Formalin-free tissue embedding is less hazardous and results in better DNA quality.

Disease diagnosis, prognosis, and therapy choice progressively rely on good-quality Deoxyribonucleic acid (DNA) for molecular analysis. As tissue processing is routinely performed worldwide with ancient techniques using toxic and DNA-damaging formaldehyde, the quality of DNA isolated from embedded tissues used for diagnostics is poor. We used a novel formalin-free tissue embedding method to process tissues and show that, after 5 years, DNA quality is superior to formalin fixation.

Osimertinib and palbociclib in an EGFR-mutated NSCLC with primary CDK4 amplification after progression under osimertinib.

Precision cancer medicine has changed the treatment paradigm of patients with non-small cell lung cancer (NSCLC) with specific molecular aberrations. A major challenge is management of the resistance that tumor cells eventually develop against targeted therapies, either through primary or acquired resistance mechanisms. We report a 61 year-old male patient with metastatic NSCLC harboring an EGFR exon 19 deletion, a PIK3CA mutation, and CDK4 amplification.

Design, validation and implementation of an automated e-alert for acute kidney injury: 6-month pilot study shows increased awareness.

Background: Acute kidney injury (AKI) is defined as a sudden episode of kidney failure but is known to be under-recognized by healthcare professionals. The Kidney Disease Improving Global Outcome (KDIGO) guidelines have formulated criteria to facilitate AKI diagnosis by comparing changes in plasma creatinine measurements (PCr). To improve AKI awareness, we implemented these criteria as an electronic alert (e-alert), in our electronic health record (EHR) system.

Added diagnostic value of routinely measured hematology variables in diagnosing immune checkpoint inhibitor mediated toxicity in the emergency department.

Background: Immune checkpoint inhibitors (ICI) show remarkable results in cancer treatment, but at the cost of immune-related adverse events (irAE). irAE can be difficult to differentiate from infections or tumor progression, thereby challenging treatment, especially in the emergency department (ED) where time and clinical information are limited. As infections are traceable in blood, we were interested in the added diagnostic value of routinely measured hematological blood cell characteristics in addition to standard diagnostic practice in the ED to aid irAE assessment.

A machine learning approach using endpoint adjudication committee labels for the identification of sepsis predictors at the emergency department.

Accurate sepsis diagnosis is paramount for treatment decisions, especially at the emergency department (ED). To improve diagnosis, clinical decision support (CDS) tools are being developed with machine learning (ML) algorithms, using a wide range of variable groups. ML models can find patterns in Electronic Health Record (EHR) data that are unseen by the human eye.