Statistical methods for predicting e-cigarette use events based on beat-to-beat interval (BBI) data collected from wearable devices.

The prevalence of e-cigarette use among young adults in the USA is high (14%). Although the majority of users plan to quit vaping, the motivation to make a quit attempt is low and available support during a quit attempt is limited. Using wearable sensors to collect physiological data (eg, heart rate) holds promise for capturing the right timing to deliver intervention messages. This study aims to fill the current knowledge gap by proposing statistical methods to (1) de-noise beat-to-beat interval (BBI) data from smartwatches worn by 12 young adult regular e-cigarette users for 7 days; and (2) summarize the de-noised data by event and control segments. We also conducted a comprehensive review of conventional methods for summarizing heart rate variability (HRV) and compared their performance with the proposed method. The results show that the proposed singular spectrum analysis (SSA) can effectively de-noise the highly variable BBI data, as well as quantify the proportion of total variation extracted. Compared to existing HRV methods, the proposed second order polynomial model yields the highest area under the curve (AUC) value of 0.76 and offers better interpretability. The findings also indicate that the average heart rate before vaping is higher and there is an increasing trend in the heart rate before the vaping event. Importantly, the development of increasing heart rate observed in this study implies that there may be time to intervene as this physiological signal emerges. This finding, if replicated in a larger scale study, may inform optimal timings for delivering messages in future intervention.

Information Based Similarity Analysis of Oxygen Saturation Recordings to Detect Pulmonary Hypertension in Preterm Infants.

Pulmonary hypertension (PH) is a complex cardiovascular condition associated with multiple morbidities and mortality risk in preterm infants. PH often complicates the clinical course of infants who have bronchopulmonary dysplasia (BPD), a more common lung disease in these neonates, causing respiratory deterioration and an even higher risk of mortality. While risk factors and prevalence of PH are not yet well defined, early screening and management of PH in infants with BPD are recommended by consensus guidelines from the American Heart Association. In this study, we propose a screening method for PH by applying a signal analysis technique to oxygen saturation in infants. Oxygen saturation data from infant groups with BPD (41 with and 60 without PH), recorded prior to their clinical PH diagnosis were analyzed in this study. An information-based similarity approach was applied to quantify the regularity of SpO2 fluctuations represented as binary words between adjacent five-minute segments. Similarity indices (SI) were observed to be lower in subjects with PH compared to those with BPD alone (p<0.001). These measures were also assessed for performance in screening for PH. SI of 7-bit words, exhibited 80% detection accuracy, 76% sensitivity and specificity of 83%. This index also exhibited a cross-validated mean (SD) F1-score of 0.80 (0.08) ensuring that sensitivity and recall of the screening were balanced. Similarity analysis of oxygen saturation patterns is a novel technique that can be potentially developed into a signal based early PH detection method to support clinical decision and care in this vulnerable population.

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.

Intermittent Hypoxemia and Bronchopulmonary Dysplasia with Pulmonary Hypertension in Preterm Infants.

Rationale: Bedside biomarkers that allow early identification of infants with bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) are critically important, given the higher risk of death in these infants. Objectives: We hypothesized that infants with BPD-PH have patterns of intermittent hypoxemia (IH) that differ from infants with BPD without PH. Methods: We conducted a matched case-control study of extremely preterm infants from 22 weeks 0 days to 28 weeks 6 days born between 2018 and 2020 at the University of Alabama at Birmingham. BPD-PH status was determined using echocardiographic data performed after postnatal Day 28. Physiologic data were compared between infants with BPD-PH (cases) and BPD alone (control subjects). Receiver operating characteristic (ROC) analysis estimated the predictive ability of cumulative hypoxemia, desaturation frequency, and duration of intermittent hypoxemic events in the week preceding echocardiography to discriminate between cases and control subjects. Measurements and Main Results: Forty infants with BPD-PH were compared with 40 infants with BPD alone. Infants with and without PH had a similar frequency of IH events, but infants with PH had more prolonged hypoxemic events for desaturations below 80% (7 s vs. 6 s; P = 0.03) and 70% (105 s vs. 58 s; P = 0.008). Among infants with BPD-PH, infants who died had longer hypoxemic events below 70% (145 s vs. 72 s; P = 0.01). Using the duration of hypoxemic events below 70%, the areas under the ROC curves for diagnosis of BPD-PH and death in BPD-PH infants were 0.71 and 0.77, respectively. Conclusions: Longer duration of intermittent hypoxemic events was associated both with a diagnosis of BPD-PH and with death among infants with BPD-PH.

Using wearable technology to detect prescription opioid self-administration.

ABSTRACT: Appropriate monitoring of opioid use in patients with pain conditions is paramount, yet it remains a very challenging task. The current work examined the use of a wearable sensor to detect self-administration of opioids after dental surgery using machine learning. Participants were recruited from an oral and maxillofacial surgery clinic. Participants were 46 adult patients (26 female) receiving opioids after dental surgery. Participants wore Empatica E4 sensors during the period they self-administered opioids. The E4 collected physiological parameters including accelerometer x-, y-, and z-axes, heart rate, and electrodermal activity. Four machine learning models provided validation accuracies greater than 80%, but the bagged-tree model provided the highest combination of validation accuracy (83.7%) and area under the receiver operating characteristic curve (0.92). The trained model had a validation sensitivity of 82%, a specificity of 85%, a positive predictive value of 85%, and a negative predictive value of 83%. A subsequent test of the trained model on withheld data had a sensitivity of 81%, a specificity of 88%, a positive predictive value of 87%, and a negative predictive value of 82%. Results from training and testing model of machine learning indicated that opioid self-administration could be identified with reasonable accuracy, leading to considerable possibilities of the use of wearable technology to advance prevention and treatment.

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.

Environmental or Nasal Cannula Supplemental Oxygen for Preterm Infants: A Randomized Cross-Over Trial.

OBJECTIVE: To test the hypothesis that environmental compared with nasal cannula oxygen decreases episodes of intermittent hypoxemia (oxygen saturations <85% for ≥10 seconds) in preterm infants on supplemental oxygen by providing a more stable hypopharyngeal oxygen concentration. STUDY DESIGN: This was a single center randomized crossover trial with a 1:1 parallel allocation to order of testing. Preterm infants on supplemental oxygen via oxygen environment maintained by a servo-controlled system or nasal cannula with flow rates ≤1.0 L per kg per minute were crossed over every 24 hours for 96 hours. Data were collected electronically to capture real time numeric and waveform data from patient monitors. RESULTS: Twenty-five infants with gestational age of 27 ± 2 weeks (mean ± SD) and a birth weight of 933 ± 328 g were studied at postnatal day 36 ± 26. The number of episodes of intermittent hypoxemia per 24 hours was 117 ± 77 (median, 98; range, 4-335) with oxygen environment vs 130 ± 63 (median, 136; range, 16-252) with nasal cannula (P = .002). Infants on oxygen environment compared with nasal cannula also had decreased episodes of severe intermittent hypoxemia (P = .005). Infants on oxygen environment compared with nasal cannula had a lower proportion of time with oxygen saturations <85% (.05 ± .03 vs .06 ± .03, P < .001), and a lower coefficient of variation of oxygen saturation (P = .02). CONCLUSIONS: In preterm infants receiving supplemental oxygen, servo-controlled oxygen environment decreases hypoxemia compared with nasal cannula. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02794662.

A role for the habenula in the regulation of locomotor activity cycles.

Although much is known about the regulation of the circadian rest-activity cycle by the hypothalamic suprachiasmatic nucleus in nocturnal rodents, little is known about the neural substrates that regulate the temporal organization of nocturnal activity within the active phase. In this report, data are presented in Syrian hamsters to implicate the habenula - believed to be involved in motivation, reward and motor control--as a candidate site for such a role. First, by examining hamsters during the day and night and by introducing a 'novel' running wheel in order to induce daytime motor activity, we showed that immunoreactive c-Fos expression in the lateral and medial habenula is related to motor activity/arousal. Second, by transecting the habenula's major efferent pathway (fasciculus retroflexus), we showed that the interruption of habenula neural output alters the daily amount of motor activity, lengthens the period of the circadian rest-activity rhythm and disrupts the species-typical pattern of nocturnal motor activity, measured as either wheel-running behavior or general locomotor activity. Instead of the usual pattern of night-time locomotion, characterized by a prolonged bout of elevated activity in the early night followed by shorter sporadic bouts or the cessation of activity altogether, lesioned animals exhibited a more homogeneous, undifferentiated temporal profile extending across the night. These data suggest a previously unrecognized function of the habenula whereby it regulates the temporal pattern of activity occurring within a circadian rest-activity window set by the suprachiasmatic nucleus.