Zafar, Sahar F.

ABSTRACT Background Critically ill patients may be overexposed to valproate because altered protein binding leads to a disproportionate free valproate fraction. The Fraser equation was derived and internally validated to estimate critically ill patients' free valproate concentrations, but it requires external validation. Methods Adult intensive care unit (ICU) patients at two academic centers with concurrently measured free and total valproate concentrations were included. Free valproate concentrations were estimated using the Fraser equation which includes total valproate, albumin and BUN concentration, and whether the patient received propofol or aspirin. The primary outcome was Fraser equation performance, assessed using Bland–Altman methods. Comparative performance against estimates from the Doré equation (an alternative predictive equation), therapeutic concordance using a target free valproate range of 5–15 mg/L, and equation improvements were explored. Results Overall, 315 patients and 556 free‐total valproate concentration pairs were included. The mean (±SD) age was 58 (±17) years and 90 (29%) patients were on valproate prior to hospital admission. The Fraser equation estimated free valproate concentrations were correlated with measured concentrations ( r = 0.728) with a negative bias (mean bias −2.77 mg/L, 95% LOA –18.9, 13.4). The Fraser equation increasingly underestimated measured concentrations as measured concentrations increased. 71% of Fraser equation estimates were therapeutically concordant (e.g., estimate and measured both within reference range) compared to 61.9% of Doré estimates ( p = 0.001). Fraser equation modifications led to minor performance improvements but did not overcome worsening underestimation with higher measured free valproate concentrations. Conclusion The Fraser equation was moderately accurate and corresponded with an appropriate interpretation for 71% of free valproate concentrations. Worse underestimation with higher measured free valproate concentrations suggests direct measurement of free valproate concentrations is warranted. While the Fraser equation could complement therapeutic decision making at centers where direct free valproate measurements are unavailable or slow to return, its accuracy is currently insufficient to replace direct measurement.

AbstractIn response to the evolving treatment landscape for new‐onset refractory status epilepticus (NORSE) and the publication of consensus recommendations in 2022, we conducted a comparative analysis of NORSE management over time. Seventy‐seven patients were enrolled by 32 centers, from July 2016 to August 2023, in the NORSE/FIRES biorepository at Yale. Immunotherapy was administered to 88% of patients after a median of 3 days, with 52% receiving second‐line immunotherapy after a median of 12 days (anakinra 29%, rituximab 25%, and tocilizumab 19%). There was an increase in the use of second‐line immunotherapies (odds ratio [OR] = 1.4, 95% CI = 1.1–1.8) and ketogenic diet (OR = 1.8, 95% CI = 1.3–2.6) over time. Specifically, patients from 2022 to 2023 more frequently received second‐line immunotherapy (69% vs 40%; OR = 3.3; 95% CI = 1.3–8.9)—particularly anakinra (50% vs 13%; OR = 6.5; 95% CI = 2.3–21.0), and the ketogenic diet (OR = 6.8; 95% CI = 2.5–20.1)—than those before 2022. Among the 27 patients who received anakinra and/or tocilizumab, earlier administration after status epilepticus onset correlated with a shorter duration of status epilepticus (ρ = .519, p = .005). Our findings indicate an evolution in NORSE management, emphasizing the increasing use of second‐line immunotherapies and the ketogenic diet. Future research will clarify the impact of these treatments and their timing on patient outcomes.

Abstract Febrile infection‐related epilepsy syndrome (FIRES) is a subset of new onset refractory status epilepticus (NORSE) that involves a febrile infection prior to the onset of the refractory status epilepticus. It is unclear whether FIRES and non‐FIRES NORSE are distinct conditions. Here, we compare 34 patients with FIRES to 30 patients with non‐FIRES NORSE for demographics, clinical features, neuroimaging, and outcomes. Because patients with FIRES were younger than patients with non‐FIRES NORSE (median = 28 vs. 48 years old, p = .048) and more likely cryptogenic (odds ratio = 6.89), we next ran a regression analysis using age or etiology as a covariate. Respiratory and gastrointestinal prodromes occurred more frequently in FIRES patients, but no difference was found for non‐infection‐related prodromes. Status epilepticus subtype, cerebrospinal fluid (CSF) and magnetic resonance imaging findings, and outcomes were similar. However, FIRES cases were more frequently cryptogenic; had higher CSF interleukin 6, CSF macrophage inflammatory protein‐1 alpha (MIP‐1a), and serum chemokine ligand 2 (CCL2) levels; and received more antiseizure medications and immunotherapy. After controlling for age or etiology, no differences were observed in presenting symptoms and signs or inflammatory biomarkers, suggesting that FIRES and non‐FIRES NORSE are very similar conditions.