IntroductionProlonged 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.MethodsWe 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.ResultsOf 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.ConclusionsAltered 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 registrationClinicalTrials.gov NCT01237886. Registered 13 October 2010.

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.

Interruption of sedation allows for uncovering a greater restoration of heart rate variability and respiratory rate variability in patients with low organ failure. The further reduction in respiratory variability during the elimination of sedation in patients with high multiple organ dysfunction syndrome suggests a differential response and benefit from sedation interruption, and merits further investigation. As reduced variability correlates with severity of illness, and need for sedation depends on organ failure, variability monitoring may offer a dynamic measure of a variable response to the benefit, timing, and duration of sedation interruption.

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.

As heart-rate variability (HRV) is under evaluation in clinical applications, the authors sought to better define the interdependent impact of age, maximal exercise, and diurnal variation under physiologic conditions. The authors evaluated the diurnal changes in HRV 24-h pre- and post-maximal aerobic exercise testing to exhaustion in young (19-25 yrs, n = 12) and middle-aged (40-55 yrs, n = 12) adults. Subjects wore a portable 5-lead electrocardiogram holter for 48 h (24 h prior to and following a maximal aerobic capacity test). Time-, frequency-, time-frequency-, and scale-invariant-domain measures of HRV were computed from RR-interval data analyzed using a 5-min window size and a 2.5-min step size, resulting in a different set of outputs every 2.5 min. Results were averaged (mean ± SE) over four prespecified time periods during the morning, afternoon, evening, and night on Day 1 and Day 2. Diurnal changes in HRV in young and middle-aged adults were compared using a two-way, repeated-measures analysis of variance (ANOVA). Young adults demonstrated higher HRV compared to middle-aged adults during periods of wakefulness and sleep prior to maximal exercise stress testing (i.e., high-frequency power during Day 1: young adults: morning 1862 ± 496 ms(2), afternoon 1797 ± 384 ms(2), evening 1908 ± 431 ms(2), and night 3202 ± 728 ms(2); middle-aged adults: morning 341 ± 53 ms(2), afternoon 405 ± 68 ms(2), evening 469 ± 80 ms(2), and night 836 ± 136 ms(2)) (p < .05). Exercise resulted in reductions in HRV such that multiple measures of HRV were not significantly different between age groups during the afternoon and evening periods. All measures of HRV demonstrated between-group differences overnight on Day 2 (p < .05). Young adults are associated with higher baseline HRV during the daytime. Sleep increases variability equally and proportionally to daytime variability. Given the higher baseline awake HRV and equal rise in HRV during sleep, the change in HRV from sleep to morning with exercise is greater in younger subjects. These physiologic results have clinical significance in understanding the pathophysiology of altered variability in ill patients.