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AimTo determine the association between total sleep time (TST) spent in increased respiratory effort (RE) and the prevalence of type 2 diabetes in a large cohort of individuals with suspected obstructive sleep apnoea (OSA) referred for in-laboratory polysomnography (PSG).Materials and methodsWe conducted a retrospective cross-sectional study using the clinical data of 1128 patients. Non-invasive measurements of RE were derived from the sleep mandibular jaw movements (MJM) bio-signal. An explainable machine-learning model was built to predict prevalent type 2 diabetes from clinical data, standard PSG indices, and MJM-derived parameters (including the proportion of TST spent with increased respiratory effort [REMOV [%TST]).ResultsOriginal data were randomly assigned to training (n = 853) and validation (n = 275) subsets. The classification model based on 18 input features including REMOV showed good performance for predicting prevalent type 2 diabetes (sensitivity = 0.81, specificity = 0.89). Post hoc interpretation using the Shapley additive explanation method found that a high value of REMOV was the most important risk factor associated with type 2 diabetes after traditional clinical variables (age, sex, body mass index), and ahead of standard PSG metrics including the apnoea-hypopnea and oxygen desaturation indices.ConclusionsThese findings show for the first time that the proportion of sleep time spent in increased RE (assessed through MJM measurements) is an important predictor of the association with type 2 diabetes in individuals with OSA.

Abstract Introduction The diaphragm thickening fraction (DTF) may be a valuable tool for estimating respiratory effort in non-invasive ventilation. The primary aim of this physiological study is the investigation of the correlation of DTF with oesophageal pressure swings (ΔPoes). A secondary aim is to assess the discriminatory capacity of the index tests for different exercise loads. Methods Healthy volunteers underwent spontaneous breathing and non-invasive ventilation with a sequence of different respirator settings. The first sequence was carried out at rest. The same sequence was repeated twice, with additional ergometry of 25 and 50 Watts, respectively. DTF and ΔPoes were measured during each ventilation configuration. Results 23 individuals agreed to participate. DTF was moderately correlated with ΔPoes (repeated measures correlation ρ = 0.410, p

Introduction: The diaphragm thickening fraction (DTF) may be a valuable tool for estimating respiratory effort in non-invasive ventilation. The primary aim of this physiological study is the investigation of the correlation of DTF with oesophageal pressure swings (ΔPoes). A secondary aim is to assess the discriminatory capacity of the index tests for different exercise loads. Methods: Healthy volunteers underwent spontaneous breathing and non-invasive ventilation with a sequence of different respirator settings. The first sequence was carried out at rest. The same sequence was repeated twice, with additional ergometry of 25 and 50 Watts, respectively. DTF and ΔPoes were measured during each ventilation configuration. Results: 23 individuals agreed to participate. DTF was moderately correlated with ΔPoes (repeated measures correlation ρ = 0.410, p < 0.001). Both ΔPoes and DTF increased consistently with exercise loading in every ventilation configuration, however ΔPoes showed greater discriminatory capacity. Conclusion: DTF was moderately correlated with ΔPoes and could discriminate reasonably between exercise loads in a small cohort of non-invasively ventilated healthy subjects. While it may not accurately reflect the absolute respiratory effort, DTF might help titrating individual non-invasive respiratory support. Further investigations are needed to test this hypothesis. Trial Registration: This study was not prospectively registered. [ABSTRACT FROM AUTHOR]

Background: Respiratory effort is considered important in the context of the diagnosis of obstructive sleep apnoea (OSA), as well as other sleep disorders. However, current monitoring techniques can be obtrusive and interfere with a patient's natural sleep. This study examines the reliability of an unobtrusive tracheal sound-based approach to monitor respiratory effort in the context of OSA, using manually marked respiratory inductance plethysmography (RIP) signals as a gold standard for validation. Methods: In total, 150 patients were trained on the use of type III cardiorespiratory polygraphy, which they took to use at home, alongside a neck-worn AcuPebble system. The respiratory effort channels obtained from the tracheal sound recordings were compared to the effort measured by the RIP bands during automatic and manual marking experiments. A total of 133 central apnoeas, 218 obstructive apnoeas, 263 obstructive hypopneas, and 270 normal breathing randomly selected segments were shuffled and blindly marked by a Registered Polysomnographic Technologist (RPSGT) in both types of channels. The RIP signals had previously also been independently marked by another expert clinician in the context of diagnosing those patients, and without access to the effort channel of AcuPebble. The classification achieved with the acoustically obtained effort was assessed with statistical metrics and the average amplitude distributions per respiratory event type for each of the different channels were also studied to assess the overlap between event types. Results: The performance of the acoustic effort channel was evaluated for the events where both scorers were in agreement in the marking of the gold standard reference channel, showing an average sensitivity of 90.5%, a specificity of 98.6%, and an accuracy of 96.8% against the reference standard with blind expert marking. In addition, a comparison using the Embla Remlogic 4.0 automatic software of the reference standard for classification, as opposed to the expert marking, showed that the acoustic channels outperformed the RIP channels (acoustic sensitivity: 71.9%; acoustic specificity: 97.2%; RIP sensitivity: 70.1%; RIP specificity: 76.1%). The amplitude trends across different event types also showed that the acoustic channels exhibited a better differentiation between the amplitude distributions of different event types, which can help when doing manual interpretation. Conclusions: The results prove that the acoustically obtained effort channel extracted using AcuPebble is an accurate, reliable, and more patient-friendly alternative to RIP in the context of OSA. [ABSTRACT FROM AUTHOR]

Abstract Background Patients with COVID-19 undergoing pressure support ventilation (PSV) with extracorporeal membrane oxygenation (ECMO) commonly had high respiratory drive, which could cause self-inflicted lung injury. The aim of this study was to evaluate the influence of different levels of partial pressure of carbon dioxide(PaCO2) on respiratory effort in COVID-19 patients undergoing PSV with ECMO. Methods ECMO gas flow was downregulated from baseline (respiratory rate

Introduction: The most widespread treatment for obstructive sleep apnoea and obesity hypoventilation syndrome is continuous positive airway pressure (CPAP). The addition of inspiratory support is a potential alternative. This is a physiological study to determine the effect of CPAP and inspiratory support pressure on respiratory effort measured by diaphragm thickening fraction (DTF) in healthy volunteers. Methods: DTF was measured in spontaneously breathing, healthy volunteers during 4 phases: (I) without connection to a ventilator, (II) on a ventilator without any applied pressures, (III) with a CPAP of 5 cmH2O, and (IV) with an additional inspiratory support pressure of 5 cmH2O. Results: Twenty-nine individuals agreed to participate. DTF was similar during the first two phases (32 ± 13% and 35 ± 22%). A considerable increase in DTF to 51 ± 21% was noted in phase III. The introduction of inspiratory support pressure during phase IV led to a reduction in DTF back to 36 ± 23% (p < 0.001). Tidal volume and minute ventilation were both slightly higher in phase IV compared to phase III. Conclusion: CPAP without inspiratory support pressure increases respiratory effort measured by DTF in healthy subjects. Further research is required to investigate this phenomenon in a clinical setting. [ABSTRACT FROM AUTHOR]

Background: Patients with COVID-19 undergoing pressure support ventilation (PSV) with extracorporeal membrane oxygenation (ECMO) commonly had high respiratory drive, which could cause self-inflicted lung injury. The aim of this study was to evaluate the influence of different levels of partial pressure of carbon dioxide(PaCO2) on respiratory effort in COVID-19 patients undergoing PSV with ECMO. Methods: ECMO gas flow was downregulated from baseline (respiratory rate < 25 bpm, peak airway pressure < 25 cm H2O, tidal volume < 6 mL/kg, PaCO2 < 40 mmHg) until PaCO2 increased by 5 − 10 mmHg. The pressure muscle index (PMI) and airway pressure swing during occlusion (ΔPOCC) were used to monitor respiratory effort, and they were measured before and after enforcement of the regulations. Results: Ten patients with COVID-19 who had undergone ECMO were enrolled in this prospective study. When the PaCO2 increased from 36 (36 − 37) to 42 (41–43) mmHg (p = 0.0020), there was a significant increase in ΔPOCC [from 5.6 (4.7–8.0) to 11.1 (8.5–13.1) cm H2O, p = 0.0020] and PMI [from 3.0 ± 1.4 to 6.5 ± 2.1 cm H2O, p < 0.0001]. Meanwhile, increased inspiratory effort determined by elevated PaCO2 levels led to enhancement of tidal volume from 4.1 ± 1.2 mL/kg to 5.3 ± 1.5 mL/kg (p = 0.0003) and respiratory rate from 13 ± 2 to 15 ± 2 bpm (p = 0.0266). In addition, the increase in PaCO2 was linearly correlated with changes in ΔPOCC and PMI (R2 = 0.7293, p = 0.0003 and R2 = 0.4105, p = 0.0460, respectively). Conclusions: In patients with COVID-19 undergoing PSV with ECMO, an increase of PaCO2 could increase the inspiratory effort. [ABSTRACT FROM AUTHOR]

Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea–hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. This comprehensive paper reviews devices, emphasizing distinctions among representative apnea devices and technologies for home detection of OSA. The collected articles are analyzed to present a clear discussion. Each article is evaluated according to diagnostic elements, the implemented automation level, and the derived level of evidence and quality rating. The findings indicate that the critical variables for monitoring sleep behavior include oxygen saturation (oximetry), body position, respiratory effort, and respiratory flow. Also, the prevalent trend is the development of level IV devices, measuring one or two signals and supported by prediction software. Noteworthy methods showcasing optimal results involve neural networks, deep learning, and regression modeling, achieving an accuracy of approximately 99%. [ABSTRACT FROM AUTHOR]

IntroductionAlthough neonatal breathing patterns vary after perinatal asphyxia, whether they change during therapeutic hypothermia (TH) remains unclear. We characterized breathing patterns in infants during TH for hypoxic-ischemic encephalopathy (HIE) and normothermia after rewarming.MethodsIn seventeen spontaneously breathing infants receiving TH for HIE and in three who did not receive TH, we analyzed respiratory flow and esophageal pressure tracings for respiratory timing variables, pulmonary mechanics and respiratory effort. Breaths were classified as braked (inspiratory:expiratory ratio ≥1.5) and unbraked (

Abstract Background in COVID-19 acute respiratory failure, the effects of CPAP and FiO2 on respiratory effort and lung stress are unclear. We hypothesize that, in the compliant lungs of early Sars-CoV-2 pneumonia, the application of positive pressure through Helmet-CPAP may not decrease respiratory effort, and rather worsen lung stress and oxygenation when compared to higher FiO2 delivered via oxygen masks. Methods In this single-center (S.Luigi Gonzaga University-Hospital, Turin, Italy), randomized, crossover study, we included patients receiving Helmet-CPAP for early (

PurposeDifferentiation between obstructive and central apneas and hypopneas requires quantitative measurement of respiratory effort (RE) using esophageal pressure (PES), which is rarely implemented. This study investigated whether the sleep mandibular movements (MM) signal recorded with a tri-axial gyroscopic chin sensor (Sunrise, Namur, Belgium) is a reliable surrogate of PES in patients with suspected obstructive sleep apnea (OSA).Patients and methodsIn-laboratory polysomnography (PSG) with PES and concurrent MM monitoring was performed. PSGs were scored manually using AASM 2012 rules. Data blocks (n=8042) were randomly sampled during normal breathing (NB), obstructive or central apnea/hypopnea (OA/OH/CA/CH), respiratory effort-related arousal (RERA), and mixed apnea (MxA). Analyses were evaluation of the similarity and linear correlation between PES and MM using the longest common subsequence (LCSS) algorithm and Pearson's coefficient; description of signal amplitudes; estimation of the marginal effect for crossing from NB to a respiratory disturbance for a given change in MM signal using a mixed linear-regression.ResultsParticipants (n=38) had mild to severe OSA (median AH index 28.9/h; median arousal index 23.2/h). MM showed a high level of synchronization with concurrent PES signals. Distribution of MM amplitude differed significantly between event types: median (95% confidence interval) values of 0.60 (0.16-2.43) for CA, 0.83 (0.23-4.71) for CH, 1.93 (0.46-12.43) for MxA, 3.23 (0.72-18.09) for OH, and 6.42 (0.88-26.81) for OA. Mixed regression indicated that crossing from NB to central events would decrease MM signal amplitude by -1.23 (CH) and -2.04 (CA) units, while obstructive events would increase MM amplitude by +3.27 (OH) and +6.79 (OA) units (all p

Background: in COVID-19 acute respiratory failure, the effects of CPAP and FiO2 on respiratory effort and lung stress are unclear. We hypothesize that, in the compliant lungs of early Sars-CoV-2 pneumonia, the application of positive pressure through Helmet-CPAP may not decrease respiratory effort, and rather worsen lung stress and oxygenation when compared to higher FiO2 delivered via oxygen masks. Methods: In this single-center (S.Luigi Gonzaga University-Hospital, Turin, Italy), randomized, crossover study, we included patients receiving Helmet-CPAP for early (< 48 h) COVID-19 pneumonia without additional cardiac or respiratory disease. Healthy subjects were included as controls. Participants were equipped with an esophageal catheter, a non-invasive cardiac output monitor, and an arterial catheter. The protocol consisted of a random sequence of non-rebreather mask (NRB), Helmet-CPAP (with variable positive pressure and FiO2) and Venturi mask (FiO2 0.5), each delivered for 20 min. Study outcomes were changes in respiratory effort (esophageal swing), total lung stress (dynamic + static transpulmonary pressure), gas-exchange and hemodynamics. Results: We enrolled 28 COVID-19 patients and 7 healthy controls. In all patients, respiratory effort increased from NRB to Helmet-CPAP (5.0 ± 3.7 vs 8.3 ± 3.9 cmH2O, p < 0.01). However, Helmet's pressure decreased by a comparable amount during inspiration (− 3.1 ± 1.0 cmH2O, p = 0.16), therefore dynamic stress remained stable (p = 0.97). Changes in static and total lung stress from NRB to Helmet-CPAP were overall not significant (p = 0.07 and p = 0.09, respectively), but showed high interpatient variability, ranging from − 4.5 to + 6.1 cmH2O, and from − 5.8 to + 5.7 cmH2O, respectively. All findings were confirmed in healthy subjects, except for an increase in dynamic stress (p < 0.01). PaO2 decreased from NRB to Helmet-CPAP with FiO2 0.5 (107 ± 55 vs 86 ± 30 mmHg, p < 0.01), irrespective of positive pressure levels (p = 0.64). Conversely, with Helmet's FiO2 0.9, PaO2 increased (p < 0.01), but oxygen delivery remained stable (p = 0.48) as cardiac output decreased (p = 0.02). When PaO2 fell below 60 mmHg with VM, respiratory effort increased proportionally (p < 0.01, r = 0.81). Conclusions: In early COVID-19 pneumonia, Helmet-CPAP increases respiratory effort without altering dynamic stress, while the effects upon static and total stress are variable, requiring individual assessment. Oxygen masks with higher FiO2 provide better oxygenation with lower respiratory effort. Trial registration Retrospectively registered (13-May-2021): clinicaltrials.gov (NCT04885517), https://clinicaltrials.gov/ct2/show/NCT04885517. [ABSTRACT FROM AUTHOR]

Purpose: Laparoscopic intraperitoneal instillation of local anaesthetic in bariatric surgery proven to reduce postoperative pain. Limited data are available regarding the use of instillation ropivacaine and its impact on the recovery of respiratory effort. This study aims to evaluate the efficacy of laparoscopic intraperitoneal instillation of ropivacaine in reducing acute postoperative pain and enhancing the recovery of respiratory effort in laparoscopic sleeve gastrectomy. Materials and Methods: This double-blinded RCT enrolled 110 patients who underwent laparoscopic sleeve gastrectomy at Hospital Canselor Tuanku Muhriz UKM from November 2020 to May 2021. Any patients with previous abdominal surgery, chronic kidney disease, or liver disease were excluded. The patients were randomised into two groups: (i) the IPLA group which received ropivacaine intraperitoneal instillation at the dissected left crus and (ii) the placebo group (sterile water instillation). Perioperative analgesia was standardised. The first 24-h postoperative pain was assessed using a VAS. The respiratory effort was assessed using incentive spirometry simultaneously. Results: Total of 110 patients were recruited. The VAS score was lower with an enhanced recovery of respiratory effort in the local anaesthetic group compared to the placebo group (P < 0.05) within the first 24 h postoperatively. In addition, the placebo group required additional postoperative analgesia (P < 0.05). No side effects were reported with the use of intraperitoneal instillation of ropivacaine. Conclusion: The use of intraperitoneal instillation of ropivacaine in laparoscopic sleeve gastrectomy is recommended as it is safe, effectively reduces acute postoperative pain, and enhances the recovery of respiratory effort postoperatively. [ABSTRACT FROM AUTHOR]

Background: Sleep apnea is a prevalent sleep-disordered breathing (SDB) condition that affects a large population worldwide. Research has demonstrated the potential of using electrocardiographic (ECG) signals (heart rate and ECG-derived respiration, EDR) to detect SDB. However, EDR may be a suboptimal replacement for respiration signals. Methods: We evaluated a previously described ECG-based deep learning algorithm in an independent dataset including 198 patients and compared performance for SDB event detection using thoracic respiratory effort versus EDR. We also evaluated the algorithm in terms of apnea-hypopnea index (AHI) estimation performance, and SDB severity classification based on the estimated AHI. Results: Using respiratory effort instead of EDR, we achieved an improved performance in SDB event detection (F1 score = 0.708), AHI estimation (Spearman's correlation = 0.922), and SDB severity classification (Cohen's kappa of 0.62 was obtained based on AHI). Conclusion: Respiratory effort is superior to EDR to assess SDB. Using respiratory effort and ECG, the previously described algorithm achieves good performance in a new dataset from an independent laboratory confirming its adequacy for this task. [ABSTRACT FROM AUTHOR]

Patient self-inflicted lung injury (P-SILI) is a life-threatening condition arising from excessive respiratory effort and work of breathing in patients with lung injury. The pathophysiology of P-SILI involves factors related to the underlying lung pathology and vigorous respiratory effort. P-SILI might develop both during spontaneous breathing and mechanical ventilation with preserved spontaneous respiratory activity. In spontaneously breathing patients, clinical signs of increased work of breathing and scales developed for early detection of potentially harmful effort might help clinicians prevent unnecessary intubation, while, on the contrary, identifying patients who would benefit from early intubation. In mechanically ventilated patients, several simple non-invasive methods for assessing the inspiratory effort exerted by the respiratory muscles were correlated with respiratory muscle pressure. In patients with signs of injurious respiratory effort, therapy aimed to minimize this problem has been demonstrated to prevent aggravation of lung injury and, therefore, improve the outcome of such patients. In this narrative review, we accumulated the current information on pathophysiology and early detection of vigorous respiratory effort. In addition, we proposed a simple algorithm for prevention and treatment of P-SILI that is easily applicable in clinical practice. [ABSTRACT FROM AUTHOR]

Objective. The accurate detection of respiratory effort during polysomnography is a critical element in the diagnosis of sleep-disordered breathing conditions such as sleep apnea. Unfortunately, the sensors currently used to estimate respiratory effort are either indirect and ignore upper airway dynamics or are too obtrusive for patients. One promising alternative is the suprasternal notch pressure (SSP) sensor: a small element placed on the skin in the notch above the sternum within an airtight capsule that detects pressure swings in the trachea. Besides providing information on respiratory effort, the sensor is sensitive to small cardiac oscillations caused by pressure perturbations in the carotid arteries or the trachea. While current clinical research considers these as redundant noise, they may contain physiologically relevant information. Approach. We propose a method to separate the signal generated by cardiac activity from the one caused by breathing activity. Using only information available from the SSP sensor, we estimate the heart rate and track its variations, then use a set of tuned filters to process the original signal in the frequency domain and reconstruct the cardiac signal. We also include an overview of the technical and physiological factors that may affect the quality of heart rate estimation. The output of our method is then used as a reference to remove the cardiac signal from the original SSP pressure signal, to also optimize the assessment of respiratory activity. We provide a qualitative comparison against methods based on filters with fixed frequency cutoffs. Main results. In comparison with electrocardiography (ECG)-derived heart rate, we achieve an agreement error of 0.06 ± 5.09 bpm, with minimal bias drift across the measurement range, and only 6.36% of the estimates larger than 10 bpm. Significance. Together with qualitative improvements in the characterization of respiratory effort, this opens the development of novel portable clinical devices for the detection and assessment of sleep disordered breathing. [ABSTRACT FROM AUTHOR]

The optimal management of respiratory failure related to SARS-CoV-2 infection is a subject of heated debates in the scientific community. The lack of solid scientific evidence, combined with the unclear pathophysiology of COVID-19 pneumonia, means that the modalities and duration of ventilator assistance often rely on subjective assessments of the doctor on call. In establishing a suitable respiratory support, it is essential to evaluate the degree of activation of the respiratory muscles as objectively as possible. Among the various methods of evaluating the inspiratory effort, measurement of the phasic variations of esophageal pressure (intended as a surrogate of pleural pressure) represents the gold standard. Esophageal pressure measurement can be implemented in a minimally invasive way in every patient category, does not require sophisticated devices, and provides objective data about respiratory muscle activity. In patients with ongoing COVID-19-related respiratory failure, esophageal pressure monitoring allows i) optimizing the type and settings of noninvasive ventilation, ii) providing objective support in the delicate choice of establishing invasive ventilation in cases in which such an indication is unclear, and iii) monitoring the clinical evolution of COVID-19 pneumonia to allow early interception of cases with progressive worsening of lung function. Esophageal manometry provides a complete and objective assessment of respiratory muscle activity. Its clinical use in patients with respiratory failure in the course of COVID-19 would allow clarifying some pathophysiological aspects of the disease and customizing ventilatory support according to the needs of specific patients.

We present contactless technology measuring abnormal ventilation and compare it with polysomnography (PSG). A 13-years old girl with Pitt-Hopkins syndrome presented hyperpnoea periods with apneic spells. The PSG was conducted simultaneously with Emfit movement sensor (Emfit, Finland) and video camera with depth sensor (NEL, Finland). The respiratory efforts from PSG, Emfit sensor, and NEL were compared. In addition, we measured daytime breathing with tracheal microphone (PneaVox,France). The aim was to deepen the knowledge of daytime hyperpnoea periods and ensure that no upper airway obstruction was present during sleep. The signs of upper airway obstruction were not detected despite of minor sleep time. Monitoring respiratory effort with PSG is demanding in all patient groups. The used unobtrusive methods were capable to reveal breathing frequency and hyperpnoea periods. Every day diagnostics need technology like this for monitoring vital signs at hospital wards and at home from subjects with disabilities and co-operation difficulties. [ABSTRACT FROM AUTHOR]

Information about respiratory mechanics such as resistance, elastance, and muscular pressure is important to mitigate ventilator‐induced lung injury. Particularly during pressure support ventilation, the available options to quantify breathing effort and calculate respiratory system mechanics are often invasive or complex. We herein propose a robust and flexible estimation of respiratory effort better than current methods. We developed a method for non‐invasively estimating breathing effort using only flow and pressure signals. Mixed‐integer quadratic programming (MIQP) was employed, and the binary variables were the switching moments of the respiratory effort waveform. Mathematical constraints, based on ventilation physiology, were set for some variables to restrict feasible solutions. Simulated and patient data were used to verify our method, and the results were compared to an established estimation methodology. Our algorithm successfully estimated the respiratory effort, resistance, and elastance of the respiratory system, resulting in more robust performance and faster solver times than a previously proposed algorithm that used quadratic programming (QP) techniques. In a numerical simulation benchmark, the worst‐case errors for resistance and elastance were 25% and 23% for QP versus <0.1% and <0.1% for MIQP, whose solver times were 4.7 s and 0.5 s, respectively. This approach can estimate several breathing effort profiles and identify the respiratory system's mechanical properties in invasively ventilated critically ill patients. [ABSTRACT FROM AUTHOR]

Jean-Louis Pepin,1,* Nhat-Nam Le-Dong,2,* Valérie Cuthbert,3 Nathalie Coumans,3 Renaud Tamisier,1 Atul Malhotra,4 Jean-Benoit Martinot3,5 1HP2 Laboratory, Inserm U1300, University Grenoble Alpes, Grenoble, France; 2Sunrise, Namur, Belgium; 3Sleep Laboratory, CHU Université Catholique de Louvain (UCL) Namur Site Sainte-Elisabeth, Namur, Belgium; 4University of California San Diego, La Jolla, CA, USA; 5Institute of Experimental and Clinical Research, UCL Bruxelles Woluwe, Brussels, Belgium*These authors contributed equally to this workCorrespondence: Jean-Benoit Martinot, Centre du Sommeil et de la Vigilance, CHU-UCL Namur Site Ste Elisabeth, 15 Place Louise Godin, Namur, 5000, Belgium, Tel +32 495502608, Fax +32 81570754, Email martinot.j@respisom.bePurpose: Differentiation between obstructive and central apneas and hypopneas requires quantitative measurement of respiratory effort (RE) using esophageal pressure (PES), which is rarely implemented. This study investigated whether the sleep mandibular movements (MM) signal recorded with a tri-axial gyroscopic chin sensor (Sunrise, Namur, Belgium) is a reliable surrogate of PES in patients with suspected obstructive sleep apnea (OSA).Patients and Methods: In-laboratory polysomnography (PSG) with PES and concurrent MM monitoring was performed. PSGs were scored manually using AASM 2012 rules. Data blocks (n=8042) were randomly sampled during normal breathing (NB), obstructive or central apnea/hypopnea (OA/OH/CA/CH), respiratory effort-related arousal (RERA), and mixed apnea (MxA). Analyses were evaluation of the similarity and linear correlation between PES and MM using the longest common subsequence (LCSS) algorithm and Pearson’s coefficient; description of signal amplitudes; estimation of the marginal effect for crossing from NB to a respiratory disturbance for a given change in MM signal using a mixed linear-regression.Results: Participants (n=38) had mild to severe OSA (median AH index 28.9/h; median arousal index 23.2/h). MM showed a high level of synchronization with concurrent PES signals. Distribution of MM amplitude differed significantly between event types: median (95% confidence interval) values of 0.60 (0.16– 2.43) for CA, 0.83 (0.23– 4.71) for CH, 1.93 (0.46– 12.43) for MxA, 3.23 (0.72– 18.09) for OH, and 6.42 (0.88– 26.81) for OA. Mixed regression indicated that crossing from NB to central events would decrease MM signal amplitude by – 1.23 (CH) and – 2.04 (CA) units, while obstructive events would increase MM amplitude by +3.27 (OH) and +6.79 (OA) units (all p< 10− 6).Conclusion: In OSA patients, MM signals facilitated the measurement of specific levels of RE associated with obstructive, central or mixed apneas and/or hypopneas. A high degree of similarity was observed with the PES gold-standard signal.Keywords: obstructive sleep apnea, respiratory effort, mandibular movements, esophageal pressure

Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea–hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. This comprehensive paper reviews devices, emphasizing distinctions among representative apnea devices and technologies for home detection of OSA. The collected articles are analyzed to present a clear discussion. Each article is evaluated according to diagnostic elements, the implemented automation level, and the derived level of evidence and quality rating. The findings indicate that the critical variables for monitoring sleep behavior include oxygen saturation (oximetry), body position, respiratory effort, and respiratory flow. Also, the prevalent trend is the development of level IV devices, measuring one or two signals and supported by prediction software. Noteworthy methods showcasing optimal results involve neural networks, deep learning, and regression modeling, achieving an accuracy of approximately 99%.

Abstract Background Whether respiratory efforts and their timing can be reliably detected during pressure support ventilation using standard ventilator waveforms is unclear. This would give the opportunity to assess and improve patient–ventilator interaction without the need of special equipment. Methods In 16 patients under invasive pressure support ventilation, flow and pressure waveforms were obtained from proximal sensors and analyzed by three trained physicians and one resident to assess patient’s spontaneous activity. A systematic method (the waveform method) based on explicit rules was adopted. Esophageal pressure tracings were analyzed independently and used as reference. Breaths were classified as assisted or auto-triggered, double-triggered or ineffective. For assisted breaths, trigger delay, early and late cycling (minor asynchronies) were diagnosed. The percentage of breaths with major asynchronies (asynchrony index) and total asynchrony time were computed. Results Out of 4426 analyzed breaths, 94.1% (70.4–99.4) were assisted, 0.0% (0.0–0.2) auto-triggered and 5.8% (0.4–29.6) ineffective. Asynchrony index was 5.9% (0.6–29.6). Total asynchrony time represented 22.4% (16.3–30.1) of recording time and was mainly due to minor asynchronies. Applying the waveform method resulted in an inter-operator agreement of 0.99 (0.98–0.99); 99.5% of efforts were detected on waveforms and agreement with the reference in detecting major asynchronies was 0.99 (0.98–0.99). Timing of respiratory efforts was accurately detected on waveforms: AUC for trigger delay, cycling delay and early cycling was 0.865 (0.853–0.876), 0.903 (0.892–0.914) and 0.983 (0.970–0.991), respectively. Conclusions Ventilator waveforms can be used alone to reliably assess patient’s spontaneous activity and patient–ventilator interaction provided that a systematic method is adopted.

Background: Whether respiratory efforts and their timing can be reliably detected during pressure support ventilation using standard ventilator waveforms is unclear. This would give the opportunity to assess and improve patient–ventilator interaction without the need of special equipment. Methods: In 16 patients under invasive pressure support ventilation, flow and pressure waveforms were obtained from proximal sensors and analyzed by three trained physicians and one resident to assess patient's spontaneous activity. A systematic method (the waveform method) based on explicit rules was adopted. Esophageal pressure tracings were analyzed independently and used as reference. Breaths were classified as assisted or auto-triggered, double-triggered or ineffective. For assisted breaths, trigger delay, early and late cycling (minor asynchronies) were diagnosed. The percentage of breaths with major asynchronies (asynchrony index) and total asynchrony time were computed. Results: Out of 4426 analyzed breaths, 94.1% (70.4–99.4) were assisted, 0.0% (0.0–0.2) auto-triggered and 5.8% (0.4–29.6) ineffective. Asynchrony index was 5.9% (0.6–29.6). Total asynchrony time represented 22.4% (16.3–30.1) of recording time and was mainly due to minor asynchronies. Applying the waveform method resulted in an inter-operator agreement of 0.99 (0.98–0.99); 99.5% of efforts were detected on waveforms and agreement with the reference in detecting major asynchronies was 0.99 (0.98–0.99). Timing of respiratory efforts was accurately detected on waveforms: AUC for trigger delay, cycling delay and early cycling was 0.865 (0.853–0.876), 0.903 (0.892–0.914) and 0.983 (0.970–0.991), respectively. Conclusions: Ventilator waveforms can be used alone to reliably assess patient's spontaneous activity and patient–ventilator interaction provided that a systematic method is adopted. [ABSTRACT FROM AUTHOR]

Background: The diaphragm is crucial for ventilator weaning, but its specific impact on weaning indicators needs further clarification. This study investigated the variability in weaning outcomes across different diaphragm function populations and the value of respiratory drive and inspiratory effort in weaning., Methods: This observational case-control study enrolled patients on mechanical ventilation for more than 48 h and completed a 30-minute spontaneous breathing trial (SBT) with pressure-support ventilation for the first time. After the SBT, airway pressure at 100 ms during occlusion (P 0.1 ), inspiratory effort, and diaphragmatic ultrasound were evaluated to predict weaning outcomes. Weaning failure was defined as re-intubation within 48 h of weaning, the need for therapeutic non-invasive ventilation, or death., Results: 68 patients with a mean age of 63.21 ± 15.15 years were included. In patients with diaphragm thickness (DT) ≥ 2 mm, P 0.1 (P=0.002), pressure-muscle index (PMI) (P=0.012), and occluded expiratory airway pressure swing (ΔP occ ) (P=0.030) were significantly higher in those who failed weaning. Conversely, for patients with DT<2 mm, PMI (P=0.003) and ΔP occ (P=0.002) were lower in the weaning failure group. Additionally, within the DT≥2 mm group, P 0.1 demonstrated a higher area under the curve (AUC) for weaning prediction (0.889 vs. 0.739) compared to those with DT<2 mm., Conclusions: PMI and ΔP occ are predictive of weaning outcomes in patients with diaphragm thickness ≥ 2 mm, where the assessment value of P 0.1 is notably higher. Diaphragm function significantly influences the accuracy of weaning predictions based on respiratory drive and inspiratory effort., Implications for Clinical Practice: Our findings indicate that the effectiveness of respiratory drive and inspiratory effort in predicting successful weaning from mechanical ventilation may vary across different patient populations. Diaphragm function plays a crucial role in weaning assessments, particularly when using P 0.1 , the pressure-muscle index (PMI), and occluded expiratory airway pressure swing (ΔP occ )., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objective: To assess the changes in lung aeration and respiratory effort generated by two different spontaneous breathing trial (SBT): T-piece (T-T) vs pressure support ventilation (PSV)., Design: Prospective, interventionist and randomized study., Setting: Intensive Care Unit (ICU) of Hospital del Mar., Participants: Forty-three ventilated patients for at least 24 h and considered eligible for an SBT were included in the study between October 2017 and March 2020., Interventions: 30-min SBT with T-piece (T-T group, 20 patients) or 8-cmH 2 O PSV and 5-cmH 2 O positive end expiratory pressure (PSV group, 23 patients)., Main Variables of Interest: Demographics, clinical data, physiological variables, lung aeration evaluated with electrical impedance tomography (EIT) and lung ultrasound (LUS), and respiratory effort using diaphragmatic ultrasonography (DU) were collected at different timepoints: basal (BSL), end of SBT (EoSBT) and one hour after extubation (OTE)., Results: There were a loss of aeration measured with EIT and LUS in the different study timepoints, without statistical differences from BSL to OTE, between T-T and PSV [LUS: 3 (1, 5.5) AU vs 2 (1, 3) AU; p = 0.088; EELI: -2516.41 (-5871.88, 1090.46) AU vs -1992.4 (-3458.76, -5.07) AU; p = 0.918]. Percentage of variation between BSL and OTE, was greater when LUS was used compared to EIT (68.1% vs 4.9%, p ≤ 0.001). Diaphragmatic excursion trend to decrease coinciding with a loss of aeration during extubation., Conclusion: T-T and PSV as different SBT strategies in ventilated patients do not show differences in aeration loss, nor estimated respiratory effort or tidal volume measured by EIT, LUS and DU., (Copyright © 2023 Elsevier España, S.L.U. and SEMICYUC. All rights reserved.)

Background: Sleep apnea is a prevalent sleep-disordered breathing (SDB) condition that affects a large population worldwide. Research has demonstrated the potential of using electrocardiographic (ECG) signals (heart rate and ECG-derived respiration, EDR) to detect SDB. However, EDR may be a suboptimal replacement for respiration signals. Methods: We evaluated a previously described ECG-based deep learning algorithm in an independent dataset including 198 patients and compared performance for SDB event detection using thoracic respiratory effort versus EDR. We also evaluated the algorithm in terms of apnea-hypopnea index (AHI) estimation performance, and SDB severity classification based on the estimated AHI. Results: Using respiratory effort instead of EDR, we achieved an improved performance in SDB event detection (F1 score = 0.708), AHI estimation (Spearman’s correlation = 0.922), and SDB severity classification (Cohen’s kappa of 0.62 was obtained based on AHI). Conclusion: Respiratory effort is superior to EDR to assess SDB. Using respiratory effort and ECG, the previously described algorithm achieves good performance in a new dataset from an independent laboratory confirming its adequacy for this task.

Objective: Automatic detection and analysis of respiratory events in sleep using a single respiratoryeffort belt and deep learning. Methods: Using 9,656 polysomnography recordings from the Massachusetts General Hospital (MGH), we trained a neural network (WaveNet) to detect obstructive apnea, central apnea, hypopnea and respiratory-effort related arousals. Performance evaluation included event-based analysis and apnea-hypopnea index (AHI) stratification. The model was further evaluated on a public dataset, the Sleep-Heart-Health-Study-1, containing 8,455 polysomnographic recordings. Results: For binary apnea event detection in the MGH dataset, the neural network obtained a sensitivity of 68%, a specificity of 98%, a precision of 65%, a F1-score of 67%, and an area under the curve for the receiver operating characteristics curve and precision-recall curve of 0.93 and 0.71, respectively. AHI prediction resulted in a mean difference of 0.41 $\pm$ 7.8 and a r2 of 0.90. For the multiclass task, we obtained varying performances: 84% of all labeled central apneas were correctly classified, whereas this metric was 51% for obstructive apneas, 40% for respiratory effort related arousals and 23% for hypopneas. Conclusion: Our fully automated method can detect respiratory events and assess the AHI accurately. Differentiation of event types is more difficult and may reflect in part the complexity of human respiratory output and some degree of arbitrariness in the criteria used during manual annotation. Significance: The current gold standard of diagnosing sleep-disordered breathing, using polysomnography and manual analysis, is time-consuming, expensive, and only applicable in dedicated clinical environments. Automated analysis using a single effort belt signal overcomes these limitations. [ABSTRACT FROM AUTHOR]

Bronchiolitis due to respiratory syncytial virus (RSV) or non-RSV agents is a health-menacing lower respiratory tract (LRT) disease of infants. Whereas RSV causes more severe disease than other viral agents may, genus-dominant fecal microbiota profiles have been identified in US hospitalized infants with bronchiolitis. We investigated the fecal microbiota composition of infants admitted to an Italian hospital with acute RSV (25/37 [67.6%]; group I) or non-RSV (12/37 [32.4%]; group II) bronchiolitis, and the relationship of fecal microbiota characteristics with the clinical characteristics of infants. Group I and group II infants differed significantly (24/25 [96.0%] versus 5/12 [41.7%]; P = 0.001) regarding 90% oxygen saturation (SpO2), which is an increased respiratory effort hallmark. Accordingly, impaired feeding in infants from group I was significantly more frequent than in infants from group II (19/25 [76.0%] versus 4/12 [33.3%]; P = 0.04). Conversely, the median (IQR) length of stay was not significantly different between the two groups (seven [3–14] for group I versus five [5–10] for group II; P = 0.11). The 16S ribosomal RNA V3–V4 region amplification of infants' fecal samples resulted in 299 annotated amplicon sequence variants. Based on alpha- and beta-diversity microbiota downstream analyses, group I and group II infants had similar bacterial communities in their samples. Additionally, comparing infants having <90% SpO2 (n = 29) with infants having ≥90% SpO2 (n = 8) showed that well-known dominant genera (Bacteroides , Bifidobacterium , Escherichia / Shigella , and Enterobacter / Veillonella) were differently, but not significantly (P = 0.44, P = 0.71, P = 0.98, and P = 0.41, respectively) abundant between the two subgroups. Overall, we showed that, regardless of RSV or non-RSV bronchiolitis etiology, no fecal microbiota-composing bacteria could be associated with the severity of acute bronchiolitis in infants. Larger and longitudinally conducted studies will be necessary to confirm these findings. [ABSTRACT FROM AUTHOR]

Abstract Background High respiratory drive in mechanically ventilated patients with spontaneous breathing effort may cause excessive lung stress and strain and muscle loading. Therefore, it is important to have a reliable estimate of respiratory effort to guarantee lung and diaphragm protective mechanical ventilation. Recently, a novel non-invasive method was found to detect excessive dynamic transpulmonary driving pressure (∆P L) and respiratory muscle pressure (P mus) with reasonable accuracy. During the Coronavirus disease 2019 (COVID-19) pandemic, it was impossible to obtain the gold standard for respiratory effort, esophageal manometry, in every patient. Therefore, we investigated whether this novel non-invasive method could also be applied in COVID-19 patients. Methods ∆P L and P mus were derived from esophageal manometry in COVID-19 patients. In addition, ∆P L and P mus were computed from the occlusion pressure (∆P occ) obtained during an expiratory occlusion maneuver. Measured and computed ∆P L and P mus were compared and discriminative performance for excessive ∆P L and P mus was assessed. The relation between occlusion pressure and respiratory effort was also assessed. Results Thirteen patients were included. Patients had a low dynamic lung compliance [24 (20–31) mL/cmH2O], high ∆P L (25 ± 6 cmH2O) and high P mus (16 ± 7 cmH2O). Low agreement was found between measured and computed ∆P L and P mus. Excessive ∆P L > 20 cmH2O and P mus > 15 cmH2O were accurately detected (area under the receiver operating curve (AUROC) 1.00 [95% confidence interval (CI), 1.00–1.00], sensitivity 100% (95% CI, 72–100%) and specificity 100% (95% CI, 16–100%) and AUROC 0.98 (95% CI, 0.90–1.00), sensitivity 100% (95% CI, 54–100%) and specificity 86% (95% CI, 42–100%), respectively). Respiratory effort calculated per minute was highly correlated with ∆P occ (for esophageal pressure time product per minute (PTPes/min) r 2 = 0.73; P = 0.0002 and work of breathing (WOB) r 2 = 0.85; P

Bronchiolitis due to respiratory syncytial virus (RSV) or non-RSV agents is a health-menacing lower respiratory tract (LRT) disease of infants. Whereas RSV causes more severe disease than other viral agents may, genus-dominant fecal microbiota profiles have been identified in US hospitalized infants with bronchiolitis. We investigated the fecal microbiota composition of infants admitted to an Italian hospital with acute RSV (25/37 [67.6%]; group I) or non-RSV (12/37 [32.4%]; group II) bronchiolitis, and the relationship of fecal microbiota characteristics with the clinical characteristics of infants. Group I and group II infants differed significantly (24/25 [96.0%] versus 5/12 [41.7%]; P = 0.001) regarding 90% oxygen saturation (SpO2), which is an increased respiratory effort hallmark. Accordingly, impaired feeding in infants from group I was significantly more frequent than in infants from group II (19/25 [76.0%] versus 4/12 [33.3%]; P = 0.04). Conversely, the median (IQR) length of stay was not significantly different between the two groups (seven [3–14] for group I versus five [5–10] for group II; P = 0.11). The 16S ribosomal RNA V3–V4 region amplification of infants’ fecal samples resulted in 299 annotated amplicon sequence variants. Based on alpha- and beta-diversity microbiota downstream analyses, group I and group II infants had similar bacterial communities in their samples. Additionally, comparing infants having

In dieser retrospektiven Querschnittsstudie wurde der Zusammenhang zwischen der Gesamtschlafzeit (TST), die mit erhöhter Atemanstrengung (RE) verbracht wurde, und der Prävalenz von Typ-2-Diabetes bei Personen mit Verdacht auf obstruktive Schlaf-apnoe (OSA) untersucht. Die Studie umfasste klinische Daten von 1128 Patienten, die zur Polysomnographie (PSG) im Labor überwie-sen wurden. Nicht invasive Messungen der RE wurden aus dem schlafbezogenen Unterkieferbewegungssignal (MJM) abgeleitet. Ein maschinelles Lernmodell wurde entwickelt, um Typ-2-Diabetes anhand von klinischen Daten, Standard-PSG-Indizes und von MJM abgeleiteten Parametern vorherzusagen, darunter der Anteil der TST, der mit erhöhter Atemanstrengung verbracht wurde (REMOV (%TST)). Die Datensätze wurden zufällig in Trainings- (n = 853) und Validierungsgruppen (n = 275) aufgeteilt. Das entwickelte Klassifizierungsmodell, basierend auf 18 Merkmalen einschließlich REMOV, zeigte eine hohe Vorhersageleistung für prävalenten Typ-2-Diabetes (Sensitivität = 0,81, Spezifität = 0,89). Die nachträgliche Interpretation mithilfe der Shapley-Erklärungsmethode ergab, dass ein hoher REMOV-Wert als signifikanter Risikofaktor für Typ-2-Diabetes bei Personen mit OSA identifiziert wurde. Diese Bedeutung von REMOV ging über traditionelle klinische Variablen wie Alter, Geschlecht und Body-Mass-Index hinaus und übertraf so-gar die Standard-PSG-Metriken wie Apnoe-Hypopnoe- und Sauerstoffentsättigungs-Indizes. Die Ergebnisse dieser Studie liefern erstmalig den Nachweis, dass der Anteil der Schlafzeit, der mit erhöhter Atemanstrengung verbracht wird (ermittelt durch MJM-Messungen), ein wichtiger Prädiktor für die Verbindung mit Typ-2-Diabetes bei Personen mit OSA ist. Diese Erkenntnisse könnten dazu beitragen, die Risikobewertung und Prävention von Typ-2-Diabetes bei OSA-Patienten zu verbessern. [ABSTRACT FROM AUTHOR]

Background: High respiratory drive in mechanically ventilated patients with spontaneous breathing effort may cause excessive lung stress and strain and muscle loading. Therefore, it is important to have a reliable estimate of respiratory effort to guarantee lung and diaphragm protective mechanical ventilation. Recently, a novel non-invasive method was found to detect excessive dynamic transpulmonary driving pressure (∆PL) and respiratory muscle pressure (Pmus) with reasonable accuracy. During the Coronavirus disease 2019 (COVID-19) pandemic, it was impossible to obtain the gold standard for respiratory effort, esophageal manometry, in every patient. Therefore, we investigated whether this novel non-invasive method could also be applied in COVID-19 patients. Methods: ∆PL and Pmus were derived from esophageal manometry in COVID-19 patients. In addition, ∆PL and Pmus were computed from the occlusion pressure (∆Pocc) obtained during an expiratory occlusion maneuver. Measured and computed ∆PL and Pmus were compared and discriminative performance for excessive ∆PL and Pmus was assessed. The relation between occlusion pressure and respiratory effort was also assessed. Results: Thirteen patients were included. Patients had a low dynamic lung compliance [24 (20–31) mL/cmH2O], high ∆PL (25 ± 6 cmH2O) and high Pmus (16 ± 7 cmH2O). Low agreement was found between measured and computed ∆PL and Pmus. Excessive ∆PL > 20 cmH2O and Pmus > 15 cmH2O were accurately detected (area under the receiver operating curve (AUROC) 1.00 [95% confidence interval (CI), 1.00–1.00], sensitivity 100% (95% CI, 72–100%) and specificity 100% (95% CI, 16–100%) and AUROC 0.98 (95% CI, 0.90–1.00), sensitivity 100% (95% CI, 54–100%) and specificity 86% (95% CI, 42–100%), respectively). Respiratory effort calculated per minute was highly correlated with ∆Pocc (for esophageal pressure time product per minute (PTPes/min) r2 = 0.73; P = 0.0002 and work of breathing (WOB) r2 = 0.85; P < 0.0001). Conclusions: ∆PL and Pmus can be computed from an expiratory occlusion maneuver and can predict excessive ∆PL and Pmus in patients with COVID-19 with high accuracy. [ABSTRACT FROM AUTHOR]

Objective. Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort. However, this type of sensor has been validated only for respiratory events in the context of obstructive sleep apnea syndrome (OSA). We aim to provide an extensive verification of the suprasternal pressure signal against RIP belts and Pes, covering both normal breathing and respiratory events. Approach. We simultaneously acquired suprasternal (207) and esophageal pressure (20) signals along with RIP belts during a clinical PSG of 207 participants. In each signal, we detected breaths with a custom algorithm, and evaluated the SSP in terms of detection quality, breathing rate estimation, and similarity of breathing patterns against RIP and Pes. Additionally, we examined how the SSP signal may diverge from RIP and Pes in presence of respiratory events scored by a sleep technician. Main results. The SSP signal proved to be a reliable substitute for both esophageal pressure (Pes) and respiratory inductance plethysmography (RIP) in terms of breath detection, with sensitivity and positive predictive value exceeding 75%, and low error in breathing rate estimation. The SSP was also consistent with Pes (correlation of 0.72, similarity 80.8%) in patterns of increasing pressure amplitude that are common in OSA. Significance. This work provides a quantitative analysis of suprasternal pressure sensors for respiratory effort measurements., (Creative Commons Attribution license.)

Introduction: Although neonatal breathing patterns vary after perinatal asphyxia, whether they change during therapeutic hypothermia (TH) remains unclear. We characterized breathing patterns in infants during TH for hypoxic-ischemic encephalopathy (HIE) and normothermia after rewarming., Methods: In seventeen spontaneously breathing infants receiving TH for HIE and in three who did not receive TH, we analyzed respiratory flow and esophageal pressure tracings for respiratory timing variables, pulmonary mechanics and respiratory effort. Breaths were classified as braked (inspiratory:expiratory ratio ≥1.5) and unbraked (<1.5)., Results: According to the expiratory flow shape braked breaths were chategorized into early peak expiratory flow, late peak expiratory flow, slow flow, and post-inspiratory hold flow (PiHF). The most braked breaths had lower rates, larger tidal volume but lower minute ventilation, inspiratory airway resistance and respiratory effort, except for the PiHF, which had higher resistance and respiratory effort. The braked pattern predominated during TH, but not during normothermia or in the uncooled infants., Conclusions: We speculate that during TH for HIE low respiratory rates favor neonatal braked breathing to preserve lung volume. Given the generally low respiratory effort, it seems reasonable to leave spontaneous breathing unassisted. However, if the PiHF pattern predominates, ventilatory support may be required., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Papoff, Caresta, D'Agostino, Midulla, Petrarca, Giannini, Pisani and Montecchia.)

Mechanical ventilation may have adverse effects on both the lung and the diaphragm. Injury to the lung is mediated by excessive mechanical stress and strain, whereas the diaphragm develops atrophy as a consequence of low respiratory effort and injury in case of excessive effort. The lung and diaphragm-protective mechanical ventilation approach aims to protect both organs simultaneously whenever possible. This review summarizes practical strategies for achieving lung and diaphragm-protective targets at the bedside, focusing on inspiratory and expiratory ventilator settings, monitoring of inspiratory effort or respiratory drive, management of dyssynchrony, and sedation considerations. A number of potential future adjunctive strategies including extracorporeal CO2 removal, partial neuromuscular blockade, and neuromuscular stimulation are also discussed. While clinical trials to confirm the benefit of these approaches are awaited, clinicians should become familiar with assessing and managing patients' respiratory effort, based on existing physiological principles. To protect the lung and the diaphragm, ventilation and sedation might be applied to avoid excessively weak or very strong respiratory efforts and patient-ventilator dysynchrony. [ABSTRACT FROM AUTHOR]

Proportional modes of ventilation assist the patient by adapting to his/her effort, which contrasts with all other modes. The two proportional modes are referred to as neurally adjusted ventilatory assist (NAVA) and proportional assist ventilation with load-adjustable gain factors (PAV+): they deliver inspiratory assist in proportion to the patient's effort, and hence directly respond to changes in ventilatory needs. Due to their working principles, NAVA and PAV+ have the ability to provide self-adjusted lung and diaphragm-protective ventilation. As these proportional modes differ from 'classical' modes such as pressure support ventilation (PSV), setting the inspiratory assist level is often puzzling for clinicians at the bedside as it is not based on usual parameters such as tidal volumes and PaCO2 targets. This paper provides an in-depth overview of the working principles of NAVA and PAV+ and the physiological differences with PSV. Understanding these differences is fundamental for applying any assisted mode at the bedside. We review different methods for setting inspiratory assist during NAVA and PAV+ , and (future) indices for monitoring of patient effort. Last, differences with automated modes are mentioned. [ABSTRACT FROM AUTHOR]

Background: Infants are currently stabilized at birth with initial low FiO2 which increases the risk of hypoxia and suppression of breathing in the first minutes after birth. We hypothesized that initiating stabilization at birth with a high O2 concentration, followed by titration, would improve breathing effort when compared to a low O2 concentration, followed by titration.Methods: In a bi-center randomized controlled trial, infants 95%. 8-iso-prostaglandin F2α (8iPGF2α) was measured to assess oxidative stress in cord blood and 1 and 24 h after birth.Results: Fifty-two infants were randomized and recordings were obtained in 44 infants (100% O2-group: n = 20, 30% O2-group: n = 24). Minute volumes were significantly higher in the 100% O2-group (146.34 ± 112.68 mL/kg/min) compared to the 30% O2-group (74.43 ± 52.19 mL/kg/min), p = 0.014. Tidal volumes and MIFR were significantly higher in the 100% O2-group, while the duration of mask ventilation given was significantly shorter. Oxygenation in the first 5 min after birth was significantly higher in infants in the 100% O2-group [85 (64–93)%] compared to the 30% O2-group [58 (46–67)%], p < 0.001. The duration of hypoxemia was significantly shorter in the 100% O2-group, while the duration of hyperoxemia was not different between groups. There was no difference in oxidative stress marker 8iPGF2α between the groups.Conclusion: Initiating stabilization of preterm infants at birth with 100% O2 led to higher breathing effort, improved oxygenation, and a shorter duration of mask ventilation as compared to 30% O2, without increasing the risk for hyperoxia or oxidative stress.Clinical Trial Registration: This study was registered in www.trialregister.nl, with registration number NTR6878.

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Objectives: To determine if recording of suprasternal pressure (SSP) can classify apneas and hypopneas as reliably as respiratory inductance plethysmography (RIP) belts and to compare the two methods to classification with esophageal pressure (Pes), the reference method for assessing respiratory effort. Methods: In addition to polysomnographic recordings that included Pes, SSP was recorded. Recordings from 32 patients (25 males, mean age 66.7 ± 15.3 years, and mean BMI 30.1 ± 4.5 kg/m2) were used to compare the classification of detected apneas and hypopneas by three methods of respiratory effort evaluation (Pes, RIP belts, and SSP). Signals were analyzed randomly and independently from each other. All recordings were analyzed according to AASM guidelines. Results: Using Pes as a reference for apnea characterization, the Cohen kappa (κ) was 0.93 for SSP and 0.87 for the RIP. The sensitivity/specificity of SSP was 97.0%/96.9% for obstructive, 93.9%/98.3% for central, and 94.9%/97.9% for mixed apneas. The sensitivity/specificity of the RIP was 97.4%/91.9% for obstructive, 87.5%/97.9% for central, and 85.6%/96.6% for mixed apneas. For hypopnea characterization using the Pes as a reference, κ was 0.92 for SSP and 0.86 for the RIP. The sensitivity/specificity of SSP was 99.7%/97.6% for obstructive and 97.6%/99.7% for central. The sensitivity/specificity of the RIP was 99.8%/81.1% for obstructive and 81.1%/99.8% for central. Conclusions: These results confirm the excellent agreement in the detection of respiratory effort between SSP, RIP belts, and Pes signals. Thus, we conclude that apnea and hypopnea characterization in adults with SSP is a reliable method. [ABSTRACT FROM AUTHOR]