Prolonging life and delaying death: The role of physicians in the context of limited intensive care resources

Critical care is in an emerging crisis of conflict between what individuals expect and the economic burden society and government are prepared to provide. The goal of critical care support is to prevent suffering and premature death by intensive therapy of reversible illnesses within a reasonable timeframe. Recently, it has become apparent that early support in an intensive care environment can improve patient outcomes. However, life support technology has advanced, allowing physicians to prolong life (and postpone death) in circumstances that were not possible in the recent past. This has been recognized by not only the medical community, but also by society at large. One corollary may be that expectations for recovery from critical illness have also become extremely high. In addition, greater numbers of patients are dying in intensive care units after having receiving prolonged durations of life-sustaining therapy. Herein lies the emerging crisis – critical care therapy must be available in a timely fashion for those who require it urgently, yet its provision is largely dependent on a finite availability of both capital and human resources. Physicians are often placed in a troubling conflict of interest by pressures to use health resources prudently while also promoting the equitable and timely access to critical care therapy. In this commentary, these issues are broadly discussed from the perspective of the individual clinician as well as that of society as a whole. The intent is to generate dialogue on the dynamic between individual clinicians navigating the complexities of how and when to use critical care support in the context of end-of-life issues, the increasing demands placed on finite critical care capacity, and the reasonable expectations of society

Frailty in the critically ill: a novel concept

The concept of frailty has been defined as a multidimensional syndrome characterized by the loss of physical and cognitive reserve that predisposes to the accumulation of deficits and increased vulnerability to adverse events. Frailty is strongly correlated with age, and overlaps with and extends aspects of a patient's disability status (that is, functional limitation) and/or burden of comorbid disease. The frail phenotype has more specifically been characterized by adverse changes to a patient's mobility, muscle mass, nutritional status, strength and endurance. We contend that, in selected circumstances, the critically ill patient may be analogous to the frail geriatric patient. The prevalence of frailty amongst critically ill patients is currently unknown; however, it is probably increasing, based on data showing that the utilization of intensive care unit (ICU) resources by older people is rising. Owing to the theoretical similarities in frailty between geriatric and critically ill patients, this concept may have clinical relevance and may be predictive of outcomes, along with showing important interaction with several factors including illness severity, comorbid disease, and the social and structural environment. We believe studies of frailty in critically ill patients are needed to evaluate how it correlates with outcomes such as survival and quality of life, and how it relates to resource utilization, such as length of mechanical ventilation, ICU stay and duration of hospitalization. We hypothesize that the objective measurement of frailty may provide additional support and reinforcement to clinicians confronted with end-of-life decisions on the appropriateness of ICU support and/or withholding of life-sustaining therapies

A review of the compressive stiffness of the human head

Published 12 November 2022Synthetic surrogate head models are used in biomechanical studies to investigate skull, brain, and cervical spine injury. To ensure appropriate biofidelity of these head models, the stiffness is often tuned so that the surrogate’s response approximates the cadaveric response corridor. Impact parameters such as energy, and loading direction and region, can influence injury prediction measures, such as impact force and head acceleration. An improved understanding of how impact parameters affect the head’s structural response is required for designing better surrogate head models. This study comprises a synthesis and review of all existing ex vivo head stiffness data, and the primary factors that influence the force–deformation response are discussed. Eighteen studies from 1972 to 2019 were identified. Head stiffness statistically varied with age (pediatric vs. adult), loading region, and rate. The contact area of the impactor likely affects stiffness, whereas the impactor mass likely does not. The head’s response to frontal impacts was widely reported, but few studies have evaluated the response to other impact locations and directions. The findings from this review indicate that further work is required to assess the effect of head constraints, loading region, and impactor geometry, across a range of relevant scenarios.Darcy W. Thompson-Bagshaw, Ryan D. Quarrington, and Claire F. Jone

Acute kidney injury in the era of big data: The 15^th Consensus Conference of the Acute Dialysis Quality Initiative (ADQI)

The world is immersed in "big data". Big data has brought about radical innovations in the methods used to capture, transfer, store and analyze the vast quantities of data generated every minute of every day. At the same time; however, it has also become far easier and relatively inexpensive to do so. Rapidly transforming, integrating and applying this large volume and variety of data are what underlie the future of big data. The application of big data and predictive analytics in healthcare holds great promise to drive innovation, reduce cost and improve patient outcomes, health services operations and value. Acute kidney injury (AKI) may be an ideal syndrome from which various dimensions and applications built within the context of big data may influence the structure of services delivery, care processes and outcomes for patients. The use of innovative forms of "information technology" was originally identified by the Acute Dialysis Quality Initiative (ADQI) in 2002 as a core concept in need of attention to improve the care and outcomes for patients with AKI. For this 15th ADQI consensus meeting held on September 6-8, 2015 in Banff, Canada, five topics focused on AKI and acute renal replacement therapy were developed where extensive applications for use of big data were recognized and/or foreseen. In this series of articles in the Canadian Journal of Kidney Health and Disease, we describe the output from these discussions

Plasma neutrophil gelatinase-associated lipocalin predicts recovery from acute kidney injury following community-acquired pneumonia

Although plasma neutrophil gelatinase-associated lipocalin (NGAL) is a promising biomarker for early detection of acute kidney injury, its ability to predict recovery is unknown. Using RIFLE criteria to define kidney injury, we tested whether higher plasma NGAL concentrations on the first day of RIFLE-F would predict failure to recover in a post hoc analysis of a multicenter, prospective, cohort study of patients with community-acquired pneumonia. Recovery was defined as alive and not requiring renal replacement therapy during hospitalization or having a persistent RIFLE-F classification at hospital discharge. Median plasma NGAL concentrations were significantly lower among the 93 of 181 patients who recovered. Plasma NGAL alone predicted failure to recover with an area under the receiver operating characteristic curve of 0.74. A clinical model using age, serum creatinine, pneumonia severity, and nonrenal organ failure predicted failure to recover with area under the curve of 0.78. Combining this clinical model with plasma NGAL concentrations did not improve prediction. The reclassification of risk of renal recovery, however, significantly improved by 17% when plasma NGAL was combined with the clinical model. Thus, in this cohort of patients with pneumonia-induced severe acute kidney injury, plasma NGAL appears to be a useful biomarker for predicting renal recovery