BACKGROUND: Little is known about how patterns of warfarin dose management contribute to percentage time in the therapeutic International Normalized Ratio (INR) range (TTR). OBJECTIVES: To quantify the contribution of warfarin dose management to TTR and to define an optimal dose management strategy. PATIENTS/ METHODS: We enrolled 3961 patients receiving warfarin from 94 community-based clinics. We derived and validated a model for the probability of a warfarin dose change under various conditions. For each patient, we computed an observed minus expected (O - E) score, comparing the number of dose changes predicted by our model to the number of changes observed. We examined the ability of O - E scores to predict TTR, and simulated various dose management strategies in the context of our model. RESULTS: Patients were observed for a mean of 15.2 months. Patients who deviated the least from the predicted number of dose changes achieved the best INR control (mean TTR 70.1% unadjusted); patients with greater deviations had lower TTR (65.8% and 62.0% for fewer and more dose changes respectively, Bonferroni-adjusted P < 0.05/3 for both comparisons). On average, clinicians in our study changed the dose when the INR was 1.8 or lower/3.2 or higher (mean TTR: 68%); optimal management would have been to change the dose when the INR was 1.7 or lower/3.3 or higher (predicted TTR: 74%). CONCLUSIONS: Our observational study suggests that INR control could be improved considerably by changing the warfarin dose only when the INR is 1.7 or lower/3.3 or higher. This should be confirmed in a randomized trial.
BACKGROUND: Little is known about how patterns of warfarin dose management contribute to percentage time in the therapeutic International Normalized Ratio (INR) range (TTR). OBJECTIVES: To quantify the contribution of warfarin dose management to TTR and to define an optimal dose management strategy. PATIENTS/ METHODS: We enrolled 3961 patients receiving warfarin from 94 community-based clinics. We derived and validated a model for the probability of a warfarin dose change under various conditions. For each patient, we computed an observed minus expected (O - E) score, comparing the number of dose changes predicted by our model to the number of changes observed. We examined the ability of O - E scores to predict TTR, and simulated various dose management strategies in the context of our model. RESULTS:Patients were observed for a mean of 15.2 months. Patients who deviated the least from the predicted number of dose changes achieved the best INR control (mean TTR 70.1% unadjusted); patients with greater deviations had lower TTR (65.8% and 62.0% for fewer and more dose changes respectively, Bonferroni-adjusted P < 0.05/3 for both comparisons). On average, clinicians in our study changed the dose when the INR was 1.8 or lower/3.2 or higher (mean TTR: 68%); optimal management would have been to change the dose when the INR was 1.7 or lower/3.3 or higher (predicted TTR: 74%). CONCLUSIONS: Our observational study suggests that INR control could be improved considerably by changing the warfarin dose only when the INR is 1.7 or lower/3.3 or higher. This should be confirmed in a randomized trial.
Authors: Anne Holbrook; Sam Schulman; Daniel M Witt; Per Olav Vandvik; Jason Fish; Michael J Kovacs; Peter J Svensson; David L Veenstra; Mark Crowther; Gordon H Guyatt Journal: Chest Date: 2012-02 Impact factor: 9.410
Authors: Sherrie L Aspinall; Xinhua Zhao; Steven M Handler; Roslyn A Stone; Janine C Kosmoski; Elizabeth A Libby; Susan Dove Francis; David A Goodman; Rebecca D Roman; Heather L Bieber; Jennifer M Voisine; Sean M Jeffery; Charley A Hepfinger; Diane G Hagen; Micki M Martin; Joseph T Hanlon Journal: J Am Geriatr Soc Date: 2010-07-19 Impact factor: 5.562
Authors: Reyes Serrano Teruel; Geir Thue; Svein Ivar Fylkesnes; Sverre Sandberg; Ann Helen Kristoffersen Journal: Scand J Prim Health Care Date: 2017-08-04 Impact factor: 2.581
Authors: Hallie B Remer; Xiaokui Gu; Brian Haymart; Geoffrey D Barnes; Mona A Ali; Eva Kline-Rogers; Tina Alexandris-Souphis; Jay H Kozlowski; James B Froehlich; Vinay Shah; Gregory D Krol; Scott Kaatz Journal: Blood Adv Date: 2022-05-24