Introduction Pulmonary Embolism (PE) represents the final effect of the sudden obstruction of the pulmonary artery or one of its branches by an embolus and is burdened by high mortality when not promptly and adequately treated. The clinical presentation is often non-specific, which explains the diagnostic difficulty and the frequent autopsy finding of PE: 90% of fatal cases occur in patients who have not undergone treatment due to the failure to formulate the diagnostic suspicion, while less than 10% of all deaths occur in treated patients. Materials and Methods The established intra-hospital management path arises from the integration between clinical suspicion, first level diagnostic tests (ECG, EGA, chest x-ray, blood chemistry tests) and pre-test clinical probability (Wells, modified Geneva). In patients with Wells 0 to 4 and negative D-dimer, the diagnosis of PE can be excluded; in other cases a pulmonary CT angiography is performed. The sPESI Score with troponin measurement and echocardiogram are used in patients with diagnosis of high-risk PE for prognostic stratification and to identify the destination of hospitalization. Results The comparison of the epidemiological data regarding PE between 2021 and 2023 allowed us to verify how, thanks to the intra-hospital shared management process, a different distribution of hospitalizations was obtained in the Operating Units involved: hospitalizations in Cardiology are reduced by 50%; on the contrary, admissions to Internal Medicine increased by 60% in 2022, remaining stable in 2023; hospitalizations in the Pneumology Operating Unit are stable. Admissions to other departments of the hospital for patients suffering from other important prevalent co-morbidities went from 3% to 7%. Conclusions The clinical presentation of PE is often non-specific, which explains the diagnostic difficulty and the frequent autopsy finding of PE not diagnosed during life. We have established an internal management process ensuring the correct diagnostic classification and timely treatment, through stratification according to risk class and identifying the most appropriate hospitalization setting.
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Girasoli et al. (2024) studied this question.
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