RESUMO
OBJECTIVE: In 2006 the apnea of prematurity (AOP) consensus group identified inaccurate counting of apnea episodes as a major barrier to progress in AOP research. We compare nursing records of AOP to events detected by a clinically validated computer algorithm that detects apnea from standard bedside monitors. STUDY DESIGN: Waveform, vital sign, and alarm data were collected continuously from all very low-birth-weight infants admitted over a 25-month period, analyzed for central apnea, bradycardia, and desaturation (ABD) events, and compared with nursing documentation collected from charts. Our algorithm defined apnea as > 10 seconds if accompanied by bradycardia and desaturation. RESULTS: Of the 3,019 nurse-recorded events, only 68% had any algorithm-detected ABD event. Of the 5,275 algorithm-detected prolonged apnea events > 30 seconds, only 26% had nurse-recorded documentation within 1 hour. Monitor alarms sounded in only 74% of events of algorithm-detected prolonged apnea events > 10 seconds. There were 8,190,418 monitor alarms of any description throughout the neonatal intensive care unit during the 747 days analyzed, or one alarm every 2 to 3 minutes per nurse. CONCLUSION: An automated computer algorithm for continuous ABD quantitation is a far more reliable tool than the medical record to address the important research questions identified by the 2006 AOP consensus group.
Assuntos
Algoritmos , Apneia/diagnóstico , Diagnóstico por Computador , Doenças do Prematuro/diagnóstico , Monitorização Fisiológica/métodos , Eletrocardiografia , Humanos , Recém-Nascido , Recém-Nascido Prematuro , Unidades de Terapia Intensiva Neonatal , Pletismografia de ImpedânciaRESUMO
BACKGROUND: Infants admitted to the neonatal intensive care unit (NICU), and especially those born with very low birth weight (VLBW; <1,500 g), are at risk for respiratory decompensation requiring endotracheal intubation and mechanical ventilation. Intubation and mechanical ventilation are associated with increased morbidity, particularly in urgent unplanned cases. METHODS: We tested the hypothesis that the systemic response associated with respiratory decompensation can be detected from physiological monitoring and that statistical models of bedside monitoring data can identify infants at increased risk of urgent unplanned intubation. We studied 287 VLBW infants consecutively admitted to our NICU and found 96 events in 51 patients, excluding intubations occurring within 12 h of a previous extubation. RESULTS: In order of importance in a multivariable statistical model, we found that the characteristics of reduced O(2) saturation, especially as heart rate was falling; increased heart rate correlation with respiratory rate; and the amount of apnea were all significant independent predictors. The predictive model, validated internally by bootstrap, had a receiver-operating characteristic area of 0.84 ± 0.04. CONCLUSION: We propose that predictive monitoring in the NICU for urgent unplanned intubation may improve outcomes by allowing clinicians to intervene noninvasively before intubation is required.
Assuntos
Evento Inexplicável Breve Resolvido/terapia , Terapia Intensiva Neonatal/métodos , Intubação Intratraqueal/métodos , Modelos Biológicos , Monitorização Fisiológica/métodos , Apneia/fisiopatologia , Área Sob a Curva , Frequência Cardíaca , Humanos , Recém-Nascido , Análise Multivariada , Oxigênio/metabolismoRESUMO
INTRODUCTION: Measurement of pH is one of the simplest and most technically validated biomarkers studied in exhaled breath condensate (EBC). The pH of EBC has been found to be lower than controls in many respiratory disorders. Published data from normal control subjects have been reasonably consistent, but the data sets are not large. This study was undertaken to establish normative EBC pH reference values. PARTICIPANTS: Four hundred four healthy subjects of all ages were enrolled. INTERVENTIONS: Each participant provided a single EBC sample using a disposable collector at modest temperature so that EBC was collected as a liquid. MEASUREMENTS AND RESULTS: Samples of EBC were bubbled with argon gas to standardize for carbon dioxide, and pH was recorded with a calibrated and validated glass microelectrode on stabilization. The median EBC pH was 8.0 with interquartile (25 to 75%) range of 7.8 to 8.1. There were no differences based on age, sex, or race. The distribution is skewed, with 6.4% of EBC samples having a pH range < 7.4. CONCLUSIONS: An extensive normal data set now exists that reveals EBC pH is maintained in a modestly alkaline and tight range in subjects who consider themselves healthy.
Assuntos
Testes Respiratórios , Expiração , Adolescente , Adulto , Idoso , Biomarcadores/análise , Criança , Feminino , Humanos , Concentração de Íons de Hidrogênio , Masculino , Pessoa de Meia-Idade , Valores de Referência , Doenças Respiratórias/diagnósticoRESUMO
RATIONALE AND OBJECTIVES: The purpose of this study is to determine hyperpolarized helium 3 (HHe) magnetic resonance (MR) findings of the lung in patients with cystic fibrosis (CF) compared with healthy subjects and determine whether HHe MR can detect changes after bronchodilator therapy or mechanical airway mucus clearance treatment. MATERIALS AND METHODS: Thirty-one subjects, 16 healthy volunteers and 15 patients with CF, underwent HHe lung ventilation MR imaging and spirometry at baseline. Eight patients with CF then were treated with nebulized albuterol, after which a follow-up HHe MR scan was obtained. Subsequently, recombinant human deoxyribonuclease (DNase) treatment and chest physical therapy were performed in these eight subjects, followed by a third HHe MR scan. For each MR study, the number of ventilation defects was scored by a human reader. RESULTS: Patients with CF had significantly more HHe MR ventilation defects per image than healthy subjects (mean, 8.2 defects in patients with CF vs 1.6 defects in healthy subjects; P < .05). Even the four subjects with CF with a normal forced expiratory volume in 1 second had significantly more ventilation defects than healthy subjects (mean, 6.5 defects in these patients with CF; P = .0002). After treatment with albuterol, there was a small, but statistically significant, decrease in number of ventilation defects (mean, 9.6-8.0 defects; P = .025). After DNase and chest physical therapy, there was a trend toward increasing ventilation defects (mean, 8.3 defects; P = .096), but with a residual net improvement relative to baseline. CONCLUSION: In patients with CF, HHe MR ventilation defects correlate with spirometry, change with treatment, and are elevated in number in patients with CF with normal spirometry results. Thus, HHe MR appears to possess many of the characteristics required of a biomarker for pulmonary CF and may be useful in the evaluation of CF pulmonary disease severity or progression.
Assuntos
Fibrose Cística/fisiopatologia , Fibrose Cística/terapia , Hélio , Pulmão/fisiopatologia , Imageamento por Ressonância Magnética , Administração por Inalação , Adulto , Albuterol/uso terapêutico , Broncodilatadores/uso terapêutico , Desoxirribonuclease I/uso terapêutico , Feminino , Humanos , Isótopos , Masculino , Ventilação Pulmonar , Proteínas Recombinantes/uso terapêutico , Testes de Função Respiratória , Terapia Respiratória , EspirometriaRESUMO
Apnea of prematurity is an important and common clinical problem, and is often the rate-limiting process in NICU discharge. Accurate detection of episodes of clinically important neonatal apnea using existing chest impedance (CI) monitoring is a clinical imperative. The technique relies on changes in impedance as the lungs fill with air, a high impedance substance. A potential confounder, however, is blood coursing through the heart. Thus, the cardiac signal during apnea might be mistaken for breathing. We report here a new filter to remove the cardiac signal from the CI that employs a novel resampling technique optimally suited to remove the heart rate signal, allowing improved apnea detection. We also develop an apnea detection method that employs the CI after cardiac filtering. The method has been applied to a large database of physiological signals, and we prove that, compared to the presently used monitors, the new method gives substantial improvement in apnea detection.