Derivation and Validation of a Novel Prediction Model to Identify Low-Risk Patients With Acute Pulmonary Embolism

• Published in: The American journal of cardiology Vol. 120; no. 4; pp. 676 - 681
• Main Authors: Subramanian, Muthiah, MD, Gopalan, Sowmya, MD, Ramadurai, Srinivasan, MD, Arthur, Preetam, MD, Prabhu, Mukund A., MD, DM, PDF, Thachathodiyl, Rajesh, MD, DM, Natarajan, Kumaraswamy, MD, DNB (Gen Med) DM, DNB (Card)
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.08.2017; Elsevier Limited
• Subjects: Acute Disease; Blood pressure; Cardiovascular; Computed Tomography Angiography - methods; Data processing; Derivation; Embolism; Embolisms; Female; Follow-Up Studies; Health risk assessment; Heart rate; Humans; Incidence; India - epidemiology; Male; Mathematical models; Medical records; Middle Aged; Mortality; Partial pressure; Patients; Predictive Value of Tests; Prognosis; Prospective Studies; Pulmonary arteries; Pulmonary Embolism - diagnosis; Pulmonary Embolism - epidemiology; Pulmonary embolisms; Reclassification; Regression analysis; Retrospective Studies; Risk; Risk Assessment; Risk groups; ROC Curve; Severity of Illness Index; Short term; Survival Rate - trends; Variables; Ventricle; Score; Outpatient; Right Ventricular Dysfunction; Mortality; Acute Pulmonary Embolism
• ISSN: 0002-9149; 1879-1913
• DOI: 10.1016/j.amjcard.2017.05.043

Abstract Accurate identification of low-risk patients with acute pulmonary embolism(PE) who may be eligible for outpatient treatment or early discharge can have substantial cost saving benefit. The purpose of this study was to derive and validate a prediction model to effectively identify PE patients at low risk of short term mortality, right ventricular (RV) dysfunction, and other non-fatal outcomes. This study analysed data from 400 consecutive patients with acute PE. We derived and internally validated our prediction rule based on clinically significant variables that are routinely available at initial examination, that were categorized and weighted using coefficients in the multivariate logistic regression. The model was externally validated in an independent cohort of 82 patients. The final model (HOPPE score) consisted of 5 categorized patient variables (1,2,or 3 points, respectively):systolic blood p ressure(>120,100-119,<99;mmHg), diastolic blood p ressure(>80,65-79,<64;mmHg), h eart rate (<80,81-100,>101;beats/min), arterial partial pressure of o xygen (>80,60-79,<59;mmHg), and modified E CG score (<2,2-4,>4). The 30- day mortality rates were 0% in low risk(0-6 points), 7.5%-8.5 in intermediate risk(7-10), and 18.2-18.8% in high risk( > 11) patients across the derivation and validation cohorts. In comparison to the previously validated PESI score, the HOPPE score had a higher discriminatory power(AUC 0.74 vs 0.85, p=0.033) and significantly improved both the discrimination(integrated discrimination improvement,p=0.002) and reclassification(net reclassification improvement,p=.003) of the model for short term mortality. In conclusion, the HOPPE score accurately identifies acute PE patients at low risk of short term mortality, RV dysfunction, and other non fatal outcomes. Prospective validation of the prediction model is necessary before implementation in clinical practice.