Quantification of periodic breathing in premature infants

Apnea, Intermittent Hypoxemia, and Bradycardia Events Predict Late-Onset Sepsis in Infants Born Extremely Preterm

OBJECTIVE

The objective of this study was to examine the association of cardiorespiratory events, including apnea, periodic breathing, intermittent hypoxemia (IH), and bradycardia, with late-onset sepsis for extremely preterm infants (<29 weeks of gestational age) on vs off invasive mechanical ventilation.

STUDY DESIGN

This is a retrospective analysis of data from infants enrolled in Pre-Vent (ClinicalTrials.gov identifier NCT03174301), an observational study in 5 level IV neonatal intensive care units. Clinical data were analyzed for 737 infants (mean gestational age: 26.4 weeks, SD 1.71). Monitoring data were available and analyzed for 719 infants (47 512 patient-days); of whom, 109 had 123 sepsis events. Using continuous monitoring data, we quantified apnea, periodic breathing, bradycardia, and IH. We analyzed the relationships between these daily measures and late-onset sepsis (positive blood culture >72 hours after birth and ≥5-day antibiotics).

RESULTS

For infants not on a ventilator, apnea, periodic breathing, and bradycardia increased before sepsis diagnosis. During times on a ventilator, increased sepsis risk was associated with longer events with oxygen saturation <80% (IH80) and more bradycardia events before sepsis. IH events were associated with higher sepsis risk but did not dynamically increase before sepsis, regardless of ventilator status. A multivariable model including postmenstrual age, cardiorespiratory variables (apnea, periodic breathing, IH80, and bradycardia), and ventilator status predicted sepsis with an area under the receiver operator characteristic curve of 0.783.

CONCLUSION

We identified cardiorespiratory signatures of late-onset sepsis. Longer IH events were associated with increased sepsis risk but did not change temporally near diagnosis. Increases in bradycardia, apnea, and periodic breathing preceded the clinical diagnosis of sepsis.

SubSol-HIe is an AMPK-dependent hypoxia-responsive subnucleus of the nucleus tractus solitarius that coordinates the hypoxic ventilatory response and protects against apnoea in mice

Functional magnetic resonance imaging (fMRI) suggests that the hypoxic ventilatory response is facilitated by the AMP-activated protein kinase (AMPK), not at the carotid bodies, but within a subnucleus (Bregma -7.5 to -7.1 mm) of the nucleus tractus solitarius that exhibits right-sided bilateral asymmetry. Here, we map this subnucleus using cFos expression as a surrogate for neuronal activation and mice in which the genes encoding the AMPK-α1 (Prkaa1) and AMPK-α2 (Prkaa2) catalytic subunits were deleted in catecholaminergic cells by Cre expression via the tyrosine hydroxylase promoter. Comparative analysis of brainstem sections, relative to controls, revealed that AMPK-α1/α2 deletion inhibited, with right-sided bilateral asymmetry, cFos expression in and thus activation of a neuronal cluster that partially spanned three interconnected anatomical nuclei adjacent to the area postrema: SolDL (Bregma -7.44 mm to -7.48 mm), SolDM (Bregma -7.44 mm to -7.48 mm) and SubP (Bregma -7.48 mm to -7.56 mm). This approximates the volume identified by fMRI. Moreover, these nuclei are known to be in receipt of carotid body afferent inputs, and catecholaminergic neurons of SubP and SolDL innervate aspects of the ventrolateral medulla responsible for respiratory rhythmogenesis. Accordingly, AMPK-α1/α2 deletion attenuated hypoxia-evoked increases in minute ventilation (normalised to metabolism), reductions in expiration time, and increases sigh frequency, but increased apnoea frequency during hypoxia. The metabolic response to hypoxia in AMPK-α1/α2 knockout mice and the brainstem and spinal cord catecholamine levels were equivalent to controls. We conclude that within the brainstem an AMPK-dependent, hypoxia-responsive subnucleus partially spans SubP, SolDM and SolDL, namely SubSol-HIe, and is critical to coordination of active expiration, the hypoxic ventilatory response and defence against apnoea.

The Derivation of Epigastric Motion to Assess Neonatal Breathing and Sleep: An Exploratory Study

INTRODUCTION

New non-medical monitors are offered for respiration monitoring of neonates. Epigastric motion during sleep was investigated by means of a wearable tracker in parallel to clinical monitoring.

COHORT

23 hospitalised neonates ready for discharge.

METHODS

A 3-axes-accelerometer and -gyroscope was placed in a standard epigastric position. Between two routine care rounds signals were recorded in parallel to monitoring of impedance pneumography (IP), ECG and pulse oximetry. Motion signals vs. time charts were evaluated using 10-min episodes and semiquantitatively assigned to breathing signal quality, regular breathing, periodic breathing and confounding artefacts. The results were compared with the impedance pneumographic data.

RESULTS

26 recordings (mean duration: 210 min/infant) were conducted without bradycardia or apnea alarm. The gestational age at birth ranged 28.9 to 41.1 and at recording from 35.6 to 42.3 postmenstrual weeks. Motion patterns of quiet sleep with regular breathing, periodic breathing and active sleep with confounding body movements were found. The longitudinal and transversal gyroscope axes resulted in best signal quality. Periodic breathing was found in up to 80% of episodes and decreased inversely with gestational age showing significantly more periodic breathing in preterm infants. Respiration signals of the gyroscope vs. IP showed a low bias and highly variating frequencies.

CONCLUSIONS

Standardized motion trackers may detect typical neonatal breathing and body-motion-patterns, that could help to classify neonatal sleep. Respiratory rates can only be determined during quiet sleep.

Experimental validation of an advanced impedance pneumography for monitoring ventilation volume during programmed cycling exercise

Objective.Impedance pneumography (IP) has provided static assessments of subjects' breathing patterns in previous studies. Evaluating the feasibility and limitation of ambulatory IP based respiratory monitoring needs further investigation on clinically relevant exercise designs. The aim of this study was to evaluate the capacity of an advanced IP in ambulatory respiratory monitoring, and its predictive value in independent ventilatory capacity quantification during cardiopulmonary exercise testing (CPET).Approach.35 volunteers were examined with the same calibration methodology and CPET exercise protocol comprising phases of rest, unloaded, incremental load, maximum load, recovery and further-recovery. In 3 or 4 deep breaths of calibration stage, thoracic impedance and criterion spirometric volume were simultaneously recorded to produce phase-specific prior calibration coefficients (CCs). The IP measurement during exercise protocol was converted by prior CCs to volume estimation curve and thus calculate minute ventilation (VE) independent from the spirometry approach.Main results.Across all measurements, the relative error of IP-derived VE (VER) and flowrate-derived VE (VEf) was less than 13.8%. In Bland-Altman plots, the aggregate VE estimation bias was statistically insignificant for all 3 phases with pedaling exercise and the discrepancy between VERand VEffell within the 95% limits of agreement (95% LoA) for 34 or all subjects in each of all CPET phases.Significance.This work reinforces the independent use of IP as an accurate and robust alternative to flowmeter for applications in cycle ergometry CPET, which could significantly encourage the clinical use of IP and improve the convenience and comfort of CPET.

Maturation of cardioventilatory physiological trajectories in extremely preterm infants

BACKGROUND

In extremely preterm infants, persistence of cardioventilatory events is associated with long-term morbidity. Therefore, the objective was to characterize physiologic growth curves of apnea, periodic breathing, intermittent hypoxemia, and bradycardia in extremely preterm infants during the first few months of life.

METHODS

The Prematurity-Related Ventilatory Control study included 717 preterm infants <29 weeks gestation. Waveforms were downloaded from bedside monitors with a novel sharing analytics strategy utilized to run software locally, with summary data sent to the Data Coordinating Center for compilation.

RESULTS

Apnea, periodic breathing, and intermittent hypoxemia events rose from day 3 of life then fell to near-resolution by 8-12 weeks of age. Apnea/intermittent hypoxemia were inversely correlated with gestational age, peaking at 3-4 weeks of age. Periodic breathing was positively correlated with gestational age peaking at 31-33 weeks postmenstrual age. Females had more periodic breathing but less intermittent hypoxemia/bradycardia. White infants had more apnea/periodic breathing/intermittent hypoxemia. Infants never receiving mechanical ventilation followed similar postnatal trajectories but with less apnea and intermittent hypoxemia, and more periodic breathing.

CONCLUSIONS

Cardioventilatory events peak during the first month of life but the actual postnatal trajectory is dependent on the type of event, race, sex and use of mechanical ventilation.

IMPACT

Physiologic curves of cardiorespiratory events in extremely preterm-born infants offer (1) objective measures to assess individual patient courses and (2) guides for research into control of ventilation, biomarkers and outcomes. Presented are updated maturational trajectories of apnea, periodic breathing, intermittent hypoxemia, and bradycardia in 717 infants born <29 weeks gestation from the multi-site NHLBI-funded Pre-Vent study. Cardioventilatory events peak during the first month of life but the actual postnatal trajectory is dependent on the type of event, race, sex and use of mechanical ventilation. Different time courses for apnea and periodic breathing suggest different maturational mechanisms.

Detecting central apneas using multichannel signals in premature infants

Objective. Monitoring of apnea of prematurity, performed in neonatal intensive care units by detecting central apneas (CAs) in the respiratory traces, is characterized by a high number of false alarms. A two-step approach consisting of a threshold-based apneic event detection algorithm followed by a machine learning model was recently presented in literature aiming to improve CA detection. However, since this is characterized by high complexity and low precision, we developed a new direct approach that only consists of a detection model based on machine learning directly working with multichannel signals.Approach. The dataset used in this study consisted of 48 h of ECG, chest impedance and peripheral oxygen saturation extracted from 10 premature infants. CAs were labeled by two clinical experts. 47 features were extracted from time series using 30 s moving windows with an overlap of 5 s and evaluated in sets of 4 consecutive moving windows, in a similar way to what was indicated for the two-step approach. An undersampling method was used to reduce imbalance in the training set while aiming at increasing precision. A detection model using logistic regression with elastic net penalty and leave-one-patient-out cross-validation was then tested on the full dataset.Main results. This detection model returned a mean area under the receiver operating characteristic curve value equal to 0.86 and, after the selection of a FPR equal to 0.1 and the use of smoothing, an increased precision (0.50 versus 0.42) at the expense of a decrease in recall (0.70 versus 0.78) compared to the two-step approach around suspected apneic events.Significance. The new direct approach guaranteed correct detections for more than 81% of CAs with lengthL≥ 20 s, which are considered among the most threatening apneic events for premature infants. These results require additional verifications using more extensive datasets but could lead to promising applications in clinical practice.

Apnea, Intermittent Hypoxemia, and Bradycardia Events Predict Late-Onset Sepsis in Extremely Preterm Infants

Objectives

Detection of changes in cardiorespiratory events, including apnea, periodic breathing, intermittent hypoxemia (IH), and bradycardia, may facilitate earlier detection of sepsis. Our objective was to examine the association of cardiorespiratory events with late-onset sepsis for extremely preterm infants (<29 weeks' gestational age (GA)) on versus off invasive mechanical ventilation.

Study Design

Retrospective analysis of data from infants enrolled in Pre-Vent (ClinicalTrials.gov identifier NCT03174301), an observational study in five level IV neonatal intensive care units. Clinical data were analyzed for 737 infants (mean GA 26.4w, SD 1.71). Monitoring data were available and analyzed for 719 infants (47,512 patient-days), of whom 109 had 123 sepsis events. Using continuous monitoring data, we quantified apnea, periodic breathing, bradycardia, and IH. We analyzed the relationships between these daily measures and late-onset sepsis (positive blood culture >72h after birth and ≥5d antibiotics).

Results

For infants not on a ventilator, apnea, periodic breathing, and bradycardia increased before sepsis diagnosis. During times on a ventilator, increased sepsis risk was associated with longer IH80 events and more bradycardia events before sepsis. IH events were associated with higher sepsis risk, but did not dynamically increase before sepsis, regardless of ventilator status. A multivariable model predicted sepsis with an AUC of 0.783.

Conclusion

We identified cardiorespiratory signatures of late-onset sepsis. Longer IH events were associated with increased sepsis risk but did not change temporally near diagnosis. Increases in bradycardia, apnea, and periodic breathing preceded the clinical diagnosis of sepsis.

Cardiorespiratory Monitoring Data to Predict Respiratory Outcomes in Extremely Preterm Infants

Rationale: Immature control of breathing is associated with apnea, periodic breathing, intermittent hypoxemia, and bradycardia in extremely preterm infants. However, it is not clear if such events independently predict worse respiratory outcome. Objectives: To determine if analysis of cardiorespiratory monitoring data can predict unfavorable respiratory outcomes at 40 weeks postmenstrual age (PMA) and other outcomes, such as bronchopulmonary dysplasia at 36 weeks PMA. Methods: The Prematurity-related Ventilatory Control (Pre-Vent) study was an observational multicenter prospective cohort study including infants born at <29 weeks of gestation with continuous cardiorespiratory monitoring. The primary outcome was either "favorable" (alive and previously discharged or inpatient and off respiratory medications/O2/support at 40 wk PMA) or "unfavorable" (either deceased or inpatient/previously discharged on respiratory medications/O2/support at 40 wk PMA). Measurements and Main Results: A total of 717 infants were evaluated (median birth weight, 850 g; gestation, 26.4 wk), 53.7% of whom had a favorable outcome and 46.3% of whom had an unfavorable outcome. Physiologic data predicted unfavorable outcome, with accuracy improving with advancing age (area under the curve, 0.79 at Day 7, 0.85 at Day 28 and 32 wk PMA). The physiologic variable that contributed most to prediction was intermittent hypoxemia with oxygen saturation as measured by pulse oximetry <90%. Models with clinical data alone or combining physiologic and clinical data also had good accuracy, with areas under the curve of 0.84-0.85 at Days 7 and 14 and 0.86-0.88 at Day 28 and 32 weeks PMA. Intermittent hypoxemia with oxygen saturation as measured by pulse oximetry <80% was the major physiologic predictor of severe bronchopulmonary dysplasia and death or mechanical ventilation at 40 weeks PMA. Conclusions: Physiologic data are independently associated with unfavorable respiratory outcome in extremely preterm infants.

Ventilatory response and stability of oxygen saturation during a hypoxic challenge in very preterm infants

BACKGROUND

Preterm infants have immature control of breathing and impaired pulmonary gas exchange. We hypothesized that infants with bronchopulmonary dysplasia (BPD) have a blunted ventilatory response and peripheral oxygen saturation (SpO₂ ) instability during a hypoxic challenge.

METHODS

We evaluated the response to hypoxia in 57 very preterm infants (38 no BPD, 10 mild BPD, 9 moderate-to-severe BPD) at 36 weeks' postmenstrual age. The fraction of inspired oxygen (F_I O₂ ) was reduced stepwise at 5-min intervals to achieve peripheral SpO₂ between 86% and 95%. The lowest permissible F_I O₂ and SpO₂ were 0.14% and 86%. We recorded SpO₂ , F_I O₂ , and the respiratory signal (respiratory inductive plethysmography). We calculated respiratory rate (RR), tidal volume (V_T ), minute ventilation (V_E ), and respiratory drive (ratio between V_T and inspiratory time, V_T /T_I ). SpO₂ variability was expressed as the interquartile range (IQR).

RESULTS

F_I O₂ was reduced from a median (Q1, Q3) of 0.21 (0.21, 0.21) to 0.17 (0.17, 0.18). We observed a marked individual variability in the ventilatory response to the hypoxic challenge, regardless of BPD severity. At the lowest permissible F_I O₂ , 37 (65%) infants reduced their V_E , and 20 (35%) increased minute ventilation; 20 infants (35%) developed periodic breathing associated with increased SpO₂ IQR and lower SpO₂ minima, and 16 (28%) exhibited an oscillatory pattern in V_E and SpO₂ without end-expiratory pauses, regardless of BPD severity.

CONCLUSION

In very preterm infants, a mild hypoxic challenge reduced ventilation, increased SpO₂ variability and periodic breathing regardless of BPD severity.

Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates

Respiratory rate (RR) monitoring is essential in neonatal intensive care units. Despite its importance, RR is still monitored intermittently by manual counting instead of continuous monitoring due to the risk of skin damage with prolonged use of contact electrodes in preterm neonates and false signals due to displacement of electrodes. Thermal imaging has recently gained significance as a non-contact method for RR detection because of its many advantages. However, due to the lack of information in thermal images, the selection and tracking of the region of interest (ROI) in thermal images for neonates are challenging. This paper presents the integration of visible (RGB) and thermal (T) image sequences for the selection and tracking of ROI for breathing rate extraction. The deep-learning based tracking-by-detection approach is employed to detect the ROI in the RGB images, and it is mapped to the thermal images using the RGB-T image registration. The mapped ROI in thermal spectrum sequences gives the respiratory rate. The study was conducted first on healthy adults in different modes, including steady, motion, talking, and variable respiratory order. Subsequently, the method is tested on neonates in a clinical settings. The findings have been validated with a contact-based reference method.The average absolute error between the proposed and belt-based contact method in healthy adults reached 0.1 bpm and for more challenging conditions was approximately 1.5 bpm and 1.8 bpm, respectively. In the case of neonates, the average error is 1.5 bpm, which are promising results. The Bland–Altman analysis showed a good agreement of estimated RR with the reference method RR and this pilot study provided the evidence of using the proposed approach as a contactless method for the respiratory rate detection of neonates in clinical settings.

Assessment of neonatal respiratory rate variability

Accurate measurement of respiratory rate (RR) in neonates is challenging due to high neonatal RR variability (RRV). There is growing evidence that RRV measurement could inform and guide neonatal care. We sought to quantify neonatal RRV during a clinical study in which we compared multiparameter continuous physiological monitoring (MCPM) devices. Measurements of capnography-recorded exhaled carbon dioxide across 60-s epochs were collected from neonates admitted to the neonatal unit at Aga Khan University-Nairobi hospital. Breaths were manually counted from capnograms and using an automated signal detection algorithm which also calculated mean and median RR for each epoch. Outcome measures were between- and within-neonate RRV, between- and within-epoch RRV, and 95% limits of agreement, bias, and root-mean-square deviation. Twenty-seven neonates were included, with 130 epochs analysed. Mean manual breath count (MBC) was 48 breaths per minute. Median RRV ranged from 11.5% (interquartile range (IQR) 6.8-18.9%) to 28.1% (IQR 23.5-36.7%). Bias and limits of agreement for MBC vs algorithm-derived breath count, MBC vs algorithm-derived median breath rate, MBC vs algorithm-derived mean breath rate were - 0.5 (- 2.7, 1.66), - 3.16 (- 12.12, 5.8), and - 3.99 (- 11.3, 3.32), respectively. The marked RRV highlights the challenge of performing accurate RR measurements in neonates. More research is required to optimize the use of RRV to improve care. When evaluating MCPM devices, accuracy thresholds should be less stringent in newborns due to increased RRV. Lastly, median RR, which discounts the impact of extreme outliers, may be more reflective of the underlying physiological control of breathing.

Algoritmically improved microwave radar monitors breathing more acurrate than sensorized belt

This paper describes a novel way to measure, process, analyze, and compare respiratory signals acquired by two types of devices: a wearable sensorized belt and a microwave radar-based sensor. Both devices provide breathing rate readouts. First, the background research is presented. Then, the underlying principles and working parameters of the microwave radar-based sensor, a contactless device for monitoring breathing, are described. The breathing rate measurement protocol is then presented, and the proposed algorithm for octave error elimination is introduced. Details are provided about the data processing phase; specifically, the management of signals acquired from two devices with different working principles and how they are resampled with a common processing sample rate. This is followed by an analysis of respiratory signals experimentally acquired by the belt and microwave radar-based sensors. The analysis outcomes were checked using Levene’s test, the Kruskal–Wallis test, and Dunn’s post hoc test. The findings show that the proposed assessment method is statistically stable. The source of variability lies in the person-triggered breathing patterns rather than the working principles of the devices used. Finally, conclusions are derived, and future work is outlined.

LKB1 is the gatekeeper of carotid body chemosensing and the hypoxic ventilatory response

The hypoxic ventilatory response (HVR) is critical to breathing and thus oxygen supply to the body and is primarily mediated by the carotid bodies. Here we reveal that carotid body afferent discharge during hypoxia and hypercapnia is determined by the expression of Liver Kinase B1 (LKB1), the principal kinase that activates the AMP-activated protein kinase (AMPK) during metabolic stresses. Conversely, conditional deletion in catecholaminergic cells of AMPK had no effect on carotid body responses to hypoxia or hypercapnia. By contrast, the HVR was attenuated by LKB1 and AMPK deletion. However, in LKB1 knockouts hypoxia evoked hypoventilation, apnoea and Cheyne-Stokes-like breathing, while only hypoventilation and apnoea were observed after AMPK deletion. We therefore identify LKB1 as an essential regulator of carotid body chemosensing and uncover a divergence in dependency on LKB1 and AMPK between the carotid body on one hand and the HVR on the other.

The principles of whole-hospital predictive analytics monitoring for clinical medicine originated in the neonatal ICU

In 2011, a multicenter group spearheaded at the University of Virginia demonstrated reduced mortality from real-time continuous cardiorespiratory monitoring in the neonatal ICU using what we now call Artificial Intelligence, Big Data, and Machine Learning. The large, randomized heart rate characteristics trial made real, for the first time that we know of, the promise that early detection of illness would allow earlier and more effective intervention and improved patient outcomes. Currently, though, we hear as much of failures as we do of successes in the rapidly growing field of predictive analytics monitoring that has followed. This Perspective aims to describe the principles of how we developed heart rate characteristics monitoring for neonatal sepsis and then applied them throughout adult ICU and hospital medicine. It primarily reflects the work since the 1990s of the University of Virginia group: the theme is that sudden and catastrophic deteriorations can be preceded by subclinical but measurable physiological changes apparent in the continuous cardiorespiratory monitoring and electronic health record.

Contactless radar-based breathing monitoring of premature infants in the neonatal intensive care unit

Vital sign monitoring systems are essential in the care of hospitalized neonates. Due to the immaturity of their organs and immune system, premature infants require continuous monitoring of their vital parameters and sensors need to be directly attached to their fragile skin. Besides mobility restrictions and stress, these sensors often cause skin irritation and may lead to pressure necrosis. In this work, we show that a contactless radar-based approach is viable for breathing monitoring in the Neonatal intensive care unit (NICU). For the first time, different scenarios common to the NICU daily routine are investigated, and the challenges of monitoring in a real clinical setup are addressed through different contributions in the signal processing framework. Rather than just discarding measurements under strong interference, we present a novel random body movement mitigation technique based on the time-frequency decomposition of the recovered signal. In addition, we propose a simple and accurate frequency estimator which explores the harmonic structure of the breathing signal. As a result, the proposed radar-based solution is able to provide reliable breathing frequency estimation, which is close to the reference cabled device values most of the time. Our findings shed light on the strengths and limitations of this technology and lay the foundation for future studies toward a completely contactless solution for vital signs monitoring.

Analysis of respiratory kinematics: a method to characterize breaths from motion signals

Breathing motion (respiratory kinematics) can be characterized by the interval and depth of each breath, and by magnitude-synchrony relationships between locations. Such characteristics and their breath-by-breath variability might be useful indicators of respiratory health. To enable breath-by-breath characterization of respiratory kinematics, we developed a method to detect breaths using motion sensors. In 34 volunteers who underwent maximal exercise testing, we used 8 motion sensors to record upper rib, lower rib and abdominal kinematics at 3 exercise stages (rest, lactate threshold and exhaustion). We recorded volumetric air flow signals using clinical exercise laboratory equipment and synchronized them with kinematic signals. Using instantaneous phase landmarks from the analytic representation of kinematic and flow signals, we identified individual breaths and derived respiratory rate (RR) signals at 1Hz. To evaluate the fidelity of kinematics-derived RR, we calculated bias, limits of agreement, and cross-correlation coefficients (CCC) relative to flow-derived RR. To identify coupling between kinematics and flow, we calculated the Shannon entropy of the relative frequency with which flow landmarks were distributed over the phase of the kinematic cycle. We found good agreement in the kinematics-derived and flow-derived RR signals [bias (95% limit of agreement) = 0.1 (± 7) breaths/minute; CCC median (IQR) = 0.80 (0.48 - 0.91)]. In individual signals, kinematics and flow were well-coupled (entropy 0.9-1.4 across sensors), but the relationship varied within (by exercise stage) and between individuals. The final result was that the flow landmarks did not consistently localize to any particular phase of the kinematic signals (entropy 2.2-3.0 across sensors). The Analysis of Respiratory Kinematics method can yield highly resolved respiratory rate signals by separating individual breaths. This method will facilitate characterization of clinically significant breathing motion patterns on a breath-by-breath basis. The relationship between respiratory kinematics and flow is much more complex than expected, varying between and within individuals.

Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction

The described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis were applied to granular computing. Signal attributes and anthropomorphic parameters were explored to develop prediction models to determine the percentage contribution of periodic-like, intermediate, and normal breathing patterns in the analyzed signals. The proposed methodology was validated employing k-nearest neighbor (k-NN) and UMAP (uniform manifold approximation and projection). The presented approach applied to respiratory pattern evaluation shows that median accuracies in a considerable number of cases exceeded 0.75. Overall, parameters related to signal analysis are indicated as more important than anthropomorphic features. It was also found that obesity characterized by a high WHR (waist-to-hip ratio) and male sex were predisposing factors for the occurrence of periodic-like or intermediate patterns of respiration. It may be among the essential findings derived from this study. Based on classification measures, it may be observed that a physician may use such a methodology as a respiratory pattern evaluation-aided method.

Evaluation of maturation in preterm infants through an ensemble machine learning algorithm using physiological signals

This study was designed to test if heart rate variability (HRV) data from preterm and full-term infants could be used to estimate their functional maturational age (FMA), using a machine learning model. We propose that the FMA, and its deviation from the postmenstrual age (PMA) of the infants could inform physicians about the progress of the maturation of the infants. The HRV data was acquired from 50 healthy infants, born between 25 and 41 weeks of gestational age, who did not present any signs of abnormal maturation relative to their age group during the period of observation. The HRV features were used as input for a machine learning model that uses filtering and genetic algorithms for feature selection, and an ensemble machine learning (EML) algorithm, which combines linear and random forest regressions, to produce as output a FMA. Using HRV data, the FMA had a mean absolute error of 0.93 weeks, 95% CI [0.78, 1.08], compared to the PMA. These results demonstrate that HRV features of newborn infants can be used by an EML model to estimate their FMA. This method was also generalized using respiration rate variability (RRV) and bradycardia data, obtaining similar results. The FMA, predicted either by HRV, RRV or bradycardia, and its deviation from the true PMA of the infants, could be used as a surrogate measure of the maturational age of the infants, which could potentially be monitored non-invasively and in real-time in the setting of neonatal intensive care units.

Central apnea and periodic breathing in children with underlying conditions

Central sleep apneas and periodic breathing are poorly described in childhood. The aim of the study was to describe the prevalence and characteristics of central sleep apnea and periodic breathing in children with associated medical conditions, and the therapeutic management. We retrospectively reviewed all poly(somno)graphies with a central apnea index ≥ 5 events per hr in children aged > 1 month performed in a paediatric sleep laboratory over a 6‐year period. Clinical data and follow‐up poly(somno)graphies were gathered. Ninety‐five out of 2,981 patients (3%) presented central sleep apnea: 40% were < 1 year, 41% aged 1–6 years, and 19% aged ≥ 6 years. Chiari malformation was the most common diagnosis (13%). Mean central apnea index was 20 ± 30 events per hr (range 5–177). Fifty‐eight (61%) children had an exclusive central pattern with < 5 obstructive events per hr. Periodic breathing was present in 79 (83%) patients, with a mean percentage of time with periodic breathing of 9 ± 16%. Among periodic breathing episodes, 40% appeared after a sigh, 8% after an obstructive event, 6% after breathing instability and 2% after bradypnea. The highest clinical apnea index and percentage of time with periodic breathing were observed in children with encephalopathy and/or epilepsy (68 ± 63 events per hr and 30 ± 34%). Clinical apnea index did not differ according to age, while periodic breathing duration was longer in children > 1 year old. Watchful waiting was performed in 22 (23%) patients with spontaneous improvement in 20. Other treatments (upper airway or neurosurgery, nocturnal oxygen therapy, continuous positive airway pressure, non‐invasive ventilation) were effective in selected patients. Central sleep apnea is rare in children and comprises heterogeneous conditions. Sleep studies are essential for the diagnosis, characterization and management of central sleep apnea.

Towards Continuous Camera-Based Respiration Monitoring in Infants

Aiming at continuous unobtrusive respiration monitoring, motion robustness is paramount. However, some types of motion can completely hide the respiration information and the detection of these events is required to avoid incorrect rate estimations. Therefore, this work proposes a motion detector optimized to specifically detect severe motion of infants combined with a respiration rate detection strategy based on automatic pixels selection, which proved to be robust to motion of the infants involving head and limbs. A dataset including both thermal and RGB (Red Green Blue) videos was used amounting to a total of 43 h acquired on 17 infants. The method was successfully applied to both RGB and thermal videos and compared to the chest impedance signal. The Mean Absolute Error (MAE) in segments where some motion is present was 1.16 and 1.97 breaths/min higher than the MAE in the ideal moments where the infants were still for testing and validation set, respectively. Overall, the average MAE on the testing and validation set are 3.31 breaths/min and 5.36 breaths/min, using 64.00% and 69.65% of the included video segments (segments containing events such as interventions were excluded based on a manual annotation), respectively. Moreover, we highlight challenges that need to be overcome for continuous camera-based respiration monitoring. The method can be applied to different camera modalities, does not require skin visibility, and is robust to some motion of the infants.

Kangaroo father care: A pilot feasibility study of physiologic, biologic, and psychosocial measures to capture the effects of father-infant and mother-infant skin-to-skin contact in the Neonatal Intensive Care Unit

Robust literature supports the positive effects of kangaroo mother care (KMC) on infant physiologic stability and parent-infant bonding in the Neonatal Intensive Care Unit (NICU). Comparatively little is known about kangaroo father care (KFC) in the NICU, and KFC implementation has been limited. Our pilot feasibility study objective was to examine KFC effects on premature infants and fathers as compared to KMC. Parents of preterm NICU infants independently completed a 90-min Kangaroo Care (KC) session on consecutive days. Infant heart rate variability (HRV) and apnea/periodicity measures were compared (pre-KC to KC; KFC to KMC). Additionally, we assessed the feasibility of administering three psychosocial questionnaires to fathers and mothers in the NICU and after discharge. Ten preterm infants completed 20 KC sessions (33^4/7 -37^4/7  weeks post-menstrual age). Results demonstrated similar infant physiologic responses between KMC and KFC, including significant differences in measures of HRV (p < .05) between KC and non-KC periods. Eighty-eight percentage of questionnaires administered were completed, supporting the utilization of these instruments in future research of this population. If confirmed, these preliminary results identify an opportunity to objectively assess KFC effects, supporting the development of empirically based KFC programs benefitting NICU families.

An overview of developmental dysregulation of autonomic control in infants

In this short review, we provide an overview of developmental disorders causing autonomic nervous system dysregulation. We briefly discuss perinatal conditions that adversely impact developmental outcomes including apnea of prematurity, sudden infant death syndrome, and Rett syndrome. We provide a brief clinical description, an overview of known or hypothesized mechanisms for the disorder, and current standard of practice for treatment of each condition. Additionally, we consider preventative measures and complications of these disorders to provide further insight into the pathogenesis of specific autonomic dysregulation in neonates. The goal of this short review is to provide an updated understanding of the impact of autonomic dysregulation on development of brainstem circuits and to briefly highlight promising future treatment options and controversies.

Leptin: Master Regulator of Biological Functions that Affects Breathing

Obesity is a global epidemic in developed countries accounting for many of the metabolic and cardiorespiratory morbidities that occur in adults. These morbidities include type 2 diabetes, sleep-disordered breathing (SDB), obstructive sleep apnea, chronic intermittent hypoxia, and hypertension. Leptin, produced by adipocytes, is a master regulator of metabolism and of many other biological functions including central and peripheral circuits that control breathing. By binding to receptors on cells and neurons in the brainstem, hypothalamus, and carotid body, leptin links energy and metabolism to breathing. In this comprehensive article, we review the central and peripheral locations of leptin's actions that affect cardiorespiratory responses during health and disease, with a particular focus on obesity, SDB, and its effects during early development. Obesity-induced hyperleptinemia is associated with centrally mediated hypoventilation with decrease CO₂ sensitivity. On the other hand, hyperleptinemia augments peripheral chemoreflexes to hypoxia and induces sympathoexcitation. Thus, "leptin resistance" in obesity is relative. We delineate the circuits responsible for these divergent effects, including signaling pathways. We review the unique effects of leptin during development on organogenesis, feeding behavior, and cardiorespiratory responses, and how undernutrition and overnutrition during critical periods of development can lead to cardiorespiratory comorbidities in adulthood. We conclude with suggestions for future directions to improve our understanding of leptin dysregulation and associated clinical diseases and possible therapeutic targets. Lastly, we briefly discuss the yin and the yang, specifically the contribution of relative adiponectin deficiency in adults with hyperleptinemia to the development of metabolic and cardiovascular disease. © 2020 American Physiological Society. Compr Physiol 10:1047-1083, 2020.

Relationship between cardiorespiratory phase coherence during hypoxia and genetic polymorphism in humans

KEY POINTS

High altitude-induced hypoxia in humans evokes a pattern of breathing known as periodic breathing (PB), in which the regular oscillations corresponding to rhythmic expiration and inspiration are modulated by slow periodic oscillations. The phase coherence between instantaneous heart rate and respiration is shown to increase significantly at the frequency of periodic breathing during acute and sustained normobaric and hypobaric hypoxia. It is also shown that polymorphism in specific genes, NOTCH4 and CAT, is significantly correlated with this coherence, and thus with the incidence of PB. Differences in phase shifts between blood flow signals and respiratory and PB oscillations clearly demonstrate contrasting origins of the mechanisms underlying normal respiration and PB. These novel findings provide a better understanding of both the genetic and the physiological mechanisms responsible for respiratory control during hypoxia at altitude, by linking genetic factors with cardiovascular dynamics, as evaluated by phase coherence.

ABSTRACT

Periodic breathing (PB) occurs in most humans at high altitudes and is characterised by low-frequency periodic alternation between hyperventilation and apnoea. In hypoxia-induced PB the dynamics and coherence between heart rate and respiration and their relationship to underlying genetic factors is still poorly understood. The aim of this study was to investigate, through novel usage of time-frequency analysis methods, the dynamics of hypoxia-induced PB in healthy individuals genotyped for a selection of antioxidative and neurodevelopmental genes. Breathing, ECG and microvascular blood flow were simultaneously monitored for 30 min in 22 healthy males. The same measurements were repeated under normoxic and hypoxic (normobaric (NH) and hypobaric (HH)) conditions, at real and simulated altitudes of up to 3800 m. Wavelet phase coherence and phase difference around the frequency of breathing (approximately 0.3 Hz) and around the frequency of PB (approximately 0.06 Hz) were evaluated. Subjects were genotyped for common functional polymorphisms in antioxidative and neurodevelopmental genes. During hypoxia, PB resulted in increased cardiorespiratory coherence at the PB frequency. This coherence was significantly higher in subjects with NOTCH4 polymorphism, and significantly lower in those with CAT polymorphism (HH only). Study of the phase shifts clearly indicates that the physiological mechanism of PB is different from that of the normal respiratory cycle. The results illustrate the power of time-evolving oscillatory analysis content in obtaining important insight into high altitude physiology. In particular, it provides further evidence for a genetic predisposition to PB and may partly explain the heterogeneity in the hypoxic response.

Sleep disordered breathing (SDB) in neonates and implications for its long-term impact

Sleep-disordered breathing (SDB) is a significant cause of morbidity in neonates and young infants. SDB occurs more commonly in preterm infants and in neonates with underlying syndromes. Recent evidence shows that infants with obstructive sleep apnoea (OSA) or SDB have greater health care resource utilization, including longer hospital stay. Management of SDB includes non-invasive ventilation or surgical interventions tailored to the patient. Screening high risk newborns should allow for early diagnosis and timely therapeutic intervention for this population. However, the thresholds for diagnosing SDB and for guiding and implementing treatment in neonates remain unclear. A collective effort is required to standardize the practice worldwide. This article will discuss neonatal sleep physiology and characteristics of neonatal sleep, with an emphasis on the epidemiology and diagnosis of SDB in neonates and its implications for long term outcomes.

Continuous vital sign analysis for predicting and preventing neonatal diseases in the twenty-first century: big data to the forefront

In the neonatal intensive care unit (NICU), heart rate, respiratory rate, and oxygen saturation are vital signs (VS) that are continuously monitored in infants, while blood pressure is often monitored continuously immediately after birth, or during critical illness. Although changes in VS can reflect infant physiology or circadian rhythms, persistent deviations in absolute values or complex changes in variability can indicate acute or chronic pathology. Recent studies demonstrate that analysis of continuous VS trends can predict sepsis, necrotizing enterocolitis, brain injury, bronchopulmonary dysplasia, cardiorespiratory decompensation, and mortality. Subtle changes in continuous VS patterns may not be discerned even by experienced clinicians reviewing spot VS data or VS trends captured in the monitor. In contrast, objective analysis of continuous VS data can improve neonatal outcomes by allowing heightened vigilance or preemptive interventions. In this review, we provide an overview of the studies that have used continuous analysis of single or multiple VS, their interactions, and combined VS and clinical analytic tools, to predict or detect neonatal pathophysiology. We make the case that big-data analytics are promising, and with continued improvements, can become a powerful tool to mitigate neonatal diseases in the twenty-first century.

Premature birth, homeostatic plasticity and respiratory consequences of inflammation

Infants who are born premature can have persistent apnea beyond term gestation, reemergence of apnea associated with inflammation during infancy, increased risk of sudden unexplained death, and sleep disorder breathing during infancy and childhood. The autonomic nervous system, particularly the central neural networks that control breathing and peripheral and central chemoreceptors and mechanoreceptors that modulate the activity of the central respiratory network, are rapidly developing during the last trimester (22-37 weeks gestation) of fetal life. With advances in neonatology, in well-resourced, developed countries, infants born as young as 23 weeks gestation can survive. Thus, a substantial part of maturation of central and peripheral systems that control breathing occurs ex-utero in infants born at the limit of viability. The balance of excitatory and inhibitory influences dictates the ultimate output from the central respiratory network. We propose in this review that simply being born early in the last trimester can trigger homeostatic plasticity within the respiratory network tipping the balance toward inhibition that persists in infancy. We discuss the intersection of premature birth, homeostatic plasticity and biological mechanisms leading to respiratory depression during inflammation in former premature infants.

Physiological instability after respiratory pauses in preterm infants

BACKGROUND

The factors influencing the severity of apnea-related hypoxemia and bradycardia are incompletely characterized, especially in infants receiving noninvasive respiratory support.

OBJECTIVES

To identify the frequency and predictors of physiological instability (hypoxemia-oxygen saturation (SpO₂ ) <80%, or bradycardia-heart rate (HR) < 100 bpm) following respiratory pauses in infants receiving noninvasive respiratory support.

METHODS

Respiratory pause duration, derived from capsule pneumography, was measured in 30 preterm infants of gestation 30 (24-32) weeks [median (interquartile range)] receiving noninvasive respiratory support and supplemental oxygen. For identified pauses of 5 to 29 seconds duration, we measured the magnitude and duration of SpO₂ and HR reductions over a period starting at the pause onset and ending 60 seconds after resumption of breathing. Temporally clustered pauses (<60 seconds separation) were analyzed separately. The relative contribution of respiratory pauses to overall physiological instability was determined, and predictors of instability were sought in regression analysis, including demographic, clinical and situational variables as inputs.

RESULTS

In total, 17 105 isolated and 9180 clustered pauses were identified. Hypoxemia and bradycardia were more likely after longer duration and temporally-clustered pauses. However, the majority of such episodes occurred after 5 to 9 second pauses given their numerical preponderance, and short-lived pauses made a substantial contribution to physiological instability overall. Birth gestation, hemoglobin concentration, form of respiratory support, caffeine treatment, respiratory pause duration and temporal clustering were identified as predictors of instability.

CONCLUSIONS

Brief respiratory pauses, especially when clustered, contribute substantially to hypoxemia and bradycardia in preterm infants.

Pre-Vent: the prematurity-related ventilatory control study

BACKGROUND

The increasing incidence of bronchopulmonary dysplasia in premature babies may be due in part to immature ventilatory control, contributing to hypoxemia. The latter responds to ventilation and/or oxygen therapy, treatments associated with adverse sequelae. This is an overview of the Prematurity-Related Ventilatory Control Study which aims to analyze the under-utilized cardiorespiratory continuous waveform monitoring data to delineate mechanisms of immature ventilatory control in preterm infants and identify predictive markers.

METHODS

Continuous ECG, heart rate, respiratory, and oxygen saturation data will be collected throughout the NICU stay in 500 infants < 29 wks gestation across 5 centers. Mild permissive hypercapnia, and hyperoxia and/or hypoxia assessments will be conducted in a subcohort of infants along with inpatient questionnaires, urine, serum, and DNA samples.

RESULTS

Primary outcomes will be respiratory status at 40 wks and quantitative measures of immature breathing plotted on a standard curve for infants matched at 36-37 wks. Physiologic and/or biologic determinants will be collected to enhance the predictive model linking ventilatory control to outcomes.

CONCLUSIONS

By incorporating bedside monitoring variables along with biomarkers that predict respiratory outcomes we aim to elucidate individualized cardiopulmonary phenotypes and mechanisms of ventilatory control contributing to adverse respiratory outcomes in premature infants.

Cross-Correlation of Heart Rate and Oxygen Saturation in Very Low Birthweight Infants: Association with Apnea and Adverse Events

BACKGROUND

 Analysis of subtle vital sign changes could facilitate earlier treatment of acute inflammatory illnesses. We previously showed that high cross-correlation of heart rate and oxygen saturation (XCorr-HR-SpO₂) occurs in some very low birthweight (VLBW) infants with sepsis, and hypothesized that this corresponds to apnea.

METHODS

 In 629 VLBW infants, we analyzed XCorr-HR-SpO₂ in relation to central apnea with bradycardia and desaturation (ABD), BD with or without central apnea (BD), and percent time in periodic breathing (PB) throughout the neonatal intensive care unit (NICU) stay (75 infant-years). We reviewed 100 days with extremely high XCorr-HR-SpO₂ (>0.7) and control days for clinical associations. Next, we identified all cases of late-onset septicemia (LOS) and necrotizing enterocolitis (NEC) and analyzed change in XCorr-HR-SpO₂ before diagnosis.

RESULTS

 Mean XCorr-HR-SpO₂ was ∼0.10, and increasing XCorr-HR-SpO₂ was associated with increasing ABD, BD, and PB (correlation coefficients >0.93). Days with maximum XCorr-HR-SpO₂ >0.7 were more likely to have an adverse event than control days (49% versus 13%). In 93 cases of LOS or NEC, there was a 67% increase in XCorr-HR-SpO₂ in the 24-hour period prior to diagnosis compared with the previous day (p < 0.01).

CONCLUSION

 High XCorr-HR-SpO₂ is associated with apnea and adverse events including LOS and NEC.

Contribution of relative leptin and adiponectin deficiencies in premature infants to chronic intermittent hypoxia: Exploring a new hypothesis

Chronic intermittent hypoxia (CIH) occurs frequently in premature infants who have apnea of prematurity. Immaturity of the respiratory network from low central respiratory drive and the greater contribution of the carotid body on baseline breathing leads to respiratory instability in premature infants presenting as apnea and periodic breathing. During the 2nd week after birth, the smallest and the youngest premature infants have increased frequency of apnea and periodic breathing and associated oxygen desaturations that can persist for weeks after birth. CIH increases the production of reactive oxygen species that causes tissue damage. Premature infants have decreased capacity to scavenge reactive oxygen species. Oxidative injury is the cause of many of the co-morbidities that are seen in premature infants. In this review we discuss who low fat mass and the resulting relative deficiencies in leptin and adiponectin could contribute to the increase frequency of oxygen desaturations that occurs days after birth in the smallest and youngest premature infants. Leptin is a central respiratory stimulant and adiponectin protects the lung from vascular leak, oxidative injury and vascular remodeling.

Eupnea, tachypnea, and autoresuscitation in a closed-loop respiratory control model

How sensory information influences the dynamics of rhythm generation varies across systems, and general principles for understanding this aspect of motor control are lacking. Determining the origin of respiratory rhythm generation is challenging because the mechanisms in a central circuit considered in isolation may be different from those in the intact organism. We analyze a closed-loop respiratory control model incorporating a central pattern generator (CPG), the Butera-Rinzel-Smith (BRS) model, together with lung mechanics, oxygen handling, and chemosensory components. We show that 1) embedding the BRS model neuron in a control loop creates a bistable system; 2) although closed-loop and open-loop (isolated) CPG systems both support eupnea-like bursting activity, they do so via distinct mechanisms; 3) chemosensory feedback in the closed loop improves robustness to variable metabolic demand; 4) the BRS model conductances provide an autoresuscitation mechanism for recovery from transient interruption of chemosensory feedback; and 5) the in vitro brain stem CPG slice responds to hypoxia with transient bursting that is qualitatively similar to in silico autoresuscitation. Bistability of bursting and tonic spiking in the closed-loop system corresponds to coexistence of eupnea-like breathing, with normal minute ventilation and blood oxygen level and a tachypnea-like state, with pathologically reduced minute ventilation and critically low blood oxygen. Disruption of the normal breathing rhythm, through either imposition of hypoxia or interruption of chemosensory feedback, can push the system from the eupneic state into the tachypneic state. We use geometric singular perturbation theory to analyze the system dynamics at the boundary separating eupnea-like and tachypnea-like outcomes.NEW & NOTEWORTHY A common challenge facing rhythmic biological processes is the adaptive regulation of central pattern generator (CPG) activity in response to sensory feedback. We apply dynamical systems tools to understand several properties of a closed-loop respiratory control model, including the coexistence of normal and pathological breathing, robustness to changes in metabolic demand, spontaneous autoresuscitation in response to hypoxia, and the distinct mechanisms that underlie rhythmogenesis in the intact control circuit vs. the isolated, open-loop CPG.

Impact of Infant-Polysomnography Studies on Discharge Management and Outcomes: A 5 Year Experience from a Tertiary Care Unit

OBJECTIVE

To evaluate the impact of infant-polysomnography studies performed in the NICU on management and outcomes.

STUDY DESIGN

Retrospective study to collect demographics and data on infant-polysomnography studies between Jan 2010 to Dec 2014.

RESULTS

110 premature neonates had polysomnography study performed at 36.9 ± 2.5 weeks post menstrual age. Almost all the studies were read as abnormal and 95% of the studied infants were discharged home on a cardiorespiratory monitor. 20% of the subjects had apnea >20 s, 18% had apnea of 15-20 s and 50% of infants had apnea of 10-15 s. 24.5% infants were discharged home on caffeine, 28% on metoclopramide and 24% on antacids. There were 11 readmissions for apparent life threatening events with no until 6 month-corrected age. There was no association between polysomnography results and readmission. There was a decline in polysomnography studies performed each year.

CONCLUSION

Cardiorespiratory monitoring, medications and polysomnography studies do not predict outcomes.

Clinical associations with immature breathing in preterm infants: part 2-periodic breathing

BACKGROUND

Periodic breathing (PB) is a normal immature breathing pattern in neonates that, if extreme, may be associated with pathologic conditions.

METHODS

We used our automated PB detection system to analyze all bedside monitor chest impedance data on all infants <35 wk' gestation in the University of Virginia Neonatal Intensive Care Unit from 2009-2014 (n = 1,211). Percent time spent in PB was calculated hourly (>50 infant-years' data). Extreme PB was identified as a 12-h period with PB >6 SDs above the mean for gestational age (GA) and postmenstrual age and >10% time in PB.

RESULTS

PB increased with GA, with the highest amount in infants 30-33 wk' GA at about 2 wk' chronologic age. Extreme PB was identified in 76 infants and in 45% was temporally associated with clinical events including infection or necrotizing enterocolitis (NEC), immunizations, or caffeine discontinuation. In 8 out of 28 cases of septicemia and 10 out of 21 cases of NEC, there was a >2-fold increase in %PB over baseline on the day prior to diagnosis.

CONCLUSION

Infants <35 wk GA spend, on average, <6% of the time in PB. An acute increase in PB may reflect illness or physiological stressors or may occur without any apparent clinical event.

Clinical associations of immature breathing in preterm infants: part 1-central apnea

BACKGROUND

Apnea of prematurity (AOP) is nearly universal among very preterm infants, but neither the apnea burden nor its clinical associations have been systematically studied in a large consecutive cohort.

METHODS

We analyzed continuous bedside monitor chest impedance and electrocardiographic waveforms and oxygen saturation data collected on all neonatal intensive care unit (NICU) patients <35 wk gestation from 2009 to 2014 (n = 1,211; >50 infant-years of data). Apneas, with bradycardia and desaturation (ABDs), defined as central apnea ≥10 s associated with both bradycardia <100 bpm and oxygen desaturation <80%, were identified using a validated automated algorithm.

RESULTS

Number and duration of apnea events decreased with increasing gestational age (GA) and postmenstrual age (PMA). ABDs were more frequent in infants <31 wk GA at birth but were not more frequent in those with severe retinopathy of prematurity (ROP), bronchopulmonary dysplasia (BPD), or severe intraventricular hemorrhage (IVH) after accounting for GA. In the day before diagnosis of late-onset septicemia and necrotizing enterocolitis, ABD events were increased in some infants. Many infants continued to experience short ABD events in the week prior to discharge home.

CONCLUSION

Frequency of apnea events is a function of GA and PMA in infants born preterm, and increased apnea is associated with acute but not with chronic pathologic conditions.

Stochastic modeling of central apnea events in preterm infants

A near-ubiquitous pathology in very low birth weight infants is neonatal apnea, breathing pauses with slowing of the heart and falling blood oxygen. Events of substantial duration occasionally occur after an infant is discharged from the neonatal intensive care unit (NICU). It is not known whether apneas result from a predictable process or from a stochastic process, but the observation that they occur in seemingly random clusters justifies the use of stochastic models. We use a hidden-Markov model to analyze the distribution of durations of apneas and the distribution of times between apneas. The model suggests the presence of four breathing states, ranging from very stable (with an average lifetime of 12 h) to very unstable (with an average lifetime of 10 s). Although the states themselves are not visible, the mathematical analysis gives estimates of the transition rates among these states. We have obtained these transition rates, and shown how they change with post-menstrual age; as expected, the residence time in the more stable breathing states increases with age. We also extrapolated the model to predict the frequency of very prolonged apnea during the first year of life. This paradigm-stochastic modeling of cardiorespiratory control in neonatal infants to estimate risk for severe clinical events-may be a first step toward personalized risk assessment for life threatening apnea events after NICU discharge.