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Trial registered on ANZCTR
Registration number
ACTRN12622001540707
Ethics application status
Approved
Date submitted
4/12/2022
Date registered
13/12/2022
Date last updated
13/12/2022
Date data sharing statement initially provided
13/12/2022
Type of registration
Prospectively registered
Titles & IDs
Public title
Posture and musculoskeletal system disorders in post-COVID-19 individuals
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Scientific title
Posture and musculoskeletal system disorders in individuals who have had COVID-19
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Secondary ID [1]
308545
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Nil known
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Universal Trial Number (UTN)
U1111-1285-7304
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Trial acronym
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
postural disorder
328392
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musculoskeletal system disorders
328393
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pain
328395
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COVID-19
328396
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Condition category
Condition code
Infection
325419
325419
0
0
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Other infectious diseases
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Respiratory
325420
325420
0
0
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Other respiratory disorders / diseases
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Musculoskeletal
325516
325516
0
0
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Other muscular and skeletal disorders
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Intervention/exposure
Study type
Observational
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Patient registry
False
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
In this study, it was planned to reveal the results of posture measurement evaluated by artificial intelligence method, pain status and musculoskeletal disorders in individuals who have had COVID-19. All evaluations of posture and musculoskeletal system disorders will be completed within a maximum of one hour in the field of university practice.
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Intervention code [1]
324990
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Not applicable
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Comparator / control treatment
No control group.
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Control group
Uncontrolled
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Outcomes
Primary outcome [1]
333282
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The pain severity will be evaluated using Numerical Rating Scale.
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Assessment method [1]
333282
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Timepoint [1]
333282
0
at survey time
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Secondary outcome [1]
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The presence of postural disorders will be evaluated with the posture analysis package based on the artificial intelligence concept created by Physiosoft and Becure.
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Assessment method [1]
416463
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Timepoint [1]
416463
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at survey time
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Secondary outcome [2]
416464
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The score of musculoskeletal disorders will be evaluated using Cornell Musculoskeletal Disorders Questionnaire.
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Assessment method [2]
416464
0
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Timepoint [2]
416464
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at survey time
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Eligibility
Key inclusion criteria
Inclusion criteria for the individuals who have had COVID-19 were:
*adult individuals aged 18 and over
*volunteering to participate in the study,
*Individuals who can understand and answer the questionnaires
*Individuals who were diagnosed with COVID-19 (individuals with a positive Polymerase Chain Reaction (PCR) test result, compatible with COVID-19 infection as a result of lung X-ray or lung tomography despite negative PCR test results) and discharged after recovery/home quarantine completed
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Exclusion criteria for the individuals who have had COVID-19 were:
* Individuals with any physical or mental disability/disease and/or cognitive impairment
• Individuals newly diagnosed with COVID-19, therefore in quarantine at home or receiving treatment in hospital
• Individuals with suspected COVID-19
• Pregnant women
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Study design
Purpose
Natural history
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Duration
Cross-sectional
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Selection
Defined population
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Timing
Prospective
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Statistical methods / analysis
The sample size required for the study was calculated using the Raosoft sample size calculator program. It was determined that at least 37 individuals should be included in the group of those with COVID-19 in order for this study to reach an a value of 0.05, and a power of 95%, to determine the response of pain rate (13.3%) in the research group.
At the end of the study, statistical analyzes will be made using the SPSS 15.0 program. By using visual (histogram and probability graphs) and analytical methods (Kolmogorov-Smirnov/Shapiro-Wilk tests), the conformity of all variables to normal distribution will be investigated. Descriptive analyzes will be given using frequency (n) and percentage (%) values for categorical variables, median, minimum and maximum values for non-normally distributed variables, mean and standard deviation (×±ss) for normally distributed variables.
The Independent Sample t test (Student t test) will be used to compare the variables that fit the normal distribution, the Mann-Whitney U test will be used to compare the data that do not fit, and the Chi-square test will be used to compare the uncountable data. The relationships between the non-normally distributed variables will be determined by Spearman and the relationships between the normally distributed variables will be determined by the Pearson correlation analysis method. The probability of error in statistical analysis will be determined as p<0.05.
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Recruitment
Recruitment status
Not yet recruiting
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Date of first participant enrolment
Anticipated
31/01/2023
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Actual
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Date of last participant enrolment
Anticipated
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Actual
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Date of last data collection
Anticipated
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Actual
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Sample size
Target
37
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Accrual to date
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Final
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Recruitment outside Australia
Country [1]
25165
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Turkey
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State/province [1]
25165
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Izmir
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Funding & Sponsors
Funding source category [1]
312793
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Government body
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Name [1]
312793
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Scientific and Technological Research Council of Turkey (TUBITAK)
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Address [1]
312793
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TÜBITAK Presidency Tunisia Street No:80 Zip code: 06680 Kavaklidere-Ankara
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Country [1]
312793
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Turkey
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Primary sponsor type
Individual
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Name
GÜLSAH BARGI
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Address
Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country
Turkey
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Secondary sponsor category [1]
314427
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Individual
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Name [1]
314427
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HELIN ÖNCEL
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Address [1]
314427
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Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country [1]
314427
0
Turkey
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Secondary sponsor category [2]
314429
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Individual
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Name [2]
314429
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SIBEL DENIZ
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Address [2]
314429
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Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country [2]
314429
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Turkey
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Secondary sponsor category [3]
314430
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Individual
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Name [3]
314430
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SARA MOHAMMADNEJADIAN
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Address [3]
314430
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Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country [3]
314430
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Turkey
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
312080
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Izmir Democracy University Non-Interventional Clinical Research of the Ethics Committee
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Ethics committee address [1]
312080
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Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir
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Ethics committee country [1]
312080
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Turkey
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Date submitted for ethics approval [1]
312080
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01/06/2022
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Approval date [1]
312080
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24/06/2022
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Ethics approval number [1]
312080
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2022/07-04
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Summary
Brief summary
Thanks to artificial intelligence and machine learning technology, evaluations such as balance and foot pressure measurement can be made in patients today, as well as applications such as exercise and patient follow-up in rehabilitation, solutions to biomedical problems can be offered. Artificial intelligence and machine learning will continue to play an important role in education, training, patient care and research in the future. On the other hand, although various psychological and physical problems have been shown in individuals who have had COVID-19 during the prolonged COVID-19 pandemic process, musculoskeletal disorders and posture problems in these individuals remain unclear. For this reason, in this study, it was aimed to reveal the results of posture measurement evaluated by artificial intelligence method, pain status and musculoskeletal disorders in individuals who have had COVID-19.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
123398
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Dr GÜLSAH BARGI
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Address
123398
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Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country
123398
0
Turkey
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Phone
123398
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+905317938766
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Fax
123398
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+90 232 260 1004
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Email
123398
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[email protected]
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Contact person for public queries
Name
123399
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GÜLSAH BARGI
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Address
123399
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Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country
123399
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Turkey
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Phone
123399
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+902322601001
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Fax
123399
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+90 232 260 1004
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Email
123399
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[email protected]
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Contact person for scientific queries
Name
123400
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GÜLSAH BARGI
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Address
123400
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Izmir Democracy University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Mehmet Ali Akman Quarter, 13th street, No. 2, 35140 Güzelyali, Konak, Izmir, Turkey.
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Country
123400
0
Turkey
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Phone
123400
0
+902322601001
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Fax
123400
0
+90 232 260 1004
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Email
123400
0
[email protected]
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Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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No/undecided IPD sharing reason/comment
I can not share the data of individuals included in the study in our country within the scope of the personal data protection law.
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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