Patients at Risk of Acute Respiratory FailureNCT07164586
Early Detection of Acute Respiratory Failure Using an Intelligent Respiratory Monitoring System
An observational study of Patients at Risk of Acute Respiratory Failure, run by University of Pernambuco at 3 sites in Brazil.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 90 yearsHealthy volunteers can take part
- Conditions the study is for
- Patients at Risk of Acute Respiratory Failure
- What is being tested?
- Respiratory Pattern Monitoring, Diaphragmatic Excursion and Respiratory muscle electrical activity
- How many people
- 300 participants
- Where
- 3 sitesBrazil
- Study dates
- 18 Aug 2025to 22 Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The population will be composed of healthy participants and patients awaiting care or receiving emergency care in hospital emergency departments and emergency care units affiliated with the study, who are in spontaneous breathing, with or without oxygen therapy, at risk of acute respiratory failure.
Who may be able to join
- 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
Who cannot join
- 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)
Trial locations and contacts
3 sites in 1 country.
Brazil3 sites
Emergency Care Unit from Engenho Velho
Jaboatão dos Guararapes, Pernambuco, 54160-000
Department of Physical Therapy
Recife, Pernambuco, 50740-560
Otávio de Freitas Hospital
Recife, Pernambuco, 50920-640
About this study
Official title: Accuracy, Validation, and Usability of an Intelligent Respiratory Pattern Monitoring System in Patients at Risk of Acute Respiratory Failure
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.
Read the detailed description
Monitoring respiratory patterns is essential in the management of respiratory diseases, yet it often still relies on subjective and visual assessments. Health technologies based on artificial intelligence (AI) can enhance clinical decision-making by providing more objective and accurate analyses. Given the high prevalence of acute and chronic respiratory diseases, implementing devices capable of detecting variables such as flow, volume, and time has become a priority for enabling more effective diagnosis and therapeutic planning. This study aims to evaluate the accuracy, validity, and usability of an intelligent system for monitoring respiratory patterns in patients at risk of acute respiratory failure.
This is a prospective cohort study to be conducted in the emergency departments of Hospital Otávio de Freitas and Urgent Care Units (UPAs), involving volunteers of both sexes, aged 18 years or older, breathing spontaneously, and under suspicion of acute respiratory failure. Daily screening will be performed, collecting sociodemographic, blood gas, laboratory, and additional clinical data. When indicated, pulmonary function tests, respiratory muscle strength assessments, and diaphragmatic ultrasonography will be performed. Respiratory patterns will be recorded using the Respiratory Diagnostic Assistant (RDA), with data collected directly at the patient's bedside, preferably in a seated position or, if not feasible, in the supine position with the head of the bed elevated to 30°. The device will be used with appropriate protective filters and a face mask properly fitted to the patient, preceded by a clinical evaluation that includes peripheral oxygen saturation, respiratory rate, and signs of respiratory distress. The protocol comprises three minutes of spontaneous basal breathing to record time, volume, and flow variables.
Simultaneously with the RDA assessment, respiratory parameters will also be measured using conventional methods-manual or multiparameter monitor respiratory rate, arterial blood gas analysis (when clinically indicated), pulse oximetry, and spirometry-serving as reference standards for diagnostic accuracy analysis. The collected data will be analyzed using correlation coefficients, agreement tests, and ROC curves to assess the sensitivity, specificity, and overall performance of the RDA algorithm. In addition to accuracy, clinical usability of the device will be evaluated using the System Usability Scale (SUS) questionnaire, assessing interface clarity, ease of mask fitting, examination duration, data interpretation, and clinical applicability. The mean SUS score will be used as an indicator of acceptance, with values ≥68 considered satisfactory.
All clinical and technical data will be securely stored on an encrypted server with access restricted to the research team, in compliance with the Declaration of Helsinki, Brazilian regulations, and the General Data Protection Law (LGPD). Participation will be voluntary, requiring the signing of an informed consent form (ICF) by patients or, when applicable, their legal representatives. Data will be stored in Microsoft Excel 2016 (Microsoft®, USA) and analyzed using SPSS Statistics v.22.0. Descriptive variables will be presented as means and standard deviations or as medians and interquartile ranges, depending on their distribution, assessed using the Kolmogorov-Smirnov test.
The analysis will be guided by three main hypotheses: (1) Accuracy - to assess whether the intelligent monitoring system provides superior performance compared to conventional methods in detecting respiratory pattern alterations, using performance metrics such as accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the ROC curve (AUC), with comparisons made using McNemar's test for paired binary data and AUC comparisons using the z-test; (2) Validation - to verify the system's precision and reliability using the Intraclass Correlation Coefficient (ICC) and Bland-Altman analysis, as well as Cohen's Kappa index for categorical variables, with ICC values above 0.75 indicating satisfactory validation; (3) Usability - to assess system acceptance based on SUS scores, complemented by analysis of average training time and operational error rates, using the Student's t-test or Mann-Whitney test depending on data distribution.
The study is expected to generate robust quantitative data on the respiratory patterns of patients with suspected acute respiratory failure, contributing to the refinement of the device, the development of more accurate AI algorithms, and its safe and effective integration into clinical practice.
- Being tested
- Respiratory Pattern Monitoring, Diaphragmatic Excursion, Respiratory muscle electrical activity, Respiratory Muscle Strength, Pulmonary Function Assessment
- Keywords
- Respiratory Mechanics, Respiratory Diseases, Technological Innovation, Intelligent Systems, Acute Respiratory Failure
- Medical subject headings
- Respiratory Tract Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Respiratory Pattern MonitoringDiagnostic test
Respiratory pattern assessment and continuous monitoring will be conducted utilizing the Respiratory Diagnostic Assistant, a device capable of providing comprehensive quantitative evaluation of respiratory variables including frequency, volume, flow rates, inspiratory/expiratory timing parameters, and respiratory entropy analysis, as well as qualitative analysis of respiratory pattern curves for volume and flow dynamics, incorporating entropy measurements for assessment of respiratory pattern complexity and variability.
Diaphragmatic ExcursionDiagnostic test
Diaphragmatic mobility assessment will be conducted using diaphragmatic ultrasonography, a method capable of providing comprehensive quantitative evaluation of diaphragmatic excursion parameters including range of motion, contraction velocity, muscle thickening during inspiration and expiration, as well as qualitative analysis of diaphragm muscle morphology and echogenicity, incorporating craniocaudal displacement measurements for assessment of contractile function and early detection of diaphragmatic dysfunction."
Respiratory muscle electrical activityDiagnostic test
espiratory muscle electrical activity assessment will be conducted using surface electromyography, a method capable of providing comprehensive quantitative evaluation of muscle activation parameters including electrical signal amplitude, firing frequency, muscle recruitment patterns during inspiration and expiration, as well as qualitative analysis of synchronization and coordination between respiratory muscles, incorporating Root Mean Square (RMS) measurements and spectral analysis for assessment of respiratory neuromuscular function and detection of muscle fatigue.
Respiratory Muscle StrengthDiagnostic test
Respiratory muscle strength assessment will be conducted using manovacuometry, a method capable of providing comprehensive quantitative evaluation of respiratory muscle force parameters including maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP), as well as qualitative analysis of contractile capacity and muscle endurance, incorporating peak pressure measurements and performance indices for assessment of global respiratory muscle function and early detection of muscle weakness
Pulmonary Function AssessmentDiagnostic test
Pulmonary function assessment will be conducted using spirometry, a method capable of providing comprehensive quantitative evaluation of respiratory function parameters including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1/FVC ratio, and forced expiratory flow 25-75% (FEF25-75%), as well as qualitative analysis of flow-volume and volume-time curves, incorporating lung capacity and volume measurements for assessment of respiratory mechanics and early detection of obstructive and restrictive ventilatory disorders."
Data Acquisition SystemOther
The PowerLab C is a biomedical data acquisition system used as an auxiliary tool for physiological monitoring. In this study, it will be employed to collect respiratory signals and diaphragmatic excursion data through specific sensors, integrated with LabChart software for data visualization and analysis. The device is not considered an investigational intervention, but a supporting tool for data collection.
Nijmegen QuestionnaireOther
The Nijmegen Questionnaire is a standardized self-report instrument designed to assess symptoms related to dysfunctional breathing and hyperventilation. In this study, it will be administered to evaluate respiratory symptoms and their impact on participants' daily life. The questionnaire is used solely for data collection and is not considered a therapeutic intervention.
System Usability Scale (SUS)Other
The System Usability Scale (SUS) is a standardized questionnaire used to evaluate the usability and user experience of systems and devices. In this study, it will be applied to assess participants' perceptions of the usability of an intelligent respiratory monitoring system. The SUS will be used solely as a data collection tool and does not constitute a therapeutic intervention.
Borg ScaleOther
The Borg Scale is a standardized self-report instrument used to assess perceived exertion and breathlessness during physical activity. In this study, it will be applied to evaluate participants' perception of respiratory effort. The scale is used solely for data collection and is not considered a therapeutic intervention.
Patient Identification QuestionnaireOther
The Patient Identification Questionnaire is a standardized form used to collect sociodemographic and basic clinical information from participants, such as age, sex, and medical history. In this study, it will serve solely for data collection and will not constitute a therapeutic intervention.
Peak Expiratory Flow (PEF) MeasurementDiagnostic test
Peak Expiratory Flow (PEF) measurement is a rapid and noninvasive method to assess the maximum expiratory volume a participant can achieve after a full inhalation. In this study, participants will be seated upright and use a mouthpiece connected to a peak flow meter. After a deep inspiration, they will exhale forcefully, and three measurements will be taken with at least one minute between attempts; the highest value will be recorded. PEF values provide an objective measure of airflow limitation, correlate with asthma symptoms, and will be used solely for data collection, not as a therapeutic intervention
| Study group | Role | What they receive |
|---|---|---|
| Control Group - Healthy Individuals | Individuals without pulmonary impairment as confirmed through comprehensive respiratory assessment including pulmonary function testing (spirometry), respiratory muscle strength evaluation (manometry), and thorough medical history screening for previous respiratory or cardiopulmonary diseases. Participants must demonstrate normal lung function parameters, adequate respiratory muscle strength, and absence of any history of chronic obstructive pulmonary disease, asthma, pneumonia, tuberculosis, or other conditions that could compromise respiratory function Receives: Diagnostic Test: Respiratory Pattern Monitoring; Diagnostic Test: Diaphragmatic Excursion; Diagnostic Test: Respiratory Muscle Strength; Diagnostic Test: Pulmonary Function Assessment; Other: Data Acquisition System; Other: Borg Scale; Other: Patient Identification Questionnaire; Diagnostic Test: Peak Expiratory Flow (PEF) Measurement | |
| Intervention Group - Patients at Risk of Acute Respiratory Failure | This group will consist of adult patients (≥18 years), of both sexes, seen in emergency departments, urgent care units, or walk-in clinics associated with the study, who are in spontaneous breathing, with or without supplemental oxygen, and present with respiratory complaints associated with the risk of acute respiratory failure. Participants will be assessed using a sociodemographic and clinical form, including their documented medical diagnosis. Respiratory pattern monitoring will be conducted using the Respiratory Diagnostic Assistant (RDA) device, diaphragmatic mobility will be evaluated via ultrasonography, and muscle electrical activity will be assessed through surface electromyography. When clinically appropriate, pulmonary function tests and respiratory muscle strength assessments will also be performed, in accordance with the recommendations of the American Thoracic Society and the European Respiratory Society. Receives: Diagnostic Test: Respiratory Pattern Monitoring; Diagnostic Test: Diaphragmatic Excursion; Diagnostic Test: Respiratory muscle electrical activity; Diagnostic Test: Respiratory Muscle Strength; Diagnostic Test: Pulmonary Function Assessment; Other: Data Acquisition System; Other: Nijmegen Questionnaire; Other: System Usability Scale (SUS); Other: Borg Scale; Other: Patient Identification Questionnaire; Diagnostic Test: Peak Expiratory Flow (PEF) Measurement |
What is being measured
The primary outcome is the main question the study is designed to answer.
Respiratory Pattern Assessment using Respiratory Diagnostic Assistant (RDA)
The Respiratory Diagnostic Assistant (RDA) is a portable, non-invasive device providing qualitative and quantitative data on respiratory variables. Participants are assessed seated (or supine 30º if needed) through three stages: baseline respiration (3 min), slow vital capacity, and inspiratory capacity maneuvers (3 repetitions each, 1-min intervals). Measured variables include respiratory rate (breaths per minute), mean inspiratory/expiratory flow (L/s), TI (s), TE (s), tidal volumes (mL), minute volumes (L/min). Data are analyzed qualitatively and quantitatively, with graphical representation. Respiratory patterns may be compared with conventional monitoring (pulse oximetry, respiratory rate, or arterial blood gas).
Measured: For an average period of four months, until the conclusion of the studies
System Usability Scale
The System Usability Scale (SUS) is a 10-item standardized questionnaire designed to assess usability and user experience of systems. Participants respond on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree), generating a total score ranging from 0 to 100. In this study, the SUS will evaluate participants' perceptions of the intelligent respiratory monitoring system, including ease of use, learnability, and satisfaction. The instrument is used solely for data collection and does not constitute a therapeutic intervention."
Measured: For an average period of four months, until the conclusion of the studies
Secondary outcomes (7)
Peak Expiratory Flow (PEF) Data
Peak Expiratory Flow (PEF) data will be collected to explore correlations with asthma symptoms. Measurements will be performed according to standardized procedures, and the highest value of three attempts will be recorded. These data are used solely for analysis and do not constitute a therapeutic intervention
Measured: For an average period of four months, until the conclusion of the studies
Diaphragmatic Excursion Assessment
Diaphragmatic excursion will be assessed using ultrasound to measure the amplitude of diaphragm movement during respiratory cycles, providing information on respiratory function and diaphragm mobility. Measurements will be performed in a standardized seated position, following consistent protocols to ensure accuracy and reproducibility. Data will be analyzed quantitatively and qualitatively and used solely for research purposes; this does not constitute a therapeutic intervention.
Measured: For an average period of four months, until the conclusion of the studies
Self-reported Dysfunctional Breathing and Hyperventilation Symptoms (Nijmegen Questionnaire)
The Nijmegen Questionnaire is a 16-item self-report instrument assessing symptoms associated with dysfunctional breathing and hyperventilation. Each item is scored 0-4, producing a total score from 0 to 64, with higher scores indicating greater symptom burden. In this study, it will be used to evaluate participants' respiratory symptoms, including dyspnea, chest tightness, and air hunger. The questionnaire is used solely for data collection and does not constitute a therapeutic intervention
Measured: For an average period of four months, until the conclusion of the studies
Sociodemographic and Clinical Baseline Data Collection (Patient Identification Questionnaire)
The Patient Identification Questionnaire is a standardized form used to collect sociodemographic and basic clinical information, including age, sex, medical history, and relevant comorbidities. It provides baseline characterization of participants and will serve solely for data collection, not constituting a therapeutic intervention
Measured: Completed once per participant at baseline to collect sociodemographic and basic clinical data
Pulmonary Function Assessment (Spirometry)
Spirometry will be performed according to ATS/ERS standards to assess pulmonary function, measuring FVC (L), FEV1 (L), FEV1/FVC ratio (%), and PEF (L/s). Values will be expressed as absolute and percent predicted. Spirometry will provide quantitative evaluation of ventilatory function and is used solely for data collection, not as a therapeutic intervention
Measured: For an average period of four months, until the conclusion of the studies
Respiratory Muscle Strength Assessment (Manovacuometry)
Manovacuometry will assess respiratory muscle strength by measuring maximal inspiratory (MIP) (cmH₂O) and expiratory pressures (MEP) (cmH₂O) using a manometer. Values will be recorded in cmH2O. This test provides quantitative evaluation of respiratory muscle performance and is used solely for data collection, not as a therapeutic intervention.
Measured: For an average period of four months, until the conclusion of the studies
Respiratory Muscle Activity and Coordination (Surface Electromyography, sEMG)
Surface electromyography (sEMG) will continuously record the electrical activity of respiratory muscles, including the diaphragm, intercostals, and accessory muscles, during baseline breathing and standardized respiratory maneuvers. Recorded signals will be processed to extract amplitude (mV), frequency (Hz), and activation patterns, providing an objective assessment of muscle recruitment, coordination, and respiratory effort. The sEMG will be used solely for data collection and does not constitute a therapeutic intervention.
Measured: For an average period of four months, until the conclusion of the studies
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Sep 2025
- Study start18 Aug 2025
- Primary completion28 Nov 2025 (estimated)
- Study completion22 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Patients at Risk of Acute Respiratory FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Pernambuco
- Sponsor type
- University, hospital or other
- 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.
- Responsible party
- Principal investigator, Shirley Lima Campos, University of Pernambuco
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07164586
- Sponsor's protocol ID
- 7.741.786
- Status last verified
- Sep 2025
- First submitted
- 21 Aug 2025
- Last updated
- 10 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Individual participant data will be pseudonymized and shared only after publication of the study results through REDCap repositories, with DOI assignment and a Creative Commons license (CC BY-NC-ND). Demographic, clinical, respiratory, and processed datasets supporting the published analyses will be made available, excluding any information that could directly or indirectly identify participants. Access may be open or granted upon justified request, depending on the sensitivity of the data, and any transfers will be governed by formal data use agreements. Data will be curated, version-controlled, and preserved in institutional and secure scientific repositories for at least five years after publication, in strict compliance with the Brazilian General Data Protection Law (LGPD), institutional policies, and all applicable ethical approvals.
Study at a glance
From the registry record, last updated by the sponsor on 10 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Accuracy, Validation, and Usability of an Intelligent Respiratory Pattern Monitoring System in Patients at Risk of Acute Respiratory Failure
- ClinicalTrials.gov ID
- NCT07164586
- Acronym / sponsor ID
- 7.741.786
- Keywords
- Respiratory Mechanics, Respiratory Diseases, Technological Innovation, Intelligent Systems, Acute Respiratory Failure
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- University of PernambucoUniversity, hospital or other
- 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.
- Study start
- 18 Aug 2025 (actual)
- Primary completion
- 28 Nov 2025 (estimated)
- Study completion
- 22 Dec 2025 (estimated)
- First posted
- 10 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Monitoring respiratory patterns is essential in the management of respiratory diseases, yet it often still relies on subjective and visual assessments. Health technologies based on artificial intelligence (AI) can enhance clinical decision-making by providing more objective and accurate analyses. Given the high prevalence of acute and chronic respiratory diseases, implementing devices capable of detecting variables such as flow, volume, and time has become a priority for enabling more effective diagnosis and therapeutic planning. This study aims to evaluate the accuracy, validity, and usability of an intelligent system for monitoring respiratory patterns in patients at risk of acute respiratory failure.
This is a prospective cohort study to be conducted in the emergency departments of Hospital Otávio de Freitas and Urgent Care Units (UPAs), involving volunteers of both sexes, aged 18 years or older, breathing spontaneously, and under suspicion of acute respiratory failure. Daily screening will be performed, collecting sociodemographic, blood gas, laboratory, and additional clinical data. When indicated, pulmonary function tests, respiratory muscle strength assessments, and diaphragmatic ultrasonography will be performed. Respiratory patterns will be recorded using the Respiratory Diagnostic Assistant (RDA), with data collected directly at the patient's bedside, preferably in a seated position or, if not feasible, in the supine position with the head of the bed elevated to 30°. The device will be used with appropriate protective filters and a face mask properly fitted to the patient, preceded by a clinical evaluation that includes peripheral oxygen saturation, respiratory rate, and signs of respiratory distress. The protocol comprises three minutes of spontaneous basal breathing to record time, volume, and flow variables.
Simultaneously with the RDA assessment, respiratory parameters will also be measured using conventional methods-manual or multiparameter monitor respiratory rate, arterial blood gas analysis (when clinically indicated), pulse oximetry, and spirometry-serving as reference standards for diagnostic accuracy analysis. The collected data will be analyzed using correlation coefficients, agreement tests, and ROC curves to assess the sensitivity, specificity, and overall performance of the RDA algorithm. In addition to accuracy, clinical usability of the device will be evaluated using the System Usability Scale (SUS) questionnaire, assessing interface clarity, ease of mask fitting, examination duration, data interpretation, and clinical applicability. The mean SUS score will be used as an indicator of acceptance, with values ≥68 considered satisfactory.
All clinical and technical data will be securely stored on an encrypted server with access restricted to the research team, in compliance with the Declaration of Helsinki, Brazilian regulations, and the General Data Protection Law (LGPD). Participation will be voluntary, requiring the signing of an informed consent form (ICF) by patients or, when applicable, their legal representatives. Data will be stored in Microsoft Excel 2016 (Microsoft®, USA) and analyzed using SPSS Statistics v.22.0. Descriptive variables will be presented as means and standard deviations or as medians and interquartile ranges, depending on their distribution, assessed using the Kolmogorov-Smirnov test.
The analysis will be guided by three main hypotheses: (1) Accuracy - to assess whether the intelligent monitoring system provides superior performance compared to conventional methods in detecting respiratory pattern alterations, using performance metrics such as accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the ROC curve (AUC), with comparisons made using McNemar's test for paired binary data and AUC comparisons using the z-test; (2) Validation - to verify the system's precision and reliability using the Intraclass Correlation Coefficient (ICC) and Bland-Altman analysis, as well as Cohen's Kappa index for categorical variables, with ICC values above 0.75 indicating satisfactory validation; (3) Usability - to assess system acceptance based on SUS scores, complemented by analysis of average training time and operational error rates, using the Student's t-test or Mann-Whitney test depending on data distribution.
The study is expected to generate robust quantitative data on the respiratory patterns of patients with suspected acute respiratory failure, contributing to the refinement of the device, the development of more accurate AI algorithms, and its safe and effective integration into clinical practice.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Control Group - Healthy Individuals | – | Diagnostic Test: Respiratory Pattern Monitoring, Diagnostic Test: Diaphragmatic Excursion, Diagnostic Test: Respiratory Muscle Strength, Diagnostic Test: Pulmonary Function Assessment, Other: Data Acquisition System, Other: Borg Scale, Other: Patient Identification Questionnaire, Diagnostic Test: Peak Expiratory Flow (PEF) MeasurementIndividuals without pulmonary impairment as confirmed through comprehensive respiratory assessment including pulmonary function testing (spirometry), respiratory muscle strength evaluation (manometry), and thorough medical history screening for previous respiratory or cardiopulmonary diseases. Participants must demonstrate normal lung function parameters, adequate respiratory muscle strength, and absence of any history of chronic obstructive pulmonary disease, asthma, pneumonia, tuberculosis, or other conditions that could compromise respiratory function |
| Intervention Group - Patients at Risk of Acute Respiratory Failure | – | Diagnostic Test: Respiratory Pattern Monitoring, Diagnostic Test: Diaphragmatic Excursion, Diagnostic Test: Respiratory muscle electrical activity, Diagnostic Test: Respiratory Muscle Strength, Diagnostic Test: Pulmonary Function Assessment, Other: Data Acquisition System, Other: Nijmegen Questionnaire, Other: System Usability Scale (SUS), Other: Borg Scale, Other: Patient Identification Questionnaire, Diagnostic Test: Peak Expiratory Flow (PEF) MeasurementThis group will consist of adult patients (≥18 years), of both sexes, seen in emergency departments, urgent care units, or walk-in clinics associated with the study, who are in spontaneous breathing, with or without supplemental oxygen, and present with respiratory complaints associated with the risk of acute respiratory failure. Participants will be assessed using a sociodemographic and clinical form, including their documented medical diagnosis. Respiratory pattern monitoring will be conducted using the Respiratory Diagnostic Assistant (RDA) device, diaphragmatic mobility will be evaluated via ultrasonography, and muscle electrical activity will be assessed through surface electromyography. When clinically appropriate, pulmonary function tests and respiratory muscle strength assessments will also be performed, in accordance with the recommendations of the American Thoracic Society and the European Respiratory Society. |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The population will be composed of healthy participants and patients awaiting care or receiving emergency care in hospital emergency departments and emergency care units affiliated with the study, who are in spontaneous breathing, with or without oxygen therapy, at risk of acute respiratory failure.
Key inclusion criteria (8 listed)
- 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
Key exclusion criteria (6 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Respiratory Pattern MonitoringRespiratory pattern assessment and continuous monitoring will be conducted utilizing the Respiratory Diagnostic Assistant, a device capable of providing comprehensive quantitative evaluation of respiratory variables including frequency, volume, flow rates, inspiratory/expiratory timing parameters, and respiratory entropy analysis, as well as qualitative analysis of respiratory pattern curves for volume and flow dynamics, incorporating entropy measurements for assessment of respiratory pattern complexity and variability. | Diagnostic test | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Diaphragmatic ExcursionDiaphragmatic mobility assessment will be conducted using diaphragmatic ultrasonography, a method capable of providing comprehensive quantitative evaluation of diaphragmatic excursion parameters including range of motion, contraction velocity, muscle thickening during inspiration and expiration, as well as qualitative analysis of diaphragm muscle morphology and echogenicity, incorporating craniocaudal displacement measurements for assessment of contractile function and early detection of diaphragmatic dysfunction." | Diagnostic test | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Respiratory muscle electrical activityespiratory muscle electrical activity assessment will be conducted using surface electromyography, a method capable of providing comprehensive quantitative evaluation of muscle activation parameters including electrical signal amplitude, firing frequency, muscle recruitment patterns during inspiration and expiration, as well as qualitative analysis of synchronization and coordination between respiratory muscles, incorporating Root Mean Square (RMS) measurements and spectral analysis for assessment of respiratory neuromuscular function and detection of muscle fatigue. | Diagnostic test | Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Respiratory Muscle StrengthRespiratory muscle strength assessment will be conducted using manovacuometry, a method capable of providing comprehensive quantitative evaluation of respiratory muscle force parameters including maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP), as well as qualitative analysis of contractile capacity and muscle endurance, incorporating peak pressure measurements and performance indices for assessment of global respiratory muscle function and early detection of muscle weakness | Diagnostic test | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Pulmonary Function AssessmentPulmonary function assessment will be conducted using spirometry, a method capable of providing comprehensive quantitative evaluation of respiratory function parameters including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1/FVC ratio, and forced expiratory flow 25-75% (FEF25-75%), as well as qualitative analysis of flow-volume and volume-time curves, incorporating lung capacity and volume measurements for assessment of respiratory mechanics and early detection of obstructive and restrictive ventilatory disorders." | Diagnostic test | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Data Acquisition SystemThe PowerLab C is a biomedical data acquisition system used as an auxiliary tool for physiological monitoring. In this study, it will be employed to collect respiratory signals and diaphragmatic excursion data through specific sensors, integrated with LabChart software for data visualization and analysis. The device is not considered an investigational intervention, but a supporting tool for data collection. | Other | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Nijmegen QuestionnaireThe Nijmegen Questionnaire is a standardized self-report instrument designed to assess symptoms related to dysfunctional breathing and hyperventilation. In this study, it will be administered to evaluate respiratory symptoms and their impact on participants' daily life. The questionnaire is used solely for data collection and is not considered a therapeutic intervention. | Other | Intervention Group - Patients at Risk of Acute Respiratory Failure |
| System Usability Scale (SUS)The System Usability Scale (SUS) is a standardized questionnaire used to evaluate the usability and user experience of systems and devices. In this study, it will be applied to assess participants' perceptions of the usability of an intelligent respiratory monitoring system. The SUS will be used solely as a data collection tool and does not constitute a therapeutic intervention. | Other | Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Borg ScaleThe Borg Scale is a standardized self-report instrument used to assess perceived exertion and breathlessness during physical activity. In this study, it will be applied to evaluate participants' perception of respiratory effort. The scale is used solely for data collection and is not considered a therapeutic intervention. | Other | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Patient Identification QuestionnaireThe Patient Identification Questionnaire is a standardized form used to collect sociodemographic and basic clinical information from participants, such as age, sex, and medical history. In this study, it will serve solely for data collection and will not constitute a therapeutic intervention. | Other | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
| Peak Expiratory Flow (PEF) MeasurementPeak Expiratory Flow (PEF) measurement is a rapid and noninvasive method to assess the maximum expiratory volume a participant can achieve after a full inhalation. In this study, participants will be seated upright and use a mouthpiece connected to a peak flow meter. After a deep inspiration, they will exhale forcefully, and three measurements will be taken with at least one minute between attempts; the highest value will be recorded. PEF values provide an objective measure of airflow limitation, correlate with asthma symptoms, and will be used solely for data collection, not as a therapeutic intervention | Diagnostic test | Control Group - Healthy Individuals, Intervention Group - Patients at Risk of Acute Respiratory Failure |
Primary outcome
Respiratory Pattern Assessment using Respiratory Diagnostic Assistant (RDA)
Time frame: For an average period of four months, until the conclusion of the studies
The Respiratory Diagnostic Assistant (RDA) is a portable, non-invasive device providing qualitative and quantitative data on respiratory variables. Participants are assessed seated (or supine 30º if needed) through three stages: baseline respiration (3 min), slow vital capacity, and inspiratory capacity maneuvers (3 repetitions each, 1-min intervals). Measured variables include respiratory rate (breaths per minute), mean inspiratory/expiratory flow (L/s), TI (s), TE (s), tidal volumes (mL), minute volumes (L/min). Data are analyzed qualitatively and quantitatively, with graphical representation. Respiratory patterns may be compared with conventional monitoring (pulse oximetry, respiratory rate, or arterial blood gas).
System Usability Scale
Time frame: For an average period of four months, until the conclusion of the studies
The System Usability Scale (SUS) is a 10-item standardized questionnaire designed to assess usability and user experience of systems. Participants respond on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree), generating a total score ranging from 0 to 100. In this study, the SUS will evaluate participants' perceptions of the intelligent respiratory monitoring system, including ease of use, learnability, and satisfaction. The instrument is used solely for data collection and does not constitute a therapeutic intervention."
7 secondary outcomes
Peak Expiratory Flow (PEF) Data
Time frame: For an average period of four months, until the conclusion of the studies
Diaphragmatic Excursion Assessment
Time frame: For an average period of four months, until the conclusion of the studies
Self-reported Dysfunctional Breathing and Hyperventilation Symptoms (Nijmegen Questionnaire)
Time frame: For an average period of four months, until the conclusion of the studies
Sociodemographic and Clinical Baseline Data Collection (Patient Identification Questionnaire)
Time frame: Completed once per participant at baseline to collect sociodemographic and basic clinical data
Pulmonary Function Assessment (Spirometry)
Time frame: For an average period of four months, until the conclusion of the studies
Respiratory Muscle Strength Assessment (Manovacuometry)
Time frame: For an average period of four months, until the conclusion of the studies
Respiratory Muscle Activity and Coordination (Surface Electromyography, sEMG)
Time frame: For an average period of four months, until the conclusion of the studies
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Sep 2025.
- Development and validation of a respiratory pattern analysis system for Post-COVID-19 patientsLink provided by the sponsor.
- Diagnosis and Epidemiology of Acute Respiratory FailureLink provided by the sponsor.
- Biomarker-Based Classification of Patients With Acute Respiratory Failure Into Inflammatory Subphenotypes: A Single-Center Exploratory StudyLink provided by the sponsor.
- Sonographic evaluation of the diaphragm in critically ill patients. Technique and clinical applicationsLink provided by the sponsor.
- Leveraging intrinsic non-sinusoidal patterns to infer search behavior to predict exposure to respiratory stressorsLink provided by the sponsor.
- Individual participant dataSharing planned: Yes. Individual participant data will be pseudonymized and shared only after publication of the study results through REDCap repositories, with DOI assignment and a Creative Commons license (CC BY-NC-ND). Demographic, clinical, respiratory, and processed datasets supporting the published analyses will be made available, excluding any information that could directly or indirectly identify participants. Access may be open or granted upon justified request, depending on the sensitivity of the data, and any transfers will be governed by formal data use agreements. Data will be curated, version-controlled, and preserved in institutional and secure scientific repositories for at least five years after publication, in strict compliance with the Brazilian General Data Protection Law (LGPD), institutional policies, and all applicable ethical approvals.
Related trials for Patients at Risk of Acute Respiratory Failure
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Patients at Risk of Acute Respiratory Failure, run by University of Pernambuco at 3 sites in Brazil.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 10 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Brazil. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Respiratory Pattern Assessment using Respiratory Diagnostic Assistant (RDA) (time frame: For an average period of four months, until the conclusion of the studies). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Sep 2025.