Evidence-based strategies to reduce the incidence of postoperative delirium: a narrative review

Delirium is one of the most commonly occurring postoperative complications in older adults. It occurs due to the vulnerability of cerebral functioning to pathophysiological stressors. Identification of those at increased risk of developing delirium early in the surgical pathway provides an opportunity for modification of predisposing and precipitating risk factors and effective shared decision-making. No single delirium prediction tool is used widely in surgical settings. Multi-component interventions to prevent delirium involve structured risk factor modification supported by geriatrician input; these are clinically efficacious and cost effective. Barriers to the widespread implementation of such complex interventions exist, resulting in an ‘implementation gap’. There is a lack of evidence for pharmacological prophylaxis for the prevention of delirium. Current evidence suggests that avoidance of peri-operative benzodiazepines, careful titration of anaesthetic depth guided by processed electroencephalogram monitoring and treatment of pain are the most effective strategies to minimise the risk of delirium. Addressing postoperative delirium requires a collaborative, whole pathway approach, beginning with the early identification of those patients who are at risk. The research agenda should continue to examine the potential for pharmacological prophylaxis to prevent delirium while also addressing how successful models of delirium prevention can be translated from one setting to another, underpinned by implementation science methodology.     

Multiscale quantification of morphological heterogeneity with creation of a predictor of longer survival in glioblastoma

Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.