Principles of environmentally-sustainable anaesthesia: a global consensus statement from the World Federation of Societies of Anaesthesiologists

The Earth’s mean surface temperature is already approximately 1.1°C higher than pre-industrial levels. Exceeding a mean 1.5°C rise by 2050 will make global adaptation to the consequences of climate change less possible. To protect public health, anaesthesia providers need to reduce the contribution their practice makes to global warming. We convened a Working Group of 45 anaesthesia providers with a recognised interest in sustainability, and used a three-stage modified Delphi consensus process to agree on principles of environmentally sustainable anaesthesia that are achievable worldwide. The Working Group agreed on the following three important underlying statements: patient safety should not be compromised by sustainable anaesthetic practices; high-, middle- and low-income countries should support each other appropriately in delivering sustainable healthcare (including anaesthesia); and healthcare systems should be mandated to reduce their contribution to global warming. We set out seven fundamental principles to guide anaesthesia providers in the move to environmentally sustainable practice, including: choice of medications and equipment; minimising waste and overuse of resources; and addressing environmental sustainability in anaesthetists’ education, research, quality improvement and local healthcare leadership activities. These changes are achievable with minimal material resource and financial investment, and should undergo re-evaluation and updates as better evidence is published. This paper discusses each principle individually, and directs readers towards further important references.     

Diffusion-weighted magnetic resonance imaging in rat kidney using two-dimensional navigated,interleaved echo-planar imaging at 7.0 T

The purpose of this study was to investigate the feasibility of two-dimensional (2D) navigated, interleaved multishot echo-planar imaging (EPI) to enhance kidney diffusion-weighted imaging (DWI) in rats at 7.0 T. Fully sampled interleaved four-shot EPI with 2D navigators was tailored for kidney DWI (Sprague–Dawley rats, n = 7) on a 7.0-T small bore preclinical scanner. The image quality of four-shot EPI was compared with T₂-weighted rapid acquisition with relaxation enhancement (RARE) (reference) and single-shot EPI (ss-EPI) without and with parallel imaging (PI). The contrast-to-noise ratio (CNR) was examined to assess the image quality for the EPI approaches. The Dice similarity coefficient and the Hausdorff distance were used for evaluation of image distortion. Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for renal cortex and medulla for all DWI approaches. The corticomedullary difference of MD and FA were assessed by Wilcoxon signed-rank test. Four-shot EPI showed the highest CNR among the three EPI variants and lowest geometric distortion versus T₂-weighted RARE (mean Dice: 0.77 for ss-EPI without PI, 0.88 for ss-EPI with twofold undersampling, and 0.92 for four-shot EPI). The FA map derived from four-shot EPI clearly identified a highly anisotropic region corresponding to the inner stripe of the outer medulla. Four-shot EPI successfully discerned differences in both MD and FA between renal cortex and medulla. In conclusion, 2D navigated, interleaved multishot EPI facilitates high-quality rat kidney DWI with clearly depicted intralayer and interlayer structure and substantially reduced image distortion. This approach enables the anatomic integrity of DWI-MRI in small rodents and has the potential to benefit the characterization of renal microstructure in preclinical studies.     

Risk as a pattern over time: Delineation of time-dependent risk factors in biological,psychological, and social variables in cancer patients

Background

Survival in cancer patients is associated with a multitude of biological, social, and psychological factors. Although it is well established that all these factors add to overall mortality, it is not well understood how the predictive power of these parameters changes in a comprehensive model and over time.

Methods

Patients who attended the authors’ outpatient clinic were invited to participate. The authors followed 5180 mixed cancer patients (51.1% female; mean age, 59.1 years [SD = 13.8]) for up to 16 years and analyzed biological (age, sex, cancer site, anemia), psychological (anxiety, depression), and social variables (marital status, education, employment status) potentially predicting overall survival in a Cox proportional hazards model.

Results

The median survival time for the entire sample was 4.3 years (95% confidence interval, 4.0–4.7). The overall survival probabilities for 1 and 10 years were 76.8% and 38.0%, respectively. Following an empirical approach, the authors split the time interval into five periods: acute, subacute, short-term, medium-term, and long-term. A complex pattern of variables predicted overall survival differently in the five periods. Biological parameters were important throughout most of the time, social parameters were either time-independent predictors or tended to be more important in the longer term. Of the psychological parameters, only depression was a significant predictor and lost its predictive power in the long-term.

Conclusions

The findings of this study allow the development of comprehensive patient-specific models of risk and resilience factors addressing biopsychosocial needs of cancer patients, paving the way for a personalized treatment plan that goes beyond biomedical cancer care.