RESUMEN
BACKGROUND: Non-invasive ventilation (NIV) is a standard of care for hypercapnic chronic respiratory failure (CRF). Obstructive sleep apnea syndrome (OSA) frequently contributes to hypoventilation in CRF patients. CPAP improves hypercapnia in selected COPD and obese patients, like NIV. We aimed to describe the profile of patients switching from NIV to CPAP in a cohort of patients on long-term ventilation and to identify the factors associated with a successful switch. METHODS: In this case-control study, 88 consecutive patients who were candidates for a NIV-CPAP switch were compared with 266 controls among 394 ventilated patients treated at the Dijon University Hospital between 2015 and 2020. They followed a standardized protocol including a poly(somno)graphy recorded after NIV withdrawal for three nights. CPAP trial was performed if severe OSA was confirmed. Patients were checked for recurrent hypoventilation after 1 and 23[14-46] nights under CPAP. RESULTS: Patients were 53% males, median age 65 [56-74] years, and median BMI 34 [25-38.5] kg/m2. Sixty four percent of patients were safely switched and remained on long-term CPAP. In multivariate analysis, the probability of a NIV-CPAP switch was correlated to older age (OR: 1.3 [1.01-1.06]), BMI (OR: 1.7 [1.03-1.12]), CRF etiology (OR for COPD: 20.37 [4.2-98,72], OR for obesity: 7.31 [1.58-33.74]), circumstances of NIV initiation (OR for acute exacerbation: 11.64 [2.03-66.62]), lower pressure support (OR: 0.90 [0.73-0.92]), lower baseline PaCO2 (OR: 0.85 [0.80-0.91]) and lower compliance (OR: 0.76 [0.64-0.90]). Among 72 patients who went home under CPAP, pressure support level was the only factor associated with the outcome of the NIV-CPAP switch, even after adjustment for BMI and age (p=0.01) with a non-linear correlation. Etiology of chronic respiratory failure, age, BMI, baseline PaCO2, circumstances of NIV initiation, time under home NIV or NIV compliance were not predictive of the outcome of the NIV-CPAP switch. CONCLUSIONS: A NIV-CPAP switch is possible in real life conditions in stable obese and COPD patients with underlying OSA.
RESUMEN
The European Health Data Space (EHDS) aims to make the primary use of health data for healthcare provision more continuous, effective, and (cost) efficient. Moreover, it pursues to facilitate the secondary use of health data for purposes such as research, innovation, and policy making. In the context of secondary use, the EHDS legislative proposal (published on 3 May 2022) argues that Member States should develop Health Data Access Bodies (HDABs) whose responsibilities include facilitating the secondary use of health data, issuing data permits, and implementing high levels of accountability and security. In Belgium, the setup in 2023 of a federal Health Data Agency (HDA) that is developing and implementing a policy strategy and framework for the secondary use of health data, aligns well with the responsibilities set out for HDABs. Even though the EHDS aspires the empowerment of citizens, for instance by giving them access to their health data and control over the healthcare professionals who can consult these data, this call for citizen empowerment resonates less loudly regarding secondary use. We think, however, that elaborating and implementing citizen engagement in the domain of secondary use is required to align secondary use with socio-ethical sensitivities, preferences, and values and to provide social legitimacy and ethical solidity to a health data governance system. When implementing the EHDS legislation on a national level, the Belgian HDA and the future HDABs in general might be excellent opportunities to realise this ambition of citizen involvement and empowerment. More specifically, we urge HDABs, firstly, to expand the field of citizen engagement towards the domain of secondary use and, secondly, to respect and facilitate the diversity of citizen engagement. This would offer citizens genuine, continuous and diversified possibilities of involvement and co-creation concerning the development of a solid ethical governance framework for health data.