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Positive predictive value and misclassification of diagnosis of pulmonary embolism and deep vein thrombosis in Swedish patient registries

Authors Öhman L, Johansson M, Jansson JH, Lind M, Johansson L

Received 13 June 2018

Accepted for publication 19 July 2018

Published 17 September 2018 Volume 2018:10 Pages 1215—1221


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Vera Ehrenstein

Ludvig Öhman, Magdalena Johansson, Jan-Håkan Jansson, Marcus Lind, Lars Johansson

Department of Public Health and Clinical Medicine, Skellefteå Research Unit, Umeå University, Umeå, Västerbotten, Sweden

Purpose: To validate diagnoses of pulmonary embolism (PE) and deep vein thrombosis (DVT) in administrative registries. We also estimated the frequency of misclassified PE and DVT events.
Patients and methods: A registry search for ICD codes representing PE and DVT was performed between 1985 and 2014 in a large population-based cohort in northern Sweden. An additional search using an extended set of ICD codes was performed to identify misclassified events. Diagnoses were validated manually by reviewing medical records and radiology reports.
Results: Searching ICD codes in the National Patient Registry and Cause of Death Registry identified 2,450 participants with a first-time diagnosis of PE or DVT. The positive predictive value (PPV) for a diagnosis of PE or DVT was 80.7% and 59.2%, respectively. For the period of 2009 to 2014, the PPV was higher for PE (85.8%) but lower for DVT (54.1%). Misclassification occurred in 16.4% of DVT events and 1.1% of PE events.
Conclusion: Registry-based data on PE, especially in recent years, are of acceptable quality and can be considered for use in registry-based studies. For DVT, we found that data were of low quality in regards to both PPV and misclassification and should not be used without validation.

Keywords: pulmonary embolism, deep vein thrombosis, positive predictive value, International Classification of Diseases, validation

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