Minding the gap: towards a shared clinical reasoning lexicon across the pre-clerkship/clerkship transition

Teaching and learning of clinical reasoning are core principles of medical education. However, little guidance exists for faculty leaders to navigate curricular transitions between pre-clerkship and clerkship curricular phases. This study compares how educational leaders in these two phases understand clinical reasoning instruction. Previously reported cross-sectional surveys of pre-clerkship clinical skills course directors, and clerkship leaders were compared. Comparisons focused on perceived importance of a number of core clinical reasoning concepts, barriers to clinical reasoning instruction, level of familiarity across the undergraduate medical curriculum, and inclusion of clinical reasoning instruction in each area of the curriculum. Analyses were performed using the Mann Whitney U test. Both sets of leaders rated lack of curricular time as the largest barrier to teaching clinical reasoning. Clerkship leaders also noted a lack of faculty with skills to teach clinical reasoning concepts as a significant barrier (p < 0.02), while pre-clerkship leaders were more likely to perceive that these concepts were too advanced for their students (p < 0.001). Pre-clerkship leaders reported a higher level of familiarity with the clerkship curriculum than clerkship leaders reported of the pre-clerkship curriculum (p < 0.001). As faculty transition students from the pre-clerkship to the clerkship phase, a shared understanding of what is taught and when, accompanied by successful faculty development, may aid the development of longitudinal, milestone-based clinical reasoning instruction.

Reliability of a Measure of Admission Intensity for Emergency Physicians

STUDY OBJECTIVE

We assess the stability of a measure of emergency department (ED) admission intensity for value-based care programs designed to reduce variation in ED admission rates. Measure stability is important to accurately assess admission rates across sites and among physicians.

METHODS

We sampled data from 358 EDs in 41 states (January 2018 to December 2021), separate from sites where the measure was derived. The measure is the ED admission rate per 100 ED visits for 16 clinical conditions and 535 included International Classification of Disease 10 diagnosis codes. We used descriptive plots and multilevel linear probability models to assess stability over time across EDs and among physicians.

RESULTS

Across included 3,571 ED-quarters, the average admission rate was 27.6% (95% confidence interval [CI] 26.0% to 28.2%). The between-facility standard deviation was 9.7% (95% CI 9.0% to 10.6%), and the within-facility standard deviation was 3.0% (95% CI 2.95% to 3.10%), with an intraclass correlation coefficient of 0.91. At the physician-quarter level, the average admission rate was 28.3% (95% CI 28.0% to 28.5%) among 7,002 physicians. Relative to their site's mean in each quarter, the between-physician standard deviation was 6.7% (95% CI 6.6% to 6.8%), and the within-physician standard deviation was 5.5% (95% CI 5.5% to 5.6%), with an intraclass correlation coefficient of 0.59. Moreover, 2.9% of physicians were high-admitting in 80%+ of their practice quarters relative to their peers in the same ED and in the same quarter, whereas 3.9% were low-admitting.

CONCLUSION

The measure exhibits stability in characterizing ED-level admission rates and reliably identifies high- and low-admitting physicians.

Telemedicine entrustable professional activities for nurses in long-term care: A modified Delphi study

BACKGROUND

As the use of telemedicine proliferates in community care, it is essential to ensure practice recommendations and guidelines are available to assist healthcare providers in providing telemedicine-based care. This study aimed to develop entrustable professional activities (EPAs) for nursing home nurses involved in telemedicine consultations.

AIM

To develop entrustable professional activities (EPAs) for nursing home nurses involved in telemedicine consultations.

DESIGN

Modified Delphi study.

METHODS

The study was conducted in two stages. First, content analysis of 28 healthcare provider interviews and literature review on telemedicine competencies was conducted to develop an initial list of EPAs. An expert workgroup comprising of an international panel of academics and clinicians reviewed the activities. In the second stage, a three-round e-Delphi technique was used to develop telemedicine EPAs for nurses in long-term care. Descriptive statistics and qualitative feedback were distributed to participants after each round. Agreement within survey rounds was computed.

RESULTS

Six core telemedicine EPAs with 28 descriptors were developed, from preparing the resident for the teleconsultation encounter to follow-up care post-teleconsultation. Agreement coefficients were high across all Delphi rounds.

CONCLUSION

This study identifies the core functions that long-term care nurses' are expected to perform in telemedicine consultations. The internationally relevant EPAs are sufficiently broad to be adapted to design telemedicine training and workplace-based assessment for nurses. Organisations may utilise the EPAs as a resource during the implementation process of telemedicine services in long-term care in designing nursing workflow and complement the learning and development of nurses for telemedicine services. Equipping long-term care nurses with this resource can ensure consistency, patient safety and quality of teleconsultations delivered to nursing home residents. However, further work is required to expand the EPAs for application to practice.

Words matter: Comments in support of diagnosis education in pharmacy

Diagnosis education is explicitly included in the Draft Accreditation Standards 2025 and should be wholeheartedly supported. To address the staggering number of diagnostic errors in the US, the National Academy of Medicine advocates for diagnosis education for all health professions. Misperceptions of pharmacists' involvement in diagnosis are exacerbated by use of implicit language and euphemisms, and it's long overdue that we provide clarity. Pharmacists are engaged in diagnosis and diagnostic reasoning in everyday practice whether realized or not. Diagnosis education is implicitly included in US pharmacy curricula in the Pharmacists' Patient Care Process, and it is time to give students the language to engage in it responsibly to be practice-ready in all states. The explicit inclusion of diagnosis in the Draft Standards 2025 has positive implications for education, practice, and graduates.

Of editorial processes, AI models, and medical literature: the Magnetic Resonance Audiometry experiment

The potential of artificial intelligence (AI) in the field of medical research is unquestionable. Nevertheless, the scientific community has raised several concerns about a possible fraudulent use of these tools that might be used to generate inaccurate or, in extreme cases, erroneous messages that could find their way into the literature. In this experiment, we asked a generative AI program to write a technical report on a non-existing Magnetic Resonance Imaging technique called Magnetic Resonance Audiometry, receiving in return a full seemingly technically sound report, substantiated by equations and references. We have submitted this report to an international peer-reviewed indexed journal, passing the first round of review with only minor changes requested. With this experiment, we showed that the current peer-review system, already burdened by the overwhelming increase in number of publications, might be not ready to also handle the explosion of these techniques, showing the urgent need for the entire community to address both the issue of generative AI in scientific literature and probably a more profound discussion on the entire peer-review process. CLINICAL RELEVANCE STATEMENT: Generative AI models are shown to be able to create a full manuscript without any human intervention that can survive peer-review. Given the explosion of these techniques, a profound discussion on the entire peer-review process by the scientific community is mandatory. KEY POINTS: • The scientific community has raised several concerns about a possible fraudulent use of AI in scientific literature. • We asked a generative AI program to write a technical report on a non-existing technique, receiving in return a full technically sound report, substantiated by equations and references, that passed peer-review. • This experiment showed that the current peer-review system might be not ready to handle the explosion of generative AI techniques, advising for a profound discussion on the entire peer-review process.

SHARP (SHort Answer, Rationale Provision): A New Item Format to Assess Clinical Reasoning

PROBLEM

Many non-workplace-based assessments do not provide good evidence of a learner's problem representation or ability to provide a rationale for a clinical decision they have made. Exceptions include assessment formats that require resource-intensive administration and scoring. This article reports on research efforts toward building a scalable non-workplace-based assessment format that was specifically developed to capture evidence of a learner's ability to justify a clinical decision.

APPROACH

The authors developed a 2-step item format called SHARP (SHort Answer, Rationale Provision), referring to the 2 tasks that comprise the item. In collaboration with physician-educators, the authors integrated short-answer questions into a patient medical record-based item starting in October 2021 and arrived at an innovative item format in December 2021. In this format, a test-taker interprets patient medical record data to make a clinical decision, types in their response, and pinpoints medical record details that justify their answers. In January 2022, a total of 177 fourth-year medical students, representing 20 U.S. medical schools, completed 35 SHARP items in a proof-of-concept study.

OUTCOMES

Primary outcomes were item timing, difficulty, reliability, and scoring ease. There was substantial variability in item difficulty, with the average item answered correctly by 44% of students (range, 4%-76%). The estimated reliability (Cronbach α ) of the set of SHARP items was 0.76 (95% confidence interval, 0.70-0.80). Item scoring is fully automated, minimizing resource requirements.

NEXT STEPS

A larger study is planned to gather additional validity evidence about the item format. This study will allow comparisons between performance on SHARP items and other examinations, examination of group differences in performance, and possible use cases for formative assessment. Cognitive interviews are also planned to better understand the thought processes of medical students as they work through the SHARP items.

Proof-of-concept study: Remote capillary blood collection for hCG analysis in early pregnancy

INTRODUCTION

Capillary blood collection, a technique traditionally used in diabetes care, shows promise for many applications including pregnancy monitoring. Serial measurement of serum human Chorionic Gonadotrophin (hCG) is frequently necessary for managing early pregnancy, including molar pregnancy, requiring multiple visits to a maternity hospital for blood collection by venepuncture. This proof-of-concept study aimed to assess the clinical performance and user acceptability of capillary blood samples collected remotely, as an alternative to venous blood for hCG measurement.

METHODS

Women attending the early pregnancy unit who required serum hCG measurement, were invited to participate. Following informed written consent, participants were shown how to collect capillary blood samples using the Mini-Collect® collection device. Matched venous and capillary blood samples were collected in clinic for hCG comparison purposes. Participants were also supplied with a home collection kit in a prepaid return envelope. They were asked to perform a finger-prick blood collection at home using the instructions provided and to return the capillary blood sample by post within 24 h of collection, along with a completed user-satisfaction questionnaire. Statistical analysis was performed using Analyse-it® software.

RESULTS

The study enrolled 71 participants and over a third of these women collected a capillary blood sample at home. The median age of participants was 33 years (range 29-36). Passing-Bablok linear regression (y = -0.037 + 1.04x) and Spearman correlation (r = 0.999, p < 0.0001), demonstrated good agreement and strong correlation between venous and capillary samples, over a broad range of hCG values (1.2 to 224,0000 IU/L). The majority of capillary samples collected remotely (39%, 27/69) had sufficient blood volume for analysis (74%, 20/27). Respondents (77%, 18/25) found the collection device easy to use and expressed willingness to use a future service if available (80%, 20/25) CONCLUSION: The study demonstrated excellent agreement between the hCG results obtained from both collection methods, suggesting that capillary blood can serve as a reliable alternative for venous hCG measurement, particularly in clinical settings requiring frequent hCG monitoring. Feedback from the study questionnaire indicates a preference for this type of follow-up among women, indicating potential improvements in compliance for blood based diagnostic tests.

Challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic: A scoping review

Background

Telemedicine has aided patients with diabetes during the COVID-19 pandemic in receiving better healthcare services. However, despite its numerous benefits, the use of this technology has faced several challenges. This study aimed to identify the challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic.

Methods

This scoping review was conducted in 2024. Relevant articles published between 2020 and 2023 were searched in databases including PubMed, Scopus, Web of Science, ProQuest, and the Cochrane Library. Initially, 822 articles were retrieved, and after screening 21 articles were selected.

Results

The challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic were categorized into the clinical, individual, organizational, and technical challenges. The clinical challenges included the lack of physical examinations and unavailability of patients' medical history. The individual challenges contained difficulties in using smart phones by patients and their low level of literacy. The organizational challenges were related to insufficient laws about obtaining patient consent and limited reimbursement for telemedicine services, and the technical challenges included limited access to the high-speed Internet services and inadequate technical infrastructure for telemedicine services. Most studies highlighted the role of individual and organizational challenges in using this technology.

Conclusions

Considering the numerous challenges experienced in using telemedicine for patients with diabetes during the COVID-19 pandemic, it seems that more attention should be paid to address each of these challenges to improve the actual usage, service quality, and user acceptance of telemedicine technology. This, in turn, can lead to saving costs and improving the health status and quality of life of patients with diabetes.

The influence of context on diagnostic reasoning: A narrative synthesis of experimental findings

AIMS AND OBJECTIVES

Contextual information which is implicitly available to physicians during clinical encounters has been shown to influence diagnostic reasoning. To better understand the psychological mechanisms underlying the influence of context on diagnostic accuracy, we conducted a review of experimental research on this topic.

METHOD

We searched Web of Science, PubMed, and Scopus for relevant articles and looked for additional records by reading the references and approaching experts. We limited the review to true experiments involving physicians in which the outcome variable was the accuracy of the diagnosis.

RESULTS

The 43 studies reviewed examined two categories of contextual variables: (a) case-intrinsic contextual information and (b) case-extrinsic contextual information. Case-intrinsic information includes implicit misleading diagnostic suggestions in the disease history of the patient, or emotional volatility of the patient. Case-extrinsic or situational information includes a similar (but different) case seen previously, perceived case difficulty, or external digital diagnostic support. Time pressure and interruptions are other extrinsic influences that may affect the accuracy of a diagnosis but have produced conflicting findings.

CONCLUSION

We propose two tentative hypotheses explaining the role of context in diagnostic accuracy. According to the negative-affect hypothesis, diagnostic errors emerge when the physician's attention shifts from the relevant clinical findings to the (irrelevant) source of negative affect (for instance patient aggression) raised in a clinical encounter. The early-diagnosis-primacy hypothesis attributes errors to the extraordinary influence of the initial hypothesis that comes to the physician's mind on the subsequent collecting and interpretation of case information. Future research should test these mechanisms explicitly. Possible alternative mechanisms such as premature closure or increased production of (irrelevant) rival diagnoses in response to context deserve further scrutiny. Implications for medical education and practice are discussed.

Venous Thrombosis in Airborne Viral Infections: Is Coronavirus Disease 2019 now Any Different from Influenza?

One of the hallmarks of coronavirus disease 2019 (COVID-19), particularly in complicated cases (i.e., requiring hospitalization or intensive care support), is persistent hemostasis activation, which may be associated with a vast array of thrombotic episodes involving both the arterial and venous systems. The renewed emphasis on the relationship between viral infections and venous thrombosis paves the way for determining whether a more common and often underestimated infection disease, such as influenza, may also be associated with a significant burden of venous thrombotic episodes, and how this eventual thrombotic risk compares to that seen in COVID-19, both in the past and with newer variants. Our review of studies comparing the burden of venous thromboembolism (VTE) in patients with COVID-19 or influenza revealed that the thrombotic risk appears to be significantly higher in patients with COVID-19 but remains certainly not meaningless in those with influenza, particularly in subjects infected by highly virulent strains (i.e., H1N1), in those who develop pneumonia and require intensive care support. In these specific clinical settings, the adoption of tailored thromboprophylaxis may be indicated though more studies are compellingly needed on this matter. As COVID-19 variants emerge, there is a possibility that the VTE burden of COVID-19 will decrease, and progress to that of other respiratory viruses.

Development and Psychometric Analysis of a Patient-Reported Measure of Diagnostic Excellence for Emergency and Urgent Care Settings

BACKGROUND

Emergency and urgent care settings face challenges with routinely obtaining performance feedback related to diagnostic care. Patients and their care partners provide an important perspective on the diagnostic process and outcome of care in these settings. We sought to develop and test psychometric properties of Patient-Report to IMprove Diagnostic Excellence in Emergency Department settings (PRIME-ED), a measure of patient-reported diagnostic excellence in these care settings.

METHODS

We developed PRIME-ED based on literature review, expert feedback, and cognitive testing. To assess psychometric properties, we surveyed AmeriSpeak, a probability-based panel that provides sample coverage of approximately 97% of the U.S. household population, in February 2022 to adult patients, or their care partners, who had presented to an emergency department or urgent care facility within the last 30 days. Respondents rated their agreement on a 5-point Likert scale with each of 17 statements across multiple domains of patient-reported diagnostic excellence. Demographics, visit characteristics, and a subset of the Emergency Department Consumer Assessment of Healthcare Providers & Systems were also collected. We conducted psychometric testing for reliability and validity.

RESULTS

Over a thousand (n = 1116) national panelists completed the PRIME-ED survey, of which 58.7% were patients and 40.9% were care partners; 49.6% received care at an emergency department and 49.9% at an urgent care facility. Responses had high internal consistency within 3 patient-reported diagnostic excellence domain groupings: diagnostic process (Cronbach's alpha 0.94), accuracy of diagnosis (0.93), and communication of diagnosis (0.94). Domain groupings were significantly correlated with concurrent Emergency Department Consumer Assessment of Healthcare Providers & Systems items. Factor analyses substantiated 3 domain groupings.

CONCLUSIONS

PRIME-ED has potential as a tool for capturing patient-reported diagnostic excellence in emergency and urgent care.

Comparison of diagnostic accuracy of rapid antigen tests for COVID19 compared to the viral genetic test in adults: a systematic review and meta-analysis

OBJECTIVE

The objective of this review is to determine the diagnostic accuracy of the currently available and upcoming point-of-care rapid antigen tests (RATs) used in primary care settings relative to the viral genetic real-time reverse transcriptase polymerase chain reaction (RT-PCR) test as a reference for diagnosing COVID-19/SARS-CoV-2 in adults.

INTRODUCTION

Accurate COVID-19 point-of-care diagnostic tests are required for real-time identification of SARS-CoV-2 infection in individuals. Real-time RT-PCR is the accepted gold standard for diagnostic testing, requiring technical expertise and expensive equipment that are unavailable in most primary care locations. RATs are immunoassays that detect the presence of a specific viral protein, which implies a current infection with SARS-CoV-2. RATs are qualitative or semi-quantitative diagnostics that lack thresholds that provide a result within a short time frame, typically within the hour following sample collection. In this systematic review, we synthesized the current evidence regarding the accuracy of RATs for detecting SARS-CoV-2 compared with RT-PCR.

INCLUSION CRITERIA

Studies that included nonpregnant adults (18 years or older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity, were included. The index test was any available SARS-CoV-2 point-of-care RAT. The reference test was any commercially distributed RT-PCR-based test that detects the RNA genome of SARS-CoV-2 and has been validated by an independent third party. Custom or in-house RT-PCR tests were also considered, with appropriate validation documentation. The diagnosis of interest was COVID-19 disease and SARS-CoV-2 infection. This review considered cross-sectional and cohort studies that examined the diagnostic accuracy of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed.

METHODS

The keywords and index terms contained in relevant articles were used to develop a full search strategy for PubMed and adapted for Embase, Scopus, Qinsight, and the WHO COVID-19 databases . Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic. Studies that met the inclusion criteria were critically appraised using QUADAS-2. Using a customized tool, data were extracted from included studies and were verified prior to analysis. The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated and presented with 95% CIs. When heterogeneity was observed, outlier analysis was conducted, and the results were generated by removing outliers.

RESULTS

Meta-analysis was performed on 91 studies of 581 full-text articles retrieved that provided true-positive, true-negative, false-positive, and false-negative values. RATs can identify individuals who have COVID-19 with high reliability (positive predictive value 97.7%; negative predictive value 95.2%) when considering overall performance. However, the lower level of sensitivity (67.1%) suggests that negative test results likely need to be retested through an additional method.

CONCLUSIONS

Most reported RAT brands had only a few studies comparing their performance with RT-PCR. Overall, a positive RAT result is an excellent predictor of a positive diagnosis of COVID-19. We recommend that Roche's SARS-CoV-2 Rapid Antigen Test and Abbott's BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR. We recommend adherence to the STARD guidelines when reporting on diagnostic data.

REVIEW REGISTRATION

PROSPERO CRD42020224250.

Collaborating with non-radiological clinical colleagues

Paediatric radiology is a challenging and intriguing subspecialty, dealing with children, guardians and non-radiological clinical colleagues. Paediatric radiologists are routinely in contact with numerous paediatric and surgical subspecialties, all having different needs, perceptions, prioritisations and expectations. Moreover, the radiologist is part of the team of radiographers, sonographers, nurses and secretaries, assisted by appropriate equipment and electronic tools. The framework of good collaboration to ensure safety and effectiveness for the imaged child is a shared responsibility among all medical practitioners involved. Communication in routine practice has many forms and includes appropriately filled radiology requests in accordance to the patient's medical records, routine and timely production of structured, problem-solving radiology reports, face-to-face or electronic-assisted communications and discussions on a pre-defined framework, mutually-agreed and evidence-based protocols adjusted to local availability, skills and national and international guidelines. Mutual understanding of advantages and limitations of imaging is paramount. Well-meant discussions, professionalism and empathy should promote soft skills, bidirectional communication and good collaboration for the benefit of added-value paediatric radiology. International societies, health authorities, medical directors and senior consultants have the responsibility to suggest and safeguard frameworks and recommendations. Regular multidisciplinary meetings and multidisciplinary research projects under openness, honesty and transparency are pathways favouring good collaboration.

LC-SRM combined with machine learning enables fast identification and quantification of bacterial pathogens in urinary tract infections

Urinary tract infections (UTIs) are a worldwide health problem. Fast and accurate detection of bacterial infection is essential to provide appropriate antibiotherapy to patients and to avoid the emergence of drug-resistant pathogens. While the gold standard requires 24h to 48h of bacteria culture prior MALDI-TOF species identification, we propose a culture-free workflow, enabling a bacterial identification and quantification in less than 4 hours using 1mL of urine. After a rapid and automatable sample preparation, a signature of 82 bacterial peptides, defined by machine learning, was monitored in LC-MS, to distinguish the 15 species causing 84% of the UTIs. The combination of the sensitivity of the SRM mode on a triple quadrupole TSQ Altis instrument and the robustness of capillary flow enabled us to analyze up to 75 samples per day, with 99.2% accuracy on bacterial inoculations of healthy urines. We have also shown our method can be used to quantify the spread of the infection, from 8x104 to 3x107 CFU/mL. Finally, the workflow was validated on 45 inoculated urines and on 84 UTI-positive urine from patients, with respectively 93.3% and 87.1% of agreement with the culture-MALDI procedure at a level above 1x105 CFU/mL corresponding to an infection requiring antibiotherapy.

Patient and family contributions to improve the diagnostic process through the OurDX electronic health record tool: a mixed method analysis

BACKGROUND

Accurate and timely diagnosis relies on sharing perspectives among team members and avoiding information asymmetries. Patients/Families hold unique diagnostic process (DxP) information, including knowledge of diagnostic safety blindspots-information that patients/families know, but may be invisible to clinicians. To improve information sharing, we co-developed with patients/families an online tool called 'Our Diagnosis (OurDX)'. We aimed to characterise patient/family contributions in OurDX and how they differed between individuals with and without diagnostic concerns.

METHOD

We implemented OurDX in two academic organisations serving patients/families living with chronic conditions in three subspecialty clinics and one primary care clinic. Prior to each visit, patients/families were invited to contribute visit priorities, recent histories and potential diagnostic concerns. Responses were available in the electronic health record and could be incorporated by clinicians into visit notes. We randomly sampled OurDX reports with and without diagnostic concerns for chart review and used inductive and deductive qualitative analysis to assess patient/family contributions.

RESULTS

7075 (39%) OurDX reports were submitted at 18 129 paediatric subspecialty clinic visits and 460 (65%) reports were submitted among 706 eligible adult primary care visits. Qualitative analysis of OurDX reports in the chart review sample (n=450) revealed that participants contributed DxP information across 10 categories, most commonly: clinical symptoms/medical history (82%), tests/referrals (54%) and diagnosis/next steps (51%). Participants with diagnostic concerns were more likely to contribute information on DxP risks including access barriers, recent visits for the same problem, problems with tests/referrals or care coordination and communication breakdowns, some of which may represent diagnostic blindspots.

CONCLUSION

Partnering with patients and families living with chronic conditions through OurDX may help clinicians gain a broader perspective of the DxP, including unique information to coproduce diagnostic safety.

Biomarkers in sepsis

Sepsis is a life-threatening condition characterized by dysregulated host response to infection leading to organ dysfunction. Despite advances in understanding its pathology, sepsis remains a global health concern and remains a major contributor to mortality. Timely identification is crucial for improving clinical outcomes, as delayed treatment significantly impacts survival. Accordingly, biomarkers play a pivotal role in diagnosis, risk stratification, and management. This review comprehensively discusses various biomarkers in sepsis and their potential application in antimicrobial stewardship and risk assessment. Biomarkers such as white blood cell count, neutrophil to lymphocyte ratio, erythrocyte sedimentation rate, C-reactive protein, interleukin-6, presepsin, and procalcitonin have been extensively studied for their diagnostic and prognostic value as well as in guiding antimicrobial therapy. Furthermore, this review explores the role of biomarkers in risk stratification, emphasizing the importance of identifying high-risk patients who may benefit from specific therapeutic interventions. Moreover, the review discusses the emerging field of transcriptional diagnostics and metagenomic sequencing. Advances in sequencing have enabled the identification of host response signatures and microbial genomes, offering insight into disease pathology and aiding species identification. In conclusion, this review provides a comprehensive overview of the current understanding and future directions of biomarker-based approaches in sepsis diagnosis, management, and personalized therapy.

Panel miRNAs are potential diagnostic markers for chronic kidney diseases: a systematic review and meta-analysis

BACKGROUND

Accurate detection of kidney damage is key to preventing renal failure, and identifying biomarkers is essential for this purpose. We aimed to assess the accuracy of miRNAs as diagnostic tools for chronic kidney disease (CKD).

METHODS

We thoroughly searched five databases (MEDLINE, Web of Science, Embase, Scopus, and CENTRAL) and performed a meta-analysis using R software. We assessed the overall diagnostic potential using the pooled area under the curve (pAUC), sensitivity (SEN), and specificity (SPE) values and the risk of bias by using the QUADAS-2 tool. The study protocol was registered on PROSPERO (CRD42021282785).

RESULTS

We analyzed data from 8351 CKD patients, 2989 healthy individuals, and 4331 people with chronic diseases. Among the single miRNAs, the pooled SEN was 0.82, and the SPE was 0.81 for diabetic nephropathy (DN) vs. diabetes mellitus (DM). The SEN and SPE were 0.91 and 0.89 for DN and healthy controls, respectively. miR-192 was the most frequently reported miRNA in DN patients, with a pAUC of 0.91 and SEN and SPE of 0.89 and 0.89, respectively, compared to those in healthy controls. The panel of miRNAs outperformed the single miRNAs (pAUC of 0.86 vs. 0.79, p < 0.05). The SEN and SPE of the panel miRNAs were 0.89 and 0.73, respectively, for DN vs. DM. In the lupus nephritis (LN) vs. systemic lupus erythematosus (SLE) cohorts, the SEN and SPE were 0.84 and 0.81, respectively. Urinary miRNAs tended to be more effective than blood miRNAs (p = 0.06).

CONCLUSION

MiRNAs show promise as effective diagnostic markers for CKD. The detection of miRNAs in urine and the use of a panel of miRNAs allows more accurate diagnosis.

Advancing Consistency in Education: A Reliability Analysis of the Clinical Reasoning Assessment Tool

INTRODUCTION

Clinical reasoning (CR) is a fundamental component of physical therapist practice in health care. The Clinical Reasoning Assessment Tool (CRAT) was developed to assess CR in Doctor of Physical Therapy (DPT) and residency education. However, the reliability of the CRAT has not been investigated. Our purpose was to investigate the interrater and intrarater reliability of the CRAT.

REVIEW OF LITERATURE

A range of assessment methods are available to assess CR, including didactic-based, simulation learning, and clinic-based assessments. The CRAT is designed to assess CR across learning environments. The CRAT assesses CR across 3 domains: (1) content knowledge, (2) procedural knowledge/psychomotor skills, and (3) conceptual reasoning.

SUBJECTS

Twenty-two faculty participated.

METHODS

Participants completed an electronic survey at 2 timepoints (T1, T2) that included training on use of the CRAT and 2 case videos of DPT students at different performance levels managing a standardized patient. Participants rated student performance with the CRAT for both case videos (T1) and repeated the sequence at least 30 days later (T2). Intraclass correlation coefficient (ICC) estimates and 95% confidence intervals were used to determine the interrater and intrarater reliability for each domain of the CRAT.

RESULTS

Video 1 was consistently rated higher for each CRAT domain (T1: 7.32-8.05; T2: 8.05-8.15) compared to video 2 (T1: 2.91-3.68; T2: 3.00-3.68). There were inverse relationships between CRAT ratings and number of years in DPT education, at an institution, and as a licensed physical therapist. At both timepoints, the interrater reliability for each domain was good to excellent (ICCs 0.60-0.79). The intrarater reliability was fair to excellent for all domains for each video (ICCs 0.45-0.75).

DISCUSSION AND CONCLUSION

The CRAT is a reliable instrument for assessing DPT student CR during a simulated patient encounter. Implementation of the CRAT in DPT education may facilitate improved consistency of CR assessment across the learner continuum.

Large Language Model Influence on Management Reasoning: A Randomized Controlled Trial

Importance

Large language model (LLM) artificial intelligence (AI) systems have shown promise in diagnostic reasoning, but their utility in management reasoning with no clear right answers is unknown.

Objective

To determine whether LLM assistance improves physician performance on open-ended management reasoning tasks compared to conventional resources.

Design

Prospective, randomized controlled trial conducted from 30 November 2023 to 21 April 2024.

Setting

Multi-institutional study from Stanford University, Beth Israel Deaconess Medical Center, and the University of Virginia involving physicians from across the United States.

Participants

92 practicing attending physicians and residents with training in internal medicine, family medicine, or emergency medicine.

Intervention

Five expert-developed clinical case vignettes were presented with multiple open-ended management questions and scoring rubrics created through a Delphi process. Physicians were randomized to use either GPT-4 via ChatGPT Plus in addition to conventional resources (e.g., UpToDate, Google), or conventional resources alone.

Main Outcomes and Measures

The primary outcome was difference in total score between groups on expert-developed scoring rubrics. Secondary outcomes included domain-specific scores and time spent per case.

Results

Physicians using the LLM scored higher compared to those using conventional resources (mean difference 6.5 %, 95% CI 2.7-10.2, p<0.001). Significant improvements were seen in management decisions (6.1%, 95% CI 2.5-9.7, p=0.001), diagnostic decisions (12.1%, 95% CI 3.1-21.0, p=0.009), and case-specific (6.2%, 95% CI 2.4-9.9, p=0.002) domains. GPT-4 users spent more time per case (mean difference 119.3 seconds, 95% CI 17.4-221.2, p=0.02). There was no significant difference between GPT-4-augmented physicians and GPT-4 alone (-0.9%, 95% CI -9.0 to 7.2, p=0.8).

Conclusions and Relevance

LLM assistance improved physician management reasoning compared to conventional resources, with particular gains in contextual and patient-specific decision-making. These findings indicate that LLMs can augment management decision-making in complex cases.

Trial registration

ClinicalTrials.gov Identifier: NCT06208423; https://classic.clinicaltrials.gov/ct2/show/NCT06208423.

Surveillance of Health Care-Associated Violence Using Natural Language Processing

BACKGROUND AND OBJECTIVES

Patient and family violent outbursts toward staff, caregivers, or through self-harm, have increased during the ongoing behavioral health crisis. These health care-associated violence (HAV) episodes are likely under-reported. We sought to assess the feasibility of using nursing notes to identify under-reported HAV episodes.

METHODS

We extracted nursing notes across inpatient units at 2 hospitals for 2019: a pediatric tertiary care center and a community-based hospital. We used a workflow for narrative data processing using a natural language processing (NLP) assisted manual review process performed by domain experts (a nurse and a physician). We trained the NLP models on the tertiary care center data and validated it on the community hospital data. Finally, we applied these surveillance methods to real-time data for 2022 to assess reporting completeness of new cases.

RESULTS

We used 70 981 notes from the tertiary care center for model building and internal validation and 19 332 notes from the community hospital for external validation. The final community hospital model sensitivity was 96.8% (95% CI 90.6% to 100%) and a specificity of 47.1% (39.6% to 54.6%) compared with manual review. We identified 31 HAV episodes in July to December 2022, of which 26 were reportable in accordance with the hospital internal criteria. Only 7 of 26 cases were reported by employees using the self-reporting system, all of which were identified by our surveillance process.

CONCLUSIONS

NLP-assisted review is a feasible method for surveillance of under-reported HAV episodes, with implementation and usability that can be achieved even at a low information technology-resourced hospital setting.

Algorithms in medical decision-making and in everyday life: what's the difference?

Algorithms are a ubiquitous part of modern life. Despite being a component of medicine since early efforts to deploy computers in medicine, clinicians' resistance to using decision support and use algorithms to address cognitive biases has been limited. This resistance is not just limited to the use of algorithmic clinical decision support, but also evidence and stochastic reasoning and the implications of the forcing function of the electronic medical record. Physician resistance to algorithmic support in clinical decision making is in stark contrast to their general acceptance of algorithmic support in other aspects of life.

FRAMED: a framework facilitating insight problem solving

Insight has been studied as an element of problem solving in the field of cognitive psychology and may play an important role in clinical reasoning. We propose a new strategy based on theories that promote insight that may help generate further diagnostic hypotheses by reviewing the interpretation of a case and an individual's list of differential diagnoses from multiple perspectives: formation (F), re-encoding (R), analogy (A), modification (M), elaboration (E), and deliberation (D) (FRAMED). The FRAMED strategy may help clinicians overcome misinterpretations and cognitive bias by systematically reflecting on previous clinical reasoning processes from multiple perspectives.

Assessment of Clinical Reasoning in Undergraduate Medical Education: A Pragmatic Approach to Programmatic Assessment

PURPOSE

Clinical reasoning, a complex construct integral to the practice of medicine, has been challenging to define, teach, and assess. Programmatic assessment purports to overcome validity limitations of judgments made from individual assessments through proportionality and triangulation processes. This study explored a pragmatic approach to the programmatic assessment of clinical reasoning.

METHOD

The study analyzed data from 2 student cohorts from the University of Utah School of Medicine (UUSOM) (n = 113 in cohort 1 and 119 in cohort 2) and 1 cohort from the University of Colorado School of Medicine (CUSOM) using assessment data that spanned from 2017 to 2021 (n = 199). The study methods included the following: (1) asking faculty judges to categorize student clinical reasoning skills, (2) selecting institution-specific assessment data conceptually aligned with clinical reasoning, (3) calculating correlations between assessment data and faculty judgments, and (4) developing regression models between assessment data and faculty judgments.

RESULTS

Faculty judgments of student clinical reasoning skills were converted to a continuous variable of clinical reasoning struggles, with mean (SD) ratings of 2.93 (0.27) for the 232 UUSOM students and 2.96 (0.17) for the 199 CUSOM students. A total of 67 and 32 discrete assessment variables were included from the UUSOM and CUSOM, respectively. Pearson r correlations were moderate to strong between many individual and composite assessment variables and faculty judgments. Regression models demonstrated an overall adjusted R2 (standard error of the estimate) of 0.50 (0.19) for UUSOM cohort 1, 0.28 (0.15) for UUSOM cohort 2, and 0.30 (0.14) for CUSOM.

CONCLUSIONS

This study represents an early pragmatic exploration of regression analysis as a potential tool for operationalizing the proportionality and triangulation principles of programmatic assessment. The study found that programmatic assessment may be a useful framework for longitudinal assessment of complicated constructs, such as clinical reasoning.

Understanding the Diagnostic Odyssey of Women with Mayer-Rokitansky-Küster-Hauser (MRKH) Syndrome in Denmark: A Qualitative Interview Study

STUDY OBJECTIVE

The diagnosis of Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is often a lengthy process that typically occurs during late adolescence. To support optimized and patient-centered care, this study aimed to investigate how women with MRKH syndrome experience the diagnostic process.

METHODS

From January 2021 to March 2021, we conducted in-depth interviews with 18 Danish women (≥25 years) diagnosed with MRKH syndrome. The interviews lasted a median of 92 minutes (range: 67-117). Data were analyzed using thematic analysis.

RESULTS

As teenagers or young women at the time, all women had experienced the diagnostic process in the nonspecialized healthcare sector as deeply upsetting due to distressing gynecological examinations, use of inappropriate language, and considerable diagnostic delay. When reaching the specialized health care sector, questions could finally be answered, but this information and support did not significantly alter their feelings of being "deviant" or "flawed". The women continued their diagnostic odyssey beyond the health care system and found online communities that gave them valuable support in living with MRKH syndrome.

CONCLUSION

Women experience the diagnostic odyssey of MRKH syndrome as upsetting and potentially traumatizing beyond the diagnosis. Healthcare professionals can influence young women's understanding and experience of MRKH syndrome by using inclusive language (eg, avoiding "deformity") and addressing all that is normal and functioning (eg, external genitalia and potential for sexual pleasure). In nonurgent conditions, young women should be given the choice to delay a genital examination.

Granulocytes in cerebrospinal fluid of adults suspected of a central nervous system infection: a prospective study of diagnostic accuracy

PURPOSE

Cerebrospinal fluid (CSF) granulocytes are associated with bacterial meningitis, but information on its diagnostic value is limited and primarily based on retrospective studies. Therefore, we assessed the diagnostic accuracy of CSF granulocytes.

METHODS

We analyzed CSF granulocytes (index test) from all consecutive patients in two prospective cohort studies in the Netherlands. Both studies included patients ≥ 16 years, suspected of a central nervous system (CNS) infection, who underwent a diagnostic lumbar puncture. All episodes with elevated CSF leukocytes (≥ 5 cells per mm3) were selected and categorized by clinical diagnosis (reference standard).

RESULTS

Of 1261 episodes, 625 (50%) had elevated CSF leukocytes and 541 (87%) were included. 117 of 541 (22%) were diagnosed with bacterial meningitis, 144 (27%) with viral meningoencephalitis, 49 (9%) with other CNS infections, 76 (14%) with CNS autoimmune disorders, 93 (17%) with other neurological diseases and 62 (11%) with systemic diseases. The area under the curve to discriminate bacterial meningitis from other diagnoses was 0.97 (95% confidence interval [CI] 0.95-0.98) for CSF granulocyte count and 0.93 (95% CI 0.91-0.96) for CSF granulocyte percentage. CSF granulocyte predominance occurred in all diagnostic categories. A cutoff at 50% CSF granulocytes gave a sensitivity of 94% (95% CI 90-98), specificity of 80% (95% CI 76-84), negative predictive value of 98% (95% CI 97-99) and positive predictive value of 57% (95% CI 52-62).

CONCLUSION

CSF granulocytes have a high diagnostic accuracy for bacterial meningitis in patients suspected of a CNS infection. CSF granulocyte predominance occurred in all diagnostic categories, limiting its value in clinical practice.

A QR code-enabled framework for fast biomedical image processing in medical diagnosis using deep learning

In the realm of disease prognosis and diagnosis, a plethora of medical images are utilized. These images are typically stored either within the local on-premises servers of healthcare providers or within cloud storage infrastructures. However, this conventional storage approach often incurs high infrastructure costs and results in sluggish information retrieval, ultimately leading to delays in diagnosis and consequential wastage of valuable time for patients. The methodology proposed in this paper offers a pioneering solution to expedite the diagnosis of medical conditions while simultaneously reducing infrastructure costs associated with data storage. Through this study, a high-speed biomedical image processing approach is designed to facilitate rapid prognosis and diagnosis. The proposed framework includes Deep learning QR code technique using an optimized database design aimed at alleviating the burden of intensive on-premises database requirements. The work includes medical dataset from Crawford Image and Data Archive and Duke CIVM for evaluating the proposed work suing different performance metrics, The work has also been compared from the previous research further enhancing the system's efficiency. By providing healthcare providers with high-speed access to medical records, this system enables swift retrieval of comprehensive patient details, thereby improving accuracy in diagnosis and supporting informed decision-making.

Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE)

OBJECTIVES

Diagnostic errors are the leading cause of preventable harm in clinical practice. Implementable tools to quantify and target this problem are needed. To address this gap, we aimed to generalize the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework by developing its computable phenotype and then demonstrated how that schema could be applied in multiple clinical contexts.

METHODS

We created an information model for the SPADE processes, then mapped data fields from electronic health records (EHR) and claims data in use to that model to create the SPADE information model (intention) and the SPADE computable phenotype (extension). Later we validated the computable phenotype and tested it in four case studies in three different health systems to demonstrate its utility.

RESULTS

We mapped and tested the SPADE computable phenotype in three different sites using four different case studies. We showed that data fields to compute an SPADE base measure are fully available in the EHR Data Warehouse for extraction and can operationalize the SPADE framework from provider and/or insurer perspective, and they could be implemented on numerous health systems for future work in monitor misdiagnosis-related harms.

CONCLUSIONS

Data for the SPADE base measure is readily available in EHR and administrative claims. The method of data extraction is potentially universally applicable, and the data extracted is conveniently available within a network system. Further study is needed to validate the computable phenotype across different settings with different data infrastructures.

Exploring sleep duration and clinical reasoning process in resident physicians: a thematic analysis

STUDY OBJECTIVES

Connecting resident physician work hours and sleep deprivation to adverse outcomes has been difficult. Our study explores clinical reasoning rather than outcomes. Diagnostic errors are a leading cause of medical error and may result from deficits in clinical reasoning. We used simulated cases to explore relationships between sleep duration and diagnostic reasoning.

METHODS

Residents were recruited for a 2-month study (inpatient/outpatient). Each participant's sleep was tracked (sleep diary/actigraphy). At the end of each month, residents watched 2 brief simulated clinical encounters and performed "think alouds" of their clinical reasoning. In each session, 1 video was straightforward and the other video contained distracting contextual factors. Sessions were recorded, transcribed, and interpreted. We conducted a thematic analysis using a constant comparative approach. Themes were compared based on sleep duration and contextual factors.

RESULTS

Residents (n = 17) slept more during outpatient compared with inpatient months (450.5 ± 7.13 vs 425.6 ± 10.78 hours, P = .02). We found the following diagnostic reasoning themes: uncertainty, disorganized knowledge, error, semantic incompetence, emotional content, and organized knowledge. Themes reflecting suboptimal clinical reasoning (disorganized knowledge, error, semantic incompetence, uncertainty) were observed more in cases with contextual factors (distractors). "Think alouds" from cases with contextual factors following sleep restriction had a greater number of themes concerning for problematic diagnostic reasoning.

CONCLUSIONS

Residents obtained significantly more sleep during outpatient compared with inpatient months. Several negative clinical reasoning themes emerged with less sleep combined with cases containing contextual distractors. Our findings reinforce the importance of adequate sleep and supervision in house officers, particularly in cases with distracting elements.

CITATION

Collen J, Durning S, Berk J, Mang J, Alcover K, Jung E. Exploring sleep duration and clinical reasoning process in resident physicians: a thematic analysis. J Clin Sleep Med. 2024;20(8):1279-1289.

Identifying Facilitators and Inhibitors of Shared Understanding: An Ethnography of Diagnosis Communication in Acute Medical Settings

BACKGROUND AND AIMS

Communication is important in determining how patients understand the diagnostic process. Empirical studies involving direct observation of communication within diagnostic processes are relatively limited. This ethnographic study aimed to identify communicative practices facilitating or inhibiting shared understanding between patients and doctors in UK acute secondary care settings.

METHODS

Data were collected in acute medical sectors of three English hospitals. Researchers observed doctors as they assessed patients; semistructured interviews were undertaken with doctors and patients directly afterwards. Patients were also interviewed 2-4 weeks later. Case studies of individual encounters (consisting of these interviews and observational notes) were created, and were cross-examined by an interdisciplinary team to identify divergence and convergence between doctors' and patients' narratives. These data were analysed thematically.

RESULTS

We conducted 228 h of observation, 24 doctor interviews, 32 patient interviews and 15 patient follow-up interviews. Doctors varied in their communication. Patient diagnostic understanding was sometimes misaligned with that of their doctors; interviews revealed that they often made incorrect assumptions to make sense of the fragmented information received. Thematic analysis identified communicative practices that seemed to facilitate, or inhibit, shared diagnostic understanding between patient and doctor, revealing three themes: (1) communicating what has been understood from the medical record, (2) sharing the thought process and diagnostic reasoning and (3) closing the loop and discharge communication. Shared understanding was best fostered by clear communication about the diagnostic process, what had already been done and what was achievable in acute settings. Written information presents an underutilised tool in such communication.

CONCLUSIONS

In UK acute secondary settings, the provision of more information about the diagnostic process often fostered shared understanding between doctor and patient, helping to minimise the confusion and dissatisfaction that can result from misaligned expectations or conclusions about the diagnosis, and the uncertainty therein.

PATIENT/PUBLIC CONTRIBUTION

A patient and public involvement group (of a range of ages and backgrounds) was consulted. They contributed to the design of the protocol, including the timing of interviews, the acceptability of a follow-up telephone interview, the development of the interview guides and the participant information sheets.

Race and Ethnicity and Diagnostic Testing for Common Conditions in the Acute Care Setting

Importance

Overuse of diagnostic testing is pervasive, but the extent to which it varies by race and ethnicity in the acute care setting is poorly understood.

Objective

To use a previously validated diagnostic intensity index to evaluate differences in diagnostic testing rates by race and ethnicity in the acute care setting, which may serve as a surrogate for diagnostic test overuse.

Design, Setting, and Participants

This was a cross-sectional study of emergency department (ED) discharges, hospital observation stays, and hospital admissions using administrative claims among EDs and acute care hospitals in Kentucky, Maryland, North Carolina, and New Jersey, from 2016 through 2018. The diagnostic intensity index pairs nonspecific principal discharge diagnoses (nausea and vomiting, abdominal pain, chest pain, and syncope) with related diagnostic tests to estimate rates of nondiagnostic testing. Adults with an acute care encounter with a principal discharge diagnosis of interest were included. Data were analyzed from January to February 2024.

Exposure

Race and ethnicity (Asian, Black, Hispanic, White, other [including American Indian, multiracial, and multiethnic], and missing).

Main Outcomes and Measures

Receipt of a diagnostic test. Generalized linear models with a hospital-specific indicator variable were estimated to calculate the adjusted odds ratio of receiving a test related to the principal discharge diagnosis by race and ethnicity, controlling for primary payer and zip code income quartile.

Results

Of 3 683 055 encounters (1 055 575 encounters [28.7%] for Black, 300 333 encounters [8.2%] for Hispanic, and 2 140 335 encounters [58.1%] for White patients; mean [SD] age of patients with encounters, 47.3 [18.8] years; 2 233 024 encounters among females [60.6%]), most (2 969 974 encounters [80.6%]) were ED discharges. Black compared with White patients discharged from the ED with a diagnosis of interest had an adjusted odds ratio of 0.74 (95% CI, 0.72-0.75) of having related diagnostic testing. No other racial or ethnic disparities of a similar magnitude were observed in any acute care settings.

Conclusions and Relevance

In this study, White patients discharged from the ED with a nonspecific diagnosis of interest were significantly more likely than Black patients to receive related diagnostic testing. The extent to which this represents diagnostic test overuse in White patients vs undertesting and missed diagnoses in Black patients deserves further study.

Masquerade of authority: hijacked journals are gaining more credibility than original ones

At the moment, the academic world is faced with various challenges that negatively impact science integrity. One is hijacked journals, a second, inauthentic website for indexed legitimate journals, managed by cybercriminals. These journals publish any manuscript by charging authors and pose a risk to scientific integrity. This piece compares a journal's original and hijacked versions regarding authority in search engines. A list of 16 medical journals, along with their hijacked versions, has been collected. The MOZ Domain Authority has been used to check the authority of both original and hijacked journals, and the results have been discussed. It indicates that hijacked journals are gaining more credibility than original ones. This should alarm academia and highlights a need for serious action against hijacked journals. The related policies should be planned, and tools should be developed to support easy detection of hijacked journals. On the publishers' side, the visibility of journals' websites must be enhanced to address this issue.

The Big Three diagnostic errors through reflections of Japanese internists

OBJECTIVES

To analyze the Big Three diagnostic errors (malignant neoplasms, cardiovascular diseases, and infectious diseases) through internists' self-reflection on their most memorable diagnostic errors.

METHODS

This secondary analysis study, based on a web-based cross-sectional survey, recruited participants from January 21 to 31, 2019. The participants were asked to recall the most memorable diagnostic error cases in which they were primarily involved. We gathered data on internists' demographics, time to error recognition, and error location. Factors causing diagnostic errors included environmental conditions, information processing, and cognitive bias. Participants scored the significance of each contributing factor on a Likert scale (0, unimportant; 10, extremely important).

RESULTS

The Big Three comprised 54.1 % (n=372) of the 687 cases reviewed. The median physician age was 51.5 years (interquartile range, 42-58 years); 65.6 % of physicians worked in hospital settings. Delayed diagnoses were the most common among malignancies (n=64, 46 %). Diagnostic errors related to malignancy were frequent in general outpatient settings on weekdays and in the mornings and were not identified for several months following the event. Environmental factors often contributed to cardiovascular disease-related errors, which were typically identified within days in emergency departments, during night shifts, and on holidays. Information gathering and interpretation significantly impacted infectious disease diagnoses.

CONCLUSIONS

The Big Three accounted for the majority of cases recalled by Japanese internists. The most relevant contributing factors were different for each of the three categories. Addressing these errors may require a unique approach based on the disease associations.

ESR Essentials: diagnostic work-up in patients with symptomatic breast disease-practice recommendations by the European Society of Breast Imaging

Breast complaints are frequent reasons for consultations in primary care or breast clinics. Breast pain, breast lumps, and nipple discharge are the most common complaints. Less common symptoms such as skin changes and axillary abnormalities also require specific diagnostic approaches. Imaging the symptomatic breast should be performed by appropriately trained breast radiologists following the best practice guidelines and quality standards. Full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), and breast ultrasound (US) are the main modalities used in this primary setting. The choice depends on the patient's age and symptoms. Women younger than 30-years-old are first imaged by US, whereas women over 40-years-old usually require both FFDM or DBT and US. For women between 30-years-old and 40-years-old, the US is the modality of choice, whereas FFDM or DBT might also be performed if needed. Pregnant or lactating women with palpable lesions or nipple discharge are imaged with US as the first method; FFDM or DBT can also be performed depending on the degree of suspicion as the dose to the fetus is minimal, and shielding may even further reduce the dose. More advanced techniques such as breast magnetic resonance imaging or contrast-enhanced mammography are not indicated in this first diagnostic setting and are reserved for cases of established malignancy (local staging) or rare cases of equivocal findings not otherwise resolved or inflammatory breast cancer. Last, but not least, male breast symptoms should also be addressed with US and/or FFDM. CLINICAL RELEVANCE STATEMENT: It is equally important to correctly diagnose an underlying malignancy and to avoid false positives that would lead to unnecessary biopsies, increased costs, and anxiety for the patient. Proper use of imaging modalities ensures optimal diagnostic approach and minimizes false negatives. KEY POINTS: Ultrasound, full-field digital mammography, or digital breast tomosynthesis are the main imaging modalities in the diagnostic setting, while MRI or contrast-enhanced mammography should be reserved to selected cases. Initial imaging modality includes ultrasound combined with mammography or digital breast tomosynthesis depending on women's age and the presence (or not) of inconclusive findings. A negative imaging evaluation should not deter biopsy when a highly suspicious finding is found on physical examination.

Advancing value-based laboratory medicine

Following the COVID-19 pandemic, the concepts of value-based medicine (VBM) and value-based laboratory medicine (VBLM) are receiving increasing interest to improve the quality, sustainability and safety of healthcare. Laboratory medicine is well positioned to support the transition to value-based healthcare as it helps to improve clinical outcomes and healthcare sustainability by reducing the time to diagnosis, improving diagnostic accuracy, providing effective guidance for tailored therapies and monitoring, and supporting screening and wellness care. However, the perception of the value of laboratory medicine is still limited, to the extent that it has been defined a "profession without a face", often lacking visibility to patients and the public. In addition, in recent decades, clinical laboratories have sought to improve the ration between outcomes and costs by increasing efficiency and reducing the cost per test rather than improving clinical outcomes. The aim of this paper is to propose a 10-point manifesto for implementing value-based laboratory medicine in clinical practice.

Multimodal data integration for oncology in the era of deep neural networks: a review

Cancer research encompasses data across various scales, modalities, and resolutions, from screening and diagnostic imaging to digitized histopathology slides to various types of molecular data and clinical records. The integration of these diverse data types for personalized cancer care and predictive modeling holds the promise of enhancing the accuracy and reliability of cancer screening, diagnosis, and treatment. Traditional analytical methods, which often focus on isolated or unimodal information, fall short of capturing the complex and heterogeneous nature of cancer data. The advent of deep neural networks has spurred the development of sophisticated multimodal data fusion techniques capable of extracting and synthesizing information from disparate sources. Among these, Graph Neural Networks (GNNs) and Transformers have emerged as powerful tools for multimodal learning, demonstrating significant success. This review presents the foundational principles of multimodal learning including oncology data modalities, taxonomy of multimodal learning, and fusion strategies. We delve into the recent advancements in GNNs and Transformers for the fusion of multimodal data in oncology, spotlighting key studies and their pivotal findings. We discuss the unique challenges of multimodal learning, such as data heterogeneity and integration complexities, alongside the opportunities it presents for a more nuanced and comprehensive understanding of cancer. Finally, we present some of the latest comprehensive multimodal pan-cancer data sources. By surveying the landscape of multimodal data integration in oncology, our goal is to underline the transformative potential of multimodal GNNs and Transformers. Through technological advancements and the methodological innovations presented in this review, we aim to chart a course for future research in this promising field. This review may be the first that highlights the current state of multimodal modeling applications in cancer using GNNs and transformers, presents comprehensive multimodal oncology data sources, and sets the stage for multimodal evolution, encouraging further exploration and development in personalized cancer care.

Rolosense: Mechanical Detection of SARS-CoV-2 Using a DNA-Based Motor

Assays that detect viral infections play a significant role in limiting the spread of diseases such as SARS-CoV-2. Here, we present Rolosense, a virus sensing platform that leverages the motion of 5 μm DNA-based motors on RNA fuel chips to transduce the presence of viruses. Motors and chips are modified with aptamers, which are designed for multivalent binding to viral targets and lead to stalling of motion. Therefore, the motors perform a "mechanical test" of the viral target and stall in the presence of whole virions, which represents a unique mechanism of transduction distinct from conventional assays. Rolosense can detect SARS-CoV-2 spiked in artificial saliva and exhaled breath condensate with a sensitivity of 103 copies/mL and discriminates among other respiratory viruses. The assay is modular and amenable to multiplexing, as demonstrated by our one-pot detection of influenza A and SARS-CoV-2. As a proof of concept, we show that readout can be achieved using a smartphone camera with a microscopic attachment in as little as 15 min without amplification reactions. Taken together, these results show that mechanical detection using Rolosense can be broadly applied to any viral target and has the potential to enable rapid, low-cost point-of-care screening of circulating viruses.

Characterizing Acute Pulmonary Embolism Cases Diagnosed at an Emergency Department Revisit Using a Statewide Clinical Registry

STUDY OBJECTIVE

To assess the rate and characteristics of acute pulmonary embolism (PE) cases diagnosed in the emergency department (ED) following an ED discharge visit within 10 days.

METHODS

This is a retrospective analysis of 40 EDs in a statewide clinical registry from 2017 to 2022. We identified adult patients with acute PEs diagnosed in the ED. We assessed PE cases wherein a prior ED visit for the same patient resulting in discharge had taken place within 10 days without interval hospitalization. We then characterized the overall rate of revisit PE cases per overall acute PE cases and per 10,000 ED discharges. We also reported on subgroups of revisit cases where the preceding visit resulted in diagnosis of COVID-19, other cardiopulmonary conditions, and cardiopulmonary symptom codes (eg, chest pain, unspecified).

RESULTS

Of 24,525 acute PEs, 1,202 (4.9%, 95% confidence interval [CI] 4.6% to 5.2%) had an ED discharge within the preceding 10 days (2.0 per 10,000 ED discharges, 95% CI 1.9 to 2.1). Two hundred thirty-three (19.4%) were originally discharged with a COVID-19 diagnosis, 107 (8.9%) were originally discharged with another cardiopulmonary condition, and 201 (16.7%) were cases discharged with a nonspecific cardiopulmonary symptom code. Discharges with diagnoses of COVID-19, pneumonia, and pleural effusion had higher rates of revisits with acute PE.

CONCLUSION

In this retrospective analysis, about 1 in 20 acute PEs and 2 in 10,000 ED discharges were associated with an ED revisit for acute PE. Some cases may represent potential diagnostic opportunities, whereas others may be progression of disease, risk factors for PE, or unrelated.

Effects of interacting with a large language model compared with a human coach on the clinical diagnostic process and outcomes among fourth-year medical students: study protocol for a prospective, randomised experiment using patient vignettes

INTRODUCTION

Versatile large language models (LLMs) have the potential to augment diagnostic decision-making by assisting diagnosticians, thanks to their ability to engage in open-ended, natural conversations and their comprehensive knowledge access. Yet the novelty of LLMs in diagnostic decision-making introduces uncertainties regarding their impact. Clinicians unfamiliar with the use of LLMs in their professional context may rely on general attitudes towards LLMs more broadly, potentially hindering thoughtful use and critical evaluation of their input, leading to either over-reliance and lack of critical thinking or an unwillingness to use LLMs as diagnostic aids. To address these concerns, this study examines the influence on the diagnostic process and outcomes of interacting with an LLM compared with a human coach, and of prior training vs no training for interacting with either of these 'coaches'. Our findings aim to illuminate the potential benefits and risks of employing artificial intelligence (AI) in diagnostic decision-making.

METHODS AND ANALYSIS

We are conducting a prospective, randomised experiment with N=158 fourth-year medical students from Charité Medical School, Berlin, Germany. Participants are asked to diagnose patient vignettes after being assigned to either a human coach or ChatGPT and after either training or no training (both between-subject factors). We are specifically collecting data on the effects of using either of these 'coaches' and of additional training on information search, number of hypotheses entertained, diagnostic accuracy and confidence. Statistical methods will include linear mixed effects models. Exploratory analyses of the interaction patterns and attitudes towards AI will also generate more generalisable knowledge about the role of AI in medicine.

ETHICS AND DISSEMINATION

The Bern Cantonal Ethics Committee considered the study exempt from full ethical review (BASEC No: Req-2023-01396). All methods will be conducted in accordance with relevant guidelines and regulations. Participation is voluntary and informed consent will be obtained. Results will be published in peer-reviewed scientific medical journals. Authorship will be determined according to the International Committee of Medical Journal Editors guidelines.

Essential New Complexity-Based Themes for Patient-Centered Diagnosis and Treatment of Dementia and Predementia in Older People: Multimorbidity and Multilevel Phenomenology

Dementia is a highly prevalent condition with devastating clinical and socioeconomic sequela. It is expected to triple in prevalence by 2050. No treatment is currently known to be effective. Symptomatic late-onset dementia and predementia (SLODP) affects 95% of patients with the syndrome. In contrast to trials of pharmacological prevention, no treatment is suggested to remediate or cure these symptomatic patients. SLODP but not young onset dementia is intensely associated with multimorbidity (MUM), including brain-perturbating conditions (BPCs). Recent studies showed that MUM/BPCs have a major role in the pathogenesis of SLODP. Fortunately, most MUM/BPCs are medically treatable, and thus, their treatment may modify and improve SLODP, relieving suffering and reducing its clinical and socioeconomic threats. Regrettably, the complex system features of SLODP impede the diagnosis and treatment of the potentially remediable conditions (PRCs) associated with them, mainly due to failure of pattern recognition and a flawed diagnostic workup. We suggest incorporating two SLODP-specific conceptual themes into the diagnostic workup: MUM/BPC and multilevel phenomenological themes. By doing so, we were able to improve the diagnostic accuracy of SLODP components and optimize detecting and favorably treating PRCs. These revolutionary concepts and their implications for remediability and other parameters are discussed in the paper.

Outpatient reception via collaboration between nurses and a large language model: a randomized controlled trial

Reception is an essential process for patients seeking medical care and a critical component influencing the healthcare experience. However, current communication systems rely mainly on human efforts, which are both labor and knowledge intensive. A promising alternative is to leverage the capabilities of large language models (LLMs) to assist the communication in medical center reception sites. Here we curated a unique dataset comprising 35,418 cases of real-world conversation audio corpus between outpatients and receptionist nurses from 10 reception sites across two medical centers, to develop a site-specific prompt engineering chatbot (SSPEC). The SSPEC efficiently resolved patient queries, with a higher proportion of queries addressed in fewer rounds of queries and responses (Q&Rs; 68.0% ≤2 rounds) compared with nurse-led sessions (50.5% ≤2 rounds) (P = 0.009) across administrative, triaging and primary care concerns. We then established a nurse-SSPEC collaboration model, overseeing the uncertainties encountered during the real-world deployment. In a single-center randomized controlled trial involving 2,164 participants, the primary endpoint indicated that the nurse-SSPEC collaboration model received higher satisfaction feedback from patients (3.91 ± 0.90 versus 3.39 ± 1.15 in the nurse group, P < 0.001). Key secondary outcomes indicated reduced rate of repeated Q&R (3.2% versus 14.4% in the nurse group, P < 0.001) and reduced negative emotions during visits (2.4% versus 7.8% in the nurse group, P < 0.001) and enhanced response quality in terms of integrity (4.37 ± 0.95 versus 3.42 ± 1.22 in the nurse group, P < 0.001), empathy (4.14 ± 0.98 versus 3.27 ± 1.22 in the nurse group, P < 0.001) and readability (3.86 ± 0.95 versus 3.71 ± 1.07 in the nurse group, P = 0.006). Overall, our study supports the feasibility of integrating LLMs into the daily hospital workflow and introduces a paradigm for improving communication that benefits both patients and nurses. Chinese Clinical Trial Registry identifier: ChiCTR2300077245 .

Patient and caregiver perspectives on causes and prevention of ambulatory adverse events: multilingual qualitative study

CONTEXT

Ambulatory adverse events (AEs) affect up to 25% of the global population and cause over 7 million preventable hospital admissions around the world. Though patients and caregivers are key actors in promoting and monitoring their own ambulatory safety, healthcare teams do not traditionally partner with patients in safety efforts. We sought to identify what patients and caregivers contribute when engaged in ambulatory AE review, focusing on under-resourced care settings.

METHODS

We recruited adult patients, caregivers and patient advisors who spoke English, Spanish and/or Cantonese, from primary care clinics affiliated with a public health network in the USA. All had experience taking or managing a high-risk medication (blood thinners, insulin or opioid). We presented two exemplar ambulatory AEs: one involving a warfarin drug-drug interaction, and one involving delayed diagnosis of colon cancer. We conducted semistructured focus groups and interviews to elicit participants' perceptions of causal factors and potential preventative measures for similar AEs. The study team conducted a mixed inductive-deductive qualitative analysis to derive major themes.

FINDINGS

The sample included 6 English-speaking patients (2 in the focus group, 4 individual interviews), 6 Spanish-speaking patients (individual interviews), 4 Cantonese-speaking patients (2 in the focus group, 2 interviews), and 6 English-speaking patient advisors (focus group). Themes included: (1) Patients and teams have specific safety responsibilities; (2) Proactive communication drives safe ambulatory care; (3) Barriers related to limited resources contribute to ambulatory AEs. Patients and caregivers offered ideas for operational changes that could drive new safety projects.

CONCLUSIONS

An ethnically and linguistically diverse group of primary care patients and caregivers defined their agency in ensuring ambulatory safety and offered pragmatic ideas to prevent AEs they did not directly experience. Patients and caregivers in a safety net health system can feasibly participate in AE review to ensure that safety initiatives include their valuable perspectives.

The potential, limitations, and future of diagnostics enhanced by generative artificial intelligence

OBJECTIVES

This short communication explores the potential, limitations, and future directions of generative artificial intelligence (GAI) in enhancing diagnostics.

METHODS

This commentary reviews current applications and advancements in GAI, particularly focusing on its integration into medical diagnostics. It examines the role of GAI in supporting medical interviews, assisting in differential diagnosis, and aiding clinical reasoning through the lens of dual-process theory. The discussion is supported by recent examples and theoretical frameworks to illustrate the practical and potential uses of GAI in medicine.

RESULTS

GAI shows significant promise in enhancing diagnostic processes by supporting the translation of patient descriptions into visual formats, providing differential diagnoses, and facilitating complex clinical reasoning. However, limitations such as the potential for generating medical misinformation, known as hallucinations, exist. Furthermore, the commentary highlights the integration of GAI with both intuitive and analytical decision-making processes in clinical diagnostics, demonstrating potential improvements in both the speed and accuracy of diagnoses.

CONCLUSIONS

While GAI presents transformative potential for medical diagnostics, it also introduces risks that must be carefully managed. Future advancements should focus on refining GAI technologies to better align with human diagnostic reasoning, ensuring GAI enhances rather than replaces the medical professionals' expertise.

Reasoning Report: Engineering Case Conferences to Maximize Clinical Reasoning Education for All Learners

Case conferences, specifically those in which an unknown case is presented and discussed, are widely utilized in the delivery of medical education. However, the format of case conferences is not always optimized to engage and challenge audience members' clinical reasoning (CR). Based on the current conception of CR and our experience, we provide recommendations on how to better engineer case conferences to maximize CR education for learners at all levels through case selection, conference format, and intentional case construction.

How to fight fake papers: a review on important information sources and steps towards solution of the problem

Scientific fake papers, containing manipulated or completely fabricated data, are a problem that has reached dramatic dimensions. Companies known as paper mills (or more bluntly as "criminal science publishing gangs") produce and sell such fake papers on a large scale. The main drivers of the fake paper flood are the pressure in academic systems and (monetary) incentives to publish in respected scientific journals and sometimes the personal desire for increased "prestige." Published fake papers cause substantial scientific, economic, and social damage. There are numerous information sources that deal with this topic from different points of view. This review aims to provide an overview of these information sources until June 2024. Much more original research with larger datasets is needed, for example on the extent and impact of the fake paper problem and especially on how to detect them, as many findings are based more on small datasets, anecdotal evidence, and assumptions. A long-term solution would be to overcome the mantra of publication metrics for evaluating scientists in academia.

Interprofessional clinical reasoning education

Clinical reasoning is considered one of the most important competencies but is not included in most healthcare curricula. The number and diversity of patient encounters are the decisive factors in the development of clinical reasoning competence. Physical real patient encounters are considered optimal, but virtual patient cases also promote clinical reasoning. A high-volume, low-fidelity virtual patient library thus can support clinical reasoning training in a safe environment and can be tailored to the needs of learners from different health care professions. It may also stimulate interprofessional understanding and team shared decisions. Implementation will be challenged by tradition, the lack of educator competence and prior experience as well as the high-density curricula at medical and veterinary schools and will need explicit address from curriculum managers and education leads.

Diagnostic errors and characteristics of patients seen at a general internal medicine outpatient clinic with a referral for diagnosis

OBJECTIVES

Patients referred to general internal medicine (GIM) outpatient clinics may face a higher risk of diagnostic errors than non-referred patients. This difference in risk is assumed to be due to the differences in diseases and clinical presentations between referred and non-referred patients; however, clinical data regarding this issue are scarce. This study aimed to determine the frequency of diagnostic errors and compare the characteristics of referred and non-referred patients visit GIM outpatient clinics.

METHODS

This study included consecutive outpatients who visited the GIM outpatient clinic at a university hospital, with or without referral. Data on age, sex, chief complaints, referral origin, and final diagnosis were collected from medical records. The Revised Safer Dx Instrument was used to detect diagnostic errors.

RESULTS

Data from 534 referred and 599 non-referred patients were analyzed. The diagnostic error rate was higher in the referral group than that in the non-referral group (2.2 % vs. 0.5 %, p=0.01). The prevalence of abnormal test results and sensory disturbances was higher in the chief complaints, and the prevalence of musculoskeletal system disorders, connective tissue diseases, and neoplasms was higher in the final diagnoses of referred patients compared with non-referred patients. Among referred patients with diagnostic errors, abnormal test results and sensory disturbances were the two most common chief complaints, whereas neoplasia was the most common final diagnosis. Problems with data integration and interpretation were found to be the most common factors contributing to diagnostic errors.

CONCLUSIONS

Paying more attention to patients with abnormal test results and sensory disturbances and considering a higher pre-test probability for neoplasms may prevent diagnostic errors in patients referred to GIM outpatient clinics.

A Dynamic and Effective Peptide-Based Strategy for Promptly Addressing Emerging SARS-CoV-2 Variants of Concern

Genomic surveillance based on sequencing the entire genetic code of SARS-CoV-2 involves monitoring and studying genetic changes and variations in disease-causing organisms such as viruses and bacteria. By tracing the virus, it is possible to prevent epidemic spread in the community, ensuring a 'precision public health' strategy. A peptide-based design was applied to provide an efficacious strategy that is able to counteract any emerging viral variant of concern dynamically and promptly to affect the outcomes of a pandemic at an early stage while waiting for the production of the anti-variant-specific vaccine, which require longer times. The inhibition of the interaction between the receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and one of the cellular receptors (DPP4) that its receptors routinely bind to infect human cells is an intriguing therapeutic approach to prevent the virus from entering human cells. Among the other modalities developed for this purpose, peptides surely offer unique advantages, including ease of synthesis, serum stability, low immunogenicity and toxicity, and small production and distribution chain costs. Here, we obtained a potent new inhibitor based on the rearrangement of a previously identified peptide that has been rationally designed on a cell dipeptidyl peptidase 4 (DPP4) sequence, a ubiquitous membrane protein known to bind the RBD-SPIKE domain of the virus. This novel peptide (named DPP4-derived), conceived as an endogenous "drug", is capable of targeting the latest tested variants with a high affinity, reducing the VSV* DG-Fluc pseudovirus Omicron's infection capacity by up to 14%, as revealed by in vitro testing in human Calu-3 cells. Surface plasmon resonance (SPR) confirmed the binding affinity of the new DPP4-derived peptide with Omicron variant RBD.