Diagnosis最新文献

Objectives: The MR imaging lesion burden described as "innumerable" is rare, and can present a diagnostic challenge. Brain MR imaging with this descriptive term has not been systematically studied. We determine risk factors and MR imaging sequences helpful in a diagnostic algorithm for innumerable brain MR lesions.

Methods: Twelve thousand four hundred ninety-five brain MR imaging studies done at our institution from July 1, 2013 to June 30, 2016 were surveyed for the term "innumerable". Inclusion criteria included 50 or more parenchymal lesions. Patients were classified into active and chronic groups, based on MR characteristics and clinical features.

Results: One hundred and twenty three reports contained the term "innumerable". Thirty-one met inclusion criteria and 19 showed active, and 12 chronic brain process. The active group included 9 metastasis, 6 infarction, 2 microbleeds, and one each, foreign body granulomatous reaction and fungal abscesses. The MR feature accompanied or heralded onset of illness in eight patients. Malignancy was a risk factor in nine patients with metastasis and in 2 with infarct from cancer-associated hypercoagulation. Other risk factors included immunosuppression, endocarditis, long bone fracture and aortic dissection.

Conclusions: MR defined active innumerable brain lesions occurred in 0.25 % of studies. Fifteen of 19 in the active group were due to metastasis or infarction, defined by T1-weighted gadolinium enhancement and restricted-diffusion respectively. A diagnostic algorithm based on MR imaging features and risk factors can guide critical decision for brain biopsy.

Objectives: During the SARS-CoV-2 pandemic, new patient evaluations in pediatric rheumatology were performed using telehealth. Given the pediatric rheumatology workforce shortage, telehealth may be a way to efficiently triage referrals. The objective was to assess the utility of telehealth visits as a diagnostic tool to accurately assess the need for in-person evaluation.

Methods: This was a retrospective cohort study of patients evaluated by telehealth for a new patient visit from March 1 to June 30, 2020 at a tertiary center. Electronic health record documentation from subsequent rheumatology, specialty, and primary care encounters over the subsequent 4 years were reviewed. The primary outcome was diagnostic concordance, defined as consistency in the documented diagnostic reasoning, between the initial telehealth video visit and in-person follow-up visits.

Results: During the study period, there were 111 telehealth visits, 80 (72 %) of which had follow-up data. 55/80 had in-person rheumatology evaluations. Only 9 % patients had discordant diagnoses, all of whom had initial concern for inflammatory arthritis during the telehealth visit but a diagnosis of a non-inflammatory condition after in-person evaluation. Nine patients with a significant rheumatic disease were identified via telehealth. There were no unplanned ED visits or hospital admissions following telehealth visits. 33 % of patients were found to not warrant rheumatologic follow-up after the telehealth visit.

Conclusions: For pediatric rheumatology new patient evaluations, diagnostic accuracy via telehealth evaluation was high. Providers triaged patients with chronic rheumatologic conditions for in-person evaluations and were able to accurately identify benign conditions that did not require in-person follow-up.

Objectives: Physicians rarely receive formal training on communicating diagnostic uncertainty to patients. Best practices in timing and educational strategies are not established. We aimed to develop, implement and assess a curriculum on communicating uncertainty for medical students.

Methods: This was a pseudorandomized and controlled study. Students on their Internal Medicine Clerkship during the study period from February to August 2023 were invited to participate and separated into control and intervention groups based on assigned rotation site. Students in the intervention group received a curriculum on communicating diagnostic uncertainty. All students completed a subscale of the Physicians' Reaction to Uncertainty Scale (PRUS) at the beginning of their clerkship and at the end of week 4 and an Objective Structured Clinical Examination (OSCE) at the end of week 4.

Results: Fifty-four students participated in the curriculum (29 intervention, 25 control). Intervention group students scored 2.13 points higher than control group students on their skills assessment (mean OSCE for intervention group=14.3, control group=12.17, p<0.001). PRUS increased in both groups, indicating improved tolerance of uncertainty, with no significant difference in change in PRUS between groups (mean change in PRUS for intervention group=2.68, control group=4.82, p=0.33). 97.7 % of students agreed that a curriculum on uncertainty should be included in their medical training.

Conclusions: Students who participated in a curriculum on communication of uncertainty demonstrated superior skills in communicating uncertainty during their OSCE. There was a significant increase in PRUS indicating decreased stress associated with uncertainty for all students. This may reflect high levels of baseline stress associated with starting a clerkship, maturation, exposure to cases, or role-modeling by the clinical team.

Understanding the pathologic basis of diseases and their clinical correlates has been growing in parallel to the relevant advances in science and medicine. However, most reformed medical school curricula have mainly addressed the overall content integration with a less emphasis on explicitly structuring the integration of pathophysiology or other relevant basic sciences in clinical skills (CS) courses. Clinicopathologic Correlations (CPCOR), when effectively designed in CS courses, link the clinical findings to their related basic science fundamental changes. Regular highlighting of relevant CPCORs in CS courses enhances student acquisition of clinical reasoning skills and at the same time triggers their translational scientific curiosity. The six-step CPCOR process, detailed in the manuscript, starts with developing session learning objectives that guide CPCOR content development relevant to the weekly CS case. A typical CPCOR session includes pre-encounter and post-encounter small group activities in which students formulate broad and narrow differential diagnosis respectively. Throughout the session, students discuss risk factors, etiopathogenesis, and history and physical examination findings for the identified differential diagnoses. These small group activities are enhanced by a large group session delivered by a Pathologist-Clinician team that leads student centered CPCOR discussions relevant to the weekly CS case. In addition to the enhanced clinical reasoning skills, the implemented CPCOR process augmented the curricular emphasis of lifelong learning skills while reinforcing the importance of the pathologic basis of the clinical findings. Our streamlined CPCOR process can easily be adapted into other medical school curricula to meet relevant needs of integration and clinical reasoning enhancements.

Objectives: Interpreting skin findings can be challenging for both laypersons and clinicians. Large language models (LLMs) offer accessible decision support, yet their diagnostic capabilities for dermatological images remain underexplored. This study evaluated the diagnostic performance of LLMs based on image interpretation of common dermatological diseases.

Methods: A total of 500 dermatological images, encompassing four prevalent skin conditions (psoriasis, vitiligo, erysipelas and rosacea), were used to compare seven multimodal LLMs (GPT-4o, GPT-4o mini, Gemini 1.5 Pro, Gemini 1.5 Flash, Claude 3.5 Sonnet, Llama3.2 90B and 11B). A standardized prompt was used to generate one top diagnosis.

Results: The highest overall accuracy was achieved by GPT-4o (67.8 %), followed by GPT-4o mini (63.8 %) and Llama3.2 11B (61.4 %). Accuracy varied considerably across conditions, with psoriasis with the highest mean LLM accuracy of 59.2 % and erysipelas demonstrating the lowest accuracy (33.4 %). 11.0 % of all images were misdiagnosed by all LLMs, whereas 11.6 % were correctly diagnosed by all models. Correct diagnoses by all LLMs were linked to clear, disease-specific features, such as sharply demarcated erythematous plaques in psoriasis. Llama3.2 90B was the only LLM to decline diagnosing images, particularly those involving intimate areas of the body.

Conclusions: LLM performance varied significantly, emphasizing the need for cautious usage. Notably, a free, locally hostable model correctly identified the top diagnosis for approximately two-thirds of all images, demonstrating the potential for safer, locally deployed LLMs. Advancements in model accuracy and the integration of clinical metadata could further enhance accessible and reliable clinical decision support systems.

Objectives: Scandinavian evaluation of laboratory equipment for point of care testing (SKUP) provides objective and supplier-independent information about analytical quality and user-friendliness of point-of-care (POC) measuring systems. The evaluation reports are freely available online and are valuable tools when selecting fit-for-purpose POC equipment. In this study, we present an overview of the performance of four POC measuring systems for monitoring prothrombin time international normalized ratio (INR) assessed against updated analytical performance specifications (APSs).

Methods: Primary healthcare centres (PHCCs) in Sweden and Norway did the practical work under real-life conditions. In each evaluation, 2-4 PHCCs participated with at least 40 patients on Warfarin treatment per site. Capillary samples were measured on the POC INR systems (qLabs Q3 Plus PT-INR Owren, Xprecia Stride, microINR or ProTime InRhythm), with venous samples analysed at hospital laboratories for comparison (STA-R Evolution or Sysmex CS5100). In the current study, APSs from SKUP, ISO 17593:2022, and CLSI POCT14-Ed2 were used. User-friendliness was assessed by addressing operational facilities, user-manual, time factors, and quality control.

Results: Only microINR coagulometer met the APS for accuracy, while qLabs Q3 Plus PT-INR Owren and ProTime InRhythm met the repeatability criteria. Xprecia Stride scored highest on user-friendliness, whereas the other systems faced challenges with sample application and unclear error messages on the devices.

Conclusions: This study highlights the potential for improvements in POC INR measuring systems and underscores the importance of performing objective evaluations under real-life conditions.

Objectives: The challenges posed by questionable journals to academia are very real, and being able to detect hijacked journals would be valuable to the research community. Using an artificial intelligence (AI) chatbot may be a promising approach to early detection. The purpose of this research is to analyze and benchmark the performance of different AI chatbots in identifying hijacked medical journals.

Methods: This study utilized a dataset comprising 21 previously identified hijacked journals and 10 newly detected hijacked journals, alongside their respective legitimate versions. ChatGPT, Gemini, Copilot, DeepSeek, Qwen, Perplexity, and Claude were selected for benchmarking. Three question types were developed to assess AI chatbots' performance in providing information about hijacked journals, identifying hijacked websites, and verifying legitimate ones.

Results: The results show that current AI chatbots can provide general information about hijacked journals, but cannot reliably identify either real or hijacked journal titles. While Copilot performed better than others, it was not error-free.

Conclusions: Current AI chatbots are not yet reliable for detecting hijacked journals and may inadvertently promote them.

Creativity is an important component of diagnostic reasoning, enabling the generation of novel and effective diagnostic hypotheses, in collaboration with abduction. The creative process not only fosters insight - critical for overcoming diagnostic challenges - but also enhances calibration by encouraging the exploration of alternative hypotheses. Insight, a key component of creativity, emerges when clinicians reconsider problems from fresh perspectives, breaking through diagnostic impasses. Similarly, calibration, essential for mitigating cognitive biases, promotes the generation and evaluation of alternative hypotheses. By fostering insight and calibration, creativity enhances precision and effectiveness of diagnostic reasoning. Leveraging insights from cognitive psychology to promote creativity can further elevate diagnostic reasoning, driving innovation and excellence in diagnosis. This article explores the pivotal role of creativity in diagnostic reasoning, its applications in diagnosis, approaches to nurture it, and its limitations, ultimately aiming to inspire innovation and excellence in the pursuit of diagnostic accuracy and patient care.

Prenatal screening (PNS) can be a very effective strategy for identifying the individuals at-risk of genetic disorders. In contrast to prenatal genetic tests, which are very expensive, require special set-ups and expertise, PNS can be of great help in reducing the burden of genetic disorders, especially in the Indian context. During the last 10 years, several advanced PNS tests utilizing new platforms, with comparatively more sensitivity and specificity, have emerged. PNS tests for chromosomal aneuploidies, microdeletion syndromes, hemoglobinopathies, neural tube defects etc. are available. However, primary health care providers need to be made more aware about the availability of different tests, the time point at which these need to be used, appropriateness of these tests to various presentations and interpretation of the result. They need to be periodically informed about the availability, limitations, sensitivity and specificity of different platforms for PNS. Further, there is a need to develop uniform, updated and practical guidelines on PNS and disseminate these to health care providers so as to benefit the mass population. This article compiles information on different types of PNS and prenatal diagnostic tests, commonly required for different genetic conditions. These recommendations may help clinicians and primary healthcare providers in PNS.