Do heart and respiratory rate variability improve prediction of extubation outcomes in critically ill patients?

INTRODUCTION: Prolonged ventilation and failed extubation are associated with increased harm and cost. The added value of heart and respiratory rate variability (HRV and RRV) during spontaneous breathing trials (SBTs) to predict extubation failure remains unknown. METHODS: We enrolled 721 patients in a multicenter (12 sites), prospective, observational study, evaluating clinical estimates of risk of extubation failure, physiologic measures recorded during SBTs, HRV and RRV recorded before and during the last SBT prior to extubation, and extubation outcomes. We excluded 287 patients because of protocol or technical violations, or poor data quality. Measures of variability (97 HRV, 82 RRV) were calculated from electrocardiogram and capnography waveforms followed by automated cleaning and variability analysis using Continuous Individualized Multiorgan Variability Analysis (CIMVA™) software. Repeated randomized subsampling with training, validation, and testing were used to derive and compare predictive models. RESULTS: Of 434 patients with high-quality data, 51 (12%) failed extubation. Two HRV and eight RRV measures showed statistically significant association with extubation failure (P <0.0041, 5% false discovery rate). An ensemble average of five univariate logistic regression models using RRV during SBT, yielding a probability of extubation failure (called WAVE score), demonstrated optimal predictive capacity. With repeated random subsampling and testing, the model showed mean receiver operating characteristic area under the curve (ROC AUC) of 0.69, higher than heart rate (0.51), rapid shallow breathing index (RBSI; 0.61) and respiratory rate (0.63). After deriving a WAVE model based on all data, training-set performance demonstrated that the model increased its predictive power when applied to patients conventionally considered high risk: a WAVE score >0.5 in patients with RSBI >105 and perceived high risk of failure yielded a fold increase in risk of extubation failure of 3.0 (95% confidence interval (CI) 1.2 to 5.2) and 3.5 (95% CI 1.9 to 5.4), respectively. CONCLUSIONS: Altered HRV and RRV (during the SBT prior to extubation) are significantly associated with extubation failure. A predictive model using RRV during the last SBT provided optimal accuracy of prediction in all patients, with improved accuracy when combined with clinical impression or RSBI. This model requires a validation cohort to evaluate accuracy and generalizability. TRIAL REGISTRATION: ClinicalTrials.gov NCT01237886. Registered 13 October 2010.

Heart rate variability during exertional heat stress: effects of heat production and treatment.

PURPOSE: We assessed the efficacy of different treatments (i.e., treatment with ice water immersion vs. natural recovery) and the effect of exercise intensities (i.e., low vs. high) for restoring heart rate variability (HRV) indices during recovery from exertional heat stress (EHS). METHODS: Nine healthy adults (26 ± 3 years, 174.2 ± 3.8 cm, 74.6 ± 4.3 kg, 17.9 ± 2.8 % body fat, 57 ± 2 mL·kg·(-1) min(-1) peak oxygen uptake) completed four EHS sessions incorporating either walking (4.0-4.5 km·h(-1), 2 % incline) or jogging (~7.0 km·h(-1), 2 % incline) on a treadmill in a hot-dry environment (40 °C, 20-30 % relative humidity) while wearing a non-permeable rain poncho for a slow or fast rate of rectal temperature (T re) increase, respectively. Upon reaching a T re of 39.5 °C, participants recovered until T re returned to 38 °C either passively or with whole-body immersion in 2 °C water. A comprehensive panel of 93 HRV measures were computed from the time, frequency, time-frequency, scale-invariant, entropy and non-linear domains. RESULTS: Exertional heat stress significantly affected 60/93 HRV measures analysed. Analyses during recovery demonstrated that there were no significant differences between HRV measures that had been influenced by EHS at the end of passive recovery vs. whole-body cooling treatment (p > 0.05). Nevertheless, the cooling treatment required statistically significantly less time to reduce T re (p < 0.001). CONCLUSIONS: While EHS has a marked effect on autonomic nervous system modulation and whole-body immersion in 2 °C water results in faster cooling, there were no observed differences in restoration of autonomic heart rate modulation as measured by HRV indices with whole-body cold-water immersion compared to passive recovery in thermoneutral conditions.

Changes in heart rate variability during the induction and decay of heat acclimation.

PURPOSE: We evaluated the changes in core temperature, heart rate, and heart rate variability (HRV) during the induction and decay of heat acclimation. METHODS: Ten males (23 ± 3 years; 79.5 ± 3.5 kg; 15.2 ± 4.5 percent body fat; 51.13 ± 4.61 mLO(2)∙kg(-1)∙min(-1) peak oxygen uptake) underwent a 14-day heat acclimation protocol comprising of 90-min cycling at ~50 % peak oxygen uptake at 40 °C and ~20 % relative humidity. Core temperature, heart rate, and 102 HRV measures were recorded during a heat tolerance test conducted at baseline (day 0) and at the end of the induction (day 14) and decay (day 28) phases. RESULTS: Heat acclimation resulted in significantly reduced core temperature [rectal (χ (2) = 1298.14, p < 0.001); esophageal (χ (2) = 1069.88, p < 0.001)] and heart rate (χ (2) = 1230.17, p < 0.001). Following the decay phase, 26, 40, and 60 % of the heat acclimation-induced reductions in rectal temperature, esophageal temperature, and heart rate, respectively, were lost. Heat acclimation was accompanied by profound and broad changes in HRV: at the end of the induction phase, 75 of the 102 variability measures computed were significantly different (p < 0.001), compared to only 47 of the 102 at the end of the decay phase. CONCLUSIONS: Heat acclimation is accompanied by reduced core temperature, significant bradycardia, and marked alterations in HRV, which we interpret as being related to vagal dominance. The observed changes in core temperature persist for at least 2 weeks of non-exposure to heat, while the changes in heart rate and HRV decay faster and are only partly evident after 2 weeks of non-exposure to heat.

Variability analysis and the diagnosis, management, and treatment of sepsis.

Severe sepsis leading to organ failure is the most common cause of mortality among critically ill patients. Variability analysis is an emerging science that characterizes patterns of variation of physiologic parameters (e.g., vital signs) and is believed to offer a means for evaluating the underlying complex system producing those dynamics. Recent studies have demonstrated that variability of a variety of physiological parameters offers a novel means for helping diagnose, manage, and treat sepsis. The purpose of this literature review is to examine existing data regarding the use of variability analysis in patients suffering from sepsis and to highlight potential uses for variability in improving care for patients with sepsis. Recent articles published on heart rate, respiratory rate, temperature, and glucose variability are reviewed. The association between reduced heart rate and temperature variability and sepsis and its severity, the relationship between augmented glucose variability and mortality risk, and current uses of respiratory rate variability in critically ill patients will all be discussed. These findings represent early days in the understanding of variability alteration and its physiological significance; further research is required to understand and implement variability analyses into meaningful clinical decision support algorithms. Large, multicenter observational studies are needed to derive and validate the associations between variability and clinical events and outcomes in order to realize the potential of variability to change sepsis care and improve clinical outcomes.

Review and classification of variability analysis techniques with clinical applications.

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Comparison of heart and respiratory rate variability measures using an intermittent incremental submaximal exercise model.

To better understand the alterations in cardiorespiratory variability during exercise, the present study characterized the patterns of change in heart rate variability (HRV), respiratory rate variability (RRV), and combined cardiorespiratory variability (HRV-RRV) during an intermittent incremental submaximal exercise model. Six males and six females completed a submaximal exercise protocol consisting of an initial baseline resting period followed by three 10-min bouts of exercise at 20%, 40%, and 60% of maximal aerobic capacity (V̇O2max). The R-R interval and interbreath interval variability were measured at baseline rest and throughout the submaximal exercise. A group of 93 HRV, 83 RRV, and 28 HRV-RRV measures of variability were tracked over time through a windowed analysis using a 5-min window size and 30-s window step. A total of 91 HRV measures were able to detect the presence of exercise, whereas only 46 RRV and 3 HRV-RRV measures were able to detect the same stimulus. Moreover, there was a loss of overall HRV and RRV, loss of complexity of HRV and RRV, and loss of parasympathetic modulation of HRV (up to 40% V̇O2max) with exercise. Conflicting changes in scale-invariant structure of HRV and RRV with increases in exercise intensity were also observed. In summary, in this simultaneous evaluation of HRV and RRV, we found more consistent changes across HRV metrics compared with RRV and HRV-RRV.

Continuous multiorgan variability analysis to track severity of organ failure in critically ill patients.

PURPOSE: The purpose of this study is to evaluate the utility of using continuous heart rate variability (HRV) and respiratory rate variability (RRV) monitoring for (a) tracking daily organ dysfunction in critically ill patients and (b) identifying patterns of variability changes during onset of shock and resolution of respiratory failure. MATERIALS AND METHODS: Thirty-three critically ill patients experiencing respiratory and/or cardiac failure underwent continuous recording of their electrocardiogram and capnogram (CO2) waveforms from admission or intubation until discharge (maximum 14 days). HRV and RRV were computed in 5-minute overlapping windows, using Continuous Individualized Multi-organ Variability Analysis software. Multiple organ dysfunction scores were recorded daily. HRV and RRV trajectories were characterized during onset of shock and resolution of respiratory failure. RESULTS: Both HRV and RRV decreased with increasing severity of multiple organ dysfunction scores for a variety of variability metrics. A decline in several measures of HRV and no decline in RRV were observed before onset of shock (n=6). In contrast, during resolution of respiratory failure, an increase in RRV was observed in patients who successfully passed extubation (n=12), with no change in RRV in those who subsequently failed extubation (n=2). CONCLUSIONS: There is an association between reduced HRV and RRV and increasing organ dysfunction in critically ill patients. The significance of observing trends of decreasing HRV (with onset of shock) and increasing RRV (with resolution of respiratory failure) merits further investigation.

Do physiological and pathological stresses produce different changes in heart rate variability?

Although physiological (e.g., exercise) and pathological (e.g., infection) stress affecting the cardiovascular system have both been documented to be associated with a reduction in overall heart rate variability (HRV), it remains unclear if loss of HRV is ubiquitously similar across different domains of variability analysis or if distinct patterns of altered HRV exist depending on the stressor. Using Continuous Individualized Multiorgan Variability Analysis (CIMVA™) software, heart rate (HR) and four selected measures of variability were measured over time (windowed analysis) from two datasets, a set (n = 13) of patients who developed systemic infection (i.e., sepsis) after bone marrow transplant (BMT), and a matched set of healthy subjects undergoing physical exercise under controlled conditions. HR and the four HRV measures showed similar trends in both sepsis and exercise. The comparison through Wilcoxon sign-rank test of the levels of variability at baseline and during the stress (i.e., exercise or after days of sepsis development) showed similar changes, except for LF/HF, ratio of power at low (LF) and high (HF) frequencies (associated with sympathovagal modulation), which was affected by exercise but did not show any change during sepsis. Furthermore, HRV measures during sepsis showed a lower level of correlation with each other, as compared to HRV during exercise. In conclusion, this exploratory study highlights similar responses during both exercise and infection, with differences in terms of correlation and inter-subject fluctuations, whose physiologic significance merits further investigation.

Monitoring and identification of sepsis development through a composite measure of heart rate variability.

Tracking the physiological conditions of a patient developing infection is of utmost importance to provide optimal care at an early stage. This work presents a procedure to integrate multiple measures of heart rate variability into a unique measure for the tracking of sepsis development. An early warning system is used to illustrate its potential clinical value. The study involved 17 adults (age median 51 (interquartile range 46-62)) who experienced a period of neutropenia following chemoradiotherapy and bone marrow transplant; 14 developed sepsis, and 3 did not. A comprehensive panel (N = 92) of variability measures was calculated for 5 min-windows throughout the period of monitoring (12 ± 4 days). Variability measures underwent filtering and two steps of data reduction with the objective of enhancing the information related to the greatest degree of change. The proposed composite measure was capable of tracking the development of sepsis in 12 out of 14 patients. Simulating a real-time monitoring setting, the sum of the energy over the very low frequency range of the composite measure was used to classify the probability of developing sepsis. The composite revealed information about the onset of sepsis about 60 hours (median value) before of sepsis diagnosis. In a real monitoring setting this quicker detection time would be associated to increased efficacy in the treatment of sepsis, therefore highlighting the potential clinical utility of a composite measure of variability.

Continuous Multiorgan Variability monitoring in critically ill patients--complexity science at the bedside.

Complex systems science has led to valuable insights regarding the care and understanding of critical illness, but has not led to fundamental improvements to care to date. Realizing the fact that there is inherent uncertainty in patient trajectory, we have developed Continuous Individual Multiorgan Variability Analysis (CIMVA) as a tool theoretically and practically designed to track the systemic emergent properties of the host response to injury or infection. We present an overview of CIMVA software, and discuss four separate potential clinical applications that we are evaluating; including early detection of infection, better prediction of extubation failure, continuous monitoring of severity of illness in the ICU, and the evaluation of cardiopulmonary fitness. Future challenges are discussed in conclusion.