Overuse of Computed Tomography Pulmonary Angiography in the Diagnosis of Pulmonary Thromboembolism "Real-Life Data".

Abstract

Purpose: Pulmonary thromboembolism (PTE) is a common cause of cardiovascular mortality with an increasing incidence rate. Scoring patients with suspected pulmonary thromboembolism according to their symptoms, findings, and risk factors is useful for empirical diagnosis and management. The combination of D-dimer and clinical scoring allows the diagnosis to be excluded in approximately 30% of patients with suspected PTE without the need for imaging methods. Despite this, clinical scores are not used effectively in the clinic. The aim of this study is to show that computed tomography pulmonary angiography (CTPA) is overused in real life and to emphasize that overuse of CTPA can be prevented with clinical tests.

Patients and methods: We studied 214 patients who underwent CTPA for suspected pulmonary thromboembolism. We evaluated whether clinical probability scoring (Wells scoring, Geneva scoring) was performed prior to CTPA from these patients' records and the health system database, and if so, the scores were evaluated. The rates and results of PERC criteria were also evaluated in patients.

Results: Pulmonary thromboembolism was not detected on CTPA in 185 patients (86.4%). PERC criteria were not evaluated in all patients before CTPA. When the PERC criteria were evaluated by the study team, it was found that there was a significant relationship between PTE diagnosis and the criteria. There was also a significant correlation between Geneva score and CTPA results (p=0.000<0.05).

Conclusion: Preventing overuse of CTPA by evaluating clinical probability scores, PERC criteria and d-dimer levels is important in many ways. Prevention of overuse of CTPA use will reduce unnecessary workload in clinical functioning and provide financial gain. Although CTPA is a diagnostic method with high diagnostic accuracy in the diagnosis of PTE, it is overused in real life. The overuse of CTPA can be significantly reduced by the combined use of clinical probability scoring (Wells and Geneva), exclusion criteria (PERC) and d-dimer results.