Design and implementation of a portable physiologic data acquisition system

Exploring the clinical relevance of vital signs statistical calculations from a new-generation clinical information system

New information on the intensive care applications of new generation 'high-density data clinical information systems' (HDDCIS) is increasingly being published in the academic literature. HDDCIS avoid data loss from bedside equipment and some provide vital signs statistical calculations to promote quick and easy evaluation of patient information. Our objective was to study whether manual records of continuously monitored vital signs in the Paediatric Intensive Care Unit could be replaced by these statistical calculations. Here we conducted a prospective observational clinical study in paediatric patients with severe diabetic ketoacidosis, using a Medlinecare® HDDCIS, which collects information from bedside equipment (1 data point per parameter, every 3-5 s) and automatically provides hourly statistical calculations of the central trend and sample dispersion. These calculations were compared with manual hourly nursing records for patient heart and respiratory rates and oxygen saturation. The central tendency calculations showed identical or remarkably similar values and strong correlations with manual nursing records. The sample dispersion calculations differed from the manual references and showed weaker correlations. We concluded that vital signs calculations of central tendency can replace manual records, thereby reducing the bureaucratic burden of staff. The significant sample dispersion calculations variability revealed that automatic random measurements must be supervised by healthcare personnel, making them inefficient.

Simultaneous Heart Rate Variability and Electroencephalographic Monitoring in Children in the Emergency Department

Changes in heart rate variability (HRV) and electroencephalographic (EEG) background are promising tools for risk stratification and outcome prediction in children seen in the Emergency Department (ED). Novel monitoring technologies offer an opportunity for determining the clinical value of these physiologic variables, however, studies evaluating these measurements obtained in the Pediatric ED are sparse. The current study used a single center, prospective, observational cohort study of HRV and EEG as early predictors of outcome in children with acute trauma. ECG and HRV data were successfully collected in 167 subjects and simultaneous collection of ECG and EEG data using a wireless monitoring device was piloted in 17 patients with 15 patients having EEG data rated as appropriate for clinical interpretation. The mean time from ED arrival to ECG and EEG recording start was 7.5 (SD 11.6) and 34.5 (SD 15.5) minutes, respectively. The mean time required for EEG electrode placement was 9.3 min (SD 5.8 min). Results showed recording early HRV and EEG is feasible in children with acute injury seen in the ED. This study suggests that high consent rates are possible with the adequate research infrastructure and physiologic variables may offer an early, non-invasive marker for injury stratification and prognosis in children.

Information technology in critical care: review of monitoring and data acquisition systems for patient care and research

There is a broad consensus that 21st century health care will require intensive use of information technology to acquire and analyze data and then manage and disseminate information extracted from the data. No area is more data intensive than the intensive care unit. While there have been major improvements in intensive care monitoring, the medical industry, for the most part, has not incorporated many of the advances in computer science, biomedical engineering, signal processing, and mathematics that many other industries have embraced. Acquiring, synchronizing, integrating, and analyzing patient data remain frustratingly difficult because of incompatibilities among monitoring equipment, proprietary limitations from industry, and the absence of standard data formatting. In this paper, we will review the history of computers in the intensive care unit along with commonly used monitoring and data acquisition systems, both those commercially available and those being developed for research purposes.

Intracranial pressure and cerebral perfusion pressure responses to head elevation changes in pediatric traumatic brain injury

OBJECTIVES

To determine the effect of and dynamic interaction between head elevation on intracranial pressure and cerebral perfusion pressure in severe pediatric traumatic head injury.

DESIGN

Prospective, randomized, interventional cohort study.

SETTING

Two tertiary pediatric critical care referral units.

PATIENTS

Ten children admitted with severe traumatic brain injury defined as Glasgow Coma Score ≤ 8 necessitating intracranial pressure monitoring (10 yrs ± 5 SD; range 2-16 yrs).

INTERVENTIONS

Head elevation was randomly increased or decreased between 0 and 40 degrees from baseline level (30 degrees) in increments or decrements of 10 degrees.

MEASUREMENTS AND MAIN RESULTS

Intracranial pressure and arterial blood pressure were continuously recorded in combination with time-stamped clinical notations. Data were available for analysis in eight subjects (seven males and one female; mean age, 10 yrs ± SD 5; range, 2-16 yrs) during 18 protocol sessions. This resulted in a total of 66 head-of-the-bed challenges. To compare results for a given change in head-of-the-bed elevation across age, we transformed head-of-the-bed angle to change in height (cm) at the level of Monro's foramen. An increase in head elevation of 10 cm resulted in an average change in intracranial pressure of -3.9 mm Hg (SD ± 3.2 mm Hg; p < .001), whereas cerebral perfusion pressure remained unchanged (0.1 ± 5.6 mm Hg; p = .957). Individual subjects showed marked variability in intracranial pressure change (range, -8.4 to +1.9 mm Hg/10 cm). The overall regression analysis for intracranial pressure response was change in intracranial pressure = -0.39/cm Δh, r2 = 0.42, and p < .001, where Δh is the change in vertical height at the level of foramen of Monro attributable to a change in the head of the bed.

CONCLUSIONS

In severe pediatric traumatic brain injury, the relationship between change in head of the bed and change in intracranial pressure was negative and linear. The lowest intracranial pressure was usually, but not always, achieved at highest head-of-the-bed angles. The effect size of a head-of-the-bed angle change depended, in part, on the subject's height. In contrast, cerebral perfusion pressure was mostly unaffected by head-of-the-bed changes.

Feasibility of continuous multiorgan variability analysis in the intensive care unit

PURPOSE

The aim of the study was to evaluate the feasibility of continuous heart and respiratory rate variability (HRV and RRV, respectively) monitoring in critically ill patients derived from electrocardiogram (ECG) and end-tidal capnography (etCO(2)) waveforms.

METHODS

Thirty-four patients (age, 56.5 ± 15.9 years; Acute Physiology and Chronic Health Evaluation II score, 22.8 ± 6.7) underwent continuous recording of ECG and etCO(2) waveforms from intensive care unit admission and intubation to discharge or maximum of 14 days. Overlapping 5-minute windows were analyzed with a wide range of variability measures (time, frequency, entropy, and scale-invariant and nonlinear domains). Waveform data quality, presence of disconnections and arrhythmias, quality of beat and breath detection, and subsequent variability computations were evaluated.

RESULTS

Patients were enrolled for 11.0 ± 3.6 days. The proportion of missing waveform data among all patients was (median [interquartile range, maximum]) 2.9% (1.3%-9.7%, 36.4%) for ECG and 3.1% (1.1%-11.4%, 84.5%) for etCO(2). Heart rate variability data loss (ie, proportion of windows removed) was 1.3% (1.0%-2.1%, 5.9%) due to disconnection, 0.6% (0.1%-3.9%, 39.5%) due to atrial fibrillation, and 6.6% (1.4%-17.9%, 89.0%) due to data cleaning. Respiratory rate variability data loss was 7.3% (2.9%-11.6%, 47.7%) due to disconnection (or apnea) and 5.5% (2.9%-8.4%, 56.4%) due to cleaning. Continuous individualized multiorgan variability analysis processing resulted in HRV and RRV computations for 81.2% ± 25.0% and 87.5% ± 11.9% of available ECG and etCO(2) waveform data, respectively.

CONCLUSIONS

The quality of continuously recorded ECG and etCO(2) waveforms in critically ill patients is adequate for subsequent continuous variability monitoring in this pilot study. The clinical utility of continuous variability analysis merits further investigation.

Using "off-the-shelf" tools for terabyte-scale waveform recording in intensive care: computer system design, database description and lessons learned

Until now, the creation of massive (long-term and multichannel) waveform databases in intensive care required an interdisciplinary team of clinicians, engineers and informaticians and, in most cases, also design-specific software and hardware development. Recently, several commercial software tools for waveform acquisition became available. Although commercial products and even turnkey systems are now being marketed as simple and effective, the performance of those solutions is not known. The additional expense upfront may be worthwhile if commercial software can eliminate the need for custom software and hardware systems and the associated investment in teams and development. We report the development of a computer system for long-term large-scale recording and storage of multichannel physiologic signals that was built using commercial solutions (software and hardware) and existing hospital IT infrastructure. Both numeric (1 Hz) and waveform (62.5-500 Hz) data were captured from 24 SICU bedside monitors simultaneously and stored in a file-based vital sign data bank (VSDB) during one-year period (total DB size is 4.21TB). In total, vital signs were recorded from 1,175 critically ill patients. Up to six ECG leads, all other monitored waveforms, and all monitored numeric data were recorded in most of the cases. We describe the details of building blocks of our system, provide description of three datasets exported from our VSDB and compare the contents of our VSDB with other available waveform databases. Finally, we summarize lessons learned during recording, storage, and pre-processing of physiologic signals.

A review of physiological simulation models of intracranial pressure dynamics

This paper reviews the literature regarding the development, testing, and application of physiology-based computer simulation models of intracranial pressure dynamics. Detailed comparative information is provided in tabular format about the model variables and logic, any data collected, model testing and validation methods, and model results. Several syntheses are given that summarize the research carried out by influential research teams and researchers, review important findings, and discuss the methods employed, limitations, and opportunities for further research.