult. Individual patient-level benchmarking can give us insights into the patient's disease status, develop practical intervention strategies, and control the cost and quality of medical care by predicting an individualized course of disability or rehabilitation. Further studies are needed to validate digital gait assessments as clinical decision support tools for day-to-day clinical operations.</div></div><div><h3>MeSH</h3><div>Gait Analysis, Smartphone, Primary Health Care, Osteoarthrosis</div></div>","PeriodicalId":12496,"journal":{"name":"Gait & posture","volume":"114 ","pages":"Pages 284-289"},"PeriodicalIF":2.2000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A clinical application of gait quality patterns in osteoarthritis\",\"authors\":\"Alan Castro Mejia , Philipp Gulde , Consuelo González Salinas\",\"doi\":\"10.1016/j.gaitpost.2024.10.011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Aim</h3><div>To investigate whether a smartphone-based gait analysis tool can reliably output gait quality parameters that can be cross-analyzed to establish individual & disease-based changes in gait quality patterns.</div></div><div><h3>Methods</h3><div>A cross-sectional study made up of a 48-patients undergoing disability certification at the “Dr. José Castro Villagrana” or the “Dr. David Fragoso Lizalde” Health Centers in Mexico City, Mexico. Their sensorimotor performance was evaluated through an in-house smartphone/IMU based digital tool. Gait was analyzed by means of frequency analysis of the acceleration of the body mass measured at the sternum. A composite gait quality score was determined through principal component analysis based primarily on the explainability and uniformity of gait. Quality independence against demographic variables (age & weight) was tested through ANCOVA. The association between gait quality and gait parameters was analyzed by using multiple linear regression.</div></div><div><h3>Results</h3><div>A multiple regression model developed with a limited set of gait quality parameters successfully predicted gait smoothness with a 97.05 % accuracy with a mean square error of 0.085 between predicted and actual quality scores. The model demonstrates different predictive capacities across disease groups, with Osteoarthrosis + Osteoporosis having the highest R<sup>2</sup> at 0.98 (p < 0.001) and Coxarthrosis having the lowest explained R<sup>2</sup> at 0.79 (p < 0.001).</div></div><div><h3>Conclusions</h3><div>The assessment of gait quality, in family medicine, with low-cost digital tools is an area of opportunity yet to be explored. This tool can potentially disrupt the current disability workflow between primary and specialty care to have an objective method of assessing gait within a clinical consult. Individual patient-level benchmarking can give us insights into the patient's disease status, develop practical intervention strategies, and control the cost and quality of medical care by predicting an individualized course of disability or rehabilitation. Further studies are needed to validate digital gait assessments as clinical decision support tools for day-to-day clinical operations.</div></div><div><h3>MeSH</h3><div>Gait Analysis, Smartphone, Primary Health Care, Osteoarthrosis</div></div>\",\"PeriodicalId\":12496,\"journal\":{\"name\":\"Gait & posture\",\"volume\":\"114 \",\"pages\":\"Pages 284-289\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gait & posture\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0966636224006398\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gait & posture","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0966636224006398","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
A clinical application of gait quality patterns in osteoarthritis
Aim
To investigate whether a smartphone-based gait analysis tool can reliably output gait quality parameters that can be cross-analyzed to establish individual & disease-based changes in gait quality patterns.
Methods
A cross-sectional study made up of a 48-patients undergoing disability certification at the “Dr. José Castro Villagrana” or the “Dr. David Fragoso Lizalde” Health Centers in Mexico City, Mexico. Their sensorimotor performance was evaluated through an in-house smartphone/IMU based digital tool. Gait was analyzed by means of frequency analysis of the acceleration of the body mass measured at the sternum. A composite gait quality score was determined through principal component analysis based primarily on the explainability and uniformity of gait. Quality independence against demographic variables (age & weight) was tested through ANCOVA. The association between gait quality and gait parameters was analyzed by using multiple linear regression.
Results
A multiple regression model developed with a limited set of gait quality parameters successfully predicted gait smoothness with a 97.05 % accuracy with a mean square error of 0.085 between predicted and actual quality scores. The model demonstrates different predictive capacities across disease groups, with Osteoarthrosis + Osteoporosis having the highest R2 at 0.98 (p < 0.001) and Coxarthrosis having the lowest explained R2 at 0.79 (p < 0.001).
Conclusions
The assessment of gait quality, in family medicine, with low-cost digital tools is an area of opportunity yet to be explored. This tool can potentially disrupt the current disability workflow between primary and specialty care to have an objective method of assessing gait within a clinical consult. Individual patient-level benchmarking can give us insights into the patient's disease status, develop practical intervention strategies, and control the cost and quality of medical care by predicting an individualized course of disability or rehabilitation. Further studies are needed to validate digital gait assessments as clinical decision support tools for day-to-day clinical operations.
MeSH
Gait Analysis, Smartphone, Primary Health Care, Osteoarthrosis
期刊介绍：
Gait & Posture is a vehicle for the publication of up-to-date basic and clinical research on all aspects of locomotion and balance.
The topics covered include: Techniques for the measurement of gait and posture, and the standardization of results presentation; Studies of normal and pathological gait; Treatment of gait and postural abnormalities; Biomechanical and theoretical approaches to gait and posture; Mathematical models of joint and muscle mechanics; Neurological and musculoskeletal function in gait and posture; The evolution of upright posture and bipedal locomotion; Adaptations of carrying loads, walking on uneven surfaces, climbing stairs etc; spinal biomechanics only if they are directly related to gait and/or posture and are of general interest to our readers; The effect of aging and development on gait and posture; Psychological and cultural aspects of gait; Patient education.
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