1
|
Pan JW, Sidarta A, Wu TL, Kwong WHP, Ong PL, Tay MRJ, Phua MW, Chong WB, Ang WT, Chua KSG. Unraveling stroke gait deviations with movement analytics, more than meets the eye: a case control study. Front Neurosci 2024; 18:1425183. [PMID: 39104608 PMCID: PMC11298395 DOI: 10.3389/fnins.2024.1425183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 07/11/2024] [Indexed: 08/07/2024] Open
Abstract
Background This study aimed to identify and quantify the kinematic and kinetic gait deviations in post-stroke hemiplegic patients with matched healthy controls using Statistical Parametric Mapping (SPM). Methods Fifteen chronic stroke patients [4 females, 11 males; age 53.7 (standard deviation 12.2) years; body mass 65.4 (10.4) kg; standing height 168.5 (9.6) cm] and 15 matched healthy controls [4 females, 11 males; age 52.9 (11.7) years; body weight 66.5 (10.7) years; standing height 168.3 (8.8) cm] were recruited. In a 10-m walking task, joint angles, ground reaction forces (GRF), and joint moments were collected, analyzed, and compared using SPM for an entire gait cycle. Results Generally, when comparing the stroke patients' affected (hemiplegic) and less-affected (contralateral) limbs with the control group, SPM identified significant differences in the late stance phase and early swing phase in the joint angles and moments in bilateral limbs (all p < 0.005). In addition, the vertical and anteroposterior components of GRF were significantly different in various periods of the stance phase (all p < 0.005), while the mediolateral component showed no differences between the two groups. Conclusion SPM was able to detect abnormal gait patterns in both the affected and less-affected limbs of stroke patients with significant differences when compared with matched controls. The findings draw attention to significant quantifiable gait deviations in the less-affected post-stroke limb with the potential impact to inform gait retraining strategies for clinicians and physiotherapists.
Collapse
Affiliation(s)
- Jing Wen Pan
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
- Department of Sports Science and Physical Education, Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Ananda Sidarta
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Tsung-Lin Wu
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Wai Hang Patrick Kwong
- Department of Rehabilitation Sciences, Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Poo Lee Ong
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
| | - Matthew Rong Jie Tay
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Min Wee Phua
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
| | - Wei Binh Chong
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
| | - Wei Tech Ang
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
| | - Karen Sui Geok Chua
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| |
Collapse
|
2
|
Pouwels PJW, Vriend C, Liu F, de Joode NT, Otaduy MCG, Pastorello B, Robertson FC, Venkatasubramanian G, Ipser J, Lee S, Batistuzzo MC, Hoexter MQ, Lochner C, Miguel EC, Narayanaswamy JC, Rao R, Janardhan Reddy YC, Shavitt RG, Sheshachala K, Stein DJ, van Balkom AJLM, Wall M, Simpson HB, van den Heuvel OA. Global multi-center and multi-modal magnetic resonance imaging study of obsessive-compulsive disorder: Harmonization and monitoring of protocols in healthy volunteers and phantoms. Int J Methods Psychiatr Res 2023; 32:e1931. [PMID: 35971639 PMCID: PMC9976605 DOI: 10.1002/mpr.1931] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 06/13/2022] [Accepted: 06/22/2022] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVES We describe the harmonized MRI acquisition and quality assessment of an ongoing global OCD study, with the aim to translate representative, well-powered neuroimaging findings in neuropsychiatric research to worldwide populations. METHODS We report on T1-weighted structural MRI, resting-state functional MRI, and multi-shell diffusion-weighted imaging of 140 healthy participants (28 per site), two traveling controls, and regular phantom scans. RESULTS Human image quality measures (IQMs) and outcome measures showed smaller within-site variation than between-site variation. Outcome measures were less variable than IQMs, especially for the traveling controls. Phantom IQMs were stable regarding geometry, SNR, and mean diffusivity, while fMRI fluctuation was more variable between sites. CONCLUSIONS Variation in IQMs persists, even for an a priori harmonized data acquisition protocol, but after pre-processing they have less of an impact on the outcome measures. Continuous monitoring IQMs per site is valuable to detect potential artifacts and outliers. The inclusion of both cases and healthy participants at each site remains mandatory.
Collapse
Affiliation(s)
- Petra J. W. Pouwels
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Chris Vriend
- Department of PsychiatryDepartment of Anatomy and NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Feng Liu
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Niels T. de Joode
- Department of PsychiatryDepartment of Anatomy and NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Maria C. G. Otaduy
- Department of RadiologyLIM44, InstituteHospital Das Clinicas‐HCFMUSPUniversity of Sao Paulo Medical SchoolSao PauloBrazil
| | - Bruno Pastorello
- Department of RadiologyLIM44, InstituteHospital Das Clinicas‐HCFMUSPUniversity of Sao Paulo Medical SchoolSao PauloBrazil
| | - Frances C. Robertson
- Cape Universities Body Imaging CentreUniversity of Cape TownCape TownSouth Africa
| | | | - Jonathan Ipser
- Department of PsychiatrySAMRC Unit on Risk & Resilience in Mental DisordersNeuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Seonjoo Lee
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Marcelo C. Batistuzzo
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
- Department of Methods and Techniques in PsychologyPontifical Catholic UniversitySao PauloSPBrazil
| | - Marcelo Q. Hoexter
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
| | - Christine Lochner
- Department of PsychiatrySAMRC Unit on Risk & Resilience in Mental DisordersStellenbosch UniversityCape TownSouth Africa
| | - Euripedes C. Miguel
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
| | | | - Rashmi Rao
- National Institute of Mental Health & Neurosciences (NIMHANS)BangaloreIndia
| | | | - Roseli G. Shavitt
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
| | | | - Dan J. Stein
- Department of PsychiatrySAMRC Unit on Risk & Resilience in Mental DisordersNeuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Anton J. L. M. van Balkom
- Department of PsychiatryAmsterdam UMCVrije UniversiteitAmsterdam Public Health Research InstituteSpecialised Mental Health CareAmsterdamThe Netherlands
| | - Melanie Wall
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Helen Blair Simpson
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Odile A. van den Heuvel
- Department of PsychiatryDepartment of Anatomy and NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| |
Collapse
|
3
|
Optimized Weighted Nearest Neighbours Matching Algorithm for Control Group Selection. ALGORITHMS 2021. [DOI: 10.3390/a14120356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
An essential criterion for the proper implementation of case-control studies is selecting appropriate case and control groups. In this article, a new simulated annealing-based control group selection method is proposed, which solves the problem of selecting individuals in the control group as a distance optimization task. The proposed algorithm pairs the individuals in the n-dimensional feature space by minimizing the weighted distances between them. The weights of the dimensions are based on the odds ratios calculated from the logistic regression model fitted on the variables describing the probability of membership of the treated group. For finding the optimal pairing of the individuals, simulated annealing is utilized. The effectiveness of the newly proposed Weighted Nearest Neighbours Control Group Selection with Simulated Annealing (WNNSA) algorithm is presented by two Monte Carlo studies. Results show that the WNNSA method can outperform the widely applied greedy propensity score matching method in feature spaces where only a few covariates characterize individuals and the covariates can only take a few values.
Collapse
|
4
|
Xue YL, Ma YT, Gao YP, Zhang SX, Su QY, Li YF, Zhang L, Ding PF, Li XW. Long-term outcomes of delayed percutaneous coronary intervention for patients with ST-segment elevation myocardial infarction: A propensity score-matched retrospective study. Medicine (Baltimore) 2021; 100:e27474. [PMID: 34797274 PMCID: PMC8601350 DOI: 10.1097/md.0000000000027474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 09/18/2021] [Indexed: 01/05/2023] Open
Abstract
The best time window of percutaneous coronary intervention (PCI) is within 12 hours for ST-segment elevation myocardial infarction (STEMI). However, there is limited evidence about the proper time of PCI for delayed STEMI patients.From June 2014 to June 2015, a total of 268 patients receiving PCI with second-generation drug-eluting stent in a Chinese hospital after 3 days of STEMI onset were enrolled in this retrospective study, who were divided into the early group (3-14 days) and the late group (>14 days). A propensity score match was conducted to reduce the baseline difference. The primary endpoint of all-cause death and secondary endpoints of major adverse cardiac and cerebrovascular event (myocardial infarction [MI], stroke, emergent revascularization, and rehospitalization due to heart failure) were compared using survival analysis.At last, 182 cases were matched after propensity score match, with no statistical difference in baseline characteristics and PCI data. Kaplan-Meier survival curve demonstrated no difference in all-cause death of the 2 groups (P = .512). However, the early group presented a higher incidence of MI than the late group (P = .036). The multivariate Cox regression analysis also demonstrated that the early PCI was an independent risk factor for MI compared with late PCI (hazard ratio = 3.83, 95%CI [1.91-8.82], P = .001). There was no statistical difference in other major adverse cardiac and cerebrovascular event, including stroke, emergent revascularization, and rehospitalization due to heart failure.Using the 2nd drug-eluting stent, early PCI (3-14 days) and late PCI (>14 days) have comparable efficacy and outcomes. However, patients receiving early PCI are subjected to a relatively higher risk of recurrent MI.
Collapse
Affiliation(s)
- Yu-Long Xue
- Department of Cardiovascular Medicine, Shanxi Dayi Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yue-Teng Ma
- Department of Cardiovascular Medicine, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yu-Ping Gao
- Department of Cardiovascular Medicine, Shanxi Dayi Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Sheng-Xiao Zhang
- Department of Rheumatology, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Qin-Yi Su
- Department of Second Clinical Medicine, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yu-Feng Li
- Department of Neurology and Stroke Center, the First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China
| | - Lei Zhang
- Department of Cardiovascular Medicine, Shanxi Dayi Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Peng-Fei Ding
- Department of Cardiovascular Medicine, Shanxi Dayi Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Xue-Wen Li
- Department of Cardiovascular Medicine, Shanxi Dayi Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi Province, China
| |
Collapse
|