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.

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 0.5 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.

The patterns of variation of physiologic parameters, such as heart and respiratory rate, and their alteration with age and illness have long been under investigation; however, the origin and significance of scale-invariant fractal temporal structures that characterize healthy biologic variability remain unknown. Quite independently, atmospheric and planetary scientists have led breakthroughs in the science of non-equilibrium thermodynamics. In this paper, we aim to provide two novel hypotheses regarding the origin and etiology of both the degree of variability and its fractal properties. In a complex dissipative system, we hypothesize that the degree of variability reflects the adaptability of the system and is proportional to maximum work output possible divided by resting work output. Reductions in maximal work output (and oxygen consumption) or elevation in resting work output (or oxygen consumption) will thus reduce overall degree of variability. Second, we hypothesize that the fractal nature of variability is a self-organizing emergent property of complex dissipative systems, precisely because it enables the system’s ability to optimally dissipate energy gradients and maximize entropy production. In physiologic terms, fractal patterns in space (e.g., fractal vasculature) or time (e.g., cardiopulmonary variability) optimize the ability to deliver oxygen and clear carbon dioxide and waste. Examples of falsifiability are discussed, along with the need to further define necessary boundary conditions. Last, as our focus is bedside utility, potential clinical applications of this understanding are briefly discussed. The hypotheses are clinically relevant and have potential widespread scientific relevance.

Objectives: To assess risk factors associated with failure and bleeding in intrapleural fibrinolytic therapy (IPFT) for pleural effusions. Design: Retrospective case series. Setting: Two tertiary-care centres in North America. Participants: We identified 237 cases that received IPFT for the treatment of pleural effusions . Data for 227 patients were compiled including demographics, investigations, radiological findings pretherapy and post-therapy and outcomes. Intervention: Fibrinolytic therapy in the form of tissue plasminogen activator (t-PA) or streptokinase. Primary and secondary outcomes: Success of therapy is defined as the presence of both clinical and radiological improvement leading to resolution. Failure was defined as persistence (ie, ineffective treatment) or complications requiring intervention from IPFT. Incidence of bleeding post-IPFT, identifying factors related to failure of therapy and bleeding. Results: IPFT was used in 237 patients with pleural effusions; 163 with empyema/complicated parapneumonic effusions, 32 malignant effusions and 23 with haemothorax. Overall, resolution was achieved in 80% of our cases. Failure occurred in 46 (20%) cases. Multivariate analysis revealed that failure was associated with the presence of pleural thickening (>2 mm) on CT scan (p=0.0031, OR 3, 95% CI 1.46 to 6.57). Bleeding was not associated with any specific variable in our study (antiplatelet medications, p=0.08). Conclusions: Pleural thickening on a CT scan was found to be associated with failure of IPFT.

Objective: Our aim is to better characterize the impact of sedation and its interruption on continuously monitored heart rate variability and respiratory rate variability in critically ill patients. We aim to explore whether sedation reduces heart rate variability and respiratory rate variability in critically ill patients and whether the extent of reduction depends on degree of organ dysfunction. Design: Prospective observational pilot study. Setting: Intensive care unit in tertiary care teaching hospital. Patients: Thirty-three critically ill adult patients experiencing respiratory and/or cardiac failure. Interventions: Electrocardiogram and end-tidal capnography waveform capture were initiated from admission or intubation, respectively, and continued to intensive care unit discharge or a maximum of 14 d. Measurements and Main Results: All patient days with a sedation interruption (defined as cessation of a continuous infusion of sedation agent) were identified. Mean heart rate variability and respiratory rate variability were computed over two periods: 4 hrs directly prior to the sedation interruption, and the duration of sedation interruption (median: 1 hr 45 mins, interquartile range: 4 hrs 15 mins or max 4 hrs). Severity of organ dysfunction was assessed through multiple organ dysfunction syndrome scores, and sedative agents were recorded for each sedation interruption. Multiple organ dysfunction syndrome levels were defined as low (0–2), medium (3–4), and high (> 4). Variability before and during sedation interruption was compared and analyzed across multiple organ dysfunction syndrome levels and sedative types. Our results suggest that both heart rate variability and respiratory rate variability increased during sedation interruption (p < 0.05 for coefficient of variation). Patients with low and medium multiple organ dysfunction syndrome experienced greater increase in heart rate variability during sedation interruption (p < 0.05 for coefficient of variation), compared to patients with high multiple organ dysfunction syndrome, who failed to mount a significant increase in heart rate variability when sedation was stopped. Similarly, sedation interruption led to increased respiratory rate variability for low multiple organ dysfunction syndrome patients (p < 0.05 for SD), but in contrast, a further deterioration in respiratory rate variability occurred in the high multiple organ dysfunction syndrome patients. All trends persisted when controlling for sedative agents. Conclusions: 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.