Iron metabolism and anemia may play an important role in multiple organ dysfunction syndrome in Coronavirus disease 2019 (COVID-19). We conducted a systematic review and meta-analysis to evaluate biomarkers of anemia and iron metabolism (hemoglobin, ferritin, transferrin, soluble transferrin receptor, hepcidin, haptoglobin, unsaturated iron-binding capacity, erythropoietin, free erythrocyte protoporphyrine, and erythrocyte indices) in patients diagnosed with COVID-19, and explored their prognostic value. Six bibliographic databases were searched up to August 3rd 2020. We included 189 unique studies, with data from 57,563 COVID-19 patients. Pooled mean hemoglobin and ferritin levels in COVID-19 patients across all ages were 129.7 g/L (95% Confidence Interval (CI), 128.51; 130.88) and 777.33 ng/mL (95% CI, 701.33; 852.77), respectively. Hemoglobin levels were lower with older age, higher percentage of subjects with diabetes, hypertension and overall comorbidities, and admitted to intensive care. Ferritin level increased with older age, increasing proportion of hypertensive study participants, and increasing proportion of mortality. Compared to moderate cases, severe COVID-19 cases had lower hemoglobin [weighted mean difference (WMD), − 4.08 g/L (95% CI − 5.12; − 3.05)] and red blood cell count [WMD, − 0.16 × 1012 /L (95% CI − 0.31; − 0.014)], and higher ferritin [WMD, − 473.25 ng/mL (95% CI 382.52; 563.98)] and red cell distribution width [WMD, 1.82% (95% CI 0.10; 3.55)]. A significant difference in mean ferritin levels of 606.37 ng/mL (95% CI 461.86; 750.88) was found between survivors and non-survivors, but not in hemoglobin levels. Future studies should explore the impact of iron metabolism and anemia in the pathophysiology, prognosis, and treatment of COVID-19.

ObjectivesCommunication breakdown is one of the main causes of adverse events in clinical routine, particularly in handover situations. The communication tool SBAR (situation, background, assessment and recommendation) was developed to increase handover quality and is widely assumed to increase patient safety. The objective of this review is to summarise the impact of the implementation of SBAR on patient safety.DesignA systematic review of articles published on SBAR was performed in PUBMED, EMBASE, CINAHL, Cochrane Library and PsycINFO in January 2017. All original research articles on SBAR fulfilling the following eligibility criteria were included: (1) SBAR was implemented into clinical routine, (2) the investigation of SBAR was the primary objective and (3) at least one patient outcome was reported.SettingA wide range of settings within primary and secondary care and nursing homes.ParticipantsA variety of heath professionals including nurses and physicians.Primary and secondary outcome measuresAspects of patient safety (patient outcomes) defined as the occurrence or incidence of adverse events.ResultsEight studies with a before–after design and three controlled clinical trials performed in different clinical settings met the inclusion criteria. The objectives of the studies were to improve team communication, patient hand-offs and communication in telephone calls from nurses to physicians. The studies were heterogeneous with regard to study characteristics, especially patient outcomes. In total, 26 different patient outcomes were measured, of which eight were reported to be significantly improved. Eleven were described as improved but no further statistical tests were reported, and six outcomes did not change significantly. Only one study reported a descriptive reduction in patient outcomes.ConclusionsThis review found moderate evidence for improved patient safety through SBAR implementation, especially when used to structure communication over the phone. However, there is a lack of high-quality research on this widely used communication tool.Trial registrationnone

Iron metabolism and anemia may play an important role in multiple organ dysfunction syndrome in Coronavirus disease 2019 (COVID-19). If confirmed, this has important implications for the more than 1.62 billion people estimated to have anemia globally. We conducted a systematic review and meta-analysis to evaluate biomarkers of anemia and iron metabolism (hemoglobin, ferritin, transferrin, soluble transferrin receptor, hepcidin, haptoglobin, unsaturated iron-binding capacity, erythropoietin, free erythrocyte protoporphyrine, and prevalence of anemia) in patients diagnosed with COVID-19, and explore their prognostic value. Six bibliographic databases were searched up to May 5th 2020. We included 56 unique studies, with data from 14,044 COVID-19 patients (59 years median age). Pooled mean hemoglobin and ferritin levels in COVID-19 patients across all ages were 130.41 g/L (95% Confidence Interval (CI), 128.42; 132.39) and 673.91 ng/mL (95% CI, 420.98; 926.84), respectively. Hemoglobin levels decreased with advancing age and increasing percentage of comorbid and critically ill patients, while levels of ferritin increased with increasing male proportion and mean hemoglobin levels. Compared to moderate cases, severe cases had lower pooled mean hemoglobin [weighted mean difference (WMD), -4.21 (95% CI -6.63; -1.78)] and higher ferritin [WMD, -730.55 ng/mL (95% CI 413.24; 1047.85)]. A significant difference in mean ferritin level of 1027.23 ng/mL (95% CI 819.53; 1234.94) was found between survivors and non-survivors, but not in hemoglobin levels. No studies provided information on anemia or other biomarkers of interest. Future studies should explore the impact of iron metabolism and anemia and in the pathophysiology, prognosis, and treatment of COVID-19.

Background Diagnostic errors occur frequently, especially in the emergency room. Estimates about the consequences of diagnostic error vary widely and little is known about the factors predicting error. Our objectives thus was to determine the rate of discrepancy between diagnoses at hospital admission and discharge in patients presenting through the emergency room, the discrepancies’ consequences, and factors predicting them. Methods Prospective observational clinical study combined with a survey in a University-affiliated tertiary care hospital. Patients’ hospital discharge diagnosis was compared with the diagnosis at hospital admittance through the emergency room and classified as similar or discrepant according to a predefined scheme by two independent expert raters. Generalized linear mixed-effects models were used to estimate the effect of diagnostic discrepancy on mortality and length of hospital stay and to determine whether characteristics of patients, diagnosing physicians, and context predicted diagnostic discrepancy. Results 755 consecutive patients (322 [42.7%] female; mean age 65.14 years) were included. The discharge diagnosis differed substantially from the admittance diagnosis in 12.3% of cases. Diagnostic discrepancy was associated with a longer hospital stay (mean 10.29 vs. 6.90 days; Cohen’s d 0.47; 95% confidence interval 0.26 to 0.70; P = 0.002) and increased patient mortality (8 (8.60%) vs. 25(3.78%); OR 2.40; 95% CI 1.05 to 5.5 P = 0.038). A factor available at admittance that predicted diagnostic discrepancy was the diagnosing physician’s assessment that the patient presented atypically for the diagnosis assigned (OR 3.04; 95% CI 1.33–6.96; P = 0.009). Conclusions Diagnostic discrepancies are a relevant healthcare problem in patients admitted through the emergency room because they occur in every ninth patient and are associated with increased in-hospital mortality. Discrepancies are not readily predictable by fixed patient or physician characteristics; attention should focus on context. Trial registration https://bmjopen.bmj.com/content/6/5/e011585 Electronic supplementary material The online version of this article (10.1186/s13049-019-0629-z) contains supplementary material, which is available to authorized users.

Diagnostic errors contribute substantially to preventable medical error. 1 Cognitive error is among the leading causes and mostly results from faulty data synthesis. 2 Furthermore, reflecting on their confidence does not prevent physicians from committing diagnostic errors. 1 Diagnostic decisions usually are not made by individual physicians working alone. Our aim was to investigate the effect of working in pairs as opposed to alone on diagnostic performance.

Combining independent decisions may substantially improve the quality of diagnoses in emergency medicine and may thus enhance patient safety.

Objectives: Treatment of epistaxis in patients on anticoagulants is challenging and associated with higher admission rates and longer hospital stays compared with patients without anticoagulation. However, there is little information about epistaxis in patients taking new direct oral anticoagulants such as rivaroxaban compared with patients on traditional vitamin K antagonists such as phenprocoumon.Design: Retrospective cohort study. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.