Derivation and Validation of a Prediction Model for Venous Thromboembolism in Primary Care
| Autor: | Giancarlo Agnelli, Claudio Cricelli, Alexander T. Cohen, Damiano Parretti, Francesco Lapi, Andrea Fontanella, Ettore Marconi, Monica Simonetti, Francesco Dentali, Gualberto Gussoni, Luca Parretti, Mauro Campanini |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Male 0301 basic medicine medicine.medical_specialty Databases Factual venous thromboembolism Population 030204 cardiovascular system & hematology Cohort Studies 03 medical and health sciences 0302 clinical medicine Risk Factors Internal medicine Humans score Medicine education Stroke Aged education.field_of_study Models Statistical business.industry Case-control study Area under the curve Reproducibility of Results antithrombotic prophylaxis prediction model primary health care Hematology Middle Aged Prognosis Explained variation medicine.disease Confidence interval 030104 developmental biology Italy Case-Control Studies Cohort Female business Follow-Up Studies Cohort study |
| Zdroj: | Thrombosis and Haemostasis. 120:692-701 |
| ISSN: | 2567-689X 0340-6245 |
| DOI: | 10.1055/s-0040-1701483 |
| Popis: | Background Most episodes of venous thromboembolism (VTE) occurred in primary care. To date, no score potentially able to identify those patients who may deserve an antithrombotic prophylaxis has been developed. Aim The objective of this study is to develop and validate a prediction model for VTE in primary care. Methods Using the Health Search Database, we identified a cohort of 1,359,880 adult patients between 2002 and 2013. The date of the first General Practitioner's (GP) visit was the cohort entry date. All VTE cases (index date) observed up to December 2014 were identified. The cohort was randomly divided in a development and a validation cohort. According to nested case-cohort analysis, up to five controls were matched to their respective cases on month and year of cohort entry and duration of follow-up.The score was evaluated according to explained variance (pseudo R2) as a performance measure, ratio of predicted to observed cases as model calibration and area under the curve (AUC) as discrimination measure. Results The score was able to explain 27.9% of the variation for VTE occurrence. The calibration measure revealed a margin of error lower than 10% in 70% of the population. In terms of discrimination, AUC was 0.82 (95% confidence interval: 0.82–0.83). Results of sensitivity analyses substantially confirmed these findings. Conclusion The present score demonstrated a very good accuracy in predicting the risk of VTE in primary care. This score may be therefore implemented in clinical practice so aiding GPs in making decision on patients potentially at risk of VTE. |
| Databáze: | OpenAIRE |
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