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Background and objectives: Preoperative anaemia is an independent risk factor for a higher morbidity and mortality, a longer hospitalization and increased perioperative transfusion rates. Managing preoperative anaemia is the first of three pillars of Patient Blood Management (PBM), a multidisciplinary concept to improve patient safety. While various studies provide medical information on (successful) anaemia treatment pathways, knowledge of organizational details of diagnosis and management of preoperative anaemia across Europe is scarce.
Materials and methods: To gain information on various aspects of preoperative anaemia management including organization, financing, diagnostics and treatment, we conducted a survey (74 questions) in ten hospitals from seven European nations within the PaBloE (Patient Blood Management in Europe) working group covering the year 2016.
Results: Organization and activity in the field of preoperative anaemia management were heterogeneous in the participating hospitals. Almost all hospitals had pathways for managing preoperative anaemia in place, however, only two nations had national guidelines. In six of the ten participating hospitals, preoperative anaemia management was organized by anaesthetists. Diagnostics and treatment focused on iron deficiency anaemia which, in most hospitals, was corrected with intravenous iron.
Conclusion: Implementation and approaches of preoperative anaemia management vary across Europe with a primary focus on treating iron deficiency anaemia. Findings of this survey motivated the hospitals involved to critically evaluate their practice and may also help other hospitals interested in PBM to develop action plans for diagnosis and management of preoperative anaemia.
Background: Approximately every third surgical patient is anemic. The most common form, iron deficiency anemia, results from persisting iron‐deficient erythropoiesis (IDE). Zinc protoporphyrin (ZnPP) is a promising parameter for diagnosing IDE, hitherto requiring blood drawing and laboratory workup.
Study design and methods: Noninvasive ZnPP (ZnPP‐NI) measurements are compared to ZnPP reference determination of the ZnPP/heme ratio by high‐performance liquid chromatography (ZnPP‐HPLC) and the analytical performance in detecting IDE is evaluated against traditional iron status parameters (ferritin, transferrin saturation [TSAT], soluble transferrin receptor–ferritin index [sTfR‐F], soluble transferrin receptor [sTfR]), likewise measured in blood. The study was conducted at the University Hospitals of Frankfurt and Zurich.
Results: Limits of agreement between ZnPP‐NI and ZnPP‐HPLC measurements for 584 cardiac and noncardiac surgical patients equaled 19.7 μmol/mol heme (95% confidence interval, 18.0–21.3; acceptance criteria, 23.2 μmol/mol heme; absolute bias, 0 μmol/mol heme). Analytical performance for detecting IDE (inferred from area under the curve receiver operating characteristics) of parameters measured in blood was: ZnPP‐HPLC (0.95), sTfR (0.92), sTfR‐F (0.89), TSAT (0.87), and ferritin (0.67). Noninvasively measured ZnPP‐NI yielded results of 0.90.
Conclusion: ZnPP‐NI appears well suited for an initial IDE screening, informing on the state of erythropoiesis at the point of care without blood drawing and laboratory analysis. Comparison with a multiparameter IDE test revealed that ZnPP‐NI values of 40 μmol/mol heme or less allows exclusion of IDE, whereas for 65 μmol/mol heme or greater, IDE is very likely if other causes of increased values are excluded. In these cases (77% of our patients) ZnPP‐NI may suffice for a diagnosis, while values in between require analyses of additional iron status parameters.
Background: Anemia is the most important complication during major surgery and transfusion of red blood cells is the mainstay to compensate for life threating blood loss. Therefore, accurate measurement of hemoglobin (Hb) concentration should be provided in real-time. Blood Gas Analysis (BGA) provides rapid point-of-care assessment using smaller sampling tubes compared to central laboratory (CL) services. Objective: This study aimed to investigate the accuracy of BGA hemoglobin testing as compared to CL services. Methods: Data of the ongoing LIBERAL-Trial (Liberal transfusion strategy to prevent mortality and anemia-associated ischemic events in elderly non-cardiac surgical patients, LIBERAL) was used to assess the bias for Hb level measured by BGA devices (ABL800 Flex analyzer®, GEM series® and RapidPoint 500®) and CL as the reference method. For that, we analyzed pairs of Hb level measured by CL and BGA within two hours. Furthermore, the impact of various confounding factors including age, gender, BMI, smoker status, transfusion of RBC, intraoperative hemodilution, and co-medication was elucidated. In order to ensure adequate statistical analysis, only data of participating centers providing more than 200 Hb pairs were used. Results: In total, three centers including 963 patients with 1,814 pairs of Hb measurements were analyzed. Mean bias was comparable between ABL800 Flex analyzer® and GEM series®: - 0.38 ± 0.15 g/dl whereas RapidPoint 500® showed a smaller bias (-0.09 g/dl) but greater median absolute deviation (± 0.45 g/dl). In order to avoid interference with different standard deviations caused by the different analytic devices, we focused on two centers using the same BGA technique (309 patients and 1,570 Hb pairs). A Bland-Altman analysis and LOWESS curve showed that bias decreased with smaller Hb values in absolute numbers but increased relatively. The smoker status showed the greatest reduction in bias (0.1 g/dl, p<0.001) whereas BMI (0.07 g/dl, p = 0.0178), RBC transfusion (0.06 g/dl, p<0.001), statins (0.04 g/dl, p<0.05) and beta blocker (0.03 g/dl, p = 0.02) showed a slight effect on bias. Intraoperative substitution of volume and other co-medications did not influence the bias significantly. Conclusion: Many interventions like substitution of fluids, coagulating factors or RBC units rely on the accuracy of laboratory measurement devices. Although BGA Hb testing showed a consistently stable difference to CL, our data confirm that BGA devices are associated with different bias. Therefore, we suggest that hospitals assess their individual bias before implementing BGA as valid and stable supplement to CL. However, based on the finding that bias decreased with smaller Hb values, which in turn are used for transfusion decision, we expect no unnecessary or delayed RBC transfusion, and no major impact on the LIBERAL trial performance.
Health economics of Patient Blood Management: a cost‐benefit analysis based on a meta‐analysis
(2019)
Background and Objectives: Patient Blood Management (PBM) is the timely application of evidence‐based medical and surgical concepts designed to improve haemoglobin concentration, optimize haemostasis and minimize blood loss in an effort to improve patient outcomes. The focus of this cost‐benefit analysis is to analyse the economic benefit of widespread implementation of a multimodal PBM programme.
Materials and Methods: Based on a recent meta‐analysis including 17 studies (>235 000 patients) comparing PBM with control care and data from the University Hospital Frankfurt, a cost‐benefit analysis was performed. Outcome data were red blood cell (RBC) transfusion rate, number of transfused RBC units, and length of hospital stay (LOS). Costs were considered for the following three PBM interventions as examples: anaemia management including therapy of iron deficiency, use of cell salvage and tranexamic acid. For sensitivity analysis, a Monte Carlo simulation was performed.
Results: Iron supplementation was applied in 3·1%, cell salvage in 65% and tranexamic acid in 89% of the PBM patients. In total, applying these three PBM interventions costs €129·04 per patient. However, PBM was associated with a reduction in transfusion rate, transfused RBC units per patient, and LOS which yielded to mean savings of €150·64 per patient. Thus, the overall benefit of PBM implementation was €21·60 per patient. In the Monte Carlo simulation, the cost savings on the outcome side exceeded the PBM costs in approximately 2/3 of all repetitions and the total benefit was €1 878 000 in 100·000 simulated patients.
Conclusion: Resources to implement a multimodal PBM concept optimizing patient care and safety can be cost‐effectively.