Accuracy, Validation, and Usability of an Intelligent Respiratory Pattern Monitoring System in Patients at Risk of Acute Respiratory Failure
Trial ID: NCT07164586
Status: ACTIVE_NOT_RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-08-18
Completion date: 2025-12-22
Sponsor: University of Pernambuco
Collaborators: Fundação de Amparo à Ciência e Tecnologia de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior.
Conditions: Patients at Risk of Acute Respiratory Failure
Interventions: Respiratory Pattern Monitoring; Diaphragmatic Excursion; Respiratory muscle electrical activity; Respiratory Muscle Strength; Pulmonary Function Assessment; Data Acquisition System; Nijmegen Questionnaire; System Usability Scale (SUS); Borg Scale; Patient Identification Questionnaire; Peak Expiratory Flow (PEF) Measurement
Locations: Emergency Care Unit from Engenho Velho; Department of Physical Therapy; Otávio de Freitas Hospital
Countries: Brazil; Brazil; Brazil
Enrollment: 300
Age range: 18 Years - 90 Years
Sex: ALL

Summary:
Introduction: The monitoring of respiratory patterns is crucial in the management of respiratory diseases, but in many cases, it still relies on subjective and visual assessment. The use of healthcare technologies based on artificial intelligence (AI) can, in these contexts, enhance clinical decision-making by providing a more objective and accurate analysis. Given the high prevalence of acute and chronic respiratory diseases, the implementation of a device capable of detecting variables such as flow, volume, and time becomes a priority for more effective diagnosis and therapeutic planning. Objective: Evaluate the accuracy, validity, and usability of an intelligent system for monitoring the respiratory pattern of patients at risk of acute respiratory failure. Methods: This is a prospective cohort study that will be conducted in the emergency departments of the Otávio de Freitas Hospital and Urgent Care Units (UPAs). The sample will consist of volunteers of both sexes, aged 18 years or older, breathing spontaneously, and suspected of having acute respiratory failure. Screening will be performed daily, where sociodemographic information, blood gas data, laboratory results, and additional information will be collected. When indicated, pulmonary function tests, respiratory muscle strength tests, and diaphragmatic ultrasound will be conducted. Respiratory pattern data will be collected using the Respiratory Diagnostic Assistant. Statistical analysis will be performed according to data modeling and treatment, adopting significant differences with p \< 0.05. Expected Results: It is expected that the results of this study will provide quantitative data on the respiratory pattern of volunteers suspected of having acute respiratory failure. This information will be integrated into a database with the aim of enhancing the device's ability to detect changes in respiratory patterns, as well as contributing to the development of artificial intelligence capable of accurately and efficiently identifying these changes.

Eligibility criteria:
Inclusion Criteria:

* Volunteers and patients of both sexes
* Age greater than or equal to 18 years
* Spontaneous breathing
* Patients awaiting care in emergency departments, urgent care units, and emergency services
* Presence of complaints associated with respiratory difficulty
* Patients at risk of acute respiratory failure
* With or without supplemental oxygen therapy
* Ability to remain without oxygen therapy for a minimum period of three minutes

Exclusion Criteria:

* Psychomotor agitation
* Anxiety validated through qualitative assessment
* Poor mask fit and/or presence of air leaks
* Facial fracture or trauma
* Refusal to participate in the study or sign the informed consent form
* Contraindications to performing manovacuometry and spirometry, when appropriate, according to the recommendations of the American Thoracic Society and European Respiratory Society (Graham et al., 2019)

Outcomes:
Respiratory Pattern Assessment using Respiratory Diagnostic Assistant (RDA); System Usability Scale