An observational study in Cystic Fibrosis (CF), sponsored by Gazi University. Completed at 1 site in Turkey (Türkiye). Open to participants aged 6 Years to 18 Years. Per ClinicalTrials.gov, last updated 2026-08-18.
Sponsored by Gazi University · Observational
Among 48 studies in Cystic Fibrosis with a site in Turkey — 3 open to participants now, 3 under way, none of them phase 3. Cystic Fibrosis · Turkey.
Among the 48 studies in Cystic Fibrosis with a site in Turkey, this one is the 21st largest by enrollment of the 27 observational ones that give a count, is one of 9 that started in 2021, is one of 27 observational ones, and was the 47th registered.
1,619 studies on the registry are indexed under Cystic Fibrosis; 199 are open to participants now.
Browse Cystic Fibrosis studies →3 of the 48 studies in Cystic Fibrosis with a site in Turkey are open now. Recruiting first, the newest first:
Izmir Democracy University · Sites in Turkey
Ages 6–18
Hacettepe University · Sites in Turkey
Ages 18–45 · Healthy volunteers
büşra başpınar · Sites in Turkey
Ages 6–18
A study can be open while its sites in Turkey have not opened yet or have stopped. Only those recruiting at a site in Turkey →
Of the 154 Cystic Fibrosis studies recruiting now, 95 (62%) set no upper age limit and 43 (28%) stop at 75 or younger; 84 take children under 18; 41 take healthy volunteers.
This study: 6 Years to 18 Years · all sexes · no healthy volunteers.
The full table on the hub →This tab as a report to print or save as PDF → With an account.
48 studies; the count open now beside each. This study's row is marked.
First in 2016; this study’s year is marked. 9 started in 2021.
This study's enrollment of 31 is below the median of 85 across 503 observational studies indexed under Cystic Fibrosis.
Median enrollment 34 across the 21 interventional studies, 50 across the 27 observational. Of the 42 that completed or were terminated, 1 (2%) have results posted.
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1 of 48 have an industry lead sponsor. The 10 most frequent:
Gazi University is the lead sponsor of 551 studies on the registry; 102 are open to participants now.
Gazi University has 4 studies filed under Cystic Fibrosis — fewer than ten, so there is no comparison to draw.
1 of the studies in Cystic Fibrosis with a site in Turkey that are under way reach primary completion within a year, 0 of them phase 3. Phase 3 first, then by date:
| Study | Primary completion |
|---|---|
| NCT06984679Izmir Democracy UniversityPhysical Impairments in Children With Cystic Fibrosis | 2027-03-01 |
Among the 48 studies in Cystic Fibrosis with a site in Turkey, from their registry updates:
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Cystic fibrosis is a multisystem genetic disorder characterized by progressive pulmonary impairment and extrapulmonary limitations. This retrospective observational study will perform a secondary analysis of previously collected data from children with cystic fibrosis. The primary objective is to determine the relative contribution of peripheral muscle oxygenation and postural balance parameters to the prediction of pulmonary function, including forced expiratory volume in 1 second, forced vital capacity, and peak expiratory flow, using machine-learning regression methods. The additional contribution of exercise-related oxygen saturation responses, symptoms, nutritional and anthropometric characteristics, physical activity, respiratory muscle function, quality of life, treatment burden, and disease-related clinical variables will also be examined. No new assessment, intervention, or participant contact will occur.
This study is a retrospective, cross-sectional, non-interventional secondary analysis of de-identified archived data obtained from children with cystic fibrosis who were evaluated at the Cardiopulmonary Rehabilitation Unit, Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Gazi University, between April 2021 and September 2022.
The source data were collected prospectively as part of a previous observational study approved by the Gazi University Ethics Commission (Decision No. 839, December 7, 2020) and prospectively registered at ClinicalTrials.gov (NCT04803643). Written informed consent was obtained from the participants and their parents or legal guardians before the assessments conducted in the source study. No new participant contact, recruitment, assessment, biological sample collection, or intervention will be performed for the present secondary analysis.
Although the parent study included an age- and sex-matched healthy control group, the present prediction analysis will be restricted to the archived records of 31 children with cystic fibrosis who satisfy the prespecified eligibility criteria and have the variables required for the planned analyses.
Pulmonary Function Outcomes
Pulmonary function was assessed using a COSMED spirometer (Class II/Internally Powered Equipment, Italy) in accordance with American Thoracic Society/European Respiratory Society standardization criteria. Measurements were performed in the seated position using a nose clip. Participants completed at least three technically acceptable forced expiratory maneuvers, and the highest acceptable values were recorded.
Forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF), expressed as both absolute and percent-predicted values, will constitute the prespecified pulmonary function prediction targets. A separate prediction model will be developed for each pulmonary function target.
Peripheral Muscle Oxygenation
Peripheral muscle oxygenation was assessed noninvasively using the Moxy Monitor, a portable near-infrared spectroscopy device (Fortiori Design LLC, Minnesota, USA). During the six-minute walk test, the sensor was positioned over the quadriceps femoris muscle of the dominant lower extremity and secured in the same position throughout the test.
Muscle oxygen saturation (SmO2) and total hemoglobin (THb) were monitored continuously during the resting, exercise, and recovery periods. The archived measurements included resting, minimum, maximum, and recovery SmO2 and THb values. Changes between resting, exercise, and recovery values will also be calculated when the required measurements are available. These muscle oxygenation variables will be treated as primary candidate predictors.
Functional Exercise Capacity and Oxygen Saturation Response
Functional exercise capacity was assessed using the six-minute walk test in accordance with American Thoracic Society procedures. Participants were instructed to walk, without running, as far as possible along a predetermined level corridor for six minutes. The total distance walked was recorded in meters.
Heart rate, blood pressure, respiratory rate, peripheral oxygen saturation, perceived dyspnea, and leg fatigue were assessed before and after the test. Peripheral oxygen saturation was monitored throughout the test, and resting, minimum, end-test, and recovery SpO2 values were recorded. Exercise-related changes in SpO2 will be derived from these archived measurements when appropriate.
Perceived dyspnea and fatigue were evaluated using the Modified Borg Scale, ranging from 0 to 10, with higher scores indicating greater symptom severity. Six-minute walk distance, SpO2 responses, and symptom scores will be evaluated as additional candidate predictors.
Respiratory Muscle Strength
Respiratory muscle strength was assessed using a portable electronic mouth-pressure measurement device in accordance with ATS/ERS recommendations. Maximal inspiratory pressure was measured from a lung volume close to residual volume, whereas maximal expiratory pressure was measured from a lung volume close to total lung capacity.
Participants performed at least three technically acceptable and reproducible maneuvers with verbal encouragement. The highest acceptable maximal inspiratory pressure and maximal expiratory pressure values were recorded in cmH2O. MIP and MEP values were also expressed as percentages of age- and sex-predicted values when available. Absolute and percent-predicted MIP and MEP measurements will be evaluated as additional candidate predictors.
Inspiratory Muscle Endurance
Inspiratory muscle endurance was assessed using an incremental threshold-loading test with the POWERbreathe Wellness device (POWERbreathe International Ltd., Birmingham, United Kingdom). The test was initiated at 20% of the participant's maximal inspiratory pressure. The threshold load was subsequently increased to 40%, 60%, 80%, and 100% of MIP at two-minute intervals.
Participants were instructed to continue breathing against the imposed resistance at each load. The test was terminated if the participant failed to complete three consecutive breaths, could not maintain the required breathing pattern, could not tolerate the load, requested termination, or met a clinical stopping criterion.
The archived respiratory muscle endurance variables included total test duration, number of breaths completed, highest successfully sustained load, and the highest load expressed as a percentage of MIP. These variables will be considered additional candidate predictors.
Static Postural Balance
Static postural balance was assessed using the Biodex Balance System. Testing was performed under four sensory conditions: eyes open on a firm surface, eyes closed on a firm surface, eyes open on a soft surface, and eyes closed on a soft surface.
Each condition was assessed three times for 20 seconds, with a 10-second rest interval between repetitions. Overall Stability Index, Anteroposterior Stability Index, and Mediolateral Stability Index values were recorded. Higher stability index values indicate greater postural sway and poorer postural stability. The stability indices obtained under the different sensory conditions will be treated as primary candidate predictors.
Objectively Measured Physical Activity
Physical activity was assessed objectively using the SenseWear Armband multisensor activity monitor (BodyMedia Inc., Pittsburgh, Pennsylvania, USA). The monitor was positioned over the triceps region of the nondominant upper arm and was worn continuously for three days, except during bathing.
The archived physical activity measurements included daily step count, total energy expenditure, active energy expenditure, physical activity duration, average metabolic equivalent, time spent at different physical activity intensities, sedentary or lying time, and sleep duration. Measurements from valid monitoring days were averaged and processed using SenseWear Software version 7.0. The physical activity variables available in the archived dataset will be evaluated as additional candidate predictors.
Cystic Fibrosis-Specific Quality of Life
Cystic fibrosis-specific health-related quality of life was assessed using the validated Turkish version of the Cystic Fibrosis Questionnaire-Revised. The age-appropriate child, adolescent, or parent-report version was administered in the source study.
The CFQ-R evaluates domains including physical functioning, emotional functioning, social or school functioning, body image, eating problems, treatment burden, health perceptions, weight perceptions, respiratory symptoms, and digestive symptoms, depending on the age-specific questionnaire version. Each domain is transformed to a score ranging from 0 to 100, with higher scores indicating better health-related quality of life. Individual domain scores, rather than an unvalidated overall total score, will be evaluated as additional candidate predictors.
Anthropometric, Nutritional, and Clinical Variables
Archived demographic and anthropometric variables included age, sex, body weight, height, body mass index, weight-for-age Z score, height-for-age Z score, and BMI-for-age Z score. BMI was calculated as body weight in kilograms divided by height in meters squared.
Disease-related clinical characteristics included age at diagnosis, disease duration, pulmonary exacerbations during the preceding year, hospital visits and admissions, medication use, treatment burden, smoking or environmental exposure, and other relevant clinical characteristics available in the archived dataset. These anthropometric, nutritional, demographic, and clinical variables will be evaluated as additional candidate predictors.
Statistical and Machine-Learning Analysis
Separate machine-learning regression models will be developed for the prespecified pulmonary function targets. Peripheral muscle oxygenation and postural balance variables will be treated as the primary candidate predictors. Functional exercise capacity, respiratory muscle strength and endurance, exercise-related oxygen saturation, physical activity, quality of life, anthropometric and nutritional indicators, and disease-related clinical characteristics will be treated as additional candidate predictors.
Categorical variables will be encoded in a form suitable for the selected models. Continuous variables will be examined for implausible values, outliers, distributional characteristics, and strong correlations. The extent and pattern of missing data will be described. Depending on the amount and pattern of missingness, complete-case analysis or an appropriate imputation procedure will be used.
Because of the limited sample size and the relatively large number of candidate predictors, model complexity and the number of variables entering an individual model will be restricted. Parsimonious and regularized regression approaches suitable for small datasets will be prioritized. Alternative low-complexity nonlinear models may be examined only when supported by the available data.
A fixed training-test split will not be used because it would produce very small and potentially unstable subsets. Internal validation will instead be based on cross-validation. All data-dependent preprocessing procedures, including imputation, standardization, variable selection, and hyperparameter tuning, will be performed using the training data within the cross-validation procedure to reduce information leakage and optimistic performance estimates.
Predictive performance will be evaluated using cross-validated R-squared, mean absolute error, and root mean squared error. Higher R-squared values and lower MAE and RMSE values will indicate better predictive performance. The distribution and variability of performance estimates across cross-validation resamples will be examined.
Model-specific variable-importance analyses and, when applicable, variable-selection stability analyses will be used to identify variables that contribute most consistently to prediction. Variable importance will not be interpreted as evidence of a causal relationship. Because the present dataset permits internal validation only, all findings will be interpreted as exploratory and hypothesis-generating, and external validation will be required before any model can be considered for clinical use.
The study population will consist of archived records from children aged 6 to 18 years with cystic fibrosis who were referred by the Division of Pediatric Pulmonology, Gazi University Faculty of Medicine, and evaluated at the Cardiopulmonary Rehabilitation Unit, Department of Physiotherapy and Rehabilitation, Gazi University Faculty of Health Sciences, between April 2021 and September 2022. Only records meeting the prespecified eligibility criteria and containing the variables required for the principal analyses will be included. No new recruitment or participant contact will occur.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.
Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Corticosteroids (steroids)
Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.
Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Archived records of children aged 6 to 18 years with cystic fibrosis who underwent multidimensional clinical and functional assessments at the Gazi University Cardiopulmonary Rehabilitation Unit between April 2021 and September 2022. The present study involves secondary data analysis only; no new intervention or assessment will be performed.
Other: Archived Multidimensional Clinical and Functional Assessment Data
Secondary analysis of archived spirometry, near-infrared spectroscopy, postural balance, exercise capacity, respiratory muscle function, physical activity, quality-of-life, anthropometric, and clinical data. No new assessment or intervention is administered.
Forced Expiratory Volume in 1 Second (FEV1), Absolute Value
FEV1 was measured by spirometry according to ATS/ERS standards and recorded in liters. The highest value from technically acceptable forced expiratory maneuvers was retained. FEV1 will be used as a prespecified pulmonary function prediction target
Time frame: At the single archived cross-sectional assessment (data originally collected between April 2021 and September 2022)
Forced Expiratory Volume in 1 Second (FEV1), Percent Predicted
FEV1 expressed as percent of the age-, sex-, and body-size-appropriate predicted value will be used as a prespecified pulmonary function prediction target. Higher values indicate better pulmonary function.
Time frame: At the single archived cross-sectional assessment (data originally collected between April 2021 and September 2022)
Forced Vital Capacity (FVC), Absolute Value
FVC was measured by spirometry according to ATS/ERS standards and recorded in liters. The highest value from technically acceptable forced expiratory maneuvers was retained. FVC will be used as a prespecified pulmonary function prediction target.
Time frame: At the single archived cross-sectional assessment (data originally collected between April 2021 and September 2022)
Forced Vital Capacity (FVC), Percent Predicted
FVC expressed as percent of the age-, sex-, and body-size-appropriate predicted value will be used as a prespecified pulmonary function prediction target. Higher values indicate better pulmonary function.
Time frame: At the single archived cross-sectional assessment (data originally collected between April 2021 and September 2022)
Peak Expiratory Flow (PEF), Absolute Value
PEF was measured by spirometry according to ATS/ERS standards and recorded in \[ L/min\]. The highest value from technically acceptable forced expiratory maneuvers was retained. PEF will be used as a prespecified pulmonary function prediction target.
Time frame: At the single archived cross-sectional assessment (data originally collected between April 2021 and September 2022)
Peak Expiratory Flow (PEF), Percent Predicted
PEF expressed as percent of the age-, sex-, and body-size-appropriate predicted value will be used as a prespecified pulmonary function prediction target. Higher values indicate better pulmonary function.
Time frame: At the single archived cross-sectional assessment (data originally collected between April 2021 and September 2022)
Cross-Validated Predictive Performance of the FEV1 Models
Separate regression models will predict absolute and percent-predicted FEV1. Cross-validated predictive performance will be summarized using R-squared, mean absolute error, and root mean squared error. Higher R-squared and lower error values indicate better predictive performance.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Cross-Validated Predictive Performance of the FVC Models
Separate regression models will predict absolute and percent-predicted FVC. Cross-validated predictive performance will be summarized using R-squared, mean absolute error, and root mean squared error. Higher R-squared and lower error values indicate better predictive performance.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Cross-Validated Predictive Performance of the PEF Models
Separate regression models will predict absolute and percent-predicted PEF. Cross-validated predictive performance will be summarized using R-squared, mean absolute error, and root mean squared error. Higher R-squared and lower error values indicate better predictive performance.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Mean Cross-validated Normalized Importance Score of Peripheral Muscle Oxygen Saturation
Peripheral muscle oxygen saturation measured using near-infrared spectroscopy will be evaluated as a single prespecified predictor. In each repeated cross-validation run, the model-derived importance score of peripheral muscle oxygen saturation will be normalized relative to all candidate predictors on a scale ranging from 0 to 100. The mean normalized importance score across all cross-validation repetitions will be reported as one value. A score of 0 indicates no predictive contribution, whereas higher scores indicate a greater relative contribution to model prediction. The result will be interpreted as exploratory and predictive rather than causal.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Selection Stability of Peripheral Muscle Oxygen Saturation Across Repeated Cross-validation
Selection stability of peripheral muscle oxygen saturation will be assessed across repeated cross-validation runs. Selection stability will be calculated as the number of cross-validation repetitions in which peripheral muscle oxygen saturation is retained by the prespecified feature-selection procedure, divided by the total number of eligible cross-validation repetitions and multiplied by 100. One selection-stability value will be reported. Values range from 0% to 100%, with higher percentages indicating greater selection stability. The result will be interpreted as exploratory and predictive rather than causal.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Mean Cross-validated Normalized Importance Score of the Postural Balance Predictor Domain
All prespecified postural balance variables will be evaluated collectively as one predictor domain. In each repeated cross-validation run, the model-derived importance scores of the individual postural balance variables will be normalized relative to all candidate predictors on a scale ranging from 0 to 100. The normalized importance scores of the postural balance variables will then be summed to obtain one domain-level postural balance importance score for each repetition. The mean domain-level score across all cross-validation repetitions will be reported as one value. A score of 0 indicates no predictive contribution, whereas higher scores indicate a greater relative contribution of the postural balance predictor domain to model prediction. The result will be interpreted as exploratory and predictive rather than causal.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Selection Stability of the Postural Balance Predictor Domain Across Repeated Cross-validation
Postural balance variables will be evaluated collectively as one predictor domain. In each repeated cross-validation run, the postural balance predictor domain will be considered selected when at least one prespecified postural balance variable is retained by the feature-selection procedure. Selection stability will be calculated as the number of cross-validation repetitions in which at least one postural balance variable is retained, divided by the total number of eligible cross-validation repetitions and multiplied by 100. One domain-level selection-stability value will be reported. Values range from 0% to 100%, with higher percentages indicating greater selection stability. The result will be interpreted as exploratory and predictive rather than causal.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Mean Cross-validated Normalized Importance Score of the Clinical-Functional Predictor Domain
All additional prespecified clinical-functional variables will be evaluated collectively as one predictor domain. In each repeated cross-validation run, the model-derived importance scores of the individual clinical-functional variables will be normalized relative to all candidate predictors on a scale ranging from 0 to 100. The normalized importance scores of the clinical-functional variables will then be summed to obtain one domain-level clinical-functional importance score for each repetition. The mean domain-level score across all cross-validation repetitions will be reported as one value. A score of 0 indicates no predictive contribution, whereas higher scores indicate a greater relative contribution of the clinical-functional predictor domain to model prediction. The result will be interpreted as exploratory and predictive rather than causal.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Selection Stability of the Clinical-Functional Predictor Domain Across Repeated Cross-validation
The additional prespecified clinical-functional variables will be evaluated collectively as one predictor domain. In each repeated cross-validation run, the clinical-functional predictor domain will be considered selected when at least one prespecified clinical-functional variable is retained by the feature-selection procedure. Selection stability will be calculated as the number of cross-validation repetitions in which at least one clinical-functional variable is retained, divided by the total number of eligible cross-validation repetitions and multiplied by 100. One domain-level selection-stability value will be reported. Values range from 0% to 100%, with higher percentages indicating greater selection stability. The result will be interpreted as exploratory and predictive rather than causal.
Time frame: During analysis of the archived dataset, through study completion (up to 12 months)
Plan to share: No
Ran from Jan 2021 to primary completion in Feb 2025, 49 months.
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