Predicting postoperative transfusion in elective total HIP and knee arthroplasty: Comparison of different machine learning models of a case-control study

2021 ◽  
pp. 106183
Author(s):  
ZeYu Huang ◽  
John Martin ◽  
Qiang Huang ◽  
Jun Ma ◽  
FuXing Pei ◽  
...  
2004 ◽  
Vol 92 (11) ◽  
pp. 1012-1017 ◽  
Author(s):  
Amir Jaffer ◽  
Jason Hurbanek ◽  
Nariman Morra ◽  
Daniel Brotman

SummaryMany orthopaedic surgeons use warfarin to prevent venous thromboembolism (VTE) following hip or knee arthroplasty. Since warfarin’s antithrombotic effects are delayed, we hypothesized that early VTE (occurring within 5 days post-operatively) would be more common in arthroplasty patients receiving warfarin monotherapy compared to those receiving enoxaparin. We performed a secondary analysis of a case-control study examining risk factors for post-operative thrombosis in postmenopausal women. We defined cases as patients who were diagnosed with thrombosis within 5 days of surgery. Controls without thrombosis were matched with cases by age, surgeon, year of surgery and surgical joint. 84 women with early post-operative thrombosis (cases) were matched with 206 controls. 18 cases (21.4%) had been prescribed warfarin monotherapy, compared with 7 controls (3.4%). 58 (69.1%) cases and 195 (94.7%) controls had been prescribed subcutaneous enoxaparin 30 mg twice daily, starting 12-24 hours after surgery. The odds ratio for any early thrombosis in patients receiving warfarin as opposed to enoxaparin 30 mg twice daily was 8.6 (p<0.0001). For proximal thrombosis, the odds ratio was 11.3 (p<0.0001). Multivariate analysis did not alter these findings. Warfarin’s delayed antithrombotic effects may not provide adequateVTE prophylaxis in the immediate post-operative setting. We suggest caution in employing warfarin monotherapy following joint arthroplasty.


Haemophilia ◽  
2020 ◽  
Vol 26 (3) ◽  
pp. 513-519
Author(s):  
Hakan Kocaoğlu ◽  
Fabian Hennes ◽  
Hussein Abdelaziz ◽  
Nemandra A. Sandiford ◽  
Thorsten Gehrke ◽  
...  

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e043487
Author(s):  
Hao Luo ◽  
Kui Kai Lau ◽  
Gloria H Y Wong ◽  
Wai-Chi Chan ◽  
Henry K F Mak ◽  
...  

IntroductionDementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case–control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history.Methods and analysisWe will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared.Ethics and disseminationThis study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients’ records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities’ Action in Response to Dementia project (https://www.tip-card.hku.hk/).


2018 ◽  
Vol 33 (10) ◽  
pp. 3288-3296.e1 ◽  
Author(s):  
Takuro Ueno ◽  
Tamon Kabata ◽  
Yoshitomo Kajino ◽  
Daisuke Inoue ◽  
Takaaki Ohmori ◽  
...  

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