For patients who donate blood for autologous use and undergo major orthopedic surgery, low basal hematocrit (Hct) is the major cause of allogeneic blood exposure. To determine whether recombinant human erythropoietin (rHuEPO) could increase autologous blood procurement and reduce allogeneic blood exposure, a prospective randomized study was conducted in 50 women undergoing total hip replacement who had basal Hct < 40 percent (0.40). Patients were randomly placed in three groups: those receiving placebo, those receiving 300 U of rHuEPO per kg, and those receiving 600 U of rHuEPO per kg every 3 to 4 days for 21 days. Oral iron (125-270 mg/day) was given; in the last 24 patients, 100 mg of iron saccharate was administered intravenously at each donation. At each visit, 350 mL of blood was collected if Hct was > or = 34 percent (0.34). Patients receiving rHuEPO donated a greater amount of blood for autologous use than did patients in the placebo group (4.5 +/- 1.1 vs. 2.8 +/- 0.6 units; p < 0.05) and received a significantly lower amount of allogeneic blood (1.2 +/- 1.4 vs. 0.4 +/- 0.8 units; p < 0.05). No difference between the effects of the two doses of rHuEPO was observed. Iron support was a critical factor in the efficacy of treatment. No untoward effects were observed. The rHuEPO emerged as a safe and effective treatment, with adequate iron support, by which to increase preoperative deposit of autologous blood and to reduce exposure to allogeneic blood for patients with low basal Hct.

Recombinant human erythropoietin is safe and effective in stimulating erythropoiesis, allowing preoperative donation of blood for autologous use, and reducing exposure to allogeneic blood for RA patients who are unable preoperatively to deposit blood because of anemia.

Background: COVID-19 causes major changes in day-to-day hospital activity due to its epidemiological characteristics and the clinical challenges it poses, especially in internal medicine wards. Therefore, it is necessary to understand and manage all of the implicated factors in order to maintain a high standard of care, even in sub-par circumstances. Methods: This was a three-phase, mixed-design study. Initially, the Delphi method allowed us to analyze the causes of poor outcomes in a cohort of an aggregate of Italian COVID-19 wards via an Ishikawa diagram. Then, for each retrieved item, a score was assigned according to a pros/cons, opportunities/threats system. Scores were also assigned according to potential value/perceived risk. Finally, the performances of MCs (Medicine-COVID-19 wards) and MCFs (Medicine-COVID-19-free: Internal Medicine wards) units were represented via a Barber’s nomogram. Results: MCFs hospitalized 790 patients (−23.90% compared to 2019 Internal Medicine admissions). The main risk factors for mortality were patients admitted from local facilities (+7%) and the presence of comorbidities (>3: 100%, ≥5: 24.7%). A total of 197 (25%) patients were treated with non-invasive ventilation (NIV). The most deaths (57.14%) occurred in patients admitted from local facilities. Conclusions: Medicine-COVID-19 wards show higher complexity and demand compared to non-COVID-19 ones and they are comparable to sub-intensive therapy wards. It is necessary to promote the use of NIV in such settings.

Clerical errors occurring during specimen collection, issue and transfusion of blood are the most common cause of AB0 incompatible transfusions. 40-50% of the transfusion fatalities result from errors in properly identifying the patient or the blood components. The frequency and type of errors observed, despite the implementation of measures to prevent them, suggests that errors are inevitable unless major changes in procedures are adopted. A fail-safe system, which physically prevents the possibility of error, was adopted in January 1993 and concurrently a quality improvement program was implemented to monitor any transfusion errors. Up to December 1994, 10,995 blood units (5,057 autologous and 5,938 allogeneic) were transfused to 3,231 patients. Seventy-one methodological errors(1/155 units) were observed, half of which were concentrated during the first 4 months of introducing the system. However the system detected and avoided four potentially fatal errors (1/2,748 units). Two cases involved the interchanging of recipient sample tubes, 1 case was due to patient misidentification and the other involved misidentification of blood units. In conclusion the system is effective in detecting otherwise undiscovered errors in transfusion practice and can prevent potential transfusion-associated fatalities caused by misidentification of blood units or recipients.

ObjectiveTo provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases.DesignUmbrella systematic review.Data sourcesPubMed, Scopus, Cochrane Library.Eligibility criteriaSystematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18–65 years old) population, published in English language.Data extraction and synthesisData were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.Study selection3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added.Study appraisalThe methodological quality of the included studies was assessed using the AMSTAR tool.Risk of bias in individual studiesRisk of Bias evaluation was carried out using the ROBIS tool.ResultsSixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone.LimitationsDue to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out.ConclusionsConsistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and employment history, social network relationships, income and education.PROSPERO registration numberCRD42018088012.