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Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). 1H-NMR-based metabonomics data of the serum samples of patients with arterial or venous thromboembolism (VTE) without APS (n = 32), thrombotic primary APS patients (APS, n = 32), and healthy controls (HCs) (n = 32) were investigated. Unique metabolic profiles between VTE and HCs, APS and HCs, and between VTE and triple-positive APS groups were indicative of the significant alterations in the metabolic pathways of glycolysis, the TCA cycle, lipid metabolism, and branched-chain amino acid (BCAA) metabolism, and pointed to the complex pathogenesis mechanisms of APS and VTE. Histidine, 3-hydroxybutyrate, and threonine were shown to be the top three metabolites with the most substantial impact on model predictions, suggesting that these metabolites play a pivotal role in distinguishing among APS, VTE, and HCs. These metabolites might be potential biomarkers to differentiate APS and VTE patients.

Post-thrombotic syndrome (PTS) is a limiting long-term complication present in 20-50% of patients with deep venous thrombosis (DVT) of the lower limbs. A panel of biomarkers with potential relevance to enhance knowledge on the pathophysiology of PTS was investigated. This case-control study included 93 patients with DVT in the lower limbs, 31 with severe PTS (cases) and 62 with mild/no PTS (controls), over 24 months after an acute episode. Thirty-one healthy individuals (HI) with no history of DVT were included as a reference to the population. FVIII activity, D-dimer, inflammatory cytokines, endothelial dysfunction markers, matrix metalloproteinases, and their inhibitors, tissue remodeling and growth factor levels were evaluated. The classification of PTS was, by the Villalta scale. Patients with severe PTS showed elevated levels of CRP, sICAM-1, sE-selectin, and decreased MMP-9 and MCP-1 levels when compared to patients with mild/no PTS. Moreover, DVT patients presented higher levels of FVIII and D-dimer when compared to HI. DVT patients present an inflammatory status, endothelial dysfunction and altered proteolysis MMPs activity, even a long time after the acute thrombotic episode, which is more significant in severe PTS. These results suggest a possible role of these mediators in the maintenance and worsening of PTS severity.

Neutrophil activation and neutrophil extracellular traps (NETs) have been associated with the pathogenesis of venous thromboembolism (VTE). Considering VTE-associated chronic sequelae, which suggest that some pathological mechanisms remain after the acute episode, we investigated whether neutrophil activation is increased in patients with a prior VTE at least one year before this investigation. Thirty-seven patients with prior VTE and 37 individuals with no history of VTE were included. Neutrophil activity was evaluated by the expression of the adhesive molecule activation-specific epitopes LFA-1 (CD11a) and MAC-1 (CD11b), chemotaxis, reactive oxygen species (ROS) and by MPO-DNA complexes as markers of NETs. The adhesive molecules sICAM-1 and sVCAM-1, involved in the cross talk between neutrophil and endothelial cells, were also evaluated. Patient neutrophils presented increased CD11a expression before and after TNF-α stimulus, whereas increased CD11b expression was observed only after TNF-α stimulus, as compared to controls. Neutrophil chemotaxis on both, basal state and after IL-8 stimulus, on circulating levels of sICAM-1 and sVCAM-1, and on MPO-DNA complexes were also increased in VTE patients. ROS release was similar between patients and controls. This is, to our knowledge, the first study to investigate neutrophil inflammatory activity in VTE patients a long period after an acute event (approximately 2 years). The results showed altered neutrophil activation patterns in these patients. While activated neutrophils can cause endothelial activation and injury, the activated endothelium can induce the release of NETs with consequent endothelial cytotoxicity, creating a vicious cycle of activation between neutrophils and endothelium that can lead to thrombosis.VTE patients (approximately 2 years after the clinical event) present an altered neutrophil activation state evidenced by increased activity of the LFA-1 and Mac-1 adhesive molecules, as well as increased chemotaxis and circulating levels of NETs remnants. Circulating levels of ICAM-1 and VCAM-1, which are endothelial adhesive molecules, are also increased in VTE patients, suggesting not only an exacerbated endothelial activation and dysfunction, but also an interaction of the neutrophil adhesive molecules with their endothelial ligands, favoring the migration process of neutrophil.

Several authors have shown that hematological parameters can be used to detect poor prognosis in patients with cancer. Thus, such features could be used in artificial intelligence (AI-based) models to predict mortality among these patients. This work aimed to develop and compare several AI-based models to predict the prognosis (death vs. survival) of cancer in patients using blood tests and patient data as inputs. At total, 908 cancer patients were assisted in a prospective study. Four artificial intelligence models were compared: artificial neural networks (ANN), supporting vector machines (SVM), decision trees and neuro-fuzzy networks. Also, four different input strategies were tested, considering the use of 49, 45, 22 and 14 inputs. The results of this study showed that the ANN and the SVM presented the best results, using 45 inputs. The ANN was the best model since it presented better statistical values for the positive (death) and negative (survival) classes. The use of blood parameters as inputs for AI-based models could be used to predict death in patients with cancer, and this methodology can be expanded to other diseases.

Deep venous thrombosis (DVT) is associated with significant morbidity and mortality. Studies on changes in the level of metabolites could have the potential to reveal biomarkers that can assist in the early detection, diagnosis, monitoring of DVT progression, response to treatment, or recurrence of DVT. In this scenario, the metabolomic analysis can provide a better understanding of the biochemical dysregulations of thrombosis. Using an untargeted metabolomic approach through magnetic resonance spectroscopy and multi- and univariate statistical analysis, we compared 40 patients with previous venous thrombosis and 40 healthy individuals, and we showed important serum differences between patients and controls, especially in the spectral regions that correspond to glucose, lipids, unsaturated lipids, and glycoprotein A. Considering the groups depending on risk factors and the local of the previous episode (lower limbs or cerebral system), we also noticed differences in metabolites linked to lipids and lactate. Comparative analyses pointed to altered ratios of glucose/lactate and branched-chain amino acids (BCAAs)/alanine, which might be associated with the fingerprints of thrombosis. Although samples for metabolomic analysis were collected months after the acute episode, these results highlighted that, alterations can still remain and may contribute to a better understanding of the complications of the disease.

To compare levels and activity of the growth factors between fresh and lyophilized platelet-rich plasma (PRP). Analysis of platelet concentration using fibroblast and human umbilical vein endothelial cell cultures were compared between fresh and lyophilized PRP obtained from peripheral blood. After lyophilization, 54% of platelets were intact whereas the fresh showed no aggregation with agonists (levels under 20%). The concentration of growth factors (VEGF, EGF, TGF-β and PDGF) in both products were similar. Fresh and lyophilized PRPs induced proliferation in the fibroblasts at 24 h (0.303 vs 0.300, respectively). Lyophilized PRP appears to be an alternative to fresh PRP and the results evidenced the role of growth factors as a key element in the activity of this product.

A prolonged activated partial thromboplastin time (APTT) of unknown cause is one of the most frequent reasons why outpatients are referred for hemostasis consultation. Nevertheless, very few data are available on the relative contribution of individual causes of this common clinical scenario. Here, we present a systematic evaluation of all causes of APTT prolongation in a consecutive population of outpatients referred for specialized hemostasis consultation during a 14‐year period. All cases referred to an academic specialized hemostasis outpatient unit due to APTT prolongation of unknown etiology whose prolonged APTT was confirmed in the first visit were included in the study. Data were obtained from the electronic medical records. Among 187 consecutive patients, the most frequent causes were antiphospholipid antibodies in 22.6%, contact pathway factor deficiencies in 17.4%, other coagulation factor deficiencies in 11.6%, and vitamin K deficiency/liver disease in 11.6%. A definite cause was not identified in 22.1% of patients. Presence of antiphospholipid antibodies, and absence of bleeding symptoms were both associated with significantly longer APTT values compared to other categories/clinical scenarios. The investigation of each case required a mean of 18.2 additional tests per patient, with estimated costs ranging from US$191.60 to US$1055.60. Our results describe the main causes of APTT prolongation in outpatients, as well as estimates of resource use required to investigate this condition, thus providing evidence supporting the importance of measures to minimize the indiscriminate use of this assay.

Fast and accurate diagnosis of COVID-19 is important to prevent dissemination and disease progression. Artificial Intelligence is known as a universal fitting tool and can be used on the formulation of predictive models for the disease’s diagnosis. Thus, we aimed to obtain a neural network (ANN) to diagnose patients as positive or negative COVID-19 based on patient data and blood tests. Data from 1003 patients followed between June/2020 and October/2020 were used. Covid-19 was confirmed in 777 patients by RT-PCR. The inputs considered were: sex, age, ethinicity, body mass index, tabagism, ex-tabagism, alveolar infiltrate, arterial hypertension, diabetes, heart rate, respiration rate, body temperature, oxygen saturation, D-dimer, activated partial thromboplastin time, prothrombin time, levels of: hemoglobin, platelet, leukocytes, lymphocytes, monocytes, neutrophils, lactate dehydrogenase, C-reactive protein, and creatinine. Blood was collected at the patient’s admission. The ANNs had 25 inputs and the output was the Covid-19 diagnosis. ANNs with one and two hidden layers were proposed. The number of neurons ranged from 5 to 35. The best result was obtained with an ANN containing 15 neurons in the first and second hidden layers, respectively. The model presented accuracy of 83%, and high capacity for the prediction of true positives (precision of 0.90). The results showed that the ANNs are promising to diagnose Covid-19 based on clinical parameters and blood tests. After future refinements and proper validation, this model could be used to diagnose Covid-19 on daily basis.

Validation protocols for the evaluation of coagulometers are needed to help professionals select the most suitable system for their regular laboratory routines. The objective of this study was to show how high standard protocols for the coagulometer validation process can fit into the daily laboratory routine. For this study, 45 healthy individuals and 112 patient samples were analyzed. From the patient samples, 51 were investigated for deep venous thrombosis, 27 for coagulopathy, 19 for antivitamin K therapy, and 15 for hemophilia. For the assessment, the performance of the 3 coagulometers and 1 point-of-care device was considered. One of the coagulometers was a new acquisition evaluated for precision, linearity, throughput, and carryover in the first moment, and the new coagulometer was then compared with the other well-established equipment in the laboratory. In normal plasma, coefficient of variation was ≤1.8% for total precision in screening tests and ≤3.5% for within-run precision in specific assays. For prothrombin time/international normalized ratio, no significant difference was found when comparing methods. Our study showed how to compare the capacity of a reagent in order to discriminate patients with severe hemophilia from patients with moderated hemophilia, and the κ coefficient agreement was 0.669 (95% confidence interval: 0.3-1.0; P < .001). d-dimer evaluated in patients with deep venous thrombosis and controls showed a 20% discrepancy between the methods. In our experience across Latin America, the number of laboratories that has performed this process is limited. In this study, we demonstrated how to adapt the validation process for the hemostasis laboratory routine to help the professional chose the best and more suitable option.

Cancer is a leading cause of death, and the fibrinolytic system shows cooperative effects that facilitate the growth of tumors and the appearance of metastases. This prospective study aimed to evaluate the fibrinolytic potential in cancer patients and its association with mortality outcomes using the fluorometric method of simultaneous thrombin and plasmin generation. The study included 323 cancer patients and 148 healthy individuals. During the 12-month follow-up, 68 patients died. Compared to the control group, cancer patients showed alterations in thrombin production consistent with a hypercoagulability profile, and an increase in plasmin generation. Mortality risk was associated with two parameters of thrombin in both univariate and multivariable analysis: maximum amplitude (Wald 11.78, p < 0.001) and area under the curve (Wald 8.0, p < 0.005), while such associations were not observed for plasmin. In conclusion, this was the first study able to demonstrate the simultaneous evaluation of thrombin and plasmin generation in newly diagnosed untreated cancer patients. Patients with cancer have been observed to exhibit a hypercoagulable profile. During the study, two parameters linked to thrombin generation, MA and AUC, were identified and found to have a potential association with mortality risk. However, no associations were found with parameters related to plasmin generation.