The Formation and Function of Granulomas.

Granulomas are organized aggregates of macrophages, often with characteristic morphological changes, and other immune cells. These evolutionarily ancient structures form in response to persistent particulate stimuli-infectious or noninfectious-that individual macrophages cannot eradicate. Granulomas evolved as protective responses to destroy or sequester particles but are frequently pathological in the context of foreign bodies, infections, and inflammatory diseases. We summarize recent findings that suggest that the granulomatous response unfolds in a stepwise program characterized by a series of macrophage activations and transformations that in turn recruit additional cells and produce structural changes. We explore why different granulomas vary and the reasons that granulomas are protective and pathogenic. Understanding the mechanisms and role of granuloma formation may uncover new therapies for the multitude of granulomatous diseases that constitute serious medical problems while enhancing the protective function of granulomas in infections.

Autoimmunity and organ damage in systemic lupus erythematosus.

Impressive progress has been made over the last several years toward understanding how almost every aspect of the immune system contributes to the expression of systemic autoimmunity. In parallel, studies have shed light on the mechanisms that contribute to organ inflammation and damage. New approaches that address the complicated interaction between genetic variants, epigenetic processes, sex and the environment promise to enlighten the multitude of pathways that lead to what is clinically defined as systemic lupus erythematosus. It is expected that each patient owns a unique 'interactome', which will dictate specific treatment.

Plasma cell-free RNA signatures of inflammatory syndromes in children.

Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circulating cell-free RNA (cfRNA) in plasma as an analyte for the differential diagnosis and characterization of pediatric inflammatory syndromes. We profiled cfRNA in 370 plasma samples from pediatric patients with a range of inflammatory conditions, including Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), viral infections, and bacterial infections. We developed machine learning models based on these cfRNA profiles, which effectively differentiated KD from MIS-C-two conditions presenting with overlapping symptoms-with high performance [test area under the curve = 0.98]. We further extended this methodology into a multiclass machine learning framework that achieved 80% accuracy in distinguishing among KD, MIS-C, viral, and bacterial infections. We further demonstrated that cfRNA profiles can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system, and the upper respiratory tract. Overall, this study identified cfRNA as a versatile analyte for the differential diagnosis and characterization of a wide range of pediatric inflammatory syndromes.

Arginine or Hypertonic Saline-Stimulated Copeptin to Diagnose AVP Deficiency.

BACKGROUND: Distinguishing between arginine vasopressin (AVP) deficiency and primary polydipsia is challenging. Hypertonic saline-stimulated copeptin has been used to diagnose AVP deficiency with high accuracy but requires close sodium monitoring. Arginine-stimulated copeptin has shown similar diagnostic accuracy but with a simpler test protocol. However, data are lacking from a head-to-head comparison between arginine-stimulated copeptin and hypertonic saline-stimulated copeptin in the diagnosis of AVP deficiency. METHODS: In this international, noninferiority trial, we assigned adult patients with polydipsia and hypotonic polyuria or a known diagnosis of AVP deficiency to undergo diagnostic evaluation with hypertonic-saline stimulation on one day and with arginine stimulation on another day. Two endocrinologists independently made the final diagnosis of AVP deficiency or primary polydipsia with use of clinical information, treatment response, and the hypertonic-saline test results. The primary outcome was the overall diagnostic accuracy according to prespecified copeptin cutoff values of 3.8 pmol per liter after 60 minutes for arginine and 4.9 pmol per liter once the sodium level was more than 149 mmol per liter for hypertonic saline. RESULTS: Of the 158 patients who underwent the two tests, 69 (44%) received the diagnosis of AVP deficiency and 89 (56%) received the diagnosis of primary polydipsia. The diagnostic accuracy was 74.4% (95% confidence interval [CI], 67.0 to 80.6) for arginine-stimulated copeptin and 95.6% (95% CI, 91.1 to 97.8) for hypertonic saline-stimulated copeptin (estimated difference, -21.2 percentage points; 95% CI, -28.7 to -14.3). Adverse events were generally mild with the two tests. A total of 72% of the patients preferred testing with arginine as compared with hypertonic saline. Arginine-stimulated copeptin at a value of 3.0 pmol per liter or less led to a diagnosis of AVP deficiency with a specificity of 90.9% (95% CI, 81.7 to 95.7), whereas levels of more than 5.2 pmol per liter led to a diagnosis of primary polydipsia with a specificity of 91.4% (95% CI, 83.7 to 95.6). CONCLUSIONS: Among adult patients with polyuria polydipsia syndrome, AVP deficiency was more accurately diagnosed with hypertonic saline-stimulated copeptin than with arginine-stimulated copeptin. (Funded by the Swiss National Science Foundation; CARGOx ClinicalTrials.gov number, NCT03572166.).

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer.

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Behçet's syndrome.

Behçet's syndrome is a rare, chronic multisystemic inflammatory disorder also known as the Silk Route disease due to its geographical distribution. Behçet's syndrome is a multifactorial disease and infectious, genetic, epigenetic, and immunological factors contribute to its pathogenesis. Its heterogeneous spectrum of clinical features include mucocutaneous, articular, ocular, vascular, neurological, and gastrointestinal manifestations that can present with a relapsing and remitting course. Differential diagnosis is often hampered by the non-specific clinical presentation and the absence of laboratory biomarkers or pathognomonic histological features. The therapeutic approach is tailored on the basis of patient-specific manifestations and relies on glucocorticoids, colchicine, and traditional and biological immunosuppressants. Despite progress in the knowledge and management of the disease, unmet needs in diagnostics, monitoring, prediction, and treatment personalisation challenge clinical practice, making Behçet's syndrome a complex disorder associated with an increased risk of morbidity.

Celiac Disease-Related Conditions: Who to Test?

Celiac disease (CeD) is a chronic immune-mediated condition triggered by gluten consumption in genetically predisposed individuals. Approximately 1% of the general population is affected by the disorder. Disease presentation is heterogeneous and, despite growing awareness among physicians and the public, it continues to be underestimated. The most effective strategy for identifying undiagnosed CeD is proactive case finding through serologic testing in high-risk groups. We reviewed the most recent evidence on the association between CeD and more than 20 conditions. In light of this review, CeD screening is recommended in individuals with (1) autoimmune disease and accompanying symptoms suggestive of CeD; (2) diseases that may mimic CeD (eg, irritable bowel syndrome [IBS], inflammatory bowel disease [IBD], and microscopic colitis); and (3) among patients with conditions with a high CeD prevalence: first-degree relatives, idiopathic pancreatitis, unexplained liver enzyme abnormalities, autoimmune hepatitis, primary biliary cholangitis, hyposplenism or functional asplenia with severe bacterial infection, type 1 diabetes mellitus, Hashimoto's thyroiditis and Graves' disease, Sjögren's syndrome, dermatitis herpetiformis, recurrent aphthous syndrome and enamel defects, unexplained ataxia, peripheral neuropathy, delayed menarche or premature menopause, Down syndrome, Turner syndrome, Williams syndrome, chronic fatigue syndrome, IgA nephropathy, and IgA deficiency. CeD serology should be the initial step in the screening process. However, for patients with any of the aforementioned disorders who are undergoing upper endoscopy, biopsies should be performed to rule out CeD.

Rapid Endoscopic Diagnosis of Benign Ulcerative Colorectal Diseases With an Artificial Intelligence Contextual Framework.

BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's disease, ischemic colitis, and intestinal tuberculosis share similar phenotypes with different etiologies and treatment strategies. To accurately diagnose closely related diseases like UCDs, we hypothesize that contextual learning is critical in enhancing the ability of the artificial intelligence models to differentiate the subtle differences in lesions amidst the vastly divergent spatial contexts. METHODS: White-light colonoscopy datasets of patients with confirmed UCDs and healthy controls were retrospectively collected. We developed a Multiclass Contextual Classification (MCC) model that can differentiate among the mentioned UCDs and healthy controls by incorporating the tissue object contexts surrounding the individual lesion region in a scene and spatial information from other endoscopic frames (video-level) into a unified framework. Internal and external datasets were used to validate the model's performance. RESULTS: Training datasets included 762 patients, and the internal and external testing cohorts included 257 patients and 293 patients, respectively. Our MCC model provided a rapid reference diagnosis on internal test sets with a high averaged area under the receiver operating characteristic curve (image-level: 0.950 and video-level: 0.973) and balanced accuracy (image-level: 76.1% and video-level: 80.8%), which was superior to junior endoscopists (accuracy: 71.8%, P < .0001) and similar to experts (accuracy: 79.7%, P = .732). The MCC model achieved an area under the receiver operating characteristic curve of 0.988 and balanced accuracy of 85.8% using external testing datasets. CONCLUSIONS: These results enable this model to fit in the routine endoscopic workflow, and the contextual framework to be adopted for diagnosing other closely related diseases.

Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study.

OBJECTIVE: We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). METHODS: Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). RESULTS: Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). INTERPRETATION: Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024;96:476-487.

Differential diagnosis of bone marrow failure syndromes guided by machine learning.

The choice to postpone treatment while awaiting genetic testing can result in significant delay in definitive therapies in patients with severe pancytopenia. Conversely, the misdiagnosis of inherited bone marrow failure (BMF) can expose patients to ineffectual and expensive therapies, toxic transplant conditioning regimens, and inappropriate use of an affected family member as a stem cell donor. To predict the likelihood of patients having acquired or inherited BMF, we developed a 2-step data-driven machine-learning model using 25 clinical and laboratory variables typically recorded at the initial clinical encounter. For model development, patients were labeled as having acquired or inherited BMF depending on their genomic data. Data sets were unbiasedly clustered, and an ensemble model was trained with cases from the largest cluster of a training cohort (n = 359) and validated with an independent cohort (n = 127). Cluster A, the largest group, was mostly immune or inherited aplastic anemia, whereas cluster B comprised underrepresented BMF phenotypes and was not included in the next step of data modeling because of a small sample size. The ensemble cluster A-specific model was accurate (89%) to predict BMF etiology, correctly predicting inherited and likely immune BMF in 79% and 92% of cases, respectively. Our model represents a practical guide for BMF diagnosis and highlights the importance of clinical and laboratory variables in the initial evaluation, particularly telomere length. Our tool can be potentially used by general hematologists and health care providers not specialized in BMF, and in under-resourced centers, to prioritize patients for genetic testing or for expeditious treatment.

Hodgkin lymphoma: A review and update on recent progress.

Hodgkin lymphoma (HL) is a unique hematopoietic neoplasm characterized by cancerous Reed-Sternberg cells in an inflammatory background. Patients are commonly diagnosed with HL in their 20s and 30s, and they present with supradiaphragmatic lymphadenopathy, often with systemic B symptoms. Even in advanced-stage disease, HL is highly curable with combination chemotherapy, radiation, or combined-modality treatment. Although the same doxorubicin, bleomycin, vinblastine, and dacarbazine chemotherapeutic regimen has been the mainstay of therapy over the last 30 years, risk-adapted approaches have helped de-escalate therapy in low-risk patients while intensifying treatment for higher risk patients. Even patients who are not cured with initial therapy can often be salvaged with alternate chemotherapy combinations, the novel antibody-drug conjugate brentuximab, or high-dose autologous or allogeneic hematopoietic stem cell transplantation. The programmed death-1 inhibitors nivolumab and pembrolizumab have both demonstrated high response rates and durable remissions in patients with relapsed/refractory HL. Alternate donor sources and reduced-intensity conditioning have made allogeneic hematopoietic stem cell transplantation a viable option for more patients. Future research will look to integrate novel strategies into earlier lines of therapy to improve the HL cure rate and minimize long-term treatment toxicities. CA Cancer J Clin 2018;68:116-132. © 2017 American Cancer Society.

Hypercalcemia and cancer: Differential diagnosis and treatment.

Incidentally detected hypercalcemia usually presents in an indolent manner and is most likely caused by primary hyperparathyroidism. In contrast, hypercalcemia in the patient with a history of cancer presents in a wide range of clinical settings and may be severe enough to warrant hospitalization. This form of hypercalcemia is usually secondary to hypercalcemia of malignancy and can be fatal. Hypercalcemia of malignancy is most commonly mediated by tumoral production of parathyroid hormone-related protein or by cytokines activating osteoclast degradation of bone. The initial workup, differential diagnoses, confirmatory laboratory testing, imaging, and medical and surgical management of hypercalcemia are described in the patient with cancer.

The incidental thyroid nodule.

Incidental thyroid nodules that are found on an imaging study performed for reasons other than thyroid pathology represent a common scenario encountered by health care providers. The initial workup for these nodules comprises a thorough history and physical examination, thyroid function tests, a dedicated thyroid ultrasound, and fine-needle aspiration of any suspicious lesions. Management ranges from observation and reassurance to surgical resection and depends on the cytologic diagnosis. In cases of cytologically indeterminate or discordant nodules, surgical excision (lobectomy) offers a definitive diagnosis, although molecular testing or a reasonable period of observation may be useful as less invasive adjuncts. CA Cancer J Clin 2018;68:97-105. © 2018 American Cancer Society.

Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease.

Rationale: Distinguishing connective tissue disease-associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. Objectives: To identify proteins that separate and classify patients with CTD-ILD and those with IPF. Methods: Four registries with 1,247 patients with IPF and 352 patients with CTD-ILD were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using recursive feature elimination to construct a proteomic classifier. Multiple machine learning models, including support vector machine, LASSO (least absolute shrinkage and selection operator) regression, random forest, and imbalanced Random Forest, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. Measurements and Main Results: A classifier with 37 proteins (proteomic classifier 37 [PC37]) was enriched in the biological process of bronchiole development and smooth muscle proliferation and immune responses. Four machine learning models used PC37 with sex and age score to generate continuous classification values. Receiver operating characteristic curve analyses of these scores demonstrated consistent areas under the curve of 0.85-0.90 in the test cohort and 0.94-0.96 in the single-sample dataset. Binary classification demonstrated 78.6-80.4% sensitivity and 76-84.4% specificity in the test cohort and 93.5-96.1% sensitivity and 69.5-77.6% specificity in the single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194 of 248) accuracy in the test cohort and 82.9% (208 of 251) in the single-sample classification dataset. Conclusions: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Many of the identified proteins are involved in immune pathways. We further developed a novel approach for single-sample classification, which could facilitate honing the differential diagnosis of ILD in challenging cases and improve clinical decision making.

Anderson-Fabry disease management: role of the cardiologist.

Anderson-Fabry disease (AFD) is a lysosomal storage disorder characterized by glycolipid accumulation in cardiac cells, associated with a peculiar form of hypertrophic cardiomyopathy (HCM). Up to 1% of patients with a diagnosis of HCM indeed have AFD. With the availability of targeted therapies for sarcomeric HCM and its genocopies, a timely differential diagnosis is essential. Specifically, the therapeutic landscape for AFD is rapidly evolving and offers increasingly effective, disease-modifying treatment options. However, diagnosing AFD may be difficult, particularly in the non-classic phenotype with prominent or isolated cardiac involvement and no systemic red flags. For many AFD patients, the clinical journey from initial clinical manifestations to diagnosis and appropriate treatment remains challenging, due to late recognition or utter neglect. Consequently, late initiation of treatment results in an exacerbation of cardiac involvement, representing the main cause of morbidity and mortality, irrespective of gender. Optimal management of AFD patients requires a dedicated multidisciplinary team, in which the cardiologist plays a decisive role, ranging from the differential diagnosis to the prevention of complications and the evaluation of timing for disease-specific therapies. The present review aims to redefine the role of cardiologists across the main decision nodes in contemporary AFD clinical care and drug discovery.

Untying the Gordian knot of composite hemangioendothelioma: Discovery of novel fusions.

Composite hemangioendothelioma is a rare, locally aggressive, and rarely metastasizing vascular neoplasm which affects both children and adults. Recently, a number of gene fusions including YAP1::MAML2, PTBP1::MAML2, and EPC1::PHC2 have been detected in a small subset of cases with or without neuroendocrine expression. Herein, we present four additional cases with novel in-frame fusions. The cohort comprises two females and two males with a wide age range at diagnosis (24-80 years). Two tumors were deep involving the right brachial plexus and mediastinum, while the remaining were superficial (right plantar foot and abdominal wall). The size ranged from 1.5 to 4.8 cm in greatest dimension. Morphologically, all tumors had an admixture of at least two architectural patterns including retiform hemangioendothelioma, hemangioma, epithelioid hemangioendothelioma, or angiosarcoma. The tumors were positive for endothelial markers CD31 (3/3), ERG (4/4), and D2-40 (1/4, focal), while SMA was expressed in 2/3 highlighting the surrounding pericytes. Synaptophysin showed immunoreactivity in 2/3 cases. One patient had a local recurrence after 40 months, while two patients had no evidence of disease 4 months post-resection. Targeted RNA sequencing detected novel in-frame fusions in each of the cases: HSPG2::FGFR1, YAP1::FOXR1, ACTB::MAML2, and ARID1B::MAML2. The two cases with neuroendocrine expression occurred as superficial lesions and harbored YAP1::FOXR1 and ARID1B::MAML2 fusions. Our study expands on the molecular spectrum of this enigmatic tumor, further enhancing our current understanding of the disease.

Novel MED15::ATF1 fusion in a pediatric melanoma with spitzoid features and aggressive presentation.

Childhood melanoma is a rare and biologically heterogeneous pediatric malignancy. The differential diagnosis of pediatric melanoma is usually broad, including a wide variety of spindle cell or epithelioid neoplasms. Different molecular alterations affecting the MAPK and PI3K/AKT/mTOR pathways, tumor suppressor genes, and telomerase reactivation have been implicated in melanoma tumorigenesis and progression. Here, we report a novel MED15::ATF1 fusion in a pediatric melanoma with spitzoid features and an aggressive clinical course.

The Ability of a 3-Gene Host Signature in Blood to Distinguish Tuberculous Meningitis From Other Brain Infections.

BACKGROUND: Tuberculous meningitis (TBM) is difficult to diagnose. We investigated whether a 3-gene host response signature in blood can distinguish TBM from other brain infections. METHODS: The expression of 3 genes (dual specificity phosphatase 3 [DUSP3], guanylate-binding protein [GBP5], krupple-like factor 2 [KLF2]) was analyzed by RNA sequencing of archived whole blood from 4 cohorts of Vietnamese adults: 281 with TBM, 279 with pulmonary tuberculosis, 50 with other brain infections, and 30 healthy controls. Tuberculosis scores (combined 3-gene expression) were calculated following published methodology and discriminatory performance compared using area under a receiver operator characteristic curve (AUC). RESULTS: GBP5 was upregulated in TBM compared to other brain infections (P < .001), with no difference in DUSP3 and KLF2 expression. The diagnostic performance of GBP5 alone (AUC, 0.74; 95% confidence interval [CI], .67-.81) was slightly better than the 3-gene tuberculosis score (AUC, 0.66; 95% CI, .58-.73) in TBM. Both GBP5 expression and tuberculosis score were higher in participants with human immunodeficiency virus (HIV; P < .001), with good diagnostic performance of GBP5 alone (AUC, 0.86; 95% CI, .80-.93). CONCLUSIONS: The 3-gene host signature in whole blood has the ability to discriminate TBM from other brain infections, including in individuals with HIV. Validation in large prospective diagnostic study is now required.

External Validation of the 2023 Duke-International Society for Cardiovascular Infectious Diseases Diagnostic Criteria for Infective Endocarditis.

BACKGROUND: The 2023 Duke-International Society of Cardiovascular Infectious Diseases (ISCVID) criteria for infective endocarditis (IE) were introduced to improve classification of IE for research and clinical purposes. External validation studies are required. METHODS: We studied consecutive patients with suspected IE referred to the IE team of Amsterdam University Medical Center (from October 2016 to March 2021). An international expert panel independently reviewed case summaries and assigned a final diagnosis of "IE" or "not IE," which served as the reference standard, to which the "definite" Duke-ISCVID classifications were compared. We also evaluated accuracy when excluding cardiac surgical and pathologic data ("clinical" criteria). Finally, we compared the 2023 Duke-ISCVID with the 2000 modified Duke criteria and the 2015 and 2023 European Society of Cardiology (ESC) criteria. RESULTS: A total of 595 consecutive patients with suspected IE were included: 399 (67%) were adjudicated as having IE; 111 (19%) had prosthetic valve IE, and 48 (8%) had a cardiac implantable electronic device IE. The 2023 Duke-ISCVID criteria were more sensitive than either the modified Duke or 2015 ESC criteria (84.2% vs 74.9% and 80%, respectively; P < .001) without significant loss of specificity. The 2023 Duke-ISCVID criteria were similarly sensitive but more specific than the 2023 ESC criteria (94% vs 82%; P < .001). The same pattern was seen for the clinical criteria (excluding surgical/pathologic results). New modifications in the 2023 Duke-ISCVID criteria related to "major microbiological" and "imaging" criteria had the most impact. CONCLUSIONS: The 2023 Duke-ISCVID criteria represent a significant advance in the diagnostic classification of patients with suspected IE.

Diagnostic Accuracy of Posterior/Anterior Periventricular WMH Ratio to Differentiate CAA From Hypertensive Arteriopathy.

BACKGROUND: Periventricular white matter hyperintensities (PVWMHs) in cerebral amyloid angiopathy (CAA) have been reported posterior predominant using semiautomated segmentation method and logarithmic transformation. We aimed to compare PVWMH extent and posterior/anterior distribution between patients with CAA and patients with hypertensive arteriopathy with radiological tools available in daily practice. METHODS: We retrospectively analyzed confluent PVWMH directly adjacent to lateral ventricles on axial FLAIR (fluid-attenuated inversion recovery) from 108 patients with CAA and 99 patients with hypertensive arteriopathy presenting with hemorrhage-related symptoms consecutively recruited in our stroke database (Nîmes University Hospital, France) between January 2015 and March 2022. For each of the left (L), right (R), anterior (A), and posterior (P) horns of lateral ventricles, the maximal distance between the outer PVWMH border and ventricle border was measured. The sum of anterior left PVWMH and anterior right PVWMH, and posterior left PVWMH and posterior right PVWMH resulted in anterior and posterior extent, respectively. RESULTS: Compared with hypertensive arteriopathy, patients with CAA were older (median, 77 versus 71; P=0.0010) and less frequently male (46% versus 64%; P=0.012) and had less frequent hypertension (45% versus 63%; P=0.013) and more chronic hemorrhages (P<0.0001). CAA showed slightly more extensive anterior right PVWMH (median, 6.50 versus 5.90 mm; P=0.034), far more extensive (all P<0.0001) posterior left PVWMH (median, 13.95 versus 6.95 mm), posterior right PVWMH (median, 14.15 versus 5.45 mm), posterior (median, 27.95 versus 13.00 mm), and total (median, 39.60 versus 24.65 mm) PVWMH, and higher posterior/anterior ratios (median, 1.82 versus 1.01). Age-/sex-adjusted model predicting CAA incorporating total PVWMH extent and posterior/anterior ratios for the given score (-4.3683+0.0268×PVWMH-T+0.3749×posterior/anterior PVWMH ratio+0.0394×age+0.3046 when female) showed highest area under the curve (0.76 [0.70-0.83]), with a 72% [62.50-80.99] sensitivity and 76% [67.18-84.12] specificity. Values above the optimal threshold of 0.22 for the score showed a crude relative risk of 2.75 (2.26-2.37; P<0.0001). CONCLUSIONS: Severe posterior PVWMH and high posterior/anterior PVWMH ratio assessed by radiological tools used in daily practice are associated with probable CAA versus hypertensive arteriopathy. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05486897.