ABSTRACT
Machine learning models are increasingly used in the medical domain to study the association between risk factors and diseases to support practitioners in understanding health outcomes. In this paper, we showcase the use of machine-learned staged tree models for investigating complex asymmetric dependence structures in health data. Staged trees are a specific class of generative, probabilistic graphical models that formally model asymmetric conditional independence and non-regular sample spaces. An investigation of the risk factors in invasive fungal infections demonstrates the insights staged trees provide to support medical decision-making.
Subject(s)
Empyema , Invasive Pulmonary Aspergillosis , Pulmonary Aspergillosis , Humans , Invasive Pulmonary Aspergillosis/complications , Invasive Pulmonary Aspergillosis/therapy , Aspergillus , Drainage , Pulmonary Aspergillosis/complications , Pulmonary Aspergillosis/diagnostic imaging , Pulmonary Aspergillosis/therapyABSTRACT
No disponible
Subject(s)
Humans , Female , Middle Aged , Vascular Diseases/diagnostic imaging , Vascular Diseases/diagnosisABSTRACT
PURPOSE: COVID-19 raises D-dimer (DD) levels even in the absence of pulmonary embolism (PE), resulting in an increase in computed tomography pulmonary angiogram (CTPA) requests. Our purpose is to determine whether there are differences between DD values in PE-positive and PE-negative COVID-19 patients and, if so, to establish a new cutoff value which accurately determines when a CTPA is needed. METHODS: This study retrospectively analyzed all COVID-19 patients who underwent a CTPA due to suspected PE between March 1 and April 30, 2020, at Ramón y Cajal University Hospital, Madrid (Spain). DD level comparisons between PE-positive and PE-negative groups were made using Student's t test. The optimal DD cutoff value to predict PE risk in COVID-19 patients was calculated in the ROC curve. RESULTS: Two hundred forty-two patients were included in the study. One hundred fifty-one (62%) were men and the median age was 68 years (IQR 55-78). An increase of DD (median 3260; IQR 1203-9625 ng/mL) was detected in 205/242 (96%) patients. 73/242 (30%) of the patients were diagnosed with PE on CTPA. The DD median value was significantly higher (p < .001) in the PE-positive group (7872, IQR 3150-22,494 ng/mL) compared with the PE-negative group (2009, IQR 5675-15,705 ng/mL). The optimal cutoff value for DD to predict PE was 2903 ng/mL (AUC was 0.76 [CI 95% 0.69-0.83], sensitivity 81%). The overall mortality rate was 16% (39/242). CONCLUSION: A higher threshold (2903 ng/mL) for D-dimer could predict the risk of PE in COVID-19 patients with a sensitivity of 81%.
Subject(s)
Computed Tomography Angiography/methods , Coronavirus Infections/epidemiology , Fibrin Fibrinogen Degradation Products/metabolism , Pneumonia, Viral/epidemiology , Pulmonary Embolism/blood , Pulmonary Embolism/diagnostic imaging , Adult , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Female , Humans , Male , Middle Aged , Pandemics , Predictive Value of Tests , Retrospective Studies , SARS-CoV-2 , Sensitivity and Specificity , Spain/epidemiologyABSTRACT
No disponible
