The neutrophil is the principal cellular component of the inflammatory host defense and contributor to host injury after severe physiologic insult. The neutrophil is inherently coupled to patient outcome in both health and disease and extensive research has focused on the mechanisms that regulate neutrophil delivery, function, and clearance from the inflammatory microenvironment.
The host response to trauma, shock and sepsis behaves as a complex nonlinear system consisting of a great number of variables and systems of variables. It is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine the clinical outcome in critically ill patients. Variability analysis of physiological rhythms provides a novel technology with which to evaluate the overall properties of a complex system.
Health is characterized by robust, complex variability, and illness by a reduction in the degree and complexity of variability. Monitoring physiologic variability (e.g. heart rate variability and respiration rate variability) can uncover otherwise hidden information within the degree and patterns of variation that inform regarding the status of a patient’s health.
As the multivariate measurement of physiological variability provides additional information regarding a patient’s condition, machine learning is well suited to transform the variability data, in addition to any relevant clinical data, into predictive models that may be useful to help with clinical decision-making.
Acknowledging the presence of irreducible uncertainty helps to directly improve patient care, patient communication, basic science and population research, as well as management of healthcare organizations, all of which will enhance our ability to care for patients.
In thoracic surgery, postoperative adverse events (AEs) are too common, ranging from 30-60% and resulting in an increase in morbidity and mortality, length of hospital stay and increased health care costs. The importance of rigorous recording of AEs is widely recognized, yet AE definitions vary widely, inadequate reporting is common and there is a lack of national best-practice recommendations. We have developed a real-time, web-based, point-of-care, software tool (tsqic.org)to collect clinical and OR data, adverse events, quality metrics and assist with clinical documentation with the goal of improving the quality and efficiency of care and communication.
Systematic continuous learning from data is vital to optimizing Canadian healthcare with improved patient outcomes and reduced costs. To improve real-time, patient and health system, data-informed healthcare quality improvement requires 1) improved capacity to dynamically add nationally collected hospital discharge data fields; 2) the creation of nationally coordinated strategic patient-level data collection and research for clinical problems and conditions of urgent health importance; and 3) the initiation and empowerment of perpetual national quality and research collectives, enabling platforms of standardized data collection, quality improvement and research.
Increasing evidence suggests that the physical drive for maximal entropy production is responsible for spontaneous formation of fractal multi-scale self-similar structures in time and space, ubiquitous and essential for health. Fractal structures spontaneously form in nature because it is the most efficient way to optimize entropy production. Moreover it is hypothesized that the evolutionary drive for enhanced function and adaptability selects states with both robust basal and maximal entropy production (i.e. the capacity to augment it when required). Based on these premises we postulate that 1) alterations in physiologic and anatomic fractal structures may be an early indicator of illness and disease and 2) enhancing a patient’s basal and maximal entropy production will improve their health.
While clinician and patient experience has demonstrated the potential of many treatments offered by naturopathic doctors to reduce adverse events and increase quality of life in cancer patients, they are generally not integrated into modern oncology care, and patients must avail themselves to these complementary therapies in isolation of their traditional therapies. To address this deficit in evidence and collaboration, large-scale, methodologically sound randomized controlled trials of integrative care interventions offered by naturopathic doctors are vitally required.
Acknowledgements:
We would like to acknowledge the following institutions and organizations for their funding and support: University of Ottawa Faculty of Medicine Tier I Clinical Research Chair, The Ottawa Hospital Academic Medical Organization (TOHAMO), Physicians’ Services Incorporated (PSI), Ontario Bioscience Innovation Organization (OBIO) Therapeutic Monitoring Systems Inc.(TMS), Canadian Association of Thoracic Surgeons (CATS), Canadian Critical Care Trials Group (CCCTG) and Health Canada.
Partners:
We would lie to thank the following partners: University of Ottawa, Ottawa Hospital Research Institute (OHRI), Therapeutic Monitoring Systems Inc. (TMS) and the Canadian Association of Thoracic Surgeons (CATS).
References:
A complete list of references for the pages listed above can be found here.
