142 research outputs found

    Copper deficiency-associated myelopathy in cryptogenic hyperzincemia: A case report

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    Copper deficiency syndrome is an underestimated cause of posterior myelitis. We describe the case of a 41-year-old woman, who developed a subacute ataxic paraparesis associated with low back pain. Her 3T spine MRI showed a thin hyperintense FS-Echo T2 longitudinally extensive lesion involving the posterior columns of the cervical cord (from C2 to C6). An extensive diagnostic work-up excluded other causes of myelopathy and blood tests pointed out hypocupremia and mild hyperzincemia. Patients affected by this rare form of oligoelement deficiency typically develop progressive posterior column dysfunction with sensory ataxia and spasticity, sometimes associated with sensori-motor polyneuropathy. Clinical and radiological characteristics of posterior myelopathy due to copper deficiency are briefly reviewed. Physicians should be aware of this condition since a prompt introduction of copper supplementation can avoid progression of the neurological damage. (www.actabiomedica.it)

    Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices

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    We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphocyte ratio, Lactate Dehydrogenase, Fibrinogen, Albumin, and D-Dimers. The best ANN based on these indices achieved accuracy 95.97%, precision 90.63%, sensitivity 93.55%. and F1-score 92.06%, verified in the validation cohort. Our preliminary findings reveal for the first time an ANN to predict ICU hospitalization accurately and early, using only 5 easily accessible laboratory indices

    Microbleed Prevalence and Burden in Anticoagulant-Associated Intracerebral Bleed

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    Prior studies suggest an association between Vitamin K antagonists (VKA) and cerebral microbleeds (CMBs); less is known about nonvitamin K oral anticoagulants (NOACs). In this observational study we describe CMB profiles in a multicenter cohort of 89 anticoagulation-related intracerebral hemorrhage (ICH) patients. CMB prevalence was 51% (52% in VKA-ICH, 48% in NOAC-ICH). NOAC-ICH patients had lower median CMB count [2(IQR:1–3) vs. 7(4–11); P \u3c 0.001]; ≥5 CMBs were less prevalent in NOAC-ICH (4% vs. 31%, P = 0.006). This inverse association between NOAC exposure and high CMB count persisted in multivariable logistic regression models adjusting for potential confounders (OR 0.10, 95%CI: 0.01–0.83; P = 0.034)

    Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

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    There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype

    Diagnostic and prognostic value of procalcitonin among febrile critically ill patients with prolonged ICU stay

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    <p>Abstract</p> <p>Background</p> <p>Procalcitonin (PCT) has been proposed as a diagnostic and prognostic sepsis marker, but has never been validated in febrile patients with prolonged ICU stay.</p> <p>Methods</p> <p>Patients were included in the study provided they were hospitalised in the ICU for > 10 days, were free of infection and presented a new episode of SIRS, with fever >38°C being obligatory. Fifty patients fulfilled the above criteria. PCT was measured daily during the ICU stay. The primary outcome was proven infection.</p> <p>Results</p> <p>Twenty-seven out of 50 patients were diagnosed with infection. Median PCT on the day of fever was 1.18 and 0.17 ng/ml for patients with and without proven infections (p < 0.001). The area under the curve for PCT was 0.85 (95% CI; 0.71-0.93), for CRP 0.65 (0.46-0.78) and for WBC 0.68 (0.49-0.81). A PCT level of 1 ng/mL yielded a negative predictive value of 72% for the presence of infection, while a PCT of 1.16 had a specificity of 100%. A two-fold increase of PCT between fever onset and the previous day was associated with proven infection (p 0.001) (OR = 8.55; 2.4-31.1), whereas a four-fold increase of PCT of any of the 6 preceding days was associated with a positive predictive value exceeding 69.65%. A PCT value less than 0.5 ng/ml on the third day after the advent of fever was associated with favorable survival (p 0.01).</p> <p>Conclusion</p> <p>The reported data support that serial serum PCT may be a valuable diagnostic and prognostic marker in febrile chronic critically ill patients.</p

    Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

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    There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype.- Pfizer Pharmaceuticals(undefined

    Alveolar hypoxia, alveolar macrophages, and systemic inflammation

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    Diseases featuring abnormally low alveolar PO2 are frequently accompanied by systemic effects. The common presence of an underlying inflammatory component suggests that inflammation may contribute to the pathogenesis of the systemic effects of alveolar hypoxia. While the role of alveolar macrophages in the immune and defense functions of the lung has been long known, recent evidence indicates that activation of alveolar macrophages causes inflammatory disturbances in the systemic microcirculation. The purpose of this review is to describe observations in experimental animals showing that alveolar macrophages initiate a systemic inflammatory response to alveolar hypoxia. Evidence obtained in intact animals and in primary cell cultures indicate that alveolar macrophages activated by hypoxia release a mediator(s) into the circulation. This mediator activates perivascular mast cells and initiates a widespread systemic inflammation. The inflammatory cascade includes activation of the local renin-angiotensin system and results in increased leukocyte-endothelial interactions in post-capillary venules, increased microvascular levels of reactive O2 species; and extravasation of albumin. Given the known extrapulmonary responses elicited by activation of alveolar macrophages, this novel phenomenon could contribute to some of the systemic effects of conditions featuring low alveolar PO2
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