# Assessing Morbidity and Malignancy Risk in Patients Presenting with Pulmonary Embolism in an Ambulatory Care Setting

## TL;DR

This study evaluates the risk of morbidity, mortality, and new cancer diagnoses in patients with pulmonary embolism managed in an outpatient setting.

## Contribution

The study introduces a classification tree method to predict new cancer sites with high specificity using age and cancer history.

## Key findings

- High sPESI scores correlate with increased 90-day mortality in pulmonary embolism patients.
- A classification tree model predicted new cancer sites with 97% specificity using age and cancer history.
- Unprovoked pulmonary embolism was observed in 52.4% of patients.

## Abstract

Venous thromboembolism (VTE), especially pulmonary embolism (PE), can be treated in an outpatient setting after appropriate risk assessment. However, front-door physicians may be resistant to follow this practice. The possibility of cancer-associated VTE complicates the outpatient management of PE. This study aimed to assess the morbidity and mortality in patients with PE who were managed in an emergency/acute medicine-led outpatient clinic as per risk stratification as well as detecting diagnoses of new cancer sites (NCSs) in these patients.

This retrospective study included all patients with confirmed PE managed in an acute medicine outpatient setting at Queens Hospital, Burton-on-Trent, United Kingdom, from 2019 to 2022. Biochemical findings, radiological findings, mortality and morbidity rates, treatment administered, simplified Pulmonary Embolism Severity Index (sPESI) scores, complications and NCS diagnosis were obtained.

A total of 82 patients were included in this study; their mean age was 63.3 ± 16.7 years and 56.1% (n = 46) were male. The two commonest presenting complaints were new shortness of breath (25.6%, n = 21) and pleuritic chest pain (19.5%, n = 16). Unprovoked PE was observed in 52.4% (n = 43) of patients. Increased sPESI scores were related to increased mortality rates; sPESI scores of 0 and 3 were associated with 0% and 50% mortality rates within 90 days, respectively. NCS was reported in 13.4% (n = 11). Statistical analyses using logistic regression and classification tree methods revealed that NCS can be predicted with 70.6% sensitivity and 97% specificity using 2 variables (history of cancer and age >73 years).

The sPESI can help in the risk stratification of patients with PE showing poor outcomes; patients at a high risk of NCS development can be identified using the classification tree method.