Algorithms to qualify respiratory data collected during the transport of trauma patients

We developed a quality indexing system to numerically qualify respiratory data collected by vital-sign monitors in order to support reliable post-hoc mining of respiratory data. Each monitor-provided (reference) respiratory rate (RR(R)) is evaluated, second-by-second, to quantify the reliability of the rate with a quality index (QI(R)). The quality index is calculated from: (1) a breath identification algorithm that identifies breaths of 'typical' sizes and recalculates the respiratory rate (RR(C)); (2) an evaluation of the respiratory waveform quality (QI(W)) by assessing waveform ambiguities as they impact the calculation of respiratory rates and (3) decision rules that assign a QI(R) based on RR(R), RR(C) and QI(W). RR(C), QI(W) and QI(R) were compared to rates and quality indices independently determined by human experts, with the human measures used as the 'gold standard', for 163 randomly chosen 15 s respiratory waveform samples from our database. The RR(C) more closely matches the rates determined by human evaluation of the waveforms than does the RR(R) (difference of 3.2 +/- 4.6 breaths min(-1) versus 14.3 +/- 19.3 breaths min(-1), mean +/- STD, p < 0.05). Higher QI(W) is found to be associated with smaller differences between calculated and human-evaluated rates (average differences of 1.7 and 8.1 breaths min(-1) for the best and worst QI(W), respectively). Establishment of QI(W) and QI(R), which ranges from 0 for the worst-quality data to 3 for the best, provides a succinct quantitative measure that allows for automatic and systematic selection of respiratory waveforms and rates based on their data quality.     

Berg balance scale: intrarater test-retest reliability among older people dependent in activities of daily living and living in residential care facilities

BACKGROUND AND PURPOSE: The Berg Balance Scale (BBS) is frequently used to assess balance in older people, but knowledge is lacking about the absolute reliability of BBS scores. The aim of this study was to investigate the absolute and relative intrarater test-retest reliability of data obtained with the BBS when it is used among older people who are dependent in activities of daily living and living in residential care facilities. SUBJECTS: The participants were 45 older people (36 women and 9 men) who were living in 3 residential care facilities. Their mean age was 82.3 years (SD=6.6, range=68-96), and their mean score on the Mini Mental State Examination was 17.5 (SD=6.3, range=4-30). METHODS: The BBS was assessed twice by the same assessor. The intrarater test-retest reliability assessments were made at approximately the same time of day and with 1 to 3 days in between assessments. Absolute reliability was calculated using an analysis of variance with a 95% confidence level, as suggested by Bland and Altman. Relative reliability was calculated using the intraclass correlation coefficient (ICC). RESULTS: The mean score was 30.1 points (SD=15.9, range=3-53) for the first BBS test and 30.6 points (SD=15.6, range=4-54) for the retest. The mean absolute difference between the 2 tests was 2.8 points (SD=2.7, range=0-11). The absolute reliability was calculated as being 7.7 points, and the ICC was calculated to .97. DISCUSSION AND CONCLUSION: Despite a high ICC value, the absolute reliability showed that a change of 8 BBS points is required to reveal a genuine change in function among older people who are dependent in activities of daily living and living in residential care facilities. This knowledge is important in the clinical setting when evaluating an individual's change in balance function over time in this group of older people.     

Noninvasive measurement of the vital signs of cancer patients with a dual-path microbend fiber sensor

A novel dual-path microbend fiber optic sensor is designed for noninvasive measurement of respiratory rate (RR) and heart rate (HR) for cancer patients. The performance of the microbend fiber sensor is assessed in two groups of cancer patients, cancer patients with pain and without pain, ranging from eighteen to ninety-six years old in a daily observational measurement with the sensor mattress under the mattress of the clinical bed. All the patients received standard clinical monitoring for evaluating the accuracy of our measurement results. The results of our study showed good consistency in the experimental results of RR and HR between the dual-path fiber sensor we proposed and the hospital equipment with average errors of 3.60 beats per minute (bpm) and 1.02 respiration per minute (rpm) in HR and RR measurement in cancer patients with pain and 1.87bpm and 1.27rpm in HR and RR measurement in cancer patients without pain, respectively. In HR monitoring, the single path microbend fiber optic sensor has 8035 minutes of data with a false report rate of 19.09%, while the dual-path microbend fiber optic sensor has 6188 minutes of data with a false report rate of 12.87%. The dual-path sensor has a smaller false report rate compared with the single path sensor due to pre-judgments of data with path 1 and path 2. To our best knowledge, it is the first time to propose and demonstrate a dual-path sensor to reduce the false report rate for HR and RR measurements. The results of the Blend-Altman method showed great agreement between our sensor and hospital standard monitor in HR and RR measurements. The independent sample t-test indicates that the HR of cancer patients may be an effective way to judge whether or not they have cancer pain. Our noninvasive dual-path microbend fiber sensor also showed the advantages of an easy fabrication process, simple structure, and low false report rate.     

Determination of saturation,heart rate,and respiratory rate at forearm using a Nellcor™ forehead SpO<Subscript>2</Subscript>-saturation sensor

Alterations in arterial blood oxygen saturation, heart rate (HR), and respiratory rate (RR) are strongly associated with intra-hospital cardiac arrests and resuscitations. A wireless, easy-to-use, and comfortable method for monitoring these important clinical signs would be highly useful. We investigated whether the Nellcor? OxiMask MAX-FAST forehead sensor could provide data for vital sign measurements when located at the distal forearm instead of its intended location at the forehead to provide improved comfortability and easy placement. In a prospective setting, we recruited 30 patients undergoing surgery requiring postoperative care. At the postoperative care unit, patients were monitored for two hours using a standard patient monitor and with a study device equipped with a Nellcor? Forehead SpO₂ sensor. The readings were electronically recorded and compared in post hoc analysis using Bland–Altman plots, Spearman’s correlation, and root-mean-square error (RMSE). Bland–Altman plot showed that saturation (SpO₂) differed by a mean of ?0.2 % points (SD, 4.6), with a patient-weighted Spearman’s correlation (r) of 0.142, and an RMSE of 4.2 points. For HR measurements, the mean difference was 0.6 bpm (SD, 2.5), r = 0.997, and RMSE = 1.8. For RR, the mean difference was ?0.5 1/min (4.1), r = 0.586, and RMSE = 4.0. The SpO₂ readings showed a low mean difference, but also a low correlation and high RMSE, indicating that the Nellcor? saturation sensor cannot reliably assess oxygen saturation at the forearm when compared to finger PPG measurements.     

Lightweight physiologic sensor performance during pre-hospital care delivered by ambulance clinicians

The aim of this study was to explore the impact of motion generated by ambulance patient management on the performance of two lightweight physiologic sensors. Two physiologic sensors were applied to pre-hospital patients. The first was the Contec Medical Systems CMS50FW finger pulse oximeter, monitoring heart rate (HR) and blood oxygen saturation (SpO2). The second was the RESpeck respiratory rate (RR) sensor, which was wireless-enabled with a Bluetooth^® Low Energy protocol. Sensor data were recorded from 16 pre-hospital patients, who were monitored for 21.2 ± 9.8 min, on average. Some form of error was identified on almost every HR and SpO₂ trace. However, the mean proportion of each trace exhibiting error was <10 % (range <1–50 % for individual patients). There appeared to be no overt impact of the gross motion associated with road ambulance transit on the incidence of HR or SpO₂ error. The RESpeck RR sensor delivered an average of 4.2 (±2.2) validated breaths per minute, but did not produce any validated breaths during the gross motion of ambulance transit as its pre-defined motion threshold was exceeded. However, this was many more data points than could be achieved using traditional manual assessment of RR. Error was identified on a majority of pre-hospital physiologic signals, which emphasised the need to ensure consistent sensor attachment in this unstable and unpredictable environment, and in developing intelligent methods of screening out such error.     

Involvement of immunoglobulin FcgammaRIIA and FcgammaRIIIB gene polymorphisms in susceptibility to rheumatic fever

OBJECTIVES: To assess the impact of the human FcgammaRIIA and FcgammaRIIIB gene polymorphisms on the risk of rheumatic fever (RF). DESIGNS AND METHODS: FcgammaRIIA-R/H-131 and FcgammaRIIIB-NA1/NA2 genotypes were determined using polymerase chain reaction in 66 RF cases and 117 healthy controls in this case control study. RESULTS: Compared with healthy controls, the RR genotype was enriched in the entire group of RF cases (odds ratio [OR] 4.98, 95% confidence interval [95% CI] 1.81-13.70). RF patients were more frequently HR heterozygotes rather than HH homozygotes (OR 3.09 vs. 0.11). The results of this study show that patients who have RF are more likely to have the RR and HR genotypes than control children. These probabilities show that RR is associated with the greatest risk for rheumatic fever and HR is associated with an intermediate risk. For the distribution of FcgammaRIIIB NA2 genotypes, a nonsignificant increase was found in RF patients (39.31% vs. 51.51%; OR 1.64, P = 0.1226). CONCLUSION: The FcgammaRIIA-R/H-131 polymorphism may be an important marker in determining predisposition to RF.     

Quantitative evaluation of diabetic autonomic neuropathy by using heart rate variations--determination of the normal range for the diagnosis of autonomic neuropathy

Heart rate (HR) variations--in supine resting position, during deep breathing and on standing--were measured in 162 healthy subjects and 168 diabetics by use of an instantaneous-HR-change continuous recorder. As indices of HR variations, the standard deviation of the HR at rest (SD of HR), the mean difference between maximal and minimal HR during deep breathing (delta I-E) and the HR increase on standing (delta HR) were determined. In healthy subjects, the values for each test declined with age and the log-transformed data fitted the linear regression. The 90% confidence limits were calculated for the normal range and the values below normal range were defined as abnormal. In diabetics, the incidence of abnormal response were 19% in the SD of HR, 38% in the delta I-E and 22% in the delta HR. The delta I-E was the most sensitive index for the autonomic neuropathy. The delta HR was considered to be able to detect the different mechanisms of neural reflexes because of the poor correlation between the delta HR and the respiratory HR variations. The present studies suggested that delta I-E and delta HR should be measured at the same time to evaluate the autonomic neuropathy.     

Approaches to Antifungal Therapies and Their Effectiveness among Patients with Cryptococcosis

The goal of this study was to determine the degree to which the persistence of cryptococcosis, overall 1-year mortality, and 1-year mortality due to cryptococcosis were influenced by initial antifungal treatment regimen in a cohort of adults with cryptococcosis treated at a tertiary care medical center. Risk factors, underlying conditions, treatment, and mortality information were obtained for 204 adults with cryptococcosis from Duke University Medical Center (DUMC) from 1996 to 2009. Adjusted risk ratios (RR) for persistence and hazard ratios (HR) for mortality were estimated for each exposure. The all-cause mortality rate among patients with nonsevere disease (20%) was similar to that in the group with disease (26%). However, the rate of cryptococcosis-attributable mortality with nonsevere disease (5%) was much lower than with severe disease (20%). Flucytosine exposure was associated with a lower overall mortality rate (HR, 0.4; 95% confidence interval [CI], 0.2 to 0.9) and attributable mortality rate (HR, 0.5; 95% CI, 0.2 to 1.2). Receiving a nonrecommended antifungal regimen was associated with a higher relative risk of persistent infection at 4 weeks (RR, 1.9; 95% CI, 0.9 to 4.3), and the rate of attributable mortality among those not receiving the recommended dose of initial therapy was higher than that of those receiving recommended dosing (HR, 2.3; 95% CI, 1.0 to 5.0). Thus, the 2010 Infectious Diseases Society of America (IDSA) guidelines are supported by this retrospective review as a best-practice protocol for cryptococcal management. Future investigations should consider highlighting the distinction between all-cause mortality and attributable mortality so as not to overestimate the true effect of cryptococcosis on patient death.     

Reliability of dynamic cerebral autoregulation measurement using spontaneous fluctuations in blood pressure

Spontaneous fluctuations in BP (blood pressure) and subsequent change in CBFV (cerebral blood flow velocity) in the MCA (middle cerebral artery) can be used to assess dynamic cerebral autoregulation using transfer function analysis; however, the reliability of this technique has not been assessed, in particular the contribution of intra-subject variability relative to inter-subject variability. Three bilateral CBFV, BP and RR interval recordings were performed in ten healthy volunteers on four separate occasions over a 2-week period. Data were analysed to provide the ARI (autoregulatory index), CBFV, RAP (resistance-area product) and CrCP (critical closing pressure). We also measured systolic and diastolic BP, and resting HR (heart rate). We calculated the SEM (standard error of measurement) and the ICC (intra-class correlation coefficient) and their 95% CIs (confidence intervals) for each parameter to assess their absolute (intra-subject) and relative (inter-subject) reliability. The CV (coefficient of variation) of SEM ranged from 1.7% (for CBFV) to 100.0% (for RAP), whereas the ICC was <0.5 for ARI, rising to >0.8 for CBFV and diastolic BP. These data demonstrate excellent absolute and relative reliability of CBFV, whereas ARI is of comparable reliability with the measurement of HR. Using these results it is possible to determine the sample size required to demonstrate a change in ARI, with a sample of 45 subjects in each group required to show a change in ARI of 1, whereas to detect a change in ARI >2 would require only 11 subjects per group. The results of the present study could be valuable to the future planning of cerebral autoregulation studies, but more work is needed to understand the determinants of intra-subject variability in autoregulatory parameters.     

Can Current Minute Ventilation Rate Adaptive Pacemakers Provide Appropriate Chronotropic Response in Pediatric Patients?

Since children have different activity patterns and exercise responses, uncertainty exists as to whether minute ventilation (MV) sensors designed for adults provide adequate chronotropic response in pediatrics. In particular, high respiratory rates (RR > 48 breaths/min), which are characteristic of the ventilatory response to exercise in children, cannot be sensed by MV rate responsive pacemakers. The purpose of this study was to evaluate the MV sensor rate response of the Medtronic Kappa 400 using exercise data from healthy children in a computer simulation of its rate response algorithm. Thirty-eight healthy children, ages 6-14, underwent a treadmill maximal exercise test. Subjects were divided based on body surface area (BSA) and MV rate response parameters were selected. Respiratory rates and tidal volumes were entered into the Kappa 400 rate response algorithm to calculate sensor-driven rates. Intrinsic heart rate (HR), oxygen uptake, and sensor-driven rates were normalized to HR reserve (HRR), metabolic reserve (MR), and sensor-driven reserve to compare across groups. Linear regression analysis among sensor-driven rate reserve, HRR, and MR was performed as described by Wilkoff. The mean slopes (+/- SD) of the relationships between the sensor-driven rate reserve and HRR were 1.06 +/- 0.34, 1.07 +/- 0.28, and 1.01 +/- 0.19 for children with BSA < 1.10 m2, 1.10 < BSA < 1.40 m2, and BSA > 1.40 m2, respectively. High correlations were found between sensor-drive rates and HR responses and between sensor-drive rates and MV throughout exercise. No significant differences were noted between sensor-drive rates and HR using the Wilkoff model. From this study the authors conclude that: (1) MV is a good physiological parameter to control heart rate and (2) simulated sensor-driven rates closely match intrinsic HRs during exercise in healthy children, which supports the appropriateness of clinical validation in pediatric pacemaker patients.     

An index related to the autocorrelation function of RR intervals for the analysis of heart rate variability

Heart rate variability (HRV) is concerned with analysis of the variations in the intervals between heartbeats, known as RR intervals. Commonly used HRV indices may be insensitive in detecting some dynamic changes related to complex autocorrelation functions of the RR intervals. For example, indices SD1 and SD2 of the Poincaré plot can be expressed by the variance and first auto-covariance of the signal. The acceleration change index is related to the autocorrelation functions of the series only at the first three lags. We extend the idea of characterizing the sign of differences of a time series to propose a new index called VRL, which is the variance of the run length of the sign of the lagged differentiated time series. The theoretical study shows that VRL is directly related to the autocorrelation functions of the RR series at larger lags. Simulated data are used to validate the theoretical results and assess the power of testing group differences measured with VRL and other HRV indices. The performance of VRL is also evaluated for classifying subjects with normal sinus rhythm and congestive heart failure using the RR intervals taken from the PhysioNet database. We apply the index to RR intervals from an animal study of long-term exposure to particulate matter. The VRL values for the young mice susceptible to atherosclerosis in the control and exposure groups decreased gradually with different slopes after several weeks of exposure. The exposure effect changes in this HRV index estimated by fitting a generalized additive model are significant after 7 weeks of exposure.     

Clinical assessment of drug-induced QT prolongation in association with heart rate changes

BACKGROUND: The formulas for heart rate (HR) correction of QT interval have been shown to overcorrect or undercorrect this interval with changes in HR. A Holter-monitoring method avoiding the need for any correction formulas is proposed as a means to assess drug-induced QT interval changes. METHODS: A thorough QT study included 2 single doses of the alpha1-adrenergic receptor blocker alfuzosin, placebo, and a QT-positive control arm (moxifloxacin) in 48 healthy subjects. Bazett, Fridericia, population-specific (QTcN), and subject-specific (QTcNi) correction formulas were applied to 12-lead electrocardio-graphic recording data. QT1000 (QT at RR = 1000 ms), QT largest bin (at the largest sample size bin), and QT average (average QT of all RR bins) were obtained from Holter recordings by use of custom software to perform rate-independent QT analysis. RESULTS: The 3 Holter end points provided similar results, as follows: Moxifloxacin-induced QT prolongation was 7.0 ms (95% confidence interval [CI], 4.4-9.6 ms) for QT1000, 6.9 ms (95% CI, 4.8-9.1 ms) for QT largest bin, and 6.6 ms (95% CI, 4.6-8.6 ms) for QT average. At the therapeutic dose (10 mg), alfuzosin did not induce significant change in the QT. The 40-mg dose of alfuzosin increased HR by 3.7 beats/min and induced a small QT1000 increase of 2.9 ms (95% CI, 0.3-5.5 ms) (QTcN, +4.6 ms [95% CI, 2.1-7.0 ms]; QTcNi, +4.7 ms [95% CI, 2.2-7.1 ms]). Data corrected by "universal" correction formulas still showed rate dependency and yielded larger QTc change estimations. The Holter method was able to show the drug-induced changes in QT rate dependence. CONCLUSIONS: The direct Holter-based QT interval measurement method provides an alternative approach to measure rate-independent estimates of QT interval changes during treatment.     

Reliability of cardiorespiratory measurements during wheelchair ergometry

The purpose of this research was to evaluate the stability of measures of heart rate (HR) and oxygen uptake (VO2) during repeated 30-minute bouts of constant work-rate wheelchair ergometry. Ten able-bodied subjects (seven male; three female) completed three sequential, single-stage wheelchair ergometer propulsion tests, to exhaustion, at least 48 hours apart, to determine the reliability of measurements of HR and VO2. Power output was determined as the resistance required to elicit 75% of the peak V02 attained during a peak graded exercise wheelchair ergometer test, at a propulsion velocity of three miles per hour and a flywheel roll distance of 6.32 meters. The HR and VO2 measurements were averaged over the last 30 seconds of the first (T1) and second (T2) thirds of the tests and at volitional exhaustion (T3). Significant differences were not observed at any of the data points except for HR at exhaustion. The HR at exhaustion was lower for the third test than for the second test. Intraclass correlation coefficients for HR (R=0.92, 0.95, and 0.86) and VO2 (R=0.95, 0.96, and 0.97) were high across the three tests, at all of the data points, respectively. Coefficients of variation were generally low. The results of this study indicated that, with the exception of HR during exercise sustained longer than approximately 30 minutes, VO2 and HR measurements can be made with high reliability during sustained wheelchair ergometer propulsion.     

Predictors of return to work in patients sick listed for sub-acute low back pain: a 12-month follow-up study.

OBJECTIVE: To investigate whether personal and work-related factors, physical performance and back-specific questionnaires predict return to work. A prospective study identifying prognostic factors for return to work. SUBJECTS: Ninety-three patients sick-listed for 8-12 weeks for non-specific sub-acute low back pain included in a randomized controlled trial. METHODS: Patients were examined with regard to demographic variables, a battery of back-specific questionnaires and physical tests before entering a randomized controlled trial. A stepwise backward Cox regression model was established to identify the most powerful predictors. RESULTS: During follow-up 78.5% of the patients have returned to full-time work. Fear-avoidance beliefs for work (relative risk (RR) for 1 SD change 0.49; 95% confidence interval (CI) 0.38-0.64), disability (RR 1.39, 95% CI 1.02-1.88) and cardiovascular fitness (RR 1.42, 95% CI 1.12-1.79) were identified as the best predictors for return to work. The prevalence of correct predictions was 69.3%. CONCLUSION: The predictors identified in the present study may reflect personal risk factors in a patient who gets acute low back pain. On the other hand, they may support that fear of pain and injury may be more disabling than pain itself, and that deconditioning is a result of altered behaviour reflecting attitudes towards low back pain in society, and information and advice given in primary healthcare.     

Learning effective brain connectivity with dynamic Bayesian networks

We propose to use dynamic Bayesian networks (DBN) to learn the structure of effective brain connectivity from functional MRI data in an exploratory manner. In our previous work, we used Bayesian networks (BN) to learn the functional structure of the brain (Zheng, X., Rajapakse, J.C., 2006. Learning functional structure from fMR images. NeuroImage 31 (4), 1601-1613). However, BN provides a single snapshot of effective connectivity of the entire experiment and therefore is unable to accurately capture the temporal characteristics of connectivity. Dynamic Bayesian networks (DBN) use a Markov chain to model fMRI time-series and thereby determine temporal relationships of interactions among brain regions. Experiments on synthetic fMRI data demonstrate that the performance of DBN is comparable to Granger causality mapping (GCM) in determining the structure of linearly connected networks. Dynamic Bayesian networks render more accurate and informative brain connectivity than earlier methods as connectivity is described in complete statistical sense and temporal characteristics of time-series are explicitly taken into account. The functional structures inferred on two real fMRI datasets are consistent with the previous literature and more accurate than those discovered by BN. Furthermore, we study the effects of hemodynamic noise, scanner noise, inter-scan interval, and the variability of hemodynamic parameters on the derived connectivity.     

Physiological noise and signal-to-noise ratio in fMRI with multi-channel array coils

Sensitivity in BOLD fMRI is characterized by the signal to noise ratio (SNR) of the time-series (tSNR), which contains fluctuations from thermal and physiological noise sources. Alteration of an acquisition parameter can affect the tSNR differently depending on the relative magnitude of the physiological and thermal noise, therefore knowledge of this ratio is essential for optimizing fMRI acquisitions. In this study, we compare image and time-series SNR from array coils at 3T with and without parallel imaging (GRAPPA) as a function of image resolution and acceleration. We use the "absolute unit" SNR method of Kellman and McVeigh to calculate the image SNR (SNR(0)) in a way that renders it comparable to tSNR, allowing determination of the thermal to physiological noise ratio, and the pseudo-multiple replica method to quantify the image noise alterations due to the GRAPPA reconstruction. The Kruger and Glover noise model, in which the physiological noise standard deviation is proportional to signal strength, was found to hold for the accelerated and non-accelerated array coil data. Thermal noise dominated the EPI time-series for medium to large voxel sizes for single-channel and 12-channel head coil configurations, but physiological noise dominated the 32-channel array acquisition even at 1 mm × 1mm × 3 mm resolution. At higher acceleration factors, image SNR is reduced and the time-series becomes increasingly thermal noise dominant. However, the tSNR reduction is smaller than the reduction in image SNR due to the presence of physiological noise.     

Evaluation of the GTRACT diffusion tensor tractography algorithm: a validation and reliability study

Fiber tracking, based on diffusion tensor imaging (DTI), is the only approach available to non-invasively study the three-dimensional structure of white matter tracts. Two major obstacles to this technique are partial volume artifacts and tracking errors caused by image noise. In this paper, a novel fiber tracking algorithm called Guided Tensor Restore Anatomical Connectivity Tractography (GTRACT) is presented. This algorithm utilizes a multi-pass approach to fiber tracking. In the first pass, a 3D graph search algorithm is utilized. The second pass incorporates anatomical connectivity information generated in the first pass to guide the tracking in this stage. This approach improves the ability to reconstruct complex fiber paths as well as the tracking accuracy. Validation and reliability studies using this algorithm were performed on both synthetic phantom data and clinical human brain data. A method is also proposed for the evaluating reliability of fiber tract generation based both on the position of the fiber tracts, as well the anisotropy values along the path. The results demonstrate that the GTRACT algorithm is less sensitive to image noise and more capable of handling areas of complex fiber crossing, compared to conventional streamline methods.     

Reliability and internal consistency findings from the C-SEI

Human patient simulation (HPS) is increasingly being used as both a teaching and an evaluation strategy in nursing education. To meaningfully evaluate student performance in HPS activities, nurse educators must be equipped with valid and reliable instruments for measuring student performance. This study used a novel method, including leveled, video-archived simulation scenarios, a virtual classroom, and webinar and e-mail communication, to assess the reliability and internal consistency of data produced using the Creighton Simulation Evaluation Instrument. The interrater reliability, calculated using intraclass correlation (2,1) and 95% confidence interval, was 0.952 (0.697, 0.993). The intrarater reliability, calculated using intraclass correlation (3,1) and 95% confidence interval, was 0.883 (-0.001, 0.992), and the internal consistency, calculated using Cronbach's alpha, was α = 0.979. This article includes a sample of the instrument and provides valuable resources and reliability data for nurse educators and researchers interested in measuring student performance in HPS activities.     

Complexity of heartbeat interval series in young healthy trained and untrained men

The origin of heart rate variability (HRV) is largely in parasympathetic activity. The direct influence of sympathetic activity and other control mechanisms, especially at an increased HR, is not well understood. The objectives of the study were to investigate the influence of increasing HR on the properties of heartbeat interval (RR) series in young healthy subjects. ECG was recorded in 9 trained and 11 untrained young men during supine rest, standing, incremental running exercise and relaxation. During exercise, a breath-to-breath gas exchange was monitored. The RR time series analysis included the spectral analysis, detrended fluctuations analysis method and sample entropy (SampEn) calculation. During exercise, spectral powers were reduced dramatically in both groups. The dependence of short-term scaling exponent (alpha(1)) on the RR included a characteristic maximum, while SampEn for the same value of the RR had a minimum. The value of HR corresponding to the maximum of alpha(1) and minimum of SampEn (IHR) corresponded to the intrinsic HR obtained by an autonomic blockade. In trained subjects, the curves alpha(1) versus RR and SampEn versus RR were moved toward larger RR, compared with control. For HR values higher than IHR, alpha(1) decreased and SampEn increased. These results reveal that the complexity of the heart rhythm above intrinsic HR decreases with an increase in HR. We suggest that at the highest HR intrinsic heart control is reflected in the heart rhythm. We point out the possibility of developing a new non-invasive method for the determination of intrinsic HR from the curve alpha(1) versus RR.