Aprotinin application has no negative effect on osseous implant integration: a biomechanical and histomorphometric investigation in a rat model

Optimizing Blood Loss and Management in Craniosynostosis Surgery: A Systematic Review of Outcomes Over the Last 40 Years

Surgical correction of craniosynostosis can involve significant blood loss. Rates of allogenic blood transfusion have been reported to approach 100%. Multiple interventions have been described to reduce blood loss and transfusion requirements. The aim of this study was to analyze various approaches over the last 4 decades to optimize blood loss and management during craniosynostosis surgery.

PRISMA guidelines for systematic reviews were followed. PubMed and Cochrane database searches identified studies analyzing approaches to minimizing blood loss or transfusion rate in craniosynostosis surgery.

Primary outcomes included rate or amount of allogenic or autologous blood transfusion, estimated blood loss (EBL), postoperative hemoglobin (Hg), or hematocrit (Hct) levels. Secondary outcomes were examined when reported.

Fifty-two studies met inclusion criteria. There was marked heterogeneity regarding design, inclusion criteria, surgical intervention, and endpoints. The majority of the studies were nonrandomized and noncomparative. Four studies analyzed erythropoietin (EPO), 6 analyzed various cell-saver (CS) technologies, 18 analyzed antifibrinolytics (tranexamic acid [TXA], aminocaproic acid [ACA], and aprotinin [APO]), 8 analyzed various alternatives, and 16 analyzed multimodal pathways & protocols. Some studies analyzed multiple approaches.

Although the majority of studies reviewed represent level III/IV evidence, several high-quality level I studies were identified and included. Level I evidence supported an improvement in blood outcomes by utilizing EPO, CS, and TXA, individually or in concert with one another. Thus, this review suggests that a multi-prong approach may be the most effective means to optimize blood loss and transfusion outcomes in craniosynostosis surgery.

Osseointegration Pharmacology: A Systematic Mapping Using Artificial Intelligence

Clinical performance of osseointegrated implants could be compromised by the medications taken by patients. The effect of a specific medication on osseointegration can be easily investigated using traditional systematic reviews. However, assessment of all known medications requires the use of evidence mapping methods. These methods allow assessment of complex questions, but they are very resource intensive when done manually. The objective of this study was to develop a machine learning algorithm to automatically map the literature assessing the effect of medications on osseointegration. Datasets of articles classified manually were used to train a machine-learning algorithm based on Support Vector Machines. The algorithm was then validated and used to screen 599,604 articles identified with an extremely sensitive search strategy. The algorithm included 281 relevant articles that described the effect of 31 different drugs on osseointegration. This approach achieved an accuracy of 95%, and compared to manual screening, it reduced the workload by 93%. The systematic mapping revealed that the treatment outcomes of osseointegrated medical devices could be influenced by drugs affecting homeostasis, inflammation, cell proliferation and bone remodeling. The effect of all known medications on the performance of osseointegrated medical devices can be assessed using evidence mappings executed with highly accurate machine learning algorithms.