Prediction of escape red blood cell transfusion in expectantly managed women with acute anaemia after postpartum haemorrhage

BJOG: An International Journal of Obstetrics and Gynaecology

Volumn 122, Issue 13, 2015, Pages 1789-1797

  Prick, B W ^a,b   Schuit, E ^c,d,e   Mignini, L ^f   Jansen, A J G ^g   Van Rhenen, D J ^g   Steegers, E A P ^b   Mol, B W ^h   Duvekot, J J ^b  

^a Maasstad Hospital   (Netherlands)

^b ERASMUS MEDICAL CENTER   (Netherlands)

^c UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^d ACADEMIC MEDICAL CENTER   (Netherlands)

^e STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f Centro Rosarino de Estudios Perinatales   (Argentina)

^g CENTRAL LABORATORY   (Netherlands)

^h UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Anaemia; blood transfusion; postpartum haemorrhage; prediction model; red blood cell transfusion

Indexed keywords

ANEMIA; APGAR SCORE; ARTICLE; BODY MASS; BOOTSTRAPPING; CLINICAL DECISION MAKING; CONTROLLED STUDY; COUNSELING; DELIVERY; DISEASE SEVERITY; EDUCATION; EPISIOTOMY; ERYTHROCYTE TRANSFUSION; ETHNICITY; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MATERNAL AGE; MULTICENTER STUDY; NETHERLANDS; OUTCOME ASSESSMENT; POSTPARTUM HEMORRHAGE; PREDICTION; PREDICTIVE VALUE; PREMATURE LABOR; PRIORITY JOURNAL; QUALITY OF LIFE; RANDOMIZED CONTROLLED TRIAL; RELIABILITY; VALIDATION PROCESS; VALIDITY; VISUAL ANALOG SCALE; ACUTE DISEASE; ADULT; ADVERSE EFFECTS; CLINICAL TRIAL; HEALTH STATUS; PREGNANCY; PROGNOSIS; QUESTIONNAIRE; REGRESSION ANALYSIS; RISK FACTOR; SENSITIVITY AND SPECIFICITY; TREATMENT OUTCOME;

ACUTE DISEASE; ADULT; ANEMIA; ERYTHROCYTE TRANSFUSION; FEMALE; HEALTH STATUS; HUMANS; NETHERLANDS; POSTPARTUM HEMORRHAGE; PREGNANCY; PROGNOSIS; QUALITY OF LIFE; REGRESSION ANALYSIS; RISK FACTORS; SENSITIVITY AND SPECIFICITY; SURVEYS AND QUESTIONNAIRES; TREATMENT OUTCOME;

EID: 84947616153     PISSN: 14700328     EISSN: 14710528     Source Type: Journal    
DOI: 10.1111/1471-0528.13224     Document Type: Article

References (50)

1. World Health Organization. WHO Guidelines for the Management of Postpartum Haemorrhage and Retained Placenta. Geneva: WHO, 2009.
2. Carroli G, Cuesta C, Abalos E, Gulmezoglu AM,. Epidemiology of postpartum haemorrhage: a systematic review. Best Pract Res Clin Obstet Gynaecol 2008; 22: 999-1012.
3. Callaghan WM, Kuklina EV, Berg CJ,. Trends in postpartum hemorrhage: United States, 1994-2006. Am J Obstet Gynecol 2010; 202: 353.e1-6.
4. Knight M, Callaghan WM, Berg C, Alexander S, Bouvier-Colle MH, Ford JB, et al., Trends in postpartum hemorrhage in high resource countries: a review and recommendations from the International Postpartum Hemorrhage Collaborative Group. BMC Pregnancy Childbirth 2009; 9: 55.
5. Joseph KS, Rouleau J, Kramer MS, Young DC, Liston RM, Baskett TF,. Investigation of an increase in postpartum haemorrhage in Canada. BJOG 2007; 114: 751-9.
6. Cameron CA, Roberts CL, Olive EC, Ford JB, Fischer WE,. Trends in postpartum haemorrhage. Aust N Z J Public Health 2006; 30: 151-6.
7. Ford JB, Roberts CL, Simpson JM, Vaughan J, Cameron CA,. Increased postpartum hemorrhage rates in Australia. Int J Gynaecol Obstet 2007; 98: 237-43.
8. Lutomski JE, Byrne BM, Devane D, Greene RA,. Increasing trends in atonic postpartum haemorrhage in Ireland: an 11-year population-based cohort study. BJOG 2012; 119: 306-14.
9. Prick BW, Steegers EA, Jansen AJ, Hop WC, Essink-Bot ML, Peters NC, et al., Well being of obstetric patients on minimal blood transfusions (WOMB trial). BMC Pregnancy Childbirth 2010; 10: 83.
10. Prick BW, Jansen AJG, Steegers EAP, Hop WCJ, Essink-Bot ML, Uyl-de Groot CA, et al., Transfusion policy after severe postpartum haemorrhage: a randomised non-inferiority trial. BJOG 2014; 121: 1005-14.
11. Smets EM, Garssen B, Bonke B, De Haes JC,. The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res 1995; 39: 315-25.
12. EuroQol Group. EuroQol- A new facility for the measurement of health-related quality of life. Health Policy 1990; 16: 199-208.
13. Statistics Netherlands. Definition of a western background. [ www.cbs.nl/ ]. Accessed 14 May 2013.
14. The Netherlands Perinatal Registry. Perinatal Care in The Netherlands 2006 (in Dutch: Perinatale Zorg in Nederland 2006). Utrecht: The Netherlands Perinatal Registry, 2008.
15. Jansen AJ, Duvekot JJ, Hop WC, Essink-Bot ML, Beckers EA, Karsdorp VH, et al., New insights into fatigue and health-related quality of life after delivery. Acta Obstet Gynecol Scand 2007; 86: 579-84.
16. van der Heijden GJ, Donders AR, Stijnen T, Moons KG,. Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example. J Clin Epidemiol 2006; 59: 1102-9.
17. Greenland S, Finkle WD,. A critical look at methods for handling missing covariates in epidemiologic regression analyses. Am J Epidemiol 1995; 142: 1255-64.
18. Harrell FE Jr, Lee KL, Mark DB,. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15: 361-87.
19. Cook NR,. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007; 115: 928-35.
20. Atkinson A,. A note on the generalized information criterion for choice of a model. Biometrika 1980; 67: 413-8.
21. Miller ME, Hui SL, Tierney WM,. Validation techniques for logistic regression models. Stat Med 1991; 10: 1213-26.
22. Hanley JA, McNeil BJ,. A method of comparing the areas under ROC curves derived from the same cases. Radiology 1983; 143: 29-36.
23. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS,. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157-72.
24. Hlatky MA, Greenland P, Arnett DK, Ballantyne CM, Criqui MH, Elkind MS, et al., Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation 2009; 119: 2408-16.
25. Cook NR,. Assessing the incremental role of novel and emerging risk factors. Curr Cardiovasc Risk Rep 2010; 4: 112-9.
26. Pencina M, D'Agostino R, Steyerberg E,. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011; 30: 11-21.
27. Hilden J, Gerds TA,. A note on the evaluation of novel biomarkers: do not rely on integrated discrimination improvement and net reclassification index. Stat Med 2014; 33: 3405-14.
28. Hoeymans N, Lindert Hv, Westert G,. The health status of the Dutch population as assessed by the EQ-6D. Qual Life Res 2005; 14: 655-63.
29. Charbit J, Mahul M, Roustan JP, Latry P, Millet I, Taourel P, et al., Hemoperitoneum semiquantitative analysis on admission of blunt trauma patients improves the prediction of massive transfusion. Am J Emerg Med 2013; 31: 130-6.
30. Hsu JM, Hitos K, Fletcher JP,. Identifying the bleeding trauma patient: predictive factors for massive transfusion in an Australasian trauma population. J Trauma Acute Care Surg 2013; 75: 359-64.
31. Cotton BA, Faz G, Hatch QM, Radwan ZA, Podbielski J, Wade C, et al., Rapid thrombelastography delivers real-time results that predict transfusion within 1 hour of admission. J Trauma 2011; 71: 407-14; discussion 14-17.
32. Leemann H, Lustenberger T, Talving P, Kobayashi L, Bukur M, Brenni M, et al., The role of rotation thromboelastometry in early prediction of massive transfusion. J Trauma 2010; 69: 1403-8; discussion 8-9.
33. Mina MJ, Winkler AM, Dente CJ,. Let technology do the work: improving prediction of massive transfusion with the aid of a smartphone application. J Trauma Acute Care Surg 2013; 75: 669-75.
34. Mitra B, Rainer TH, Cameron PA,. Predicting massive blood transfusion using clinical scores post-trauma. Vox Sang 2012; 102: 324-30.
35. Fotland SS, Reikvam H, Hervig T, Seghatchian J,. Does the preoperative iron status predict transfusion requirement of orthopedic patients? Transfus Apher Sci 2009; 40: 213-7.
36. Kadar A, Chechik O, Steinberg E, Reider E, Sternheim A,. Predicting the need for blood transfusion in patients with hip fractures. Int Orthop 2013; 37: 693-700.
37. Noticewala MS, Nyce JD, Wang W, Geller JA, Macaulay W,. Predicting need for allogeneic transfusion after total knee arthroplasty. J Arthroplasty 2012; 27: 961-7.
38. Guerin S, Collins C, Kapoor H, McClean I, Collins D,. Blood transfusion requirement prediction in patients undergoing primary total hip and knee arthroplasty. Transfus Med 2007; 17: 37-43.
39. Elmistekawy EM, Errett L, Fawzy HF,. Predictors of packed red cell transfusion after isolated primary coronary artery bypass grafting-the experience of a single cardiac center: a prospective observational study. J Cardiothorac Surg 2009; 4: 20.
40. Josefy S, Briones R, Bryant BJ,. Preoperative coagulation studies to predict blood component usage in coronary artery bypass graft surgery. Immunohematology 2011; 27: 151-3.
41. Moskowitz DM, Klein JJ, Shander A, Cousineau KM, Goldweit RS, Bodian C, et al., Predictors of transfusion requirements for cardiac surgical procedures at a blood conservation center. Ann Thorac Surg 2004; 77: 626-34.
42. Shehata N, Naglie G, Alghamdi AA, Callum J, Mazer CD, Hebert P, et al., Risk factors for red cell transfusion in adults undergoing coronary artery bypass surgery: a systematic review. Vox Sang 2007; 93: 1-11.
43. Araujo T, Cordeiro A, Proenca P, Perdigoto R, Martins A, Barroso E,. Predictive variables affecting transfusion requirements in orthotopic liver transplantation. Transplant Proc 2010; 42: 1758-9.
44. Massicotte L, Beaulieu D, Thibeault L, Roy JD, Marleau D, Lapointe R, et al., Coagulation defects do not predict blood product requirements during liver transplantation. Transplantation 2008; 85: 956-62.
45. Modanlou KA, Oliver DA, Grossman BJ,. Liver donor's age and recipient's serum creatinine predict blood component use during liver transplantation. Transfusion 2009; 49: 2645-51.
46. Roullet S, Biais M, Millas E, Revel P, Quinart A, Sztark F,. Risk factors for bleeding and transfusion during orthotopic liver transplantation. Ann Fr Anesth Reanim 2011; 30: 349-52.
47. Pulitano C, Arru M, Bellio L, Rossini S, Ferla G, Aldrighetti L,. A risk score for predicting perioperative blood transfusion in liver surgery. Br J Surg 2007; 94: 860-5.
48. Sima CS, Jarnagin WR, Fong Y, Elkin E, Fischer M, Wuest D, et al., Predicting the risk of perioperative transfusion for patients undergoing elective hepatectomy. Ann Surg 2009; 250: 914-21.
49. Stotler B, Padmanabhan A, Devine P, Wright J, Spitalnik SL, Schwartz J,. Transfusion requirements in obstetric patients with placenta accreta. Transfusion 2011; 51: 2627-33.
50. Fong A, Leake J, Pan D, Ogunyemi D,. Demographic, institutional and obstetrical risk factors for postpartum haemorrhage mortality. J Obstet Gynaecol 2010; 30: 470-5.