Dataset Information

Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study.

ABSTRACT:

Background

Computed tomography pulmonary angiography (CTPA) is frequently used in the emergency department (ED) for the diagnosis of pulmonary embolism (PE), while posing risk for contrast-induced nephropathy and radiation-induced malignancy.

Objective

We aimed to create an automated process to calculate the Wells score for pulmonary embolism for patients in the ED, which could potentially reduce unnecessary CTPA testing.

Methods

We designed an automated process using electronic health records data elements, including using a combinatorial keyword search method to query free-text fields, and calculated automated Wells scores for a sample of all adult ED encounters that resulted in a CTPA study for PE at 2 tertiary care hospitals in New York, over a 2-month period. To validate the automated process, the scores were compared to those derived from a 2-clinician chart review.

Results

A total of 202 ED encounters resulted in a completed CTPA to form the retrospective study cohort. Patients classified as "PE likely" by the automated process (126/202, 62%) had a PE prevalence of 15.9%, whereas those classified as "PE unlikely" (76/202, 38%; Wells score >4) had a PE prevalence of 7.9%. With respect to classification of the patient as "PE likely," the automated process achieved an accuracy of 92.1% when compared with the chart review, with sensitivity, specificity, positive predictive value, and negative predictive value of 93%, 90.5%, 94.4%, and 88.2%, respectively.

Conclusions

This was a successful development and validation of an automated process using electronic health records data elements, including free-text fields, to classify risk for PE in ED visits.

SUBMITTER: Zhang NJ

PROVIDER: S-EPMC8922138 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study.

Zhang Nasen Jonathan NJ Rameau Philippe P Julemis Marsophia M Liu Yan Y Solomon Jeffrey J Khan Sundas S McGinn Thomas T Richardson Safiya S

JMIR formative research 20220228 2

<h4>Background</h4>Computed tomography pulmonary angiography (CTPA) is frequently used in the emergency department (ED) for the diagnosis of pulmonary embolism (PE), while posing risk for contrast-induced nephropathy and radiation-induced malignancy.<h4>Objective</h4>We aimed to create an automated process to calculate the Wells score for pulmonary embolism for patients in the ED, which could potentially reduce unnecessary CTPA testing.<h4>Methods</h4>We designed an automated process using elect ...[more]

PMID: 35225812

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Project description:Pulmonary embolism (PE) is a leading cause of mortality in postoperative patients. Numerous PE prevention clinical practice guidelines are available but not consistently implemented. This study aimed to develop and validate a novel risk assessment model to assess the risk of PE in postoperative patients. Patients who underwent Grade IV surgery between September 2012 and January 2020 (n = 26,536) at the Affiliated Dongyang Hospital of Wenzhou Medical University were enrolled in our study. PE was confirmed by an identified filling defect in the pulmonary artery system in CT pulmonary angiography. The PE incidence was evaluated before discharge. All preoperative data containing clinical and laboratory variables were extracted for each participant. A novel risk assessment model (RAM) for PE was developed with multivariate regression analysis. The discrimination ability of the RAM was evaluated by the area under the receiver operating characteristic curve, and model calibration was assessed by the Hosmer-Lemeshow statistic. We included 53 clinical and laboratory variables in this study. Among them, 296 postoperative patients developed PE before discharge, and the incidence rate was 1.04%. The distribution of variables between the training group and the validation group was balanced. After using multivariate stepwise regression, only variable age (OR 1.070 [1.054-1.087], P < 0.001), drinking (OR 0.477 [0.304-0.749], P = 0.001), malignant tumor (OR 2.552 [1.745-3.731], P < 0.001), anticoagulant (OR 3.719 [2.281-6.062], P < 0.001), lymphocyte percentage (OR 2.773 [2.342-3.285], P < 0.001), neutrophil percentage (OR 10.703 [8.337-13.739], P < 0.001), red blood cell (OR 1.872 [1.384-2.532], P < 0.001), total bilirubin (OR 1.038 [1.012-1.064], P < 0.001), direct bilirubin (OR 0.850 [0.779-0.928], P < 0.001), prothrombin time (OR 0.768 [0.636-0.926], P < 0.001) and fibrinogen (OR 0.772 [0.651-0.915], P < 0.001) were selected and significantly associated with PE. The final model included four variables: neutrophil percentage, age, malignant tumor and lymphocyte percentage. The AUC of the model was 0.949 (95% CI 0.932-0.966). The risk prediction model still showed good calibration, with reasonable agreement between the observed and predicted PE outcomes in the validation set (AUC 0.958). The information on sensitivity, specificity and predictive values according to cutoff points of the score in the training set suggested a threshold of 0.012 as the optimal cutoff value to define high-risk individuals. We developed a new approach to select hazard factors for PE in postoperative patients. This tool provided a consistent, accurate, and effective method for risk assessment. This finding may help decision-makers weigh the risk of PE and appropriately select PE prevention strategies.

Dataset Information

Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study.

Background

Objective

Methods

Results

Conclusions

Publications

Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study.

Similar Datasets

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