Impact of the methylation classifier and ancillary methods on CNS tumor diagnostics.

BACKGROUND: Accurate CNS tumor diagnosis can be challenging, and methylation profiling can serve as an adjunct to classify diagnostically difficult cases. METHODS: An integrated diagnostic approach was employed for a consecutive series of 1258 surgical neuropathology samples obtained primarily in a consultation practice over 2-year period. DNA methylation profiling and classification using the DKFZ/Heidelberg CNS tumor classifier was performed, as well as unsupervised analyses of methylation data. Ancillary testing, where relevant, was performed. RESULTS: Among the received cases in consultation, a high-confidence methylation classifier score (>0.84) was reached in 66.4% of cases. The classifier impacted the diagnosis in 46.7% of these high-confidence classifier score cases, including a substantially new diagnosis in 26.9% cases. Among the 289 cases received with only a descriptive diagnosis, methylation was able to resolve approximately half (144, 49.8%) with high-confidence scores. Additional methods were able to resolve diagnostic uncertainty in 41.6% of the low-score cases. Tumor purity was significantly associated with classifier score (P = 1.15e-11). Deconvolution demonstrated that suspected glioblastomas (GBMs) matching as control/inflammatory brain tissue could be resolved into GBM methylation profiles, which provided a proof-of-concept approach to resolve tumor classification in the setting of low tumor purity. CONCLUSIONS: This work assesses the impact of a methylation classifier and additional methods in a consultative practice by defining the proportions with concordant vs change in diagnosis in a set of diagnostically challenging CNS tumors. We address approaches to low-confidence scores and confounding issues of low tumor purity.

The Role of the Physical Environment in Shaping Interruptions and Disruptions in Complex Health Care Settings: A Scoping Review.

Interruptions and disruptions in complex healthcare environments, such as trauma rooms, can lead to compromised workflow and safety issues due to the physical environment's characteristics. This scoping review investigated the impact of the physical environment on interruptions and disruptions and the associated outcomes in complex environments, as they relate to the components of the Systems Engineering Initiative for Patient Safety. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to conduct the scoping review. CINAHL, Web of Science, and PubMed databases were searched. After removing duplicates and eligibility screening, quality assessment was conducted using the Mixed Methods Appraisal Tool (MMAT). Of 1,158 articles found, 20 were selected. Poor layout configurations, tripping hazards, and technology integration were common examples. More research must be conducted to unveil the impact of the physical environment on interruptions and disruptions.