The Michigan Risk Score to predict peripherally inserted central catheter‐associated thrombosis
| Autor: | Paul J. Grant, Steven J. Bernstein, Sanjay Saint, Mary A.M. Rogers, Scott Kaatz, Vineet Chopra, Scott A. Flanders, Anna Conlon, David Paje |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Catheter Obstruction
Male Catheterization Central Venous medicine.medical_specialty 030204 cardiovascular system & hematology Risk Assessment Peripherally inserted central catheter Decision Support Techniques 03 medical and health sciences Catheters Indwelling 0302 clinical medicine Predictive Value of Tests Risk Factors Upper Extremity Deep Vein Thrombosis Internal medicine Catheterization Peripheral Odds Ratio Central Venous Catheters Humans Medicine Registries 030212 general & internal medicine Internal validation Aged Proportional Hazards Models Framingham Risk Score business.industry Hematology Odds ratio Middle Aged medicine.disease Thrombosis Hospital medicine Surgery Logistic Models Multivariate Analysis Female Risk classification business Thrombotic complication |
| Zdroj: | Journal of Thrombosis and Haemostasis. 15:1951-1962 |
| ISSN: | 1538-7836 |
| DOI: | 10.1111/jth.13794 |
| Popis: | Essentials How best to quantify thrombosis risk with peripherally inserted central catheters (PICC) is unknown. Data from a registry were used to develop the Michigan Risk Score (MRS) for PICC thrombosis. Five risk factors were associated with PICC thrombosis and used to develop a risk score. MRS was predictive of the risk of PICC thrombosis and can be useful in clinical practice. SummaryBackground Peripherally inserted central catheters (PICCs) are associated with upper extremity deep vein thrombosis (DVT). We developed a score to predict risk of PICC-related thrombosis. Methods Using data from the Michigan Hospital Medicine Safety Consortium, image-confirmed upper-extremity DVT cases were identified. A logistic, mixed-effects model with hospital-specific random intercepts was used to identify factors associated with PICC-DVT. Points were assigned to each predictor, stratifying patients into four classes of risk. Internal validation was performed by bootstrapping with assessment of calibration and discrimination of the model. Results Of 23 010 patients who received PICCs, 475 (2.1%) developed symptomatic PICC-DVT. Risk factors associated with PICC-DVT included: history of DVT; multi-lumen PICC; active cancer; presence of another CVC when the PICC was placed; and white blood cell count greater than 12 000. Four risk classes were created based on thrombosis risk. Thrombosis rates were 0.9% for class I, 1.6% for class II, 2.7% for class III and 4.7% for class IV, with marginal predicted probabilities of 0.9% (0.7, 1.2), 1.5% (1.2, 1.9), 2.6% (2.2, 3.0) and 4.5% (3.7, 5.4) for classes I, II, III, and IV, respectively. The risk classification rule was strongly associated with PICC-DVT, with odds ratios of 1.68 (95% CI, 1.19, 2.37), 2.90 (95% CI, 2.09, 4.01) and 5.20 (95% CI, 3.65, 7.42) for risk classes II, III and IV vs. risk class I, respectively. Conclusion The Michigan PICC-DVT Risk Score offers a novel way to estimate risk of DVT associated with PICCs and can help inform appropriateness of PICC insertion. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text