Volume 9, Issue 2

We provide here a pooled analysis of accuracy of Fujirebio Lumipulse SARS-CoV-2 Antigen chemiluminescent immunoassay for diagnosing acute SARS-CoV-2 infections. An electronic search was conducted in Scopus and Medline with the keywords “Lumipulse” AND “antigen” AND “SARS-CoV-2” or “COVID-19”, up to January 21, 2022, for identifying clinical investigations (minimum sample size ≥100) where diagnostic accuracy of Lumipulse G SARS-CoV-2 Ag was tested against reference molecular techniques. All studies which allowed to construct a 2 × 2 table were included in a pooled analysis. A final number of 21 studies, totalling 17,648 nasopharyngeal and 8538 saliva specimens, were finally included. The pooled diagnostic sensitivity and specificity in nasopharyngeal swabs were 0.80 (95%CI, 0.78–0.81) and 0.98 (95%CI, 0.97–0.98), respectively, whilst the area under the curve and agreement were 0.980 (95%CI, 0.973–0.986) and 94.9%, respectively. In the twelve studies which used the fixed 1.34 pg/mL currently recommended manufacturer’s threshold, the diagnostic accuracy remained unvaried. In saliva samples, the pooled diagnostic sensitivity and specificity were 0.75 (95%CI, 0.71–0.75) and 1.00 (95%CI, 0.99–1.00), respectively, whilst the area under the curve and were 0.976 (95%CI, 0.969–0.984) and 98.4%, respectively. In the five studies which used the fixed 0.67 pg/mL currently recommended manufacturer’s threshold, the diagnostic accuracy remained unvaried. In conclusion, Lumipulse G SARS-CoV-2 Ag assay demonstrates good diagnostic sensitivity and specificity, thus representing a valuable complementary and integrative option to molecular testing for SARS-CoV-2 in the current pandemic.

Objectives We provide a systematic literature review on tissue miRNAs in patients with RCC to evaluate and summarize their usefulness as prognostic markers. We undertook a systematic search for articles in English using the PubMed-Medline database from January 2010 to December 2020. Studies were identified and selected according to the PRISMA criteria and the PICO methodology. The population consisted of RCC patients undergoing nephrectomy and the main outcome of interest was recurrence-free survival (RFS). Only studies providing hazard ratios (HRs) from multivariate or univariate analyzes with corresponding 95% confidence intervals (CI) and/or area under the curve (AUC) were considered. Content All nine included studies (1,541 patients) analyzed the relationship between tissue miRNA expression levels (up or downregulated) and RFS. Some of these found that the methylation status of miR-9-1, miR-9-3 and miR-124 was associated with a high risk of relapse. Moreover, miR-200b overexpression was associated with OS. MiR-210 overexpression indicated a shorter OS than those who were miR-210 negative. Finally, patients with high miR-125b expression had shorter cancer-specific survival (CSS) than those with low expression; similarly, patients with low miR-126 expression also had shorter CSS time. Summary and outlook Several studies tested the usefulness of specific miRNAs to predict RCC recurrence. Some of them showed a fair accuracy and strong relationship between specific miRNA over or under-expression and survival outcomes. However, results from these studies are preliminary and miRNAs use in routine clinical practice is still far to come.

Objectives Improving diagnosis-related education in the health professions has great potential to improve the quality and safety of diagnosis in practice. Twelve key diagnostic competencies have been delineated through a previous initiative. The objective of this project was to identify the next steps necessary for these to be incorporated broadly in education and training across the health professions. Methods We focused on medicine, nursing, and pharmacy as examples. A literature review was conducted to survey the state of diagnosis education in these fields, and a consensus group was convened to specify next steps, using formal approaches to rank suggestions. Results The literature review confirmed initial but insufficient progress towards addressing diagnosis-related education. By consensus, we identified the next steps necessary to advance diagnosis education, and five required elements relevant to every profession: 1) Developing a shared, common language for diagnosis, 2) developing the necessary content, 3) developing assessment tools, 4) promoting faculty development, and 5) spreading awareness of the need to improve education in regard to diagnosis. Conclusions The primary stakeholders, representing education, certification, accreditation, and licensure, in each profession must now take action in their own areas to encourage, promote, and enable improved diagnosis, and move these recommendations forward.

Medical error is now recognized as one of the leading causes of death in the United States. Of the medical errors, diagnostic failure appears to be the dominant contributor, failing in a significant number of cases, and associated with a high degree of morbidity and mortality. One of the significant contributors to diagnostic failure is the cognitive performance of the provider, how they think and decide about the process of diagnosis. This thinking deficit in clinical reasoning, referred to as a mindware gap, deserves the attention of medical educators. A variety of specific approaches are outlined here that have the potential to close the gap.

There is consensus that clinical reasoning (CR) is crucial for increasing the value of diagnosis, medical decision-making and error reduction. These skills should be developed throughout medical education, starting with undergraduate study. International guidance provides principles for CR curricula but interventions to date, are short term in nature. In this report, we describe the creation of a longitudinal, spiral CR curriculum within a large UK medical school programme (2500 students). A working group drove systematic evidence-based reform of existing structures. We utilised recognised models for curriculum development and mapping, relating learning outcomes to competency frameworks. Application of multiple teaching methodologies, rooted in enquiry-based learning and reported in CR literature, encourage metacognition for information-processing and illness script development. Development of CR is emphasised with recurrent, progressive learning opportunities, each stage purposefully building upon previous experiences. Formative and summative assessment approaches to drive learning, encouraging students’ ability to apply and articulate CR, is constructed via Miller’s Prism of Clinical Competence. Implementation of pedagogy is contingent on faculty development. Whilst many clinicians practice sound CR, the ability to articulate it to students is often a novel skill. Engagement in faculty development was strengthened through cross-institutional recognition of teaching workload and flexibility of delivery. We report lessons learned from the implementation phase and plans for measuring impact.

With the ongoing coronavirus disease 2019 (COVID-19) pandemic continuing worldwide, mass screening of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection is a cornerstone of strategies for limiting viral spread within communities. Although mass screening of body temperature with handheld, non-contact infrared thermometers and thermal imagine scanners is now widespread in a kaleidoscope of social and healthcare settings for the purpose of detecting febrile individuals bearing SARS-CoV-2 infection, this strategy carries some drawbacks, which will be highlighted and discussed in this article. These caveats basically include high rate of asymptomatic SARS-CoV-2 infections, the challenging definition of “normal” body temperature, variation of measured values according to the body district, false negative cases due to antipyretics, device inaccuracy, impact of environmental temperature, along with the low specificity of this symptom for screening COVID-19 in patients with other febrile conditions. Some pragmatic suggestions will also be endorsed for increasing accuracy and precision of mass screening of body temperature. These encompass the regular assessment of body temperature (possibly twice) with validated devices, which shall be constantly monitored over time and used following manufacturer’s instructions, the definition of a range of “normal” body temperatures in the local population, patients interrogation on usual body temperature, measurement standardization of one body district, allowance of sufficient environmental acclimatization before temperature check, integration with contact history and other clinical information, along with exclusion of other causes of increased body temperature. We also endorse the importance of individual and primary care physician’s regular and repeated check of personal body temperature.

Objectives To use a case review approach for investigating the types of cognitive error identifiable following a complicated patient admission with a multisystem disorder in an acute care setting where diagnosis was difficult and delayed. Methods A case notes review was undertaken to explore the cognitive factors associated with diagnostic error in the case of an 18-year-old male presenting acutely unwell with myalgia, anorexia and vomiting. Each clinical interaction was analysed and identified cognitive factors were categorised using a framework developed by Graber et al. Results Cognitive factors resulting in diagnostic errors most frequently occurred within the first five days of hospital admission. The most common were premature closure; failure to order or follow up an appropriate test; over-reliance on someone else’s findings or opinion; over-estimating or underestimating usefulness or salience of a finding, and; ineffective, incomplete or faulty history and physical examination. Cognitive factors were particularly frequent around transitions of care and patient transfers from one clinical area to another. The presence of senior staff did not necessarily mitigate against diagnostic error from cognitive factors demonstrated by junior staff or diagnostic errors made out-of-hours. Conclusions Cognitive factors are a significant cause of diagnostic error within the first five days after admission, especially around transitions of care between different clinical settings and providers. Medical education interventions need to ensure clinical reasoning training supports individuals and teams to develop effective strategies for mitigating cognitive factors when faced with uncertainty over complex patients presenting with non-specific symptoms in order to reduce diagnostic error.

Objectives Experienced physicians must rapidly identify ill pediatric patients. We evaluated the ability of an illness rating score (IRS) to predict admission to a pediatric hospital and explored the underlying clinical reasoning of the gestalt assessment of illness. Methods We used mixed-methods to study pediatric emergency medicine physicians at an academic children’s hospital emergency department (ED). Physicians rated patients’ illness severity with the IRS, anchored by 0 (totally well) and 10 (critically ill), and shared their rationale with concurrent think-aloud responses. The association between IRS and need for hospitalization, respiratory support, parenteral antibiotics, and resuscitative intravenous (IV) fluids were analyzed with mixed effects linear regression. Area under the curve (AUC) receiver operator characteristic (ROC) curve and test characteristics at different cut-points were calculated for IRS as a predictor of admission. Think-aloud responses were qualitatively analyzed via inductive process. Results A total of 141 IRS were analyzed (mean 3.56, SD 2.30, range 0–9). Mean IRS were significantly higher for patients requiring admission (4.32 vs. 3.13, p<0.001), respiratory support (6.15 vs. 3.98, p = 0.033), IV fluids (4.53 vs. 3.14, p < 0.001), and parenteral antibiotics (4.68 vs. 3.32, p = 0.009). AUC for IRS as a predictor of admission was 0.635 (95% CI: 0.534–0.737). Analysis of 95 think-aloud responses yielded eight categories that describe the underlying clinical reasoning. Conclusions Rapid assessments as captured by the IRS differentiated pediatric patients who required admission and medical interventions. Think-aloud responses for the rationale for rapid assessments may form the basis for teaching the skill of identifying ill pediatric patients.

Objectives To compare pediatric emergency clinicians’ attitudes toward three feedback modalities and assess clinicians’ case-based feedback preferences. Methods Electronic survey sent to pediatric emergency medicine (PEM) physicians and fellows; general pediatricians; and advanced practice providers (APPs) with nine questions exploring effectiveness and emotional impact of three feedback modalities: case-based feedback, bounce-back notifications, and biannual performance reports. Additional questions used a four-point ordinal agreement response scale and assessed clinicians’ attitudes toward case review notification, case-based feedback preferences, and emotional support. Survey responses were compared by feedback modality using Pearson’s chi-squared. Results Of 165 eligible providers, 93 (56%) responded. Respondents agreed that case-based feedback was timely (81%), actionable (75%), prompted reflection on decision-making (92%), prompted research on current clinical practice (53%), and encouraged practice change (58%). Pediatric Emergency Care Applied Research Network (PECARN) performance reports scored the lowest on all metrics except positive feedback. No more than 40% of providers indicated that any feedback modality provided emotional support. Regarding case-based feedback, 88% of respondents desired email notification before case review and 88% desired feedback after case review. Clinicians prefer receiving feedback from someone with similar or more experience/training. Clinicians receiving feedback desire succinctness, supporting evidence, consistency, and sensitive delivery. Conclusions Case-based feedback scored highest of the three modalities and is perceived to be the most likely to improve decision-making and promote practice change. Most providers did not perceive emotional support from any feedback modality. Emotional safety warrants purposeful attention in feedback delivery. Critical components of case-based feedback include succinctness, supporting evidence, consistency, and sensitive delivery.

Objectives We sought to understand the knowledge, attitudes, and beliefs of emergency medicine (EM) physicians towards non-specific neurological conditions and the use of clinical decision support (CDS) to improve diagnostic accuracy. Methods We conducted semi-structured interviews of EM physicians at four emergency departments (EDs) affiliated with a single US healthcare system. Interviews were conducted until thematic saturation was achieved. Conventional content analysis was used to identify themes related to EM physicians’ perspectives on acute diagnostic neurology; directed content analysis was used to explore views regarding CDS. Each interview transcript was independently coded by two researchers using an iteratively refined codebook with consensus-based resolution of coding differences. Results We identified two domains regarding diagnostic safety: (1) challenges unique to neurological complaints and (2) challenges in EM more broadly. Themes relevant to neurology included: (1) knowledge gaps and uncertainty, (2) skepticism about neurology, (3) comfort with basic as opposed to detailed neurological examination, and (4) comfort with non-neurological diseases. Themes relevant to diagnostic decision making in the ED included: (1) cognitive biases, (2) ED system/environmental issues, (3) patient barriers, (4) comfort with diagnostic uncertainty, and (5) concerns regarding diagnostic error identification and measurement. Most participating EM physicians were enthusiastic about the potential for well-designed CDS to improve diagnostic accuracy for non-specific neurological complaints. Conclusions Physicians identified diagnostic challenges unique to neurological diseases as well as issues related more generally to diagnostic accuracy in EM. These physician-reported issues should be accounted for when designing interventions to improve ED diagnostic accuracy.

Objectives Since the widespread adoption of electronic medical records (EMRs), medical scribes have been increasingly utilized in emergency department (ED) settings to offload the documentation burden of emergency physicians (EPs). Scribes have been shown to increase EP productivity and satisfaction; however, little is known about their effects on the EP’s diagnostic process. We aimed to assess what effect, if any, scribes have on EP diagnostic test ordering and their documentation of differential diagnoses. Methods We conducted a retrospective cohort study utilizing a chart review to compare diagnostic practices of EPs working both with and without scribes. We analyzed the number of laboratory and radiologic diagnostic studies ordered per encounter as well as characteristics of differential diagnosis documentation. Results Scribes did not affect laboratory studies ordered per encounter (mean 6.31 by scribes vs. 7.35 by EPs, difference −1.04; 95% confidence interval [CI] −2.34 to 0.26) or radiologic studies ordered per encounter (mean 1.49 by scribes vs. 1.39 by EPs, difference 0.10; 95% CI −0.15 to 0.35). Scribes did not affect the frequency of documenting a differential diagnosis or the number of diagnoses considered in each differential, but they were associated with higher word counts in EP differentials (mean 72.29 by scribes vs. 50.00 by EPs, mean difference 22.79; 95% CI 6.77 to 38.81). Conclusions Scribe use does not appear to affect EP diagnostic test ordering but may have a small effect on their documentation of differential diagnoses.

Objectives Identification of diagnostic error is complex and mostly relies on expert ratings, a severely limited procedure. We developed a system that allows to automatically identify diagnostic labelling error from diagnoses coded according to the international classification of diseases (ICD), often available as routine health care data. Methods The system developed (index test) was validated against rater based classifications taken from three previous studies of diagnostic labeling error (reference standard). The system compares pairs of diagnoses through calculation of their distance within the ICD taxonomy. Calculation is based on four different algorithms. To assess the concordance between index test and reference standard, we calculated the area under the receiver operating characteristics curve (AUROC) and corresponding confidence intervals. Analysis were conducted overall and separately per algorithm and type of available dataset. Results Diagnoses of 1,127 cases were analyzed. Raters previously classified 24.58% of cases as diagnostic labelling errors (ranging from 12.3 to 87.2% in the three datasets). AUROC ranged between 0.821 and 0.837 overall, depending on the algorithm used to calculate the index test (95% CIs ranging from 0.8 to 0.86). Analyzed per type of dataset separately, the highest AUROC was 0.924 (95% CI 0.887–0.962). Conclusions The trigger system to automatically identify diagnostic labeling error from routine health care data performs excellent, and is unaffected by the reference standards’ limitations. It is however only applicable to cases with pairs of diagnoses, of which one must be more accurate or otherwise superior than the other, reflecting a prevalent definition of a diagnostic labeling error.

Objectives To explore how patients describe their diagnoses following Emergency Department (ED) discharge, and how this compares to electronic medical record (EMR) documentation. Methods We conducted a cohort study of patients discharged from three EDs. Patients completed questionnaires regarding their understanding of their diagnosis. Inclusion criteria: adult ED patients aged 18 and older seen within the last seven days. We independently compared patient-reported new diagnoses following discharge to EMR-documented diagnoses regarding diagnostic content (identical, insignificantly different, different, not enough detail) and the level of technical language in diagnostic description (technical, semi-technical, lay). Results The majority of participants (n=95 out of 137) reported receiving a diagnosis and stated the given diagnosis. Of those who reported their diagnosis, 66%, were females (n=62), the average age was 43 (SD 16), and a fourth (n=24) were Black and 66% (n=63) were white. The majority (84%) described either the same or an insignificantly different diagnosis. For 11% the patient-reported diagnosis differed from the one documented. More than half reported their diagnosis using semi-technical (34%) or technical language (26%), and over a third (40%) described their diagnosis in lay language. Conclusions Patient-reported diagnoses following ED discharge had moderate agreement with EMR-documented diagnoses. Findings suggest that patients might reproduce verbatim semi-technical or technical diagnoses they received from clinicians, but not fully understood what the diagnosis means for them.

Objectives Medical expertise manifests itself by the ability of a physician to rapidly diagnose patients. How this expertise develops from a neural-activation perspective is not well understood. The objective of the present study was to investigate practice-related activation changes in the prefrontal cortex (PFC) as medical students learn to diagnose chest X-rays. Methods The experimental paradigm consisted of a learning and a test phase. During the learning phase, 26 medical students were trained to diagnose four out of eight chest X-rays. These four cases were presented repeatedly and corrective feedback was provided. During the test phase, all eight cases were presented together with near- and far-transfer cases to examine whether participants’ diagnostic learning went beyond simple rote recognition of the trained X-rays. During both phases, participants’ PFC was scanned using functional near-infrared spectroscopy. Response time and diagnostic accuracy were recorded as behavioural indicators. One-way repeated measures ANOVA were conducted to analyse the data. Results Results revealed that participants’ diagnostic accuracy significantly increased during the learning phase (F=6.72, p<0.01), whereas their response time significantly decreased (F=16.69, p<0.001). Learning to diagnose chest X-rays was associated with a significant decrease in PFC activity (F=33.21, p<0.001) in the left dorsolateral prefrontal cortex, the orbitofrontal area, the frontopolar area and the frontal eye field. Further, the results of the test phase indicated that participants’ diagnostic accuracy was significantly higher for the four trained cases, second highest for the near-transfer, third highest for the far-transfer cases and lowest for the untrained cases (F=167.20, p<0.001) and response time was lowest for the trained cases, second lowest for the near-transfer, third lowest for the far-transfer cases and highest for the untrained cases (F=9.72, p<0.001). In addition, PFC activity was lowest for the trained and near-transfer cases, followed by the far-transfer cases and highest for the untrained cases (F=282.38, p<0.001). Conclusions The results suggest that learning to diagnose X-rays is associated with a significant decrease in PFC activity. In terms of dual-process theory, these findings support the notion that students initially rely more on slow analytical system-2 reasoning. As expertise develops, system-2 reasoning transitions into faster and automatic system-1 reasoning.

Objectives Diagnostic error is a critical patient safety issue that can be addressed in part through teaching clinical reasoning. Medical schools with clinical reasoning curricula tend to emphasize general reasoning concepts (e.g., differential diagnosis generation). Few published curricula go beyond teaching the steps in the diagnostic process to address how students should structure their knowledge to optimize diagnostic performance in future clinical encounters or to discuss elements outside of individual cognition that are essential to diagnosis. Methods In 2016, the University of California, San Francisco School of Medicine launched a clinical reasoning curriculum that simultaneously emphasizes reasoning concepts and intentional knowledge construction; the roles of patients, families, interprofessional colleagues; and communication in diagnosis. The curriculum features a longitudinal thread beginning in first year, with an immersive three week diagnostic reasoning (DR) course in the second year. Students evaluated the DR course. Additionally, we conducted an audit of the multiyear clinical reasoning curriculum using the Society to Improve Diagnosis in Medicine-Macy Foundation interprofessional diagnostic education competencies. Results Students rated DR highly (range 4.13–4.18/5 between 2018 and 2020) and reported high self-efficacy with applying clinical reasoning concepts and communicating reasoning to supervisors. A course audit demonstrated a disproportionate emphasis on individual (cognitive) competencies with inadequate attention to systems and team factors in diagnosis. Conclusions Our clinical reasoning curriculum led to high student self-efficacy. However, we stressed cognitive aspects of reasoning with limited instruction on teams and systems. Diagnosis education should expand beyond the cognitive- and physician-centric focus of most published reasoning courses.

Objectives A few CLIA automated immunoassays for the recognition of anti S1-RBD SARS-CoV-2 antibodies have recently been placed on the market. Preliminary data demonstrate a high correlation between methods but wide differences in absolute concentrations. A new WHO international standard for anti-SARS-CoV-2 immunoglobulin, NIBSC code 20/136, has been recently introduced to reduce the differences. The aim of this study is thus to verify the harmonization made by NIBSC 20/136 on Ab anti S1-RBD measurement on real samples. Methods The following assays were studied: LIAISON ® SARS-CoV-2 TrimericS IgG (DiaSorin); Elecsys ® anti-SARS-CoV-2 S (ROCHE); Atellica IM SARS-CoV-2 IgG (sCOVG) (Siemens); MAGLUMI ® SARS-CoV-2 S-RBD IgG (Snibe), measuring 210 samples from 70 health workers with no previous SARS-CoV2 infection, during their Pfizer-BioNTech’s BNT162b2 vaccination period. Results The recalculation of concentrations based on the NIBSC 20/136 standardization improve the analytical and diagnostic comparability but do not cancel this variability between methods: recalibrated results remain different across methods, both in terms of tendency and single data. Conclusions The recalculation of concentrations based on the NIBSC 20/136 standardization improves the analytical and diagnostic comparability but does not cancel the differences between methods: recalibrated results remain different across methods, both in terms of tendency and single data.

Objectives Cognitive biases can result in clinical reasoning failures that can lead to diagnostic errors. Autobrewery syndrome is a rare, but likely underdiagnosed, condition in which gut flora ferment glucose, producing ethanol. It most frequently presents with unexplained episodes of inebriation, though more case studies are necessary to better characterize the syndrome. Case presentation This is a case of a 41-year old male with a past medical history notable only for frequent sinus infections, who presented with recurrent episodes of acute pancreatitis. In the week prior to his first episode of pancreatitis, he consumed four beers, an increase from his baseline of 1–2 drinks per month. At home, he had several episodes of confusion, which he attributed to fatigue. He underwent laparoscopic cholecystectomy and testing for genetic and autoimmune causes of pancreatitis, which were non-revealing. He was hospitalized 10 more times during that 9-month period for acute pancreatitis with elevated transaminases. During these admissions, he had elevated triglycerides requiring an insulin drip and elevated alcohol level despite abstaining from alcohol for the prior eight months. His alcohol level increased after consumption of complex carbohydrates, confirming the diagnosis of autobrewery syndrome. Conclusions Through integrated commentary on the diagnostic reasoning process, this case underscores how overconfidence can lead to premature closure and anchoring resulting in diagnostic error. Using a metacognitive overview, case discussants describe the importance of structured reflection and a standardized approach to early hypothesis generation to navigate these cognitive biases.