Geographical variations in the correlates of blood donor turnout rates: An investigation of Canadian metropolitan areas

<p>Abstract</p> <p>Background</p> <p>Like other countries, Canada's population is aging, and the implications of this demographic change need to be better understood from the perspective of blood supply. Analysis of donor data will help to identify systematic patterns of donation and its correlates.</p> <p>Data</p> <p>Geo-coded blood donor and donor clinic data are provided by Canadian Blood Services. Blood donor data is provided for the fiscal year 2006-2007 indicating the total number of donors for each Canadian postal code, excluding the province of Québec. Potential correlates of blood donation are selected based on social and economic characteristics, as well as descriptors of city size and geographical location in the urban hierarchy measures of accessibility, and capacity of donor clinics.</p> <p>Methods</p> <p>Data is aggregated to <it>n </it>= 3,746 census tracts in 40 Census Metropolitan Areas (CMA) across the country. The number of donors per population in a census tract is regressed against the set of potential donation correlates. Autocorrelation is tested for and results adjusted to provide parsimonious models.</p> <p>Results</p> <p>A number of factors are found to influence donation across the country, including the proportion of younger residents, English ability, proportion of people with immigrant status, higher education, and a population-based measure of accessibility.</p> <p>Conclusion</p> <p>While a number of correlates of blood donation are observed across Canada, important contextual effects across metropolitan areas are highlighted. The paper concludes by looking at policy options that are aimed toward further understanding donor behaviour.</p

Perioperative oral eltrombopag versus intravenous immunoglobulin in patients with immune thrombocytopenia:a non-inferiority, multicentre, randomised trial

Background: Patients with immune thrombocytopenia are at risk of bleeding during surgery, and intravenous immunoglobulin is commonly used to increase the platelet count. We aimed to establish whether perioperative eltrombopag was non-inferior to intravenous immunoglobulin. Methods: We did a randomised, open-label trial in eight academic hospitals in Canada. Patients were aged at least 18 years, with primary or secondary immune thrombocytopenia and platelet counts less than 100 × 109 cells per L before major surgery or less than 50 × 109 cells per L before minor surgery. Previous intravenous immunoglobulin within 2 weeks or thrombopoietin receptor agonists within 4 weeks before randomisation were not permitted. Patients were randomly assigned to receive oral daily eltrombopag 50 mg from 21 days preoperatively to postoperative day 7 or intravenous immunoglobulin 1 g/kg or 2 g/kg 7 days before surgery. Eltrombopag dose adjustments were allowed weekly based on platelet counts. The randomisation sequence was generated by a computerised random number generator, concealed and stratified by centre and surgery type (major or minor). The central study statistician was masked to treatment allocation. The primary outcome was achievement of perioperative platelet count targets (90 × 109 cells per L before major surgery or 45 × 109 cells per L before minor surgery) without rescue treatment. We did intention-to-treat and per-protocol analyses using an absolute non-inferiority margin of –10%. This trial is registered with ClinicalTrials.gov, NCT01621204. Findings: Between June 5, 2013, and March 7, 2019, 92 patients with immune thrombocytopenia were screened, of whom 74 (80%) were randomly assigned: 38 to eltrombopag and 36 to intravenous immunoglobulin. Median follow-up was 50 days (IQR 49–55). By intention-to-treat analysis, perioperative platelet targets were achieved for 30 (79%) of 38 patients assigned to eltrombopag and 22 (61%) of 36 patients assigned to intravenous immunoglobulin (absolute risk difference 17·8%, one-sided lower limit of the 95% CI 0·4%; pnon-inferiority=0·005). In the per-protocol analysis, perioperative platelet targets were achieved for 29 (78%) of 37 patients in the eltrombopag group and 20 (63%) of 32 in the intravenous immunoglobulin group (absolute risk difference 15·9%, one-sided lower limit of the 95% CI –2·1%; pnon-inferiority=0·009). Two serious adverse events occurred in the eltrombopag group: one treatment-related pulmonary embolism and one vertigo. Five serious adverse events occurred in the intravenous immunoglobulin group (atrial fibrillation, pancreatitis, vulvar pain, chest tube malfunction and conversion to open splenectomy); all were related to complications of surgery. No treatment-related deaths occurred. Interpretation: Eltrombopag is an effective alternative to intravenous immunoglobulin for perioperative treatment of immune thrombocytopenia. However, treatment with eltrombopag might increase risk of thrombosis. The decision to choose one treatment over the other will depend on patient preference, resource limitations, cost, and individual risk profiles. Funding: GlaxoSmithKline and Novartis

Author Correction: Convalescent plasma for hospitalized patients with COVID-19: an open-label, randomized controlled trial (Nature Medicine, (2021), 27, 11, (2012-2024), 10.1038/s41591-021-01488-2)

In the version of this Article initially published, there was an omission in the member list for the CONCOR-1 Study Group. Valérie Arsenault (Héma-Québec, Montreal, Quebec, Canada) has now been included in the CONCOR-1 Study Group in the online version of the article

Do expert assessments converge? An exploratory case study of evaluating and managing a blood supply risk

Abstract Background Examining professional assessments of a blood product recall/withdrawal and its implications for risk and public health, the paper introduces ideas about perceptions of minimal risk and its management. It also describes the context of publicly funded blood transfusion in Canada and the withdrawal event that is the basis of this study. Methods Interviews with 45 experts from administration, medicine, blood supply, laboratory services and risk assessment took place using a multi-level sampling framework in the aftermath of the recall. These experts either directly dealt with the withdrawal or were involved in the management of the blood supply at the national level. Data from these interviews were coded in NVivo for analysis and interpretation. Analytically, data were interpreted to derive typifications to relate interview responses to risk management heuristics. Results While all those interviewed agreed on the importance of patient safety, differences in the ways in which the risk was contextualized and explicated were discerned. Risk was seen in terms of patient safety, liability or precaution. These different risk logics are illustrated by selected quotations. Conclusions Expert assessments did not fully converge and it is possible that these different risk logics and discourses may affect the risk management process more generally, although not necessarily in a negative way. Patient safety is not to be compromised but management of blood risk in publicly funded systems may vary. We suggest ways of managing blood risk using formal and safety case approaches.</p

Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models

Platelet products are both expensive and have very short shelf lives. As usage rates for platelets are highly variable, the effective management of platelet demand and supply is very important yet challenging. The primary goal of this paper is to present an efficient forecasting model for platelet demand at Canadian Blood Services (CBS). To accomplish this goal, four different demand forecasting methods, ARIMA (Auto Regressive Moving Average), Prophet, lasso regression (least absolute shrinkage and selection operator) and LSTM (Long Short-Term Memory) networks are utilized and evaluated. We use a large clinical dataset for a centralized blood distribution centre for four hospitals in Hamilton, Ontario, spanning from 2010 to 2018 and consisting of daily platelet transfusions along with information such as the product specifications, the recipients' characteristics, and the recipients' laboratory test results. This study is the first to utilize different methods from statistical time series models to data-driven regression and a machine learning technique for platelet transfusion using clinical predictors and with different amounts of data. We find that the multivariate approaches have the highest accuracy in general, however, if sufficient data are available, a simpler time series approach such as ARIMA appears to be sufficient. We also comment on the approach to choose clinical indicators (inputs) for the multivariate models