Role of inflammatory signaling pathways involving the CD40-CD40L-TRAF cascade in diabetes and hypertension-insights from animal and human studies.

CD40L-CD40-TRAF signaling plays a role in atherosclerosis progression and affects the pathogenesis of coronary heart disease (CHD). We tested the hypothesis that CD40L-CD40-TRAF signaling is a potential therapeutic target in hyperlipidemia, diabetes, and hypertension. In mouse models of hyperlipidemia plus diabetes (db/db mice) or hypertension (1 mg/kg/d angiotensin-II for 7 days), TRAF6 inhibitor treatment (2.5 mg/kg/d for 7 or 14 days) normalized markers of oxidative stress and inflammation. As diabetes and hypertension are important comorbidities aggravating CHD, we explored whether the CD40L-CD40-TRAF signaling cascade and their associated inflammatory pathways are expressed in CHD patients suffering from comorbidities. Therefore, we analyzed vascular bypass material (aorta or internal mammary artery) and plasma from patients with CHD with diabetes and/or hypertension. Our Olink targeted plasma proteomic analysis using the IMMUNO-ONCOLOGY panel revealed a pattern of step-wise increase for 13/92 markers of low-grade inflammation with significant changes. CD40L or CD40 significantly correlated with 38 or 56 other inflammatory targets. In addition, specific gene clusters that correlate with the comorbidities were identified in isolated aortic mRNA of CHD patients through RNA-sequencing. These signaling clusters comprised CD40L-CD40-TRAF, immune system, hemostasis, muscle contraction, metabolism of lipids, developmental biology, and apoptosis. Finally, immunological analysis revealed key markers correlated with comorbidities in CHD patients, such as CD40L, NOX2, CD68, and 3-nitrotyrosine. These data indicate that comorbidities increase inflammatory pathways in CHD, and targeting these pathways will be beneficial in reducing cardiovascular events in CHD patients with comorbidities.

A cluster of blood-based protein biomarkers associated with decreased cerebral blood flow relates to future cardiovascular events in patients with cardiovascular disease.

Biological processes underlying decreased cerebral blood flow (CBF) in patients with cardiovascular disease (CVD) are largely unknown. We hypothesized that identification of protein clusters associated with lower CBF in patients with CVD may explain underlying processes. In 428 participants (74% cardiovascular diseases; 26% reference participants) from the Heart-Brain Connection Study, we assessed the relationship between 92 plasma proteins from the Olink® cardiovascular III panel and normal-appearing grey matter CBF, using affinity propagation and hierarchical clustering algorithms, and generated a Biomarker Compound Score (BCS). The BCS was related to cardiovascular risk and observed cardiovascular events within 2-year follow-up using Spearman correlation and logistic regression. Thirteen proteins were associated with CBF (ρSpearman range: -0.10 to -0.19, pFDR-corrected <0.05), and formed one cluster. The cluster primarily reflected extracellular matrix organization processes. The BCS was higher in patients with CVD compared to reference participants (pFDR-corrected <0.05) and was associated with cardiovascular risk (ρSpearman 0.42, p < 0.001) and cardiovascular events (OR 2.05, p < 0.01). In conclusion, we identified a cluster of plasma proteins related to CBF, reflecting extracellular matrix organization processes, that is also related to future cardiovascular events in patients with CVD, representing potential targets to preserve CBF and mitigate cardiovascular risk in patients with CVD.

Circulating biomarkers of cardiovascular disease are related to aneurysm volume in abdominal aortic aneurysm.

BACKGROUND: Surveillance programs in abdominal aortic aneurysms (AAA) are mainly based on imaging and leave room for improvement to timely identify patients at risk for AAA growth. Many biomarkers are dysregulated in patients with AAA, which fuels interest in biomarkers as indicators of disease progression. We examined associations of 92 cardiovascular disease (CVD)-related circulating biomarkers with AAA and sac volume. METHODS: In a cross-sectional analysis, we separately investigated (1) 110 watchful waiting (WW) patients (undergoing periodic surveillance imaging without planned intervention) and (2) 203 patients after endovascular aneurysm repair (EVAR). The Cardiovascular Panel III (Olink Proteomics AB, Sweden) was used to measure 92 CVD-related circulating biomarkers. We used cluster analyses to investigate protein-based subphenotypes, and linear regression to examine associations of biomarkers with AAA and sac volume on CT scans. RESULTS: Cluster analyses revealed two biomarker-based subgroups in both WW and EVAR patients, with higher levels of 76 and 74 proteins, respectively, in one subgroup versus the other. In WW patients, uPA showed a borderline significant association with AAA volume. Adjusting for clinical characteristics, there was a difference of -0.092 (-0.148, -0.036) loge mL in AAA volume per SD uPA. In EVAR patients, after multivariable adjustment, four biomarkers remained significantly associated with sac volume. The mean effects on sac volume per SD difference were: LDLR: -0.128 (-0.212, -0.044), TFPI: 0.139 (0.049, 0.229), TIMP4: 0.110 (0.023, 0.197), IGFBP-2: 0.103 (0.012, 0.194). CONCLUSION: LDLR, TFPI, TIMP4, and IGFBP-2 were independently associated with sac volume after EVAR. Subgroups of patients with high levels of the majority of CVD-related biomarkers emphasize the intertwined relationship between AAA and CVD.ClinicalTrials.gov Identifier: NCT03703947.

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. METHODS: For every new PCr measurement measured in the University Medical Center Utrecht that triggered the e-alert, we provided the physician with actionable insights in the form of a memo, to improve or stabilize kidney function. Since e-alerts qualify for software as a medical device (SaMD), we designed, implemented and validated the e-alert according to the European Union In Vitro Diagnostic Regulation (IVDR). RESULTS: We evaluated the impact of the e-alert using pilot data six months before and after implementation. 2,053 e-alerts of 866 patients were triggered in the before implementation, and 1,970 e-alerts of 853 patients were triggered after implementation. We found improvements in AKI awareness as measured by (1) 2 days PCr follow up (56.6-65.8%, p-value: 0.003), and (2) stop of nephrotoxic medication within 7 days of the e-alert (59.2-63.2%, p-value: 0.002). CONCLUSION: Here, we describe the design and implementation of the e-alert in line with the IVDR, leveraging a multi-disciplinary team consisting of physicians, clinical chemists, data managers and data scientists, and share our firsts results that indicate an improved awareness among treating physicians.

In-vitro and in-silico evidence for oxidative stress as drivers for RDW.

Red blood cell distribution width (RDW) is a biomarker associated with a variety of clinical outcomes. While anemia and subclinical inflammation have been posed as underlying pathophysiology, it is unclear what mechanisms underlie these assocations. Hence, we aimed to unravel the mechanisms in silico using a large clinical dataset and validate our findings in vitro. We retrieved complete blood counts (CBC) from 1,403,663 measurements from the Utrecht Patient Oriented Database, to model RDW using gradient boosting regression. We performed (sex-stratified) analyses in patients with anemia, patients younger/older than 50 and validation across platforms and care settings. We then validated our hypothesis regarding oxidative stress using an in vitro approach. Only percentage microcytic (pMIC) and macrocytic (pMAC) erythrocytes and mean corpuscular volume were most important in modelling RDW (RMSE = 0.40, R2 = 0.96). Subgroup analyses and validation confirmed our findings. In vitro induction of oxidative stress underscored our results, namely increased RDW and decreased erythrocyte volume, yet no vesiculation was observed. We found that erythrocyte size, especially pMIC, is most informative in predicting RDW, but no role for anemia or inflammation. Oxidative stress affecting the size of the erythrocytes may play a role in the association between RDW and clinical outcomes.

Characteristics of peripheral blood cells are independently related to major adverse cardiovascular events after carotid endarterectomy.

Background and aims: Patients who underwent carotid endarterectomy (CEA) still have a residual risk of 13% of developing a major adverse cardiovascular event (MACE) within 3 years. Inflammatory processes leading up to MACE are not fully understood. Therefore, we examined blood cell characteristics (BCCs), possibly reflecting inflammatory processes, in relation to MACE to identify BCCs that may contribute to an increased risk. Methods: We analyzed 75 pretreatment BCCs from the Sapphire analyzer, and clinical data from the Athero-Express biobank in relation to MACE after CEA using Random Survival Forests, and a Generalized Additive Survival Model. To understand biological mechanisms, we related the identified variables to intraplaque hemorrhage (IPH). Results: Of 783 patients, 97 (12%) developed MACE within 3 years after CEA. Red blood cell distribution width (RDW) (HR 1.23 [1.02, 1.68], p = 0.022), CV of lymphocyte size (LACV) (HR 0.78 [0.63, 0.99], p = 0.043), neutrophil complexity of the intracellular structure (NIMN) (HR 0.80 [0.64, 0.98], p = 0.033), mean neutrophil size (NAMN) (HR 0.67 [0.55, 0.83], p < 0.001), mean corpuscular volume (MCV) (HR 1.35 [1.09, 1.66], p = 0.005), eGFR (HR 0.65 [0.52, 0.80], p < 0.001); and HDL-cholesterol (HR 0.62 [0.45, 0.85], p = 0.003) were related to MACE. NAMN was related to IPH (OR 0.83 [0.71-0.98], p = 0.02). Conclusions: This is the first study to present a higher RDW and MCV and lower LACV, NIMN and NAMN as biomarkers reflecting inflammatory processes that may contribute to an increased risk of MACE after CEA.

Cohort profile of PLUTO: a perioperative biobank focusing on prediction and early diagnosis of postoperative complications.

PURPOSE: Although elective surgery is generally safe, some procedures remain associated with an increased risk of complications. Improved preoperative risk stratification and earlier recognition of these complications may ameliorate postoperative recovery and improve long-term outcomes. The perioperative longitudinal study of complications and long-term outcomes (PLUTO) cohort aims to establish a comprehensive biorepository that will facilitate research in this field. In this profile paper, we will discuss its design rationale and opportunities for future studies. PARTICIPANTS: Patients undergoing elective intermediate to high-risk non-cardiac surgery are eligible for enrolment. For the first seven postoperative days, participants are subjected to daily bedside visits by dedicated observers, who adjudicate clinical events and perform non-invasive physiological measurements (including handheld spirometry and single-channel electroencephalography). Blood samples and microbiome specimens are collected at preselected time points. Primary study outcomes are the postoperative occurrence of nosocomial infections, major adverse cardiac events, pulmonary complications, acute kidney injury and delirium/acute encephalopathy. Secondary outcomes include mortality and quality of life, as well as the long-term occurrence of psychopathology, cognitive dysfunction and chronic pain. FINDINGS TO DATE: Enrolment of the first participant occurred early 2020. During the inception phase of the project (first 2 years), 431 patients were eligible of whom 297 patients consented to participate (69%). Observed event rate was 42% overall, with the most frequent complication being infection. FUTURE PLANS: The main purpose of the PLUTO biorepository is to provide a framework for research in the field of perioperative medicine and anaesthesiology, by storing high-quality clinical data and biomaterials for future studies. In addition, PLUTO aims to establish a logistical platform for conducting embedded clinical trials. TRIAL REGISTRATION NUMBER: NCT05331118.

Analysis of C-reactive protein from finger stick dried blood spot to predict high risk of cardiovascular disease.

C-reactive protein (CRP) is an acute-phase protein involved in inflammation. Furthermore, CRP is an important biomarker used in diagnostics to predict risk of cardiovascular disease (CVD) in addition to monitoring bacterial and viral infections. To measure plasma CRP, venipuncture is still necessitated and has to be performed by trained phlebotomists. As a solution, dried blood spots (DBS) are used for minimally invasive at-home sampling of blood and can be send to diagnostic laboratories by regular mail. In this study, we included 53 patients that presented to the outpatient clinic of the University Medical Center Utrecht. Capillary finger stick was used to spot blood on a filter paper card and allowed to dry. After extraction of DBS, CRP was analyzed on an automated high-throughput chemistry analyzer. Additional validation steps regarding stability, effect of hematocrit, precision, and limits of blank and quantitation were conducted according to corresponding Clinical and Laboratory Standards Institute standards. An excellent regression analysis of R2 (95% confidence interval) = 0.986 (0.982-0.989) was found. This enabled correct classification for high CVD risk of all 25 cases with sensitivity (95% CI) of 1.00 (1.00-1.00) and specificity (95% CI) of 0.96 (0.89-1.03) and correct diagnosis of inflammation of 12/13 cases with sensitivity (95% CI) of 0.92 (0.77-1.07) and specificity (95% CI) of 1.00 (1.00-1.00). Furthermore, CRP was found to be stable for 31 days and observed hematocrit variation amongst patients was clinically acceptable. CRP from DBS can be accurately measured on an automated high-throughput chemistry analyzer and used to diagnose inflammation and classify high CVD risk. This method enables individuals to engage in at-home sampling of blood on DBS for (tele)diagnostics, screening programs, patient follow-up, and medication management.

A Preliminary Analysis of Thyrotropin Measurement from Finger Stick Dried Blood Spot with an Automated High-Throughput Immunoassay Analyzer.

Background: Hyper- and hypothyroidism are prevalent in Western countries and often go unnoticed for long periods. Thyrotropin (TSH) as a biomarker of thyroid dysfunction is regularly measured in venous plasma/serum. In newborn screening for congenital hypothyroidism, TSH is measured from dried blood spots (DBSs). DBS enables minimally invasive (at-home) sampling of a small blood volume that can be sent to diagnostic laboratories by regular mail. Methods: In this study, we included 109 patients who presented to the outpatient clinic of the University Medical Center Utrecht. Capillary finger stick was used to spot blood on a filter paper card and was dried. After extraction of TSH from DBS, method comparison with venous TSH was performed on an automated high-throughput immunoassay analyzer. Additional validation steps regarding stability, effect of hematocrit (Hct), precision, and limits of blank and quantitation were conducted according to corresponding Clinical and Laboratory Standards Institute evaluation protocol. Results: Method comparison of TSH from venous plasma versus finger stick DBSs showed an R2 [95% confidence interval] = 0.988 [0.986-0.990]. This enabled correct diagnosis of hypothyrotropinemia and hypothyroidism in 12 of 14 and 6 of 7 cases, respectively, with no false positives. Furthermore, TSH from DBS was stable for at least 4 days at temperatures between -20°C and +30°C, and the maximum decrease of eluate TSH was 1.13% for 1% increase in Hct. Conclusions: TSH from DBS may be accurately measured on an automated high-throughput immunoassay analyzer and could be used to diagnose hypothyroidism and, for the first time, hypothyrotropinemia. This method, when confirmed in larger field studies, may enable individuals to engage in (at-home) sampling of blood on DBSs for telediagnostics, screening programs, patient follow-up, and medication management.

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. A prerequisite for a good model is the use of high-quality labels. Sepsis gold-standard labels are hard to define due to a lack of reliable diagnostic tools for sepsis at the ED. Therefore, standard clinical tools, such as clinical prediction scores (e.g. modified early warning score and quick sequential organ failure assessment), and claims-based methods (e.g. ICD-10) are used to generate suboptimal labels. As a consequence, models trained with these "silver" labels result in ill-trained models. In this study, we trained ML models for sepsis diagnosis at the ED with labels of 375 ED visits assigned by an endpoint adjudication committee (EAC) that consisted of 18 independent experts. Our objective was to evaluate which routinely measured variables show diagnostic value for sepsis. We performed univariate testing and trained multiple ML models with 95 routinely measured variables of three variable groups; demographic and vital, laboratory and advanced haematological variables. Apart from known diagnostic variables, we identified added diagnostic value for less conventional variables such as eosinophil count and platelet distribution width. In this explorative study, we show that the use of an EAC together with ML can identify new targets for future sepsis diagnosis research.

A Wolf in Sheep's Clothing: Reuse of Routinely Obtained Laboratory Data in Research.

Electronic health records (EHRs) contain valuable data for reuse in science, quality evaluations, and clinical decision support. Because routinely obtained laboratory data are abundantly present, often numeric, generated by certified laboratories, and stored in a structured way, one may assume that they are immediately fit for (re)use in research. However, behind each test result lies an extensive context of choices and considerations, made by both humans and machines, that introduces hidden patterns in the data. If they are unaware, researchers reusing routine laboratory data may eventually draw incorrect conclusions. In this paper, after discussing health care system characteristics on both the macro and micro level, we introduce the reader to hidden aspects of generating structured routine laboratory data in 4 steps (ordering, preanalysis, analysis, and postanalysis) and explain how each of these steps may interfere with the reuse of routine laboratory data. As researchers reusing these data, we underline the importance of domain knowledge of the health care professional, laboratory specialist, data manager, and patient to turn routine laboratory data into meaningful data sets to help obtain relevant insights that create value for clinical care.

A Network of Serum Proteins Predict the Need for Systemic Immunomodulatory Therapy at Diagnosis in Noninfectious Uveitis.

Purpose: Early identification of patients with noninfectious uveitis requiring steroid-sparing immunomodulatory therapy (IMT) is currently lacking in objective molecular biomarkers. We evaluated the proteomic signature of patients at the onset of disease and associated proteomic clusters with the need for IMT during the course of the disease. Design: Multicenter cohort study. Participants: Two hundred thirty treatment-free patients with active noninfectious uveitis. Methods: We used aptamer-based proteomics (n = 1305 proteins) and a bioinformatic pipeline as a molecular stratification tool to define the serum protein network of a Dutch discovery cohort (n = 78) of patients and healthy control participants and independently validated our results in another Dutch cohort (n = 111) and a United States cohort (n = 67). Multivariate Cox analysis was used to assess the relationship between the protein network and IMT use. Main Outcome Measures: Serum protein levels and use of IMT. Results: Network-based analyses revealed a tightly coexpressed serum cluster (n = 85 proteins) whose concentration was consistently low in healthy control participants (n = 26), but varied among patients with noninfectious uveitis (n = 52). Patients with high levels of the serum cluster at disease onset showed a significantly increased need for IMT during follow-up, independent of anatomic location of uveitis (hazard ratio, 3.42; 95% confidence interval, 1.22-9.5; P = 0.019). The enrichment of neutrophil-associated proteins in the protein cluster led to our finding that the neutrophil count could serve as a clinical proxy for this proteomic signature (correlation: r = 0.57, P = 0.006). In an independent Dutch cohort (n = 111), we confirmed that patients with relatively high neutrophil count at diagnosis (> 5.2 × 109/L) had a significantly increased chance of requiring IMT during follow-up (hazard ratio, 3.2; 95% confidence interval, 1.5-6.8; P = 0.002). We validated these findings in a third cohort of 67 United States patients. Conclusions: A serum protein signature correlating with neutrophil levels was highly predictive for IMT use in noninfectious uveitis. We developed a routinely available tool that may serve as a novel objective biomarker to aid in clinical decision-making for noninfectious uveitis.

Axial light loss of monocytes as a readily available prognostic biomarker in patients with suspected infection at the emergency department.

OBJECTIVES: To evaluate the prognostic value of the coefficient of variance of axial light loss of monocytes (cv-ALL of monocytes) for adverse clinical outcomes in patients suspected of infection in the emergency department (ED). METHODS: We performed an observational, retrospective monocenter study including all medical patients ≥18 years admitted to the ED between September 2016 and June 2019 with suspected infection. Adverse clinical outcomes included 30-day mortality and ICU/MCU admission <3 days after presentation. We determined the additional value of monocyte cv-ALL and compared to frequently used clinical prediction scores (SIRS, qSOFA, MEWS). Next, we developed a clinical model with routinely available parameters at the ED, including cv-ALL of monocytes. RESULTS: A total of 3526 of patients were included. The OR for cv-ALL of monocytes alone was 2.21 (1.98-2.47) for 30-day mortality and 2.07 (1.86-2.29) for ICU/MCU admission <3 days after ED presentation. When cv-ALL of monocytes was combined with a clinical score, the prognostic accuracy increased significantly for all tested scores (SIRS, qSOFA, MEWS). The maximum AUC for a model with routinely available parameters at the ED was 0.81 to predict 30-day mortality and 0.81 for ICU/MCU admission. CONCLUSIONS: Cv-ALL of monocytes is a readily available biomarker that is useful as prognostic marker to predict 30-day mortality. Furthermore, it can be used to improve routine prediction of adverse clinical outcomes at the ED. CLINICAL TRIAL REGISTRATION: Registered in the Dutch Trial Register (NTR) und number 6916.

Performance of the Abbott Architect Immuno-Chemiluminometric NT-proBNP Assay.

Background: We evaluated the performance of the Abbott N-terminal pro-brain natriuretic peptide (NT-proBNP) assay against the Roche NT-proBNP immunoassay across two sites. Methods: Precision, linearity, and sensitivity studies were performed. A combined method of comparison and regression analysis was performed between the Roche and Abbott assays using samples from both sites (n = 494). To verify biotin interference, lyophilised biotin powder was reconstituted and spiked into serum samples at two medical decision levels (final concentration 500/4250 ng/mL) and compared to controls. NT-proBNP was also measured in anonymised leftover sera (n = 388) in a cardio-renal healthy population and stratified into three age bands­<50 (n = 145), 50−75 (n = 183) and >75 (n = 60). Results: Between-run precision (CV%) for NT-proBNP was 4.17/4.50 (139.5/142.0 pg/mL), 3.83/2.17 (521.6/506.3), and 4.60/2.51 (5053/4973), respectively. The assay was linear from 0.7−41,501 pg/mL. The limit of blank/quantitation was 1.2/7.9 pg/mL. The assay showed no interference from biotin up to 4250 ng/mL. Passing−Bablok regression analysis showed excellent agreement between the two assays (r = 0.999, 95% CI 0.999 to 0.999, p < 0.0001). The Roche assay had a slightly persistent, negative bias across different levels of NT-proBNP. ESC age cut-offs for diagnosing acute heart failure are applicable for the Abbott assay, with the median NT-proBNP of subjects < 50 years old at 43.0 pg/mL (range 4.9−456 pg/mL), 50−75 years old at 95.1 pg/mL (range 10.5−1079 pg/mL), and >75 years old at 173.1 pg/mL (range 23.2−1948 pg/mL). Conclusions: The Abbott Architect NT-proBNP assay has good performance that agrees with the manufacturer's specifications. ESC/AHA recommended NT-proBNP age groups for acute heart failure diagnosis are applicable to this assay.

Targeted proteomics improves cardiovascular risk prediction in secondary prevention.

AIMS: Current risk scores do not accurately identify patients at highest risk of recurrent atherosclerotic cardiovascular disease (ASCVD) in need of more intensive therapeutic interventions. Advances in high-throughput plasma proteomics, analysed with machine learning techniques, may offer new opportunities to further improve risk stratification in these patients. METHODS AND RESULTS: Targeted plasma proteomics was performed in two secondary prevention cohorts: the Second Manifestations of ARTerial disease (SMART) cohort (n = 870) and the Athero-Express cohort (n = 700). The primary outcome was recurrent ASCVD (acute myocardial infarction, ischaemic stroke, and cardiovascular death). Machine learning techniques with extreme gradient boosting were used to construct a protein model in the derivation cohort (SMART), which was validated in the Athero-Express cohort and compared with a clinical risk model. Pathway analysis was performed to identify specific pathways in high and low C-reactive protein (CRP) patient subsets. The protein model outperformed the clinical model in both the derivation cohort [area under the curve (AUC): 0.810 vs. 0.750; P < 0.001] and validation cohort (AUC: 0.801 vs. 0.765; P < 0.001), provided significant net reclassification improvement (0.173 in validation cohort) and was well calibrated. In contrast to a clear interleukin-6 signal in high CRP patients, neutrophil-signalling-related proteins were associated with recurrent ASCVD in low CRP patients. CONCLUSION: A proteome-based risk model is superior to a clinical risk model in predicting recurrent ASCVD events. Neutrophil-related pathways were found in low CRP patients, implying the presence of a residual inflammatory risk beyond traditional NLRP3 pathways. The observed net reclassification improvement illustrates the potential of proteomics when incorporated in a tailored therapeutic approach in secondary prevention patients.

Thrombosis pathways in COVID-19 vs. influenza-associated ARDS: A targeted proteomics approach.

BACKGROUND: Pulmonary embolism (PE) occurs in one-third of critically-ill COVID-19 patients. Although prior studies identified several pathways contributing to thrombogenicity, it is unknown whether this is COVID-19-specific or also occurs in ARDS patients with another infection. OBJECTIVE: To compare pathway activity among patients having COVID-19 with PE (C19PE+), COVID-19 without PE (C19PE-), and influenza-associated ARDS (IAA) using a targeted proteomics approach. METHODS: We exploited an existing biorepository containing daily plasma samples to carefully match C19PE+ cases to C19PE- and IAA controls on mechanical ventilation duration, PEEP, FiO2, and cardiovascular-SOFA (n = 15 per group). Biomarkers representing various thrombosis pathways were measured using proximity extension- and ELISA-assays. Summed z-scores of individual biomarkers were used to represent total pathway activity. RESULTS: We observed no relevant between-group differences among 22 biomarkers associated with activation of endothelium, platelets, complement, coagulation, fibrinolysis or inflammation, except sIL-1RT2 and sST2, which were lower in C19PE- than IAA (log2-Foldchange -0.67, p = .022 and -1.78, p = .022, respectively). However, total pathway analysis indicated increased activation of endothelium (z-score 0.2 [-0.3-1.03] vs. 0.98 [-2.5--0.3], p = .027), platelets (1.0 [-1.3-3.0] vs. -3.3 [-4.1--0.6], p = .023) and coagulation (0.8 [-0.5-2.0] vs. -1.0 [-1.6-1.0], p = .023) in COVID-19 patients (C19PE+/C19PE- groups combined) compared to IAA. CONCLUSION: We observed only minor differences between matched C19PE+, C19PE-, and IAA patients, which suggests individual biomarkers mostly reflect disease severity. However, analysis of total pathway activity suggested upregulation of some distinct processes in COVID-19 could be etiologically related to increased PE-risk.

A cluster of blood-based protein biomarkers reflecting coagulation relates to the burden of cerebral small vessel disease.

Biological processes underlying cerebral small vessel disease (cSVD) are largely unknown. We hypothesized that identification of clusters of inter-related bood-based biomarkers that are associated with the burden of cSVD provides leads on underlying biological processes. In 494 participants (mean age 67.6 ± 8.7 years; 36% female; 75% cardiovascular diseases; 25% reference participants) we assessed the relation between 92 blood-based biomarkers from the OLINK cardiovascular III panel and cSVD, using cluster-based analyses. We focused particularly on white matter hyperintensities (WMH). Nineteen biomarkers individually correlated with WMH ratio (r range: 0.16-0.27, Bonferroni corrected p-values <0.05), of which sixteen biomarkers formed one biomarker cluster. Pathway analysis showed that this biomarker cluster predominantly reflected coagulation processes. This cluster related also significantly to other cSVD manifestations (lacunar infarcts, microbleeds, and enlarged perivascular spaces), which supports generalizability beyond WMHs. To study possible causal effects of biological processes reflected by the cluster we performed a mediation analysis that showed a mediation effect of the cluster on the relation between age and WMH ratio (proportion mediated 17%), and hypertension and WMH-volume (proportion mediated 21%). In conclusion, we identified a cluster of blood-based biomarkers reflecting coagulation, that is related to manifestations of cSVD, corroborating involvement of coagulation abnormalities in the etiology of cSVD.

Preventing unnecessary imaging in patients suspect of coronary artery disease through machine learning of electronic health records.

Aims: With the ageing European population, the incidence of coronary artery disease (CAD) is expected to rise. This will likely result in an increased imaging use. Symptom recognition can be complicated, as symptoms caused by CAD can be atypical, particularly in women. Early CAD exclusion may help to optimize use of diagnostic resources and thus improve the sustainability of the healthcare system. To develop sex-stratified algorithms, trained on routinely available electronic health records (EHRs), raw electrocardiograms, and haematology data to exclude CAD in patients upfront. Methods and results: We trained XGBoost algorithms on data from patients from the Utrecht Patient-Oriented Database, who underwent coronary computed tomography angiography (CCTA), and/or stress cardiac magnetic resonance (CMR) imaging, or stress single-photon emission computerized tomography (SPECT) in the UMC Utrecht. Outcomes were extracted from radiology reports. We aimed to maximize negative predictive value (NPV) to minimize the false negative risk with acceptable specificity. Of 6808 CCTA patients (31% female), 1029 females (48%) and 1908 males (45%) had no diagnosis of CAD. Of 3053 CMR/SPECT patients (45% female), 650 females (47%) and 881 males (48%) had no diagnosis of CAD. On the train and test set, the CCTA models achieved NPVs and specificities of 0.95 and 0.19 (females) and 0.96 and 0.09 (males). The CMR/SPECT models achieved NPVs and specificities of 0.75 and 0.041 (females) and 0.92 and 0.026 (males). Conclusion: Coronary artery disease can be excluded from EHRs with high NPV. Our study demonstrates new possibilities to reduce unnecessary imaging in women and men suspected of CAD.

Defining the awake baseline blood pressure in patients undergoing carotid endarterectomy.

BACKGROUND: To minimize the incidence of intraoperative stroke following carotid endarterectomy (CEA) under general anesthesia, blood pressure (BP) is suggested to be maintained between "awake baseline" BP and 20% above. However, there is neither a widely accepted protocol nor a definition to determine this awake BP. In this study, we analyzed the BP during hospital admission in the days before CEA and propose a definition of how to determine awake BP. METHODS: In our cohort of 1180 CEA-patients, all noninvasive BP measurements were retrospectively analyzed. BP was measured during preoperative outpatient screening (POS), the last three days before surgery at the ward and in the operating room (OR) directly before anesthesia. Primary outcome was the comparability of all these preoperative BP measurements. Secondary outcome was the comparability of preoperative BP measurements stratified for postoperative stroke within 30 days. RESULTS: POS BP (148±22/80±12 mmHg [mean arterial pressure, MAP: 103±14 mmHg]) and the BP measured on the ward 3, 2, 1 days before surgery and on the day of surgery (146±25/77±13 [MAP: 100±15]), (142±23/76±13 [MAP: 98±15]), (145±23/76±12 [MAP: 99±14]) and (144±22/75±12 mmHg [MAP: 98±14]) were comparable (all P=NS). However, BP in the OR directly before anesthesia was higher, (163±27/88±15 mmHg [MAP: 117±18mmHg]) (P<0.01 vs. all other preoperative moments). A significant higher preinduction systolic BP and MAP was observed in patients suffering a stroke within 30 days compared to patients without (P=0.03 and 0.04 respectively). CONCLUSIONS: Awake BP should be determined by averaging available BP values collected preoperatively on the ward and POS. BP measured in the OR directly before induction of anesthesia overestimates "awake" BP; and therefore, it should not be used.

Neutral Effects of Combined Treatment With GLP-1R Agonist Exenatide and MR Antagonist Potassium Canrenoate on Cardiac Function in Porcine and Murine Chronic Heart Failure Models.

Background: Ischemia-reperfusion and cardiac remodeling is associated with cardiomyocyte death, excessive fibrosis formation, and functional decline, eventually resulting in heart failure (HF). Glucagon-like peptide (GLP)-1 agonists are reported to reduce apoptosis and myocardial infarct size after ischemia-reperfusion. Moreover, mineralocorticoid receptor antagonists (MRAs) have been described to reduce reactive fibrosis and improve cardiac function. Here, we investigated whether combined treatment with GLP-1R agonist exenatide and MRA potassium canrenoate could minimize cardiac injury and limit HF progression in animal models of chronic HF. Methods and Results: Forty female Topigs Norsvin pigs were subjected to 150 min balloon occlusion of the left anterior descending artery (LAD). Prior to reperfusion, pigs were randomly assigned to placebo or combination therapy (either low dose or high dose). Treatment was applied for two consecutive days or for 8 weeks with a continued high dose via a tunneled intravenous catheter. Using 2,3,5-Triphenyltetrazolium chloride (TTC) staining we observed that combination therapy did not affect the scar size after 8 weeks. In line, left ventricular volume and function assessed by three-dimensional (3D) echocardiography (baseline, 7 days and 8 weeks), and cardiac magnetic resonance imaging (CMR, 8 weeks) did not differ between experimental groups. In addition, 36 C57Bl/6JRj mice underwent permanent LAD-occlusion and were treated with either placebo or combination therapy prior to reperfusion, for two consecutive days via intravenous injection, followed by continued treatment via placement of osmotic mini-pumps for 28 days. Global cardiac function, assessed by 3D echocardiography performed at baseline, 7, 14, and 28 days, did not differ between treatment groups. Also, no differences were observed in cardiac hypertrophy, assessed by heart weight/bodyweight and heart weight/tibia length ratio. Conclusion: In the current study, combined treatment with GLP-1R agonist exenatide and MR antagonist potassium canrenoate did not show beneficial effects on cardiac remodeling nor resulted in functional improvement in a small and large animal chronic HF model.