Miles S. Ellenby

An automatic beat detection algorithm for pressure signals

Beat detection algorithms have many clinical applications including pulse oximetry, cardiac arrhythmia detection, and cardiac output monitoring. Most of these algorithms have been developed by medical device companies and are proprietary. Thus, researchers who wish to investigate pulse contour analysis must rely on manual annotations or develop their own algorithms. We designed an automatic detection algorithm for pressure signals that locates the first peak following each heart beat. This is called the percussion peak in intracranial pressure (ICP) signals and the systolic peak in arterial blood pressure (ABP) and pulse oximetry (SpO/sub 2/) signals. The algorithm incorporates a filter bank with variable cutoff frequencies, spectral estimates of the heart rate, rank-order nonlinear filters, and decision logic. We prospectively measured the performance of the algorithm compared to expert annotations of ICP, ABP, and SpO/sub 2/ signals acquired from pediatric intensive care unit patients. The algorithm achieved a sensitivity of 99.36% and positive predictivity of 98.43% on a dataset consisting of 42,539 beats.

A novel algorithm to estimate the pulse pressure variation index /spl Delta/PP

We designed a new methodology to estimate the pulse pressure variation index (/spl Delta/PP) in arterial blood pressure (ABP). The method uses automatic detection algorithms, kernel smoothing, and rank-order filters to continuously estimate /spl Delta/PP. The technique can be used to estimate /spl Delta/PP from ABP alone, eliminating the need for simultaneously acquiring airway pressure.

Physiologic data acquisition system and database for the study of disease dynamics in the intensive care unit.

ObjectiveTo describe a real-time, continuous physiologic data acquisition system for the study of disease dynamics in the intensive care unit. DesignDescriptive report. SettingA 16-bed pediatric intensive care unit in a tertiary care children’s hospital. PatientsA total of 170 critically ill or injured pediatric patients. InterventionsNone. Main Outcome MeasuresNone. ResultsWe describe a computerized data acquisition and analysis system for the study of critical illness and injury from the perspective of complex dynamic systems. Both parametric (1 Hz) and waveform (125–500 Hz) signals are recorded and analyzed. Waveform data include electrocardiogram, respiration, systemic arterial pressure (invasive and noninvasive), central venous pressure, pulmonary arterial pressure, left and right atrial pressures, intracranial pressure, body temperature, and oxygen saturation. Details of the system components are explained and examples are given from the resultant physiologic database of signal processing algorithms and signal analyses using linear and nonlinear metrics. ConclusionsWe have successfully developed a real-time, continuous physiologic data acquisition system that can capture, store, and archive data from pediatric intensive care unit patients for subsequent time series analysis of dynamic changes in physiologic state. The physiologic signal database generated from this system is available for analysis of dynamic changes caused by critical illness and injury.

The impact of telemedicine intensivist support and a pediatric hospitalist program on a community hospital

BACKGROUND Because of centralization of care, pediatric patients often require transfer for subspecialty care. We evaluated the impact of telemedicine critical care consultation and a pediatric hospitalist program on enabling patients to remain at a community hospital. PATIENTS AND METHODS This is a retrospective chart review of pediatric patients at a community hospital receiving critical care consultation from a tertiary childrens hospital from January 2006 to October 2009. Patient cohorts differed by modality of intensivist consultation (telephone versus telemedicine) and modality of inpatient ward care at the community hospital (primary care physician versus hospitalist). Patients were compared for differences in transfer rate and rate of diversion from the pediatric intensive care unit to the tertiary ward. RESULTS One hundred fifty-three charts were analyzed: 41 from prior to hospitalist and telemedicine implementation (Cohort 1), 56 from post-implementation of telemedicine but pre-hospitalist program (Cohort 2), and 56 after implementation of both the telemedicine and hospitalist programs (Cohort 3). Baseline data did not differ among cohorts. Transfer rates after intensivist consultation were lower after implementation of telemedicine consultation (100%, 85.7%, and 87.5% in Cohorts 1-3, respectively; p=0.04). The proportion of transferred patients who were diverted to the tertiary ward decreased over time (19.5%, 14.5%, and 6.1% in Cohorts 1-3, respectively; p=0.003). CONCLUSIONS Telemedicine consultation between pediatric intensivists and community hospital physicians combined with a pediatric hospitalist program at the community hospital has the potential to improve triage of pediatric patients and reduce the need to transfer patients.

Design and implementation of a portable physiologic data acquisition system

Objective: To describe and report the reliability of a portable, laptop-based, real-time, continuous physiologic data acquisition system (PDAS) that allows for synchronous recording of physiologic data, clinical events, and event markers at the bedside for physiologic research studies in the intensive care unit. Design: Descriptive report of new research technology. Setting: Adult and pediatric intensive care units in three tertiary care academic hospitals. Patients: Sixty-four critically ill and injured patients were studied, including 34 adult (22 males and 12 females) and 30 pediatric (19 males and 11 females). Interventions: None. Measurements and Main Results: Data transmission errors during bench and field testing were measured. The PDAS was used in three separate research studies, by multiple users, and for repeated recordings of the same set of signals at various intervals for different lengths of time. Both parametric (1 Hz) and waveform (125–500 Hz) signals were recorded and analyzed. Details of the PDAS components are explained and examples are given from the three experimental physiology-based protocols. Waveform data include electrocardiogram, respiration, systemic arterial pressure (invasive and noninvasive), oxygen saturation, central venous pressure, pulmonary arterial pressure, left and right atrial pressures, intracranial pressure, and regional cerebral blood flow. Bench and field testing of the PDAS demonstrated excellent reliability with 100% accuracy and no data transmission errors. The key feature of simultaneously capturing physiologic signal data and clinical events (e.g., changes in mechanical ventilation, drug administration, clinical condition) is emphasized. Conclusions: The PDAS provides a reliable tool to record physiologic signals and associated clinical events on a second-to-second basis and may serve as an important adjunctive research tool in designing and performing clinical physiologic studies in critical illness and injury.

The role of telemedicine in pediatric critical care.

Telemedicine technologies involve real-time, live, interactive video and audio communication and allow pediatric critical care physicians to have a virtual presence at the bedsides of critically ill children. Telemedicine use is increasing and will be a common in remote emergency departments, inpatient wards, and intensive care units for pediatric care. Hospitals and physicians that use telemedicine technologies provide higher quality of care, are more efficient in resource use with improved cost-effectiveness, and have higher satisfaction among patients, parents, and remote providers. More research will result in improved access to pediatric critical care expertise.

Precursors to rapid elevations in intracranial pressure

Intracranial pressure (ICP) monitoring and management have substantially improved the outcome of patients with traumatic brain injury (TBI). However, rapid elevations in ICP remain a significant problem as they may lead to secondary brain injury and worse outcome due to cerebral ischemia. Current therapy is targeted towards treating rapid ICP elevations after they occur. Ideally, anticipatory treatment to obviate any elevation in ICP could occur if reliable precursors to ICP elevation were determined. In this paper, we report evidence for a physiologic transition zone prior to rapid elevations in ICP. We found that in thirty-three episodes of ICP elevation recorded from eleven patients, there was a statistically consistent decrease in the cardiac component of the ICP signal and the coefficient of correlation between the ICP trend and the pulse amplitude. We conclude that specific ICP signal metrics may serve as precursors that characterize the transition zone prior to a rapid elevation and may enable prediction of these elevations up to thirty seconds ahead.

Modeling respiration from blood pressure waveform signals: an independent component approach

We describe a method for extracting the additive effect of respiration from arterial blood pressure and central venous pressure waveform signals. Our method estimates a finite impulse response (FIR) separating filter using an independent component approach, analogous to minimizing the coherence of the separated components. We compare the extracted respiration component with the impedance based respiration signal and with a respiration estimate extracted using an LMS-optimal bandpass filter of comparable order.

Update on intensive care ECG and cardiac event monitoring.

This brief review is aimed primarily as a resource for the clinician and summarizes recent advancements in electrocardiographic monitoring in the intensive care unit. Emphasis is placed on recent advances in ICU ECG and cardiac event monitoring with particular attention to arrhythmia detection in patients following myocardial infarction. Specific topics addressed include: clinical indicators of impending arrhythmic events and sudden death, signal averaged ECG, QT dispersion, ST segment fluctuation, T-wave alternans, QT interval beat-to-beat variability, heart rate variability, and advances in automated arrhythmia detection.

A new resource for independent and blinded assessment of QRS detection algorithms

We describe a new resource for developers of QRS detection algorithms that provides a standardized assessment of algorithm performance that is blinded, objective, independent, and reproducible. This overcomes the problems of using a single data set for both development and assessment that leads to favorably biased estimates of performance.