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662 Background: Alkylating-based chemotherapy (ALK) is one of the main treatments used in patients with advanced pancreatic neuroendocrine tumors (PanNETs). Its use has been associated with an increased risk of grade progression and acquisition of a hypermutator phenotype, associated with frequent alterations of the mismatch repair (MMR) genes. This suggests a potential benefit of immune checkpoint inhibitors (ICI) that are otherwise ineffective in ALK-naïve PanNETs, which are mostly hypomutated. We aimed to describe the efficacy of ICI in patients with advanced PanNET pretreated with ALK. Methods: We assembled an international retrospective cohort of patients with advanced PanNET who received at least one cycle of ICI, and who had previously received at least 3 months of ALK. Patients with poorly-differentiated neuroendocrine carcinoma were excluded. The primary endpoint was progression-free survival (PFS) and the secondary endpoint was the objective response rate (ORR). The impact of tumor mutational burden (TMB, high being defined by >10 mut/Mb) and MMR alterations (mutations or IHC) was explored. Results: We included 39 patients (median age 58.7, male sex 62%). All PanNETs were progressive at baseline and presented a median of 3 (IQR, 2-4) metastatic sites. Tumors were predominantly classified as G2 (47%) or G3 (42%), with a median Ki-67 of 18.5% (IQR, 12-35). 23/27 patients with tumor tissue or ctDNA NGS testing had high TMB (median, 35 mut/Mb; IQR, 24-106) and 12/22 had MMR alterations. Patients had previously received an average of 14 cycles (IQR, 7-25) of ALK (temozolomide 78%, streptozotocin 18%, dacarbazine 4%), which had yielded objective response in 72% of cases. In addition, patients had received a median of 4 (IQR, 3-5) other treatments (including platinum drugs in 80% and PRRT in 51%). ICI mainly consisted in an anti-PDL1/PD1 + anti-CTLA4 combination (85%) or a monotherapy (15%), with a median of 3 (IQR, 2-8) cycles. The ORR was 18% and the disease control rate was 46%. Median PFS was 2.8 months (95% CI, 0.62-4.96) and 6-month PFS rate was 31%. 19% of patients had grade 3-4 toxicity. Patients with high TMB had higher ORR (30% vs. 0%, p=0.03) and longer median PFS (4.9 vs. 2.1 months, p=0.004) compared with patients with low/unknown TMB. Patients with altered MMR had higher ORR (42% vs. 7%, p=0.02) and longer median PFS (8.9 vs. 2.5 months, p=0.014) compared with patients with no/unknown MMR alterations. Conclusions: While ICI shows limited efficacy in unselected patients with advanced PanNETs pretreated with ALK, it may be an effective treatment option in case of high TMB and MMR alterations.

ABSTRACTBackground and AimsAcute liver failure (ALF) is a serious condition, typically in individuals without prior liver disease. Drug‐induced ALF (DIALF) constitutes a major portion of ALF cases. Our research aimed to identify potential genetic predispositions to DIALF.MethodsWe analysed the potential genetic variants associated with DIALF using the whole exome sequencing data from 75 cases, including 40 non‐Finnish European cases in the pilot study. Chi‐square tests were performed for case–control analysis against the 1000 genomes project as the control. A replication study of 44 DIALF cases that included 24 non‐Finnish Europeans was conducted to validate candidate variants. The association between clinical phenotype and genotypes was analysed using one‐way analysis of variance.ResultsEight variants (rs561037, rs561042, rs608339, rs655260, rs1142886, rs1142888, rs1142889 and rs1142890) in the guanylate binding protein 4 (GBP4) were significantly associated with DIALF in non‐Finnish Europeans in the pilot study and confirmed in the replication study. Rs561037 and rs561042 were highly significant with the lowest allele frequencies in both pilot and replication studies. An association was also found between these variants and milder clinical outcomes, indicated by lower peak levels of ALT, AST and higher Karnofsky performance scores.ConclusionOur study identified eight GBP4 missense variants linked to a lower risk of DIALF in the non‐Finnish European population. The GBP4 protein, activated by interferon‐gamma, plays a critical role in innate immunity. These findings suggest that GBP4 variants might influence immune and inflammatory responses in DIALF, though further studies are needed to elucidate the underlying mechanisms.

Importance Depressive symptoms are associated with cognitive decline in older individuals. Uncertainty about underlying mechanisms hampers diagnostic and therapeutic efforts. This large-scale study aimed to elucidate the association between depressive symptoms and amyloid pathology. Objective To examine the association between depressive symptoms and amyloid pathology and its dependency on age, sex, education, and APOE genotype in older individuals without dementia. Design, Setting, and Participants Cross-sectional analyses were performed using data from the Amyloid Biomarker Study data pooling initiative. Data from 49 research, population-based, and memory clinic studies were pooled and harmonized. The Amyloid Biomarker Study has been collecting data since 2012 and data collection is ongoing. At the time of analysis, 95 centers were included in the Amyloid Biomarker Study. The study included 9746 individuals with normal cognition (NC) and 3023 participants with mild cognitive impairment (MCI) aged between 34 and 100 years for whom data on amyloid biomarkers, presence of depressive symptoms, and age were available. Data were analyzed from December 2022 to February 2024. Main Outcomes and Measures Amyloid-β1-42 levels in cerebrospinal fluid or amyloid positron emission tomography scans were used to determine presence or absence of amyloid pathology. Presence of depressive symptoms was determined on the basis of validated depression rating scale scores, evidence of a current clinical diagnosis of depression, or self-reported depressive symptoms. Results In individuals with NC (mean [SD] age, 68.6 [8.9] years; 5664 [58.2%] female; 3002 [34.0%] APOE ε4 carriers; 937 [9.6%] had depressive symptoms; 2648 [27.2%] had amyloid pathology), the presence of depressive symptoms was not associated with amyloid pathology (odds ratio [OR], 1.13; 95% CI, 0.90-1.40; P = .29). In individuals with MCI (mean [SD] age, 70.2 [8.7] years; 1481 [49.0%] female; 1046 [44.8%] APOE ε4 carriers; 824 [27.3%] had depressive symptoms; 1668 [55.8%] had amyloid pathology), the presence of depressive symptoms was associated with a lower likelihood of amyloid pathology (OR, 0.73; 95% CI 0.61-0.89; P = .001). When considering subgroup effects, in individuals with NC, the presence of depressive symptoms was associated with a higher frequency of amyloid pathology in APOE ε4 noncarriers (mean difference, 5.0%; 95% CI 1.0-9.0; P = .02) but not in APOE ε4 carriers. This was not the case in individuals with MCI. Conclusions and Relevance Depressive symptoms were not consistently associated with a higher frequency of amyloid pathology in participants with NC and were associated with a lower likelihood of amyloid pathology in participants with MCI. These findings were not influenced by age, sex, or education level. Mechanisms other than amyloid accumulation may commonly underlie depressive symptoms in late life.

ImportanceBlood culture (BC) use benchmarks in US hospitals have not been defined.ObjectiveTo characterize BC use in adult intensive care units (ICUs) and wards in US hospitals.Design, Setting, and ParticipantsA retrospective cross-sectional study of BC use in adult medical ICUs, medical-surgical ICUs, medical wards, and medical-surgical wards from acute care hospitals from the 4 US geographic regions was conducted. Critical access hospitals, less than 6 months of BC data, and non-US hospitals were excluded. The study included BC use data from September 1, 2019, to August 31, 2021. Data were analyzed from February 23 to July 14, 2024.Main Outcomes and MeasuresThe primary outcome was BC use per 1000 patient-days. Adjusted means with 95% CIs were calculated using mixed-effects negative binomial regression models adjusted for unit type, hospital bed size, geographic region, seasonality, and state COVID-19 case load, with random intercepts accounting for clustering at unit and hospital levels. Secondary outcomes included blood culture positivity, single BCs, BC contamination, and minimum threshold for BC use where blood culture positivity would be optimized.ResultsA total of 362 327 blood cultures were analyzed from 27 medical ICUs, 35 medical-surgical ICUs, 121 medical wards, and 109 medical-surgical wards from 48 hospitals in 19 states and the District of Columbia. The adjusted mean BC use per 1000 patient-days was 273.1 (95% CI, 270.2-275.9) for medical ICUs, 146.0 (95% CI, 144.5-147.5) for medical-surgical ICUs, 80.3 (95% CI, 79.8-80.7) for medical wards, and 65.1 for medical-surgical wards. Blood culture use was significantly higher across all 4 unit types in hospitals with more than 500 beds compared with 500 or less beds and in the West-Midwest compared with other regions. Single blood culture and positive blood culture rates were below 10% across all 4 unit types. Of the 292 units, 97% had a mean BC contamination rate within 3% of the recommended threshold, and 51% were within 1%. The minimum BC use thresholds (ie, BC use below this number may represent undertesting) were 120 BCs per 1000 patient-days for medical ICUs, 80 BCs per 1000 patient-days for medical-surgical ICUs, and 30 BCs per 1000 patient-days for medical-surgical wards.Conclusions and RelevanceThe findings of this study suggest that blood culture positivity may help determine appropriate BC use for individual unit types.

Accurate identification of surgical instruments is crucial for efficient workflows and patient safety within the operating room, particularly in preventing complications such as retained surgical instruments. Artificial Intelligence (AI) models have shown the potential to automate this process. This study evaluates the accuracy of publicly available Large Language Models (LLMs)—ChatGPT-4, ChatGPT-4o, and Gemini—and a specialized commercial mobile application, Surgical-Instrument Directory (SID 2.0), in identifying surgical instruments from images. The study utilized a dataset of 92 high-resolution images of 25 surgical instruments (retractors, forceps, scissors, and trocars) photographed from multiple angles. Model performance was evaluated using accuracy, weighted precision, recall, and F1 score. ChatGPT-4o exhibited the highest accuracy (89.1%) in categorizing instruments (e.g., scissors, forceps). SID 2.0 (77.2%) and ChatGPT-4 (76.1%) achieved comparable accuracy, while Gemini (44.6%) demonstrated lower accuracy in this task. For precise subtype identification of instrument names (like “Mayo scissors” or “Kelly forceps”), all models had low accuracy, with SID 2.0 having an accuracy of 39.1%, followed by ChatGPT-4o (33.69%). Subgroup analysis revealed ChatGPT-4 and 4o recognized trocars in all instances. Similarly, Gemini identified surgical scissors in all instances. In conclusion, publicly available LLMs can reliably identify surgical instruments at the category level, with ChatGPT-4o demonstrating an overall edge. However, precise subtype identification remains a challenge for all models. These findings highlight the potential of AI-driven solutions to enhance surgical-instrument management and underscore the need for further refinements to improve accuracy and support patient safety.

AbstractBackgroundAnti‐amyloid monoclonal antibody therapies for AD have documented plaque removal on amyloid PET scans. We evaluate the findings for amyloid PET, tau PET, FDG PET and volumetric MRI over the course the open label extension (OLE) for the DIAN‐TU gantenerumab treatment, compared to the last imaging obtained prior to the OLE (to evaluate for potential rebound effects) and in comparison to longitudinal imaging in the DIAN Observational study.MethodThis double‐blind, phase 2/3 trial (2012‐2019), followed by open‐label extension (OLE), investigated varying gantenerumab doses up to 1500 mg SQ q2 weeks [NCT NCT01760005]. We report long‐term amyloid‐plaque removal by PET and findings for metabolic FDG PET and tau PET, and additionally changes of atrophy on volumetric MRI. Imaging measures were secondary outcome analyses. Comparison is made between the treatment cohort and controls (DB placebo participants who didn’t enter OLE, plus external controls from the DIAN OBS). Estimated years to onset was included as a covariate. The gap period of ∼1 year is specifically analyzed to estimate any “rebound” effect on amyloid or tau accumulation or neurodegeneration. Volumetric MRI measures include hippocampal volumes, lateral ventricular volumes, and white matter hyperintensities.ResultIn participants who were asymptomatic at baseline and treated with gantenerumab (n = 53), amyloid‐plaque removal measured by PIB‐PET in Centiloids was dose‐dependent. Few participants had reached completely negative levels (below 24). No statistical significance was found for FDG PET, tau PET, or volumetric MRI, including hippocampal volumes. Impact of the gap period of ∼1 year (gap in treatment) on the rate of amyloid accumulation compared to the rate of accumulation predicted in observational studies of this cohort is under evaluation, as are the other imaging measures.ConclusionWhile no overall effect was observed in the total group for non‐amyloid measures, results suggest dose dependent clearance of amyloid plaque in asymptomatic DIAD mutation carriers following long‐term, high‐dose gantenerumab. The potential “rebound effect” of elevated amyloid accumulation for participants for whom there was a significant gap in therapy between the trial and the OLE is under evaluation and will be presented, as will the variables for FDG PET, tau PET, and volumetric MRI.

AbstractBackgroundAutosomal dominant Alzheimer disease (ADAD) is characterized by genetic mutations affecting the beta‐amyloid (Aβ) pathway. However, vascular and immune factors play important roles which are not completely understood. Understanding the function of the neurovascular unit (NVU) comprised of neurons, glial cells, and vasculature, at different disease stages appears ideal to developing and evaluating therapeutics. Omics approaches can inform NVU changes and their disease associations.MethodsCSF proteomic data using the Somalogic® platform was generated from 485 participants in the DIAN study, who also had PiB‐PET and MRI assessing Aβ burden, white matter hyperintensity (WMH), and cerebral microhemorrhage (CMH). From previously published AD studies, we identified 33 NVU‐associated proteins with corresponding Somalogic aptamers (Figure 1). We used Principal Component Analysis (PCA) on participants with complete data (n=262, 166 mutation‐carriers and 96 non‐carriers) to find groups of proteins associated with mutation status and disease stage as measured with estimated year to symptom onset (EYO), PiB‐PET, and clinical status. Linear‐mixed effect models and two‐part zero‐inflated negative binomial mixed models further evaluated the link between significant principal components (PCs) and WMH and CMH, respectively. Models accounted for age, APOE‐e4 status, sex, and education.ResultsThe first ten PCs explained >60% of the variance in NVU‐related protein levels (Figure 2A) with only PC5 (4.8%) associated with mutation*EYO, suggesting relationship with ADAD‐specific disease progression (***p<0.0001, Figure 2B). While asymptomatic PiB‐negative individuals were not significantly different from non‐carriers, asymptomatic PiB‐positive individuals had higher PC5 scores than non‐carriers and symptomatic individuals scored still higher (**p<0.005, ***p<0.0001, Figure 2C). The main proteins composing PC5 were: neurofilament light‐chain, angiopoietin‐2, SMOC1, LRP1, E‐selectin, and sTREM2, suggesting strong association with proinflammatory glial response from neuronal injury (Figure 2D). PC5 was also associated with WMH volumes (*p<0.05, Figure 3A) and with CMH count in participants with CMH (**p<0.005, Figure 3B).ConclusionsThis PCA approach indicates that some groups of NVU‐associated proteins are related with mutation status and disease stage, and that they are differentially associated with features of ADAD such as white matter integrity as measured by WMH volume. Weighted Correlation Network Analysis will be of interest to further understand these associations.Funding: K01AG080123, RF1‐AG044546, UF1AG032438

AbstractBackgroundAutosomal dominant Alzheimer disease (ADAD) is characterized by genetic mutations affecting the beta‐amyloid (Aß) pathway. However, vascular and immune factors play important roles which are not completely understood. Understanding the function of the neurovascular unit (NVU) comprised of neurons, glial cells, and vasculature, at different disease stages appears ideal to developing and evaluating therapeutics. Omics approaches can inform NVU changes and their disease associations.MethodsCSF proteomic data using the Somalogic® platform was generated from 485 participants in the DIAN study, who also had PiB‐PET and MRI assessing Aß burden, white matter hyperintensity (WMH), and cerebral microhemorrhage (CMH). From previously published AD studies, we identified 33 NVU‐associated proteins with corresponding Somalogic aptamers (Figure 1). We used Principal Component Analysis (PCA) on participants with complete data (n = 262, 166 mutation‐carriers and 96 non‐carriers) to find groups of proteins associated with mutation status and disease stage as measured with estimated year to symptom onset (EYO), PiB‐PET, and clinical status. Linear‐mixed effect models and two‐part zero‐inflated negative binomial mixed models further evaluated the link between significant principal components (PCs) and WMH and CMH, respectively. Models accounted for age, APOE‐e4 status, sex, and education.ResultsThe first ten PCs explained >60% of the variance in NVU‐related protein levels (Figure 2A) with only PC5 (4.8%) associated with mutation*EYO, suggesting relationship with ADAD‐specific disease progression (***p<0.0001, Figure 2B). While asymptomatic PiB‐negative individuals were not significantly different from non‐carriers, asymptomatic PiB‐positive individuals had higher PC5 scores than non‐carriers and symptomatic individuals scored still higher (**p<0.005, ***p<0.0001, Figure 2C). The main proteins composing PC5 were: neurofilament light‐chain, angiopoietin‐2, SMOC1, LRP1, E‐selectin, and sTREM2, suggesting strong association with proinflammatory glial response from neuronal injury (Figure 2D). PC5 was also associated with WMH volumes (*p<0.05, Figure 3A) and with CMH count in participants with CMH (**p<0.005, Figure 3B).ConclusionsThis PCA approach indicates that some groups of NVU‐associated proteins are related with mutation status and disease stage, and that they are differentially associated with features of ADAD such as white matter integrity as measured by WMH volume. Weighted Correlation Network Analysis will be of interest to further understand these associations. Funding: K01AG080123, RF1‐AG044546, UF1AG032438

Current clinical care relies heavily on complex, rule-based systems for tasks like diagnosis and treatment. However, these systems can be cumbersome and require constant updates. This study explores the potential of the large language model (LLM), LLaMA 2, to address these limitations. We tested LLaMA 2′s performance in interpreting complex clinical process models, such as Mayo Clinic Care Pathway Models (CPMs), and providing accurate clinical recommendations. LLM was trained on encoded pathways versions using DOT language, embedding them with SentenceTransformer, and then presented with hypothetical patient cases. We compared the token-level accuracy between LLM output and the ground truth by measuring both node and edge accuracy. LLaMA 2 accurately retrieved the diagnosis, suggested further evaluation, and delivered appropriate management steps, all based on the pathways. The average node accuracy across the different pathways was 0.91 (SD ± 0.045), while the average edge accuracy was 0.92 (SD ± 0.122). This study highlights the potential of LLMs for healthcare information retrieval, especially when relevant data are provided. Future research should focus on improving these models’ interpretability and their integration into existing clinical workflows.

OBJECTIVE While the relationship between smoking and subarachnoid hemorrhage is well established, data regarding the probability of detecting unruptured intracranial aneurysms (UIAs) in smokers remain sparse. The aim of this systematic review and meta-analysis is to provide a comprehensive understanding of the relationship between smoking and the likelihood of identifying UIAs in healthy asymptomatic patients who underwent brain imaging for indications unrelated to UIAs. METHODS A systematic review was conducted following the PRISMA guidelines. The PubMed and Scopus databases were searched for studies published before March 2024 that reported on the presence of UIAs in healthy asymptomatic patients who had undergone brain imaging for indications unrelated to UIAs. Three independent reviewers assessed the eligibility of all retrieved studies. Risk of bias for the included observational studies was assessed using the methodological index for non-randomized studies. Data on UIA prevalence, smoking status, and patient and aneurysm characteristics were extracted. The association between smoking and the presence of UIA was studied. A prevalence proportional meta-analysis was conducted across the included studies. A meta-analysis was performed with a random-effects model by using summary statistics from the included studies. RESULTS Six studies involving 47,788 patients who had undergone brain imaging were identified for quantitative analysis. The pooled UIA prevalence in the sample was 3.07% (95% CI 2.27%–4.16%). Patients who smoked had higher rates of aneurysm detection than the patients who did not smoke (pooled prevalence of 2.96%, 95% CI 2.68%–3.27% vs 2.23%, 95% CI 2.08%–2.39%). Although the relation between the two was not statistically significant (p = 0.06), smoking was associated with higher odds for UIA detection, yielding an OR of 1.34 (95% CI 1.07–1.67) with an I 2 value of 53%. CONCLUSIONS This study suggests a potentially higher risk of UIAs in patients who smoked than in those who never smoked. However, the results of this meta-analysis revealed that smoking was not statistically associated with higher UIA detection. This result could be explained by the limited number of studies published on this topic. If these findings reach statistical significance in future larger studies, it could justify revising guidelines to include cigarette smokers in intracranial aneurysm screening.