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Article type: Research Article
Authors: Alassaf, Nabila; * | Reitsma, Johannes B.b
Affiliations: [a] Department of Orthopaedic Surgery, Dr Sulaiman Al-Habib Medical Group, Riyadh, Saudi Arabia | [b] Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht, The Netherlands
Correspondence: [*] Corresponding author: Nabil Alassaf, Department of Orthopaedic Surgery, Dr Sulaiman Al-Habib Medical Group, P.O. Box 2000, Riyadh 11393, Saudi Arabia. E-mail: [email protected].
Abstract: BACKGROUND: Blood transfusion is a common practice, but it is not without cost and risk. A model that predicts the risk of blood transfusion could guide informed preoperative blood ordering and use of blood loss preventive measures. OBJECTIVE: This study aimed to develop a prediction model of blood transfusion in children with developmental dysplasia of the hip (DDH) undergoing surgery. METHODS: A retrospective cohort of DDH patients from 2008 to 2017. The included patients were between 1 to 9 years old, underwent anterior open reduction and/or acetabular osteotomy with and without femoral shortening. The unit of analysis was undergoing such an operation. The outcome was allogenic blood transfusion. Potential predictors were age, sex, body mass index (BMI), international hip dysplasia institute grade, type of surgery, intervention bilaterally during the same operative session, primary versus reoperation surgery, the addition of regional anaesthesia, preoperative haemoglobin and hematocrit. RESULTS: A total of 524 patients who met the inclusion criteria underwent 721 operative sessions. The median age (interquartile range) at operation was 23 (20–33) months. The blood transfusion rate was 11.8%. Independent predictors were lower preoperative haemoglobin, reduced BMI, simultaneous bilateral surgery and the extent of surgical treatment. CONCLUSIONS: The developed prognostic model allows prediction for blood transfusion in DDH patients undergoing surgery.
Keywords: Children, hip dislocation, hip dysplasia, blood transfusion, surgery, decision modeling
DOI: 10.3233/THC-181547
Journal: Technology and Health Care, vol. 27, no. 3, pp. 327-334, 2019
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