DOI: 10.6084/m9.figshare.27117142
title: Data.xlsx

description: Background/Objectives: Pulmonary embolism (PE) is a potentially serious condition characterized by the blockage of blood vessels in the lungs, often presenting significant diagnostic challenges due to its non-specific symptoms. This study aimed to evaluate the utility of the alveolar-arterial (A-a) oxygen gradient as a diagnostic tool for PE, hypothesizing that it could enhance early detection when combined with other clinical markers. Methods: We conducted a retrospective analysis of 168 patients at the University Hospital Center Split. The study correlated A-a gradients with PE confirmed by CT pulmonary angiography. Key clinical and biochemical markers, including heart rate, C-reactive protein (CRP), pro-brain natriuretic peptide (NT-proBNP), D-dimer, high-sensitivity troponin (hs-troponin), and arterial oxygen pressure (PaO2), were assessed. Results: Our findings revealed that patients with PE had significantly higher A-a gradients compared to those without PE. The observed-to-expected ratio for A-a gradient was notably increased in the PE group. Additionally, patients with PE exhibited elevated levels of heart rate, CRP, NT-proBNP, D-dimer, and hs-troponin, while PaO2 levels were notably lower. Conclusions: This study demonstrates that an elevated A-a gradient reflects the severity of gas exchange impairment in PE. The results suggest that early diagnosis of PE may be improved by incorporating A-a gradient analysis alongside other clinical markers, potentially leading to more effective and timely interventions.Methods (detailed): The study included 168 patients aged 17 to 91 years. The patients were examined upon emergency admission. The examination included a detailed anamnesis with a focus on risk factors for pulmonary embolism, where it was noted whether the patient had active cancer, hemoptysis related to the current condition, a history of pulmonary embolism or deep vein thrombosis, or any surgical procedures within the last 4 weeks. Each patient underwent a clinical examination, where heart rate was recorded, along with the presence of clinical signs of DVT. Blood was drawn for hematology, coagulation, and biochemistry tests. An arterial blood sample was taken for gas analysis, which is simple, painless, and provides immediate results. The ABL90 FLEX device from Radiometer was used for this calculation in the emergency department. The recorded data of interest included: oxygen saturation of arterial blood, arterial oxygen pressure, and arterial carbon dioxide pressure. When a working diagnosis of PE was made, the patient was sent for CT pulmonary angiography with Optiray contrast. A-a gradients were calculated using the standard equation: A−a=PAO2−PaO2. A normal gradient is defined as being less than or equal to the sum of the patient’s age plus 10, divided by 4. The validation set consisted of patients who had nor-mal CT angiography results from 2019 to 2023. All statistical calculations and analyses were performed using SPSS (Statistical Package for the Social Sciences) version 26.0 and R version 4.0.5. To assess differences between groups (patients with and without PE), the Mann-Whitney U test was used, as the data on the A-a ratio values showed an asymmetric distribution. The Mann-Whitney U test is a non-parametric test that compares the medians of two in-dependent groups. The significance of differences between groups was assessed at a significance level of P &lt; 0.05. For analyzing the distribution of binary outcomes in this study we used the chi-square test, which assesses whether there is a statistically significant difference in frequency between two or more categorical variables. To evaluate the diagnostic accuracy of the ratio of expected and observed A-a values in predicting PE, a ROC curve (Receiver Operating Characteristic) analysis was used, and the AUC (Area Under the Curve) value was calculated. The ROC curve shows the ratio of sensitivity and 1-specificity across different threshold values (cut-off), and the AUC value serves as an overall measure of the model's diagnostic accuracy. To determine the optimal cut-off for the ratio of expected and observed A-a values, the Youden index (J) was used, which maximizes the combination of sensitivity and specificity.