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Laura González-Ramos 1, Clara Seghers-Carreras 2, Javier Sayas-Catalán 2, 3
1 Servicio de Neumologia, Hospital Universitario Marqués de Valdecilla, Santander, Spain; 2 Hospital Universitario 12 de Octubre, Madrid, Spain; 3 Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
Laura González-Ramos, Clara Seghers-Carreras, Javier Sayas-Catalán
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*Correspondence: Clara Seghers-Carreras, Email not available
Home mechanical ventilation devices incorporate built-in software (BIS) that continuously records adherence, leaks, tidal volume, respiratory rate, and the apnea-hypopnea index (AHI), constituting a fundamental pillar in the follow-up of patients with chronic respiratory failure on non-invasive ventilation. Reliability of leak estimation and AHI varies considerably between manufacturers. The predictive use of BIS for early detection of chronic obstructive pulmonary disease (COPD) exacerbations is promising but requires prospective validation. Telemonitoring integrates BIS with cloud platforms, enabling remote adjustment and early warning, although hospitalisation reduction in severe COPD remains unproven. Artificial intelligence and Big Data represent the most novel frontier. Ideal software should provide full access to ventilator parameters and alarms, simultaneous multi-signal visualization, transcutaneous capnography integration, and manual event correction tools.
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