Evaluation of clinical coding data to determine causes of critical bleeding in patients receiving massive transfusion: a bi-national, multicentre, cross-sectional study-Reference-Cited by-同舟云学术

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Evaluation of clinical coding data to determine causes of critical bleeding in patients receiving massive transfusion: a bi-national, multicentre, cross-sectional study

Published:2016-12-13 Issue:2 Volume:27 Page:114-121
ISSN:0958-7578
Container-title:Transfusion Medicine
language:en
Short-container-title:Transfusion Med

Author:

McQuilten Z. K.¹²,Zatta A. J.¹²,Andrianopoulos N.³,Aoki N.¹,Stevenson L.⁴,Badami K. G.⁵,Bird R.⁶⁷,Cole-Sinclair M. F.⁸,Hurn C.⁹^ORCID,Cameron P. A.³,Isbister J. P.¹⁰,Phillips L. E.¹,Wood E. M.¹,

Affiliation:

1. Transfusion Research Unit; Monash University; Melbourne Australia

2. Australian and New Zealand Intensive Care Research Centre (ANZIC-RC); Monash University; Melbourne Australia

3. Department of Epidemiology and Preventive Medicine; Monash University; Melbourne Australia

4. Barwon Health; University Hospital Geelong; Geelong Australia

5. New Zealand Blood Service; Christchurch New Zealand

6. Princess Alexandra Hospital; Brisbane Queensland

7. School of Medicine; Griffith University; Brisbane Australia

8. Department of Haematology; St Vincent's Hospital; Melbourne Australia

9. School of Medicine; University of Queensland; Brisbane Australia

10. Royal North Shore Hospital; The University of Sydney; Sydney Australia

Funder

National Health and Medical Research Council

NHMRC Peter Doherty Fellowship

Publisher

Wiley

Subject

Hematology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/tme.12377/fullpdf

Reference19 articles.

1. Red alert - a new perspective on patterns of blood use in the South Australian public sector;Allden;Australian Health Review,2011

2. A systematic review of discharge coding accuracy;Campbell;Journal of Public Health Medicine,2001

3. The kappa statistic was representative of empirically observed inter-rater agreement for physical findings;Gorelick;Journal of Clinical Epidemiology,2006

4. Epidemiology of massive transfusion: a binational study from Sweden and Denmark;Halmin;Critical Care Medicine,2016

5. Quality of diagnosis and procedure coding in ICD-10 administrative data;Henderson;Medical Care,2006

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Epidemiology of Massive Transfusion – A Common Intervention in Need of a Definition;Transfusion Medicine Reviews;2021-10

2. Age of red blood cells is not associated with in-hospital mortality in massively transfused patients;Journal of Trauma and Acute Care Surgery;2021-06-10

3. Blood transfusion trends by disease category in the United States, 2000 to 2014;Transfusion and Apheresis Science;2021-02

4. Reply: “Sensitivity” and “specificity” reduction of blood transfusion after transcatheter aortic valve replacement: Is that all that matters?;The Journal of Thoracic and Cardiovascular Surgery;2019-12

5. Clinical coding data algorithm to categorize type of gastrointestinal bleeding as a primary reason for massive transfusion: results from the Australian and New Zealand Massive Transfusion Registry;Vox Sanguinis;2019-09-06

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