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| ID | Type | Description | Link |
|---|---|---|---|
| 2017-A02831-52 | Other Identifier | ID RCB |
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| Name | Class |
|---|---|
| AGIR Ã Dom | OTHER |
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Health care renunciation is a factor that can alter patients' health status and increase the costs of its support.
To date, there is no national data on the renunciation of care. This study will initially characterize the different forms of health care renunciation in patients with chronic respiratory diseases, treated with continuous positive airway pressure (CPAP) or non-invasive ventilation (NIV) , and analyze it impact on treatment compliance and health processes.
The follow-up of these patients during 5 years will define renunciation trajectories (transition from the state of "renouncing" to "non-renouncing" and vice versa) and their impact on treatment compliance.
The investigators hypothesize that a patient becoming renounced on a given treatment also decreases his treatment compliance (CPAP or NIV ).
The impact of the renunciation trajectory on the patient's follow-up in terms of hospitalizations and deaths will also be studied.
A questionnaire of health care renunciation will be administered to the patient at Day 0 and each year during 5 years, to determine whether or not he has given up one or more care in the last 12 months.
The compliance to the CPAP or NIV will be extracted from the database of the Health care provider (AGIR Ã dom).
The primary outcome is to determine the impact of health care renunciation on treatment compliance and overall health care processes.
The analysis of the primary outcome (compliance) will be performed using a simple or generalized linear model (based on its observed distribution). Variables most associated with compliance will be introduced into a multivariate model, including healthcare renunciation variables.
For the secondary objective (identifying the determinants of cessation of health care) a first approach based on unsupervised learning will make it possible to classify patients according to homogeneous profiles on the basis of the different information collected.
A classical multivariate analysis using a hierarchical logistic regression model will quantify the weight of the different determinants in the renunciation of care. Finally, an exploratory approach based on structural equation models based on latent variables will be implemented to establish the direct and indirect relationships of the different qualitative determinants collected in the questionnaires on caregiving.
Regarding the longitudinal approach, this will be the subject of several analysis steps. Firstly, on an annual basis, a descriptive analysis will be carried out to investigate the determinants of the cessation of care according to the status of patients (renouncing or not renouncing) the previous year. Regarding the five-year follow-up, mixed models will be used to identify different trajectories of patients with regard to the renunciation of care from the initial follow-up and to study their impact on the prognosis at 5 years in terms of deaths and number hospitalizations
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| Measure | Description | Time Frame |
|---|---|---|
| Treatment compliance to CPAP or NIV | Extracted from the database of AGIR Ã dom | Baseline and 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Age (years) | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care processes in patients with chronic respiratory diseases. | Baseline and 1 year |
| Gender (male/female) |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with chronic respiratory diseases treated for at least 12 months by CPAP, NIV therapy and monitored by AGIR Ã dom.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| EFCR HP2 Laboratory | Grenoble | Auvergne-Rhône-Alpes | 38000 | France | ||
| Bruno LEPAULE |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27568340 | Background | Senaratna CV, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, Hamilton GS, Dharmage SC. Prevalence of obstructive sleep apnea in the general population: A systematic review. Sleep Med Rev. 2017 Aug;34:70-81. doi: 10.1016/j.smrv.2016.07.002. Epub 2016 Jul 18. | |
| 27980399 | Background | Deniz S, Sengul A, Aydemir Y, Celdir Emre J, Ozhan MH. Clinical factors and comorbidities affecting the cost of hospital-treated COPD. Int J Chron Obstruct Pulmon Dis. 2016 Dec 2;11:3023-3030. doi: 10.2147/COPD.S120637. eCollection 2016. |
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| ID | Term |
|---|---|
| D020181 | Sleep Apnea, Obstructive |
| D012131 | Respiratory Insufficiency |
| ID | Term |
|---|---|
| D012891 | Sleep Apnea Syndromes |
| D001049 | Apnea |
| D012120 | Respiration Disorders |
| D012140 | Respiratory Tract Diseases |
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This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care |
| Baseline |
| Type of housing (urban , peri-urban or non-urban) | This variable will be defined via the patient's address and used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| Type of pathology (OSAS, Respiratory failure) | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| Number of hospitalizations per year | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| BMI (Kg/m^2) | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| Epworth Sleepiness Scale (ESS) | This scale range from 0 to 24 . ESS from 0 to 5 is interpreted as a lower normal daytime Sleepiness ESS from 6 to 10 is interpreted as a higher Normal Daytime Sleepiness ESS from 11 to 12 is interpreted as a mild Excessive Daytime Sleepiness ESS from 13 to 15 is interpreted as a moderate Excessive Daytime Sleepiness ESS from 16 to 24 is interpreted as a severe Excessive Daytime Sleepiness This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| AHI (event/hour) | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care . The interpretation of the score : Score from 0 to 6: Good sleep; score 7 to 8: average; score> 9: Risk of pathological somnolence. | Baseline and 1 year |
| Socio-Professional Category | The modalities of the variables are :
| Baseline and 1 year |
| Family situation The modalities of this variables are : - Alone - Alone with dependent children - Couples without dependent children - Couples with dependent children | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| Type of health insurance | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| Presence or absence and nature of complementary health insurance | This variable will be used to characterize the different forms of health care renunciation and analyze its impact on treatment compliance and overall care | Baseline and 1 year |
| Échirolles |
| 38130 |
| France |
| Centre Santé Sommeil | Grenoble | 38000 | France |
| 24912564 | Background | Borel JC, Pepin JL, Pison C, Vesin A, Gonzalez-Bermejo J, Court-Fortune I, Timsit JF. Long-term adherence with non-invasive ventilation improves prognosis in obese COPD patients. Respirology. 2014 Aug;19(6):857-65. doi: 10.1111/resp.12327. Epub 2014 Jun 9. |
| 34485235 | Derived | Daabek N, Tamisier R, Foote A, Revil H, Joyeux-Jaure M, Pepin JL, Bailly S, Borel JC. Impact of Healthcare Non-Take-Up on Adherence to Long-Term Positive Airway Pressure Therapy. Front Public Health. 2021 Aug 17;9:713313. doi: 10.3389/fpubh.2021.713313. eCollection 2021. |
| D020919 |
| Sleep Disorders, Intrinsic |
| D020920 | Dyssomnias |
| D012893 | Sleep Wake Disorders |
| D009422 | Nervous System Diseases |