Background: There are no overviews of systematic reviews investigating haemoglobin thresholds for transfusion. This is important as the literature on transfusion thresholds has grown considerably in recent years. Our aim was to synthesise evidence from systematic reviews and meta-analyses of the effects of restrictive and liberal transfusion strategies on mortality. Methods: This was a systematic review of systematic reviews (overview). We searched MEDLINE, Embase, Web of Science Core Collection, PubMed, Google Scholar, and the Joanna Briggs Institute EBP Database, from 2008 to 2018. We included systematic reviews and meta-analyses of randomised controlled trials comparing mortality in patients assigned to red cell transfusion strategies based on haemoglobin thresholds. Two independent reviewers extracted data and assessed methodological quality. We assessed the methodological quality of included reviews using AMSTAR 2 and the quality of evidence pooled using an algorithm to assign GRADE levels. Results: We included 19 systematic reviews reporting 33 meta-analyses of mortality outcomes from 53 unique randomised controlled trials. Of the 33 meta-analyses, one was graded as high quality, 15 were moderate, and 17 were low. Of the meta-analyses presenting high- to moderate-quality evidence, 12 (75.0%) reported no statistically significant difference in mortality between restrictive and liberal transfusion groups and four (25.0%) reported significantly lower mortality for patients assigned to a restrictive transfusion strategy. We found few systematic reviews addressed clinical differences between included studies: variation was observed in haemoglobin threshold concentrations, the absolute between group difference in haemoglobin threshold concentration, time to randomisation (resulting in transfusions administered prior to randomisation), and transfusion dosing regimens. Conclusions: Meta-analyses graded as high to moderate quality indicate that in most patient populations no difference in mortality exists between patients assigned to a restrictive or liberal transfusion strategy. Trial registration: PROSPERO CRD42019120503

Summary: Our study investigated whether pre‐operative screening and treatment for anaemia and suboptimal iron stores in a patient blood management clinic is cost effective. We used outcome data from a retrospective cohort study comparing colorectal surgery patients admitted pre‐ and post‐implementation of a pre‐operative screening programme. We applied propensity score weighting techniques with multivariable regression models to adjust for differences in baseline characteristics between groups. Episode‐level hospitalisation costs were sourced from the health service clinical costing data system; the economic evaluation was conducted from a Western Australia Health System perspective. The primary outcome measure was the incremental cost per unit of red cell transfusion avoided. We compared 441 patients screened in the pre‐operative anaemia programme with 239 patients not screened; of the patients screened, 180 (40.8%) received intravenous iron for anaemia and suboptimal iron stores. The estimated mean cost of screening and treating pre‐operative anaemia was AU$332 (£183; US$231; €204) per screened patient. In the propensity score weighted analysis, screened patients were transfused 52% less red cell units when compared with those not screened (rate ratio = 0.48, 95%CI 0.36–0.63, p < 0.001). The mean difference in total screening, treatment and hospitalisation cost between groups was AU$3776 lower in the group screened (£2080; US$2629; €2325) (95%CI AU$1604–5947, p < 0.001). Screening elective patients pre‐operatively for anaemia and suboptimal iron stores reduced the number of red cell units transfused. It also resulted in lower total costs than not screening patients, thus demonstrating cost effectiveness.

The Classification of Hospital Acquired Diagnoses reporting system might seem complex, but this study shows that automating it can allow users to analyse complication rates by clinically meaningful factors, such as specialty or ward. Potential applications include assessing the benefits of patient safety initiatives and identifying ways of preventing lengthy hospital stays.

As defined by evidence-based medicine randomized controlled trials rank higher than observational studies in the hierarchy of clinical research. Accordingly, when assessing the effects of treatments on patient outcomes, there is a tendency to focus on the study method rather than also appraising the key elements of study design. A long-standing debate regarding findings of randomized controlled trials compared with those of observational studies, their strengths and limitations and questions regarding causal inference, has recently come into focus in relation to research assessing patient outcomes in transfusion medicine. Observational studies are seen to have limitations that are largely avoided with randomized controlled trials, leading to the view that observational studies should not generally be used to inform practice. For example, observational studies examining patient outcomes associated with blood transfusion often present higher estimates of adverse outcomes than randomized controlled trials. Some have explained this difference as being a result of observational studies not properly adjusting for differences between patients transfused and those not transfused. However, one factor often overlooked, likely contributing to these variances between study methods is different exposure criteria. Another common to both study methods is exposure dose, specifically, measuring units transfused during only a part of the patient’s hospital stay. When comparing the results of observational studies with randomized controlled trials assessing transfusion outcomes it is important that one consider not only the study method, but also the key elements of study design. Any study, regardless of its method, should focus on accurate measurement of the exposure and outcome variables of interest. Failure to do so may subject the study, regardless of its type, to bias and the need to interpret the results with caution.