Prognostic models have been developed to help make decisions in the treatment of pulmonary embolism (PE). Among them, the Pulmonary Embolism Severity Index (PESI) and simplified PESI (sPESI), however they have not been validated in our setting. The objective was to evaluate PESI and sPESI scores ability to predict in-hospital mortality in patients with PE in Argentina. We analyzed a database of 75 academic centers in Argentina that included consecutive patients with PE from 2016 to 2017. The scores were prospectively calculated, and in-hospital and 30 days mortality were assessed. The validation of the models was assessed through discrimination using the area under the ROC curve (AUC), and calibration with the Hosmer-Lemeshow (HL) test. The cohort included 684 patients. In-hospital mortality was 12% and at 30 days an additional 3.2% mortality was registered. The AUC (95% CI) for in-hospital mortality was 0.75 (0.69-0.81) for PESI and 0.77 (0.71-0.82) for sPESI (p = 0.2 between scores). AUC of 30-day mortality 0.75 (0.68-0.8) and 0.78 (0.74-0.83) for PESI and sPESI (p = 0.2 between scores). Both models presented good calibration. The PESI and sPESI risk scores demonstrated similar performance and good accuracy in predicting hospital and 30-day mortality. Both scores can be established as simple prediction tools for PE patients in Argentina.
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Postgrad Med J
December 2024
Dicle University Faculty of Medicine, Department of Emergency Medicine, Internal Medicine, 21280 Diyarbakir, Türkiye.
Background: Pulmonary thromboembolism (PTE), often arising from deep vein thrombosis, remains a high-mortality condition despite diagnostic advancements. Prognostic models like Pulmonary Embolism Severity Index (PESI) and sPESI identify low-risk groups effectively. The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score, reflecting nutritional status and systemic inflammation, shows prognostic value in cancers and cardiovascular diseases.
View Article and Find Full Text PDFClin Appl Thromb Hemost
August 2024
Department of Cardiology, Loyola University Medical Center, Maywood, IL, USA.
Objectives: To construct a new scoring system utilizing biomarkers, vitals, and imaging data to predict 30-day mortality in acute pulmonary embolism (PE).
Background: Acute PE, a well-known manifestation of venous thromboembolic disease, is responsible for over 100,000 deaths worldwide yearly. Contemporary management algorithms rely on a multidisciplinary approach to care via PE response teams (PERT) in the identification of low, intermediate, and high-risk patients.
BMC Med Inform Decis Mak
May 2024
Department of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Beijing, China.
Background: Acute pulmonary thromboembolism (PTE) is a common cardiovascular disease and recognizing low prognosis risk patients with PTE accurately is significant for clinical treatment. This study evaluated the value of federated learning (FL) technology in PTE prognosis risk assessment while ensuring the security of clinical data.
Methods: A retrospective dataset consisted of PTE patients from 12 hospitals were collected, and 19 physical indicators of patients were included to train the FL-based prognosis assessment model to predict the 30-day death event.
Thromb Haemost
December 2024
University of Michigan Medical School, Ann Arbor, Michigan, United States.
Background: High-sensitivity troponin T (HS-TnT) may improve risk-stratification in hemodynamically stable acute pulmonary embolism (PE), but an optimal strategy for combining this biomarker with clinical risk-stratification tools has not been determined.
Study Hypothesis: We hypothesized that different HS-TnT cutoff values may be optimal for identifying (1) low-risk patients who may be eligible for outpatient management and (2) patients at increased risk of clinical deterioration who might benefit from advanced PE therapies.
Methods: Retrospective analysis of hemodynamically stable patients in the University of Michigan acute ED-PE registry with available HS-TnT values.
Clin Appl Thromb Hemost
May 2024
Department of Cardiology, Loyola University Medical Center, Maywood, IL, USA.
Several risk stratification systems aid clinicians in classifying pulmonary embolism (PE) severity and prognosis. We compared 2 clinical PE scoring systems, the PESI and sPESI scores, with 2 comorbidity indices, the Charlson Comorbidity Index (CCI) and the val Walraven Elixhauser Comorbidity Index (ECI), to determine the utility of each in predicting mortality and hospital readmission. Information was collected from 436 patients presenting with PE via retrospective chart review.
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