Parents' perspective on recovery at home following adenotonsillectomy: a prospective single-centre qualitative analysis.

PURPOSE: In North America, pediatric adenotonsillectomy (TA) is conducted as an ambulatory procedure, thus shifting the burden of postoperative care to parents. The purpose of this study was to describe this parental experience. METHODS: We conducted a prospective single-centre qualitative study, recruiting the families of children (n = 317) undergoing elective TA in 2018. Parents were invited to submit written comments to two open-ended questions. We coded the comments from 144 parents in a grounded theory analysis and report representative exemplars. Themes and subthemes for the problems encountered, and strategies employed by parents, were developed. We then coded and classified factors that helped/hindered parents and developed models of the experience. RESULTS: Some parents felt ill-prepared for the severity and duration of pain. Specific findings included a lack of strategies to manage pain at night, refusals, and night terrors. Parents identified the use of pain scales, pain diaries, and liaison with the research team as helpful supports at home. Inconsistent messaging was a barrier. The odynophagia associated with elixirs of acetaminophen and ibuprofen was a barrier to achieving analgesia. CONCLUSIONS: The findings from this qualitative analysis provide insight into the challenges faced by parents when caring for their children at home following TA; these challenges included difficulties managing physical needs and pain. The analysis suggests that educational content should be standardized and include the use of pain scales and diaries, and both pharmacologic and nonpharmacologic strategies. Development of support at home, including a practicable liaison with health care providers, seems to be warranted. STUDY REGISTRATION: ClinicalTrials.gov (NCT03378830); registered 20 December 2017.

RéSUMé: OBJECTIF: En Amérique du Nord, l'adéno-amygdalectomie pédiatrique est réalisée en intervention ambulatoire, transférant ainsi le fardeau des soins postopératoires aux parents. Le but de cette étude était de décrire cette expérience parentale. MéTHODE: Nous avons réalisé une étude qualitative prospective monocentrique, recrutant les familles d'enfants (n = 317) subissant une adéno-amygdalectomie non urgente en 2018. Les parents ont été invités à soumettre des commentaires écrits sur deux questions ouvertes. Nous avons codé les commentaires de 144 parents dans une analyse théorique ancrée et rapporté des exemples représentatifs. Des thèmes et sous-thèmes pour les problèmes rencontrés, ainsi que des stratégies employées par les parents, ont été développés. Nous avons ensuite codé et classé les facteurs qui aidaient / gênaient les parents et développé des modèles de l'expérience. RéSULTATS: Certains parents se sentaient mal préparés à la gravité et à la durée de la douleur. Les résultats spécifiques comprenaient un manque de stratégies pour gérer la douleur la nuit, les refus et les terreurs nocturnes. Les parents ont indiqué que l'utilisation d'échelles de douleur, de journaux de douleur et de liaison avec l'équipe de recherche étaient des soutiens utiles à la maison. Le manque d'uniformité des messages a constitué un obstacle. L'odynophagie associée aux élixirs d'acétaminophène et d'ibuprofène était un obstacle à l'analgésie. CONCLUSION: Les résultats de cette analyse qualitative donnent un aperçu des défis auxquels font face les parents lorsqu'ils et elles s'occupent de leurs enfants à la maison après une adéno-amygdalectomie; ces défis comprenaient des difficultés à gérer les besoins physiques et la douleur. L'analyse suggère que le contenu éducatif devrait être normalisé et inclure l'utilisation d'échelles et de journaux de douleur, ainsi que de stratégies pharmacologiques et non pharmacologiques. L'élaboration d'un soutien à domicile, y compris d'une communication fonctionnelle avec les prestataires de soins de santé, semble justifiée. ENREGISTREMENT DE L'éTUDE: ClinicalTrials.gov (NCT03378830); enregistrée le 20 décembre 2017.

Automated prediction of extubation success in extremely preterm infants: the APEX multicenter study.

BACKGROUND: Extremely preterm infants are frequently subjected to mechanical ventilation. Current prediction tools of extubation success lacks accuracy. METHODS: Multicenter study including infants with birth weight ≤1250 g undergoing their first extubation attempt. Clinical data and cardiorespiratory signals were acquired before extubation. Primary outcome was prediction of extubation success. Automated analysis of cardiorespiratory signals, development of clinical and cardiorespiratory features, and a 2-stage Clinical Decision-Balanced Random Forest classifier were used. A leave-one-out cross-validation was done. Performance was analyzed by ROC curves and determined by balanced accuracy. An exploratory analysis was performed for extubations before 7 days of age. RESULTS: A total of 241 infants were included and 44 failed (18%) extubation. The classifier had a balanced accuracy of 73% (sensitivity 70% [95% CI: 63%, 76%], specificity 75% [95% CI: 62%, 88%]). As an additional clinical-decision tool, the classifier would have led to an increase in extubation success from 82% to 93% but misclassified 60 infants who would have been successfully extubated. In infants extubated before 7 days of age, the classifier identified 16/18 failures (specificity 89%) and 73/105 infants with success (sensitivity 70%). CONCLUSIONS: Machine learning algorithms may improve a balanced prediction of extubation outcomes, but further refinement and validation is required. IMPACT: A machine learning-derived predictive model combining clinical data with automated analyses of individual cardiorespiratory signals may improve the prediction of successful extubation and identify infants at higher risk of failure with a good balanced accuracy. Such multidisciplinary approach including medicine, biomedical engineering and computer science is a step forward as current tools investigated to predict extubation outcomes lack sufficient balanced accuracy to justify their use in future trials or clinical practice. Thus, this individualized assessment can optimize patient selection for future trials of extubation readiness by decreasing exposure of low-risk infants to interventions and maximize the benefits of those at high risk.

Parental Engagement of a Prototype Electronic Diary in an Ambulatory Setting Following Adenotonsillectomy in Children: A Prospective Cohort Study.

Adenotonsillectomy is performed in children on an outpatient basis, and pain is managed by parents. A pain diary would facilitate pain management in the ambulatory setting. Our objective was to evaluate the parental response rate and the compliance of a prototype electronic pain diary (e-diary) with cloud storage in children aged 2-12 years recovering from adenotonsillectomy and to compare the e-diary with a paper diary (p-diary). Parents recorded pain scores twice daily in a pain diary for 2 weeks post-operation. Parents were given the choice of an e-diary or p-diary with picture message. A total of 208 patients were recruited, of which 35 parents (16.8%) chose the e-diary. Most parents (98%) chose to be contacted by text message. Eighty-one families (47%) returned p-diaries to us by mail. However, the response rate increased to 77% and was similar to that of the e-diary (80%) when we included data texted to the research phone from 53 families. The proportion of diaries with Complete (e-diary:0.37 vs. p-diary:0.4) and Incomplete (e-diary:0.43 vs. p-diary:0.38) data entries were similar. E-diaries provide a means to follow patients in real time after discharge. Our findings suggest that a smartphone-based medical health application coupled with a cloud would meet the needs of families and health care providers alike.

Automatic unsupervised respiratory analysis of infant respiratory inductance plethysmography signals.

Infants are at risk for potentially life-threatening postoperative apnea (POA). We developed an Automated Unsupervised Respiratory Event Analysis (AUREA) to classify breathing patterns obtained with dual belt respiratory inductance plethysmography and a reference using Expectation Maximization (EM). This work describes AUREA and evaluates its performance. AUREA computes six metrics and inputs them into a series of four binary k-means classifiers. Breathing patterns were characterized by normalized variance, nonperiodic power, instantaneous frequency and phase. Signals were classified sample by sample into one of 5 patterns: pause (PAU), movement (MVT), synchronous (SYB) and asynchronous (ASB) breathing, and unknown (UNK). MVT and UNK were combined as UNKNOWN. Twenty-one preprocessed records obtained from infants at risk for POA were analyzed. Performance was evaluated with a confusion matrix, overall accuracy, and pattern specific precision, recall, and F-score. Segments of identical patterns were evaluated for fragmentation and pattern matching with the EM reference. PAU exhibited very low normalized variance. MVT had high normalized nonperiodic power and low frequency. SYB and ASB had a median frequency of respectively, 0.76Hz and 0.71Hz, and a mode for phase of 4o and 100o. Overall accuracy was 0.80. AUREA confused patterns most often with UNKNOWN (25.5%). The pattern specific F-score was highest for SYB (0.88) and lowest for PAU (0.60). PAU had high precision (0.78) and low recall (0.49). Fragmentation was evident in pattern events <2s. In 75% of the EM pattern events >2s, 50% of the samples classified by AUREA had identical patterns. Frequency and phase for SYB and ASB were consistent with published values for synchronous and asynchronous breathing in infants. The low normalized variance in PAU, was consistent with published scoring rules for pediatric apnea. These findings support the use of AUREA to classify breathing patterns and warrant a future evaluation of clinically relevant respiratory events.

Cardiorespiratory behavior of preterm infants receiving continuous positive airway pressure and high flow nasal cannula post extubation: randomized crossover study.

BACKGROUND: Nasal continuous positive airway pressure (NCPAP) and high flow nasal cannula (HFNC) are modes of non-invasive respiratory support commonly used after extubation in extremely preterm infants. However, the cardiorespiratory physiology of these infants on each mode is unknown. METHODS: Prospective, randomized crossover study in infants with birth weight ≤1250 g undergoing their first extubation attempt. NCPAP and HFNC were applied randomly for 45 min each, while ribcage and abdominal movements, electrocardiogram, oxygen saturation, and fraction of inspired oxygen (FiO2) were recorded. Respiratory signals were analyzed using an automated method, and differences between NCPAP and HFNC features and changes in FiO2 were analyzed. RESULTS: A total of 30 infants with median [interquartile range] gestational age of 27 weeks [25.7, 27.9] and birth weight of 930 g [780, 1090] were studied. Infants were extubated at 5 days [2, 13] of life with 973 g [880, 1170] and three failed (10%). No differences in cardiorespiratory behavior were noted, except for longer respiratory pauses (9.2 s [5.0, 11.5] vs. 7.3 s [4.6, 9.3]; p = 0.04) and higher FiO2 levels (p = 0.02) during HFNC compared to NCPAP. CONCLUSIONS: In extremely preterm infants studied shortly after extubation, the use of HFNC was associated with longer respiratory pauses and higher FiO2 requirements.

Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants.

Extremely preterm infants often require endotracheal intubation and mechanical ventilation during the first days of life. Due to the detrimental effects of prolonged invasive mechanical ventilation (IMV), clinicians aim to extubate infants as soon as they deem them ready.Unfortunately, existing strategies for prediction of extubation readiness vary across clinicians and institutions, and lead to high reintubation rates. We present an approach using Random Forest classifiers for the analysis of cardiorespiratory variability to predict extubation readiness. We address the issue of data imbalance by employing random undersampling of examples from the majority class before training each Decision Tree in a bag. By incorporating clinical domain knowledge, we further demonstrate that our classifier could have identified 71% of infants who failed extubation, while maintaining a success detection rate of 78%.

Optimal Classification of Respiratory Patterns From Manual Analyses Using Expectation-Maximization.

Manual scoring (MS) of cardiorespiratory signals is the gold standard method for the analysis of respiratory data in sleep laboratories. In MS, trained, expert scorers characterize respiratory patterns by scrolling through a data record and visually identifying patterns. However, MS is limited by high intra- and inter-scorer variability and subjectivity. A strategy to mitigate this is to analyze the same respiratory data multiple times and generate a consensus. This consensus is generally determined by a majority vote (MV), where the most frequent pattern is selected as the true pattern. This paper presents expectation-maximization pattern sequence (EM-PSEQ), a novel method based on EM that estimates the true patterns optimally. A simulation study examined the accuracies of EM-PSEQ, MV, and individual scorers (IS) as a function of the number of analyses. Accuracy was measured with the Fleiss κ statistic, and is reported as , where , the median value, is the expected accuracy, and , the 5th percentile value, gives the minimum accuracy for 95% confidence. IS accuracy remained constant at as the number of analyses increased. MV accuracy increased slowly with the number of analyses and plateaued at after five analyses. In contrast, EM-PSEQ accuracy improved quickly, reaching an almost perfect value of with four analyses, and perfect accuracy after 25 analyses. EM-PSEQ performed much better than either MV or IS, and required only modest computational effort. Consequently, we believe EM-PSEQ will be a very valuable tool for clinical studies, as it can dramatically improve the accuracy of manual respiratory analysis with minimal additional cost.

The anatomy of the pediatric airway: Has our knowledge changed in 120 years? A review of historic and recent investigations of the anatomy of the pediatric larynx.

BACKGROUND: There is disagreement regarding the anatomy of the pediatric airway, particularly regarding the shape of the cricoid cartilage and the location of the narrowest portion of the larynx. AIMS: The aim of this review is to clarify the origin and the science behind these differing views. METHODS: We undertook a review of published literature, University Libraries, and authoritative textbooks with key search words and phrases. RESULTS: In vivo observations suggest that the narrowest portion of the airway is more proximal than the cricoid cartilage. However, in vitro studies of autopsy specimens measured with rods or calipers, confirm that the nondistensible and circular or near circular cricoid outlet is the narrowest level. These anatomic studies confirmed the classic "funnel" shape of the pediatric larynx. In vivo studies are potentially misleading as the aryepiglottic, vestibular, and true vocal folds are in constant motion with respiration. These studies also do not consider the effects of normal sleep, inhalation agents, and comorbidities such as adenoid or tonsil hypertrophy that cause some degree of pharyngeal collapse and alter the normal movement of the laryngeal tissues. Thus, the radiologic studies suggesting that the narrowest portion of the airway is not the cricoid cartilage may be the result of an artifact depending upon which phase of respiration was imaged. CONCLUSION: In vivo studies do not take into account the motion of the highly pliable laryngeal upper airway structures (aryepiglottic, vestibular, and vocal folds). Maximal abduction of these structures with tracheal tubes or bronchoscopes always demonstrates a larger opening of the glottis compared to the outlet of the cricoid ring. Injury to the larynx depends upon ease of tracheal tube or endoscope passage past the cricoid cartilage and not passage through the readily distensible more proximal structures. The infant larynx is funnel shaped with the narrowest portion the circular or near circular cricoid cartilage confirmed by multiple in vitro autopsy specimens carried out over the past century.

A semi-Markov chain approach to modeling respiratory patterns prior to extubation in preterm infants.

After birth, extremely preterm infants often require specialized respiratory management in the form of invasive mechanical ventilation (IMV). Protracted IMV is associated with detrimental outcomes and morbidities. Premature extubation, on the other hand, would necessitate reintubation which is risky, technically challenging and could further lead to lung injury or disease. We present an approach to modeling respiratory patterns of infants who succeeded extubation and those who required reintubation which relies on Markov models. We compare the use of traditional Markov chains to semi-Markov models which emphasize cross-pattern transitions and timing information, and to multi-chain Markov models which can concisely represent non-stationarity in respiratory behavior over time. The models we developed expose specific, unique similarities as well as vital differences between the two populations.

Impact of Time Lapse on ASCP Board of Certification Medical Laboratory Scientist (MLS) and Medical Laboratory Technician (MLT) Examination Scores.

BACKGROUND: Research in several professional fields has demonstrated that delays (time lapse) in taking certification examinations may result in poorer performance by examinees. Thirteen states and/or territories require licensure for laboratory personnel. A core component of licensure is passing a certification exam. Also, many facilities in states that do not require licensure require certification for employment or preferentially hire certified individuals. OBJECTIVE: To analyze examinee performance on the American Society for Clinical Pathology (ASCP) Board of Certification (BOC) Medical Laboratory Scientist (MLS) and Medical Laboratory Technician (MLT) certification examinations to determine whether delays in taking the examination from the time of program completion are associated with poorer performance. METHODS: We obtained examination data from April 2013 through December 2014 to look for changes in mean (SD) exam scaled scores and overall pass/fail rates. First-time examinees (MLS: n = 6037; MLT, n = 3920) were divided into 3-month categories based on the interval of time between date of program completion and taking the certification exam. RESULTS: We observed significant decreases in mean (SD) scaled scores and pass rates after the first quarter in MLS and MLT examinations for applicants who delayed taking their examination until the second, third, and fourth quarter after completing their training programs. CONCLUSIONS: Those who take the ASCP BOC MLS and MLT examinations are encouraged to do so shortly after completion of their educational training programs. Delays in taking an exam are generally not beneficial to the examinee and result in poorer performance on the exam.

Scoring Tools for the Analysis of Infant Respiratory Inductive Plethysmography Signals.

Infants recovering from anesthesia are at risk of life threatening Postoperative Apnea (POA). POA events are rare, and so the study of POA requires the analysis of long cardiorespiratory records. Manual scoring is the preferred method of analysis for these data, but it is limited by low intra- and inter-scorer repeatability. Furthermore, recommended scoring rules do not provide a comprehensive description of the respiratory patterns. This work describes a set of manual scoring tools that address these limitations. These tools include: (i) a set of definitions and scoring rules for 6 mutually exclusive, unique patterns that fully characterize infant respiratory inductive plethysmography (RIP) signals; (ii) RIPScore, a graphical, manual scoring software to apply these rules to infant data; (iii) a library of data segments representing each of the 6 patterns; (iv) a fully automated, interactive formal training protocol to standardize the analysis and establish intra- and inter-scorer repeatability; and (v) a quality control method to monitor scorer ongoing performance over time. To evaluate these tools, three scorers from varied backgrounds were recruited and trained to reach a performance level similar to that of an expert. These scorers used RIPScore to analyze data from infants at risk of POA in two separate, independent instances. Scorers performed with high accuracy and consistency, analyzed data efficiently, had very good intra- and inter-scorer repeatability, and exhibited only minor confusion between patterns. These results indicate that our tools represent an excellent method for the analysis of respiratory patterns in long data records. Although the tools were developed for the study of POA, their use extends to any study of respiratory patterns using RIP (e.g., sleep apnea, extubation readiness). Moreover, by establishing and monitoring scorer repeatability, our tools enable the analysis of large data sets by multiple scorers, which is essential for longitudinal and multicenter studies.

Automated analysis of respiratory behavior for the prediction of apnea in infants following general anesthesia.

Infants recovering from general anesthesia are at risk of postoperative apnea (POA), a potentially life threatening event. There is no accurate way to identify which infants will experience POA, and thus all infants with postmenstrual age <; 60 weeks are monitored for apnea in hospital postoperatively. Using a comprehensive, automated analysis of the postoperative breathing patterns, we identified the occurrence of respiratory pauses in 24 infants at age risk for POA. We determined the POA category for each infant by using K-medoids to cluster the duration of the longest respiratory pause. Two clusters were identified, corresponding to APNEA and NO-APNEA, with a threshold of 14.6 s, a value consistent with the clinically accepted threshold of 15 s. K-medoids derived POA labels were used to evaluate the predictive ability of demographic and anesthetic management variables. Weight and the intraoperative doses of atropine, propofol, and opioids discriminated between the APNEA and NO-APNEA groups. A linear Gaussian discriminant analysis classifier provided a very good classification with a probability of detection PD = 0.73 and a probability of false alarm PFA = 0.22. This approach provides a promising tool for the systematic, objective study of infants at risk of POA.

A new movement artifact detector for photoplethysmographic signals.

Oximeters are commonly used in abbreviated cardiorespiratory studies (ACS) to monitor blood oxygen saturation and heart rate using the photoplethysmography (PPG) signal. These data are prone to movement artifacts, especially in infants who move or need to be handled often. Therefore segments of PPG data contaminated by movement artifact must be detected as a first stage of analysis. In ACS this identification is generally done manually, by having an expert visually assess the quality of the signal. This is subjective and very time consuming, especially for long data records. For this reason we present a novel detector of PPG movement artifacts that uses moving average filters to remove trends, reduce the effect of white noise, and notch filter pulse-related information. The normalized root mean square of the filtered signal is then used as a detection statistic. We demonstrate its detection properties using a data set from infants recovering from anesthesia, and show that it performs better than other automated methods based on entropy or higher-order statistics. Furthermore, the new method is more robust than the other methods in the presence of large noise.

Novel measurements of the length of the subglottic airway in infants and young children.

BACKGROUND: To date, the lengths of the subglottic and tracheal airway segments have been measured from autopsy specimens. Images of the head and neck obtained from computerized tomography (CT) provide an alternate method. Our objective in this study was to identify anatomic landmarks from CT scans in infants and young children to estimate the lengths of the subglottic and tracheal airway segments and to correlate these lengths with age. METHODS: We performed a retrospective analysis of CT images of the neck for various diagnostic indications in children ≤3 years. We obtained planes of reconstruction at the level of the vocal cords (VCs), cricoid cartilage, and carina (C) which were parallel to each other and perpendicular to sagittal long axis of the trachea. The lengths of the subglottic airway (LengthSG) and total length of the laryngotracheal airway (LengthVC-C) were measured from the distance between, respectively, the VC versus cricoid cartilage and the VC versus C planes of reconstruction. Tracheal length was then calculated as the difference between LengthVC-C and LengthSG. RESULTS: Fifty-six children met the inclusion criteria. There were 29 boys. The median weight was 10.7 kg (range 3.1-19.0 kg). Regression analysis yielded mean LengthSG (mm) = 7.8 + 0.03·corrected age (months), r(2) = 0.07, P = 0.056; lower and upper 95% confidence interval for ß = 0.03 were -0.001 and 0061. The mean LengthSG was 8.4 mm with an SD of 1.4 mm. The 95th percentile for LengthSG was 10.8 mm, and the 5% to 95% interquartile range was 4.9 mm. The estimate for the 95% confidence interval of the 95th percentile was between 10.2 and 11.3 mm. The LengthVC-C increased with age: mean LengthVC-C (cm) = 5.3 + 0.05·corrected age (months), r(2) = 0.7, P < 0.001. Tracheal length also increased with age: mean tracheal length (cm) = 4.5 + 0.05·corrected age (months), r(2) = 0.6, P < 0.001. CONCLUSION: We report a novel estimate method for the lengths of the airway segments between the VC and C in 56 infants and young children and suggest that the growth characteristics of the subglottic and tracheal airway may differ.

Does employee safety influence customer satisfaction? Evidence from the electric utility industry.

PROBLEM: Research on workplace safety has not examined implications for business performance outcomes such as customer satisfaction. METHOD: In a U.S. electric utility company, we surveyed 821 employees in 20 work groups, and also had access to archival safety data and the results of a customer satisfaction survey (n=341). RESULTS: In geographically-based work units where there were more employee injuries (based on archival records), customers were less satisfied with the service they received. Safety climate, mediated by safety citizenship behaviors (SCBs), added to the predictive power of the group-level model, but these two constructs exerted their influence independently from actual injuries. In combination, two safety-related predictor paths (injuries and climate/SCB) explained 53% of the variance in customer satisfaction. DISCUSSION: Results offer preliminary evidence that workplace safety influences customer satisfaction, suggesting that there are likely spillover effects between the safety environment and the service environment. Additional research will be needed to assess the specific mechanisms that convert employee injuries into palpable results for customers. IMPACT ON INDUSTRY: Better safety climate and reductions in employee injuries have the potential to offer payoffs in terms of what customers experience.

Home noninvasive ventilation: what does the anesthesiologist need to know?

Treatment of chronic respiratory failure with noninvasive ventilation (NIV) is standard pediatric practice, and NIV systems are commonly used in the home setting. Although practice guidelines on the perioperative management of children supported with home NIV systems have yet to be published, increasingly these patients are referred for consultation regarding perioperative management. Just as knowledge of pharmacology underlies the safe prescription of medication, so too knowledge of biomedical design is necessary for the safe prescription of NIV therapy. The medical device design requirements developed by the Organization for International Standardization provide a framework to rationalize the safe prescription of NIV for hospitalized patients supported at home with NIV systems. This review article provides an overview of the indications for home NIV therapy, an overview of the medical devices currently available to deliver it, and a specific discussion of the management conundrums confronting anesthesiologists.

Prediction of extubation readiness in extreme preterm infants based on measures of cardiorespiratory variability.

The majority of extreme preterm infants require endotracheal intubation and mechanical ventilation (ETT-MV) during the first days of life to survive. Unfortunately this therapy is associated with adverse clinical outcomes and consequently, it is desirable to remove ETT-MV as quickly as possible. However, about 25% of extubated infants will fail and require re-intubation which is also associated with a 5-fold increase in mortality and a longer stay in the intensive care unit. Therefore, the ultimate goal is to determine the optimal time for extubation that will minimize the duration of MV and maximize the chances of success. This paper presents a new objective predictor to assist clinicians in making this decision. The predictor uses a modern machine learning method (Support Vector Machines) to determine the combination of measures of cardiorespiratory variability, computed automatically, that best predicts extubation readiness. Our results demonstrate that this predictor accurately classified infants who would fail extubation.

Detection of breathing segments in respiratory signals.

The typical approach for analysis of respiratory records consists of detection of respiratory pauses and elimination of segments corrupted by movement artifacts. This is motivated by established rules used for manual scoring of respiratory events, which focus on pause segmentation and do not define criteria to identify breathing segments. With this strategy, breathing segments can only be inferred indirectly from the absence of abnormalities, yielding an unclear and ambiguous definition. In this work we present novel detectors for synchronous and asynchronous breathing, and compare them with AUREA, a novel system for Automated Unsupervised Respiratory Event Analysis, which performs indirect classification of breathing. Results from analysis of real infant respiratory data show an improvement in the identification of synchronous and asynchronous breathing of 9% and 27% respectively, demonstrating that direct detection of breathing enhances the classification performance.