![]() ![]() The FCM group reported fewer infections during hospitalisation. Patients who received ABTs appeared to have a longer hospital stay. The preoperative Hb value improved when FMC was used. The economic impact of using FCM was around 19%. Economic analysis showed that FCM could reduce allogenic blood products consumption and the associated costs. However, there were fewer nosocomial infections in the FCM group (11.9% versus 21.2%) and mortality was higher in the transfusion group (21.2% versus 4.2%). Regarding the clinical outcomes of nosocomial infection and mortality, there was no evidence that the rate of infection or mortality differed in each group (p = 0.075 and p = 0.243, respectively). Concerning the length of hospital stay, the group administered with ABTs had a longer hospital stay (p < 0.001). Hb values tended to decrease, with 44.1% of patients moving from mild anaemia before transfusion to moderate anaemia in the postoperative period. In the ABT group, there were significant differences between pre- and postoperative Hb levels (p < 0.001). There were significant differences (p < 0.001) before and after correction of preoperative anaemia and/or iron deficiency with FCM in Hb, serum ferritin and transferrin saturation rate (TS). In the FCM preoperative cohort, there was an increase in patients with normal preoperative Hb, from 14.4 to 45.7%, before and after FCM, respectively, a decrease from 31.7 to 9.6% in moderate anaemia and no cases of severe anaemia after FCM administration, while 7.7% of patients were severely anaemic before FCM treatment. A total of 405 patients from seven hospitals were included 108 (26.7%) underwent FCM preoperatively and 197 (48.6%) were transfused with ABTs on demand. Those patients ended up being treated with ABTs on demand. Therefore, the existence of Iron Deficiency Anaemia (IDA) or Iron Deficiency (ID) without anaemia was not early detected, and there was no possibility of treating these patients with iron in order to optimise their Hb and/or iron stores. ![]() Before the implementation of PBM in Portugal, most patients did not undergo preoperative laboratory evaluation with blood count and iron kinetics. In this work, only the first pillar of the PBM model issue by Directorate-General for Health (DGS) was evaluated, which involves optimising Hb in the preoperative period with iron treatment if it’s necessary/indicated. This was an observational study conducted in a retrospective and multicentre cohort with adults from elective orthopaedic, cardiac and colorectal surgeries, treated according to local standards of PBM with allogeneic blood product transfusions (ABTs) on demand and with FCM to correct iron deficiency with or without anaemia. Direct Marketing – Easier access to pre-built models, better ways to score data, and access to customer information in Salesforce.Ferric carboxymaltose (FCM) can be used in Patient Blood Management (PBM) to promote the optimization of preoperative haemoglobin (Hb), which aims to minimise the use of allogeneic blood components and improve clinical outcomes, with better cost-effectiveness.Default Measurement Level – Automatically sets your measurement level during analysis in IBM SPSS Statistics Base and modules.Syntax Editor – More than a dozen performance and ease-of-use enhancements for writing syntax in IBM SPSS Statistics Base and modules.Automatic Linear Models – Build powerful linear models in an easy, automated way in IBM SPSS Statistics Base and IBM SPSS Statistics Server.Statistics portal – Provide customized, Web-based analysis capabilities to colleagues and customers in IBM SPSS Statistics Server.Faster Performance - For compiled transformations in IBM SPSS Statistics Server and up to 200% performance gain for generating pivot tables in IBM SPSS Statistics Base.Generalized Linear Mixed Models – Create more accurate models for predicting non-linear outcomes in the Advanced Statistics module.With major performance enhancements, improved procedures, and even more ease-of-use features, IBM SPSS Statistics 19 speeds and simplifies your analytic tasks so you get more done in less time. ![]()
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