BACKGROUND: Studies addressing patterns and trends in red blood cell transfusion use in US hemodialysis patients surprisingly have received little attention in the last decade. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Point prevalent (as of January 1 of each calendar year 1992 to 2005) dialysis patients with Medicare Part A and Part B as primary insurance (n = 77,347 in 1992, n = 164,933 in 2005). The 6 months preceding January 1 of each year were used to assemble a comorbidity profile based on administrative claims data. PREDICTORS: Hemoglobin levels, patient characteristics, comorbid conditions. OUTCOMES: Blood transfusion events obtained from Part A and Part B files using code files for both whole and packed red blood cell transfusions and hemoglobin levels. MEASUREMENTS: Comorbid conditions were defined by the presence of 1 or more inpatient/outpatient institutional claims (inpatient hospitalization, skilled nursing facility, or home health agency), 2 or more outpatient or physician/supplier claims, or 1 or more outpatient and 1 or more physician/supplier claims for atherosclerotic heart disease, congestive heart failure, cerebrovascular accidents/transient ischemic attacks, peripheral vascular disease, other cardiovascular diseases, chronic obstructive pulmonary disease, gastrointestinal disorders, liver disease, arrhythmia, and diabetes mellitus. RESULTS: Raw transfusion rates decreased in both outpatient and inpatient settings from 535.33/1,000 patient-years for 1992 prevalent dialysis patients to 263.65/1,000 patient-years in 2005 (P for trend < 0.001, 1992 versus 1999 and 1999 versus 2005). Adjusted rates decreased similarly. This phenomenon could not be explained by changes in case mix. LIMITATIONS: Cause, effect, and confounding cannot be separated in this observational study. The accuracy of blood transfusion billing data is unknown. Temporal trends may be related to factors other than erythropoiesis-stimulating agent use. CONCLUSION: Transfusion events in hemodialysis patients decreased more than 2-fold from 1992 to 2005; most of the decrease occurred in the first 5 years after erythropoietin was introduced.
BACKGROUND: Studies addressing patterns and trends in red blood cell transfusion use in US hemodialysis patients surprisingly have received little attention in the last decade. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Point prevalent (as of January 1 of each calendar year 1992 to 2005) dialysis patients with Medicare Part A and Part B as primary insurance (n = 77,347 in 1992, n = 164,933 in 2005). The 6 months preceding January 1 of each year were used to assemble a comorbidity profile based on administrative claims data. PREDICTORS: Hemoglobin levels, patient characteristics, comorbid conditions. OUTCOMES: Blood transfusion events obtained from Part A and Part B files using code files for both whole and packed red blood cell transfusions and hemoglobin levels. MEASUREMENTS: Comorbid conditions were defined by the presence of 1 or more inpatient/outpatient institutional claims (inpatient hospitalization, skilled nursing facility, or home health agency), 2 or more outpatient or physician/supplier claims, or 1 or more outpatient and 1 or more physician/supplier claims for atherosclerotic heart disease, congestive heart failure, cerebrovascular accidents/transient ischemic attacks, peripheral vascular disease, other cardiovascular diseases, chronic obstructive pulmonary disease, gastrointestinal disorders, liver disease, arrhythmia, and diabetes mellitus. RESULTS: Raw transfusion rates decreased in both outpatient and inpatient settings from 535.33/1,000 patient-years for 1992 prevalent dialysis patients to 263.65/1,000 patient-years in 2005 (P for trend < 0.001, 1992 versus 1999 and 1999 versus 2005). Adjusted rates decreased similarly. This phenomenon could not be explained by changes in case mix. LIMITATIONS: Cause, effect, and confounding cannot be separated in this observational study. The accuracy of blood transfusion billing data is unknown. Temporal trends may be related to factors other than erythropoiesis-stimulating agent use. CONCLUSION: Transfusion events in hemodialysis patients decreased more than 2-fold from 1992 to 2005; most of the decrease occurred in the first 5 years after erythropoietin was introduced.
Authors: Elizabeth V Lawler; Brian D Bradbury; Jennifer R Fonda; J Michael Gaziano; David R Gagnon Journal: Clin J Am Soc Nephrol Date: 2010-03-18 Impact factor: 8.237
Authors: Ju-Yeh Yang; Tsung-Chun Lee; Maria E Montez-Rath; Jane Paik; Glenn M Chertow; Manisha Desai; Wolfgang C Winkelmayer Journal: J Am Soc Nephrol Date: 2012-01-19 Impact factor: 10.121
Authors: Julie M Yabu; Matthew W Anderson; Deborah Kim; Brian D Bradbury; Calvin D Lou; Jeffrey Petersen; Jerome Rossert; Glenn M Chertow; Dolly B Tyan Journal: Nephrol Dial Transplant Date: 2013-09-05 Impact factor: 5.992
Authors: Wolfgang C Winkelmayer; Aya A Mitani; Benjamin A Goldstein; M Alan Brookhart; Glenn M Chertow Journal: JAMA Intern Med Date: 2014-05 Impact factor: 21.873
Authors: Li Zuo; Mia Wang; Fanfan Hou; Yucheng Yan; Nan Chen; Jiaqi Qian; Mei Wang; Brian Bieber; Ronald L Pisoni; Bruce M Robinson; Shuchi Anand Journal: Blood Purif Date: 2016-03-31 Impact factor: 2.614
Authors: Robert Toto; Jeffrey Petersen; Jeffrey S Berns; Eldrin Foster Lewis; Qui Tran; Matthew R Weir Journal: J Am Soc Nephrol Date: 2020-12-07 Impact factor: 10.121
Authors: Kathleen M Fox; Jerry Yee; Ze Cong; John M Brooks; Jeffrey Petersen; Lois Lamerato; Shravanthi R Gandra Journal: BMC Nephrol Date: 2012-01-24 Impact factor: 2.388
Authors: Matthew Gitlin; J Andrew Lee; David M Spiegel; Jeffrey L Carson; Xue Song; Brian S Custer; Zhun Cao; Katherine A Cappell; Helen V Varker; Shaowei Wan; Akhtar Ashfaq Journal: BMC Nephrol Date: 2012-11-02 Impact factor: 2.388
Authors: Nareg H Roubinian; Edward L Murphy; Bix E Swain; Marla N Gardner; Vincent Liu; Gabriel J Escobar Journal: BMC Health Serv Res Date: 2014-05-10 Impact factor: 2.655