Pulmonary embolism in patients with chronic coronary syndrome masquerading as acute coronary syndrome: a case report and literature review.

BACKGROUND: Pulmonary embolisms (PEs) exhibit clinical features similar to those of acute coronary syndrome (ACS), including electrocardiographic abnormalities and elevated troponin levels, which frequently lead to misdiagnoses in emergency situations. CASE PRESENTATION: Here, we report a case of PE coinciding with chronic coronary syndrome in which the patient's condition was obscured by symptoms mimicking ACS. A 68-year-old female with syncope presented to the hospital. Upon admission, she was found to have elevated troponin levels and an electrocardiogram showing ST-segment changes across multiple leads, which initially led to a diagnosis of ACS. Emergency coronary arteriography revealed occlusion of the posterior branches of the left ventricle of the right coronary artery, but based on the complexity of the intervention, the occlusion was considered chronic rather than acute. On the 3rd day after admission, the patient experienced recurrent chest tightness and shortness of breath, which was confirmed as acute PE by emergency computed tomography pulmonary angiography. Following standardized anticoagulation treatment, the patient improved and was subsequently discharged. CONCLUSIONS: This case report highlights the importance of recognizing the nonspecific features of PE. Clinicians should be vigilant when identifying other clinical features that are difficult to explain accompanying the expected disease, and it is necessary to carefully identify the causes to prevent missed diagnoses or misdiagnoses.

Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research.

Background: The persistence of diagnostic errors, despite advances in medical knowledge and diagnostics, highlights the importance of understanding atypical disease presentations and their contribution to mortality and morbidity. Artificial intelligence (AI), particularly generative pre-trained transformers like GPT-4, holds promise for improving diagnostic accuracy, but requires further exploration in handling atypical presentations. Objective: This study aimed to assess the diagnostic accuracy of ChatGPT in generating differential diagnoses for atypical presentations of common diseases, with a focus on the model's reliance on patient history during the diagnostic process. Methods: We used 25 clinical vignettes from the Journal of Generalist Medicine characterizing atypical manifestations of common diseases. Two general medicine physicians categorized the cases based on atypicality. ChatGPT was then used to generate differential diagnoses based on the clinical information provided. The concordance between AI-generated and final diagnoses was measured, with a focus on the top-ranked disease (top 1) and the top 5 differential diagnoses (top 5). Results: ChatGPT's diagnostic accuracy decreased with an increase in atypical presentation. For category 1 (C1) cases, the concordance rates were 17% (n=1) for the top 1 and 67% (n=4) for the top 5. Categories 3 (C3) and 4 (C4) showed a 0% concordance for top 1 and markedly lower rates for the top 5, indicating difficulties in handling highly atypical cases. The χ2 test revealed no significant difference in the top 1 differential diagnosis accuracy between less atypical (C1+C2) and more atypical (C3+C4) groups (χ²1=2.07; n=25; P=.13). However, a significant difference was found in the top 5 analyses, with less atypical cases showing higher accuracy (χ²1=4.01; n=25; P=.048). Conclusions: ChatGPT-4 demonstrates potential as an auxiliary tool for diagnosing typical and mildly atypical presentations of common diseases. However, its performance declines with greater atypicality. The study findings underscore the need for AI systems to encompass a broader range of linguistic capabilities, cultural understanding, and diverse clinical scenarios to improve diagnostic utility in real-world settings.

Laboratory specimen rejection rate and associated factors among referred specimens at Debre Markos Referral Hospital, Ethiopia: prospective cross-sectional study.

Introduction: laboratory errors mostly emerge from the pre-analytical phase, mainly those related to collection, handling, transportation, and storage of diagnostic specimens. Specimen rejection due to improper sample collection, may lead to poor patient outcomes, such as incorrect diagnosis, inappropriate treatment, and death. This study aimed to assess the specimen rejection rate and associated factors among referred specimens at Debre Markos Referral Hospital. Methods: a prospective cross-sectional study design was applied from January 2020 to April 2020 to investigate specimen rejection rate and associated factors among referred specimens. The study population was all laboratory specimens referred for viral load, CD4 count, gene expert, and early infant diagnosis to the Debre Markos Referral Hospital laboratory. The statistical analysis was done with Statistical Package for Social Sciences version 20.0 software. Results: of the total of 2750 specimens submitted to the laboratory from January 2020 to April 2020, 37 (1.34%) specimens were rejected due to different reasons like insufficient volume, hemolysis, and an inappropriate specimen container. Specimen collector training status and experience had a significant association with the specimen rejection rate. Conclusion: the results of our study show that the specimen rejection rate among referred specimens was high, indicating that more interventions are required to decrease the specimen rejection rate.

Odontogenic Cutaneous Fistula: A Zombie Diagnosis.

BACKGROUND: Odontogenic cutaneous fistula (OCF) is a pathologic communication between the cutaneous surface of the face and oral cavity. Majority of oral cutaneous fistulas are reported to arise from chronic dental infection. Delay in treatment may result in chronic tissue injury as well as cosmetic deformities. Lesions are often misdiagnosed, leading to delayed management. Misdiagnosis may be the result of the variability of clinical morphological presentation and location of lesions compounded by the lack of knowledge that these lesions can have dental etiology. It is estimated that half of patients with OCF undergo multiple dermatologic surgical operations, antibiotic regimens, and other excisions and biopsies before a correct diagnosis is made. Herein, we present a systematic review to detail cases of odontogenic cutaneous lesions that had been previously misdiagnosed or managed inappropriately. In addition, we include a case report from our own institution. The aims are to demonstrate various presentations of OCF, increase awareness of plastic surgeons and oral maxillofacial surgeons to this pathological condition, and reinforce the importance of prompt diagnosis and treatment. METHODS: The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A literature search was conducted in PubMed, Web of Science, and Cochrane databases from January 1, 2013 to July 24, 2023. The following search terms were utilized: "odontogenic cutaneous fistula" OR "odontogenic cutaneous sinus." RESULTS: Twenty-three articles published between 2013 and 2023 were included in this review. In addition, we report a case from our own institution. A total of 28 cases were included in the review. CONCLUSIONS: Diagnosis of OCF is challenging for numerous reasons. Misdiagnosis can lead to multiple trials of antibiotics and surgical procedures as well as reoccurrence of the lesion. Cases summarized highlight the importance of communication between oral maxillofacial surgery, plastic surgery, other medical subspecialists, and dentists in the evaluation of patients with head and neck lesions. Physicians should consider dental etiology in the differential diagnosis of orofacial skin lesions, even if teeth appear normal on oral examination.

Spectrum of Cognitive Biases in Diagnostic Radiology.

Cognitive biases are systematic thought processes involving the use of a filter of personal experiences and preferences arising from the tendency of the human brain to simplify information processing, especially when taking in vast amounts of data such as from imaging studies. These biases encompass a wide spectrum of thought processes and frequently overlap in their concepts, with multiple biases usually in operation when interpretive and perceptual errors occur in radiology. The authors review the gamut of cognitive biases that occur in radiology. These biases are organized according to their expected stage of occurrence while the radiologist reads and interprets an imaging study. In addition, the authors propose several additional cognitive biases that have not yet, to their knowledge, been defined in the radiologic literature but are applicable to diagnostic radiology. Case examples are used to illustrate potential biases and their impact, with emergency radiology serving as the clinical paradigm, given the associated high imaging volumes, wide diversity of imaging examinations, and rapid pace, which can further increase a radiologist's reliance on biases and heuristics. Potential strategies to recognize and overcome one's personal biases at each stage of image interpretation are also discussed. Awareness of such biases and their unintended effects on imaging interpretations and patient outcomes may help make radiologists cognizant of their own biases that can result in diagnostic errors. Identification of cognitive bias in departmental and systematic quality improvement practices may represent another tool to prevent diagnostic errors in radiology. ©RSNA, 2024 See the invited commentary by Larson in this issue.

Performance evaluation of ChatGPT in detecting diagnostic errors and their contributing factors: an analysis of 545 case reports of diagnostic errors.

BACKGROUND: Manual chart review using validated assessment tools is a standardised methodology for detecting diagnostic errors. However, this requires considerable human resources and time. ChatGPT, a recently developed artificial intelligence chatbot based on a large language model, can effectively classify text based on suitable prompts. Therefore, ChatGPT can assist manual chart reviews in detecting diagnostic errors. OBJECTIVE: This study aimed to clarify whether ChatGPT could correctly detect diagnostic errors and possible factors contributing to them based on case presentations. METHODS: We analysed 545 published case reports that included diagnostic errors. We imputed the texts of case presentations and the final diagnoses with some original prompts into ChatGPT (GPT-4) to generate responses, including the judgement of diagnostic errors and contributing factors of diagnostic errors. Factors contributing to diagnostic errors were coded according to the following three taxonomies: Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC) and Generic Diagnostic Pitfalls (GDP). The responses on the contributing factors from ChatGPT were compared with those from physicians. RESULTS: ChatGPT correctly detected diagnostic errors in 519/545 cases (95%) and coded statistically larger numbers of factors contributing to diagnostic errors per case than physicians: DEER (median 5 vs 1, p<0.001), RDC (median 4 vs 2, p<0.001) and GDP (median 4 vs 1, p<0.001). The most important contributing factors of diagnostic errors coded by ChatGPT were 'failure/delay in considering the diagnosis' (315, 57.8%) in DEER, 'atypical presentation' (365, 67.0%) in RDC, and 'atypical presentation' (264, 48.4%) in GDP. CONCLUSION: ChatGPT accurately detects diagnostic errors from case presentations. ChatGPT may be more sensitive than manual reviewing in detecting factors contributing to diagnostic errors, especially for 'atypical presentation'.

Misidentification of Brucella melitensis as Ochrobactrum species: potential pitfalls in the diagnosis of brucellosis.

We describe a case of brucellosis in a man in his 20s, who presented to the emergency department with a 1-month history of fevers, dry cough and knee pain. Blood cultures were positive after 55 hours and Ochrobactrum daejeonense was identified on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometry. Ochrobactrum spp are Gram-negative organisms that are phylogenetically related to Brucella spp but commercially available MALDI-TOF libraries cannot distinguish between the two genera. Further positive blood cultures for O. daejeonense combined with characteristic growth patterns for Brucella spp led to targeted questioning of the patient regarding potential exposure risks, which revealed a history of consumption of unpasteurised camel milk in the Middle East 3 months earlier. Treatment of brucellosis was initiated and subsequent whole genome sequencing identified the blood culture isolate as Brucella melitensis confirming the diagnosis of brucellosis. This case highlights the challenges in the diagnosis of brucellosis in low-incidence settings.

[Analysis of cases of cervical cystic lymph node metastasis with an unknown primary misdiagnosed as branchial cleft carcinoma].

Objectives: To analyze the location, discovery time and possible causes of cases of cervical cystic lymph node metastasis with an unknown primary misdiagnosed as branchial cleft carcinoma. Methods: A retrospective analysis was performed on clinical and pathological data of 15 patients misdiagnosed as branchiogenic carcinoma at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College between January 2000 and December 2020. Results: Among the 15 patients, 6 were nasopharyngeal squamous cell carcinoma, 4 tonsil squamous cell carcinoma, 2 tongue root squamous cell carcinoma, 2 hypopharyngeal squamous cell carcinoma and 1 thyroid papillary carcinoma. The median time from the diagnosis of branchial cleft carcinoma to the discovery of primary lesions was 3.58 months (0-76 months). The causes of misdiagnosis might be the lack of experience in the diagnosis and treatment of branchial cleft carcinoma, and not enough attention to comprehensive examination and close follow-up. Conclusions: Different from oropharyngeal cancer reported internationally, the proportion of misdiagnosed cases with nasopharyngeal carcinoma as the primary site in the current article is higher. As a country with a high incidence of nasopharyngeal carcinoma, the examination of nasopharynx should not be taken lightly. Most hidden cases can be found in the comprehensive examination in a short time, while a few cases need long-term follow-up. Finding the primary sites should not rely too much on imaging examination, and we cannot ignore the importance of clinical physical examination.

Medication-Related Osteonecrosis of the Jaw (MRONJ) Mistaken for Acute Apical Abscess.

The objective of this case study is to report on the diagnosis and treatment of medication-related osteonecrosis of the jaw (MRONJ), which was originally misdiagnosed and mistreated as endodontic disease. A patient was referred for worsening odontalgia despite root canal therapy on tooth No. 19 and a course of oral antibiotics. Examination demonstrated slight buccal swelling and tenderness in the left masseter and a 7-mm diameter area of exposed bone on the mandibular left lingual torus. Further history-taking revealed prior bisphosphonate therapy for metastatic breast cancer. MRONJ was identified as the likely diagnosis, and the patient was appropriately referred to oral and maxillofacial surgery where the diagnosis was confirmed and surgical debridement performed. The case study demonstrates how the symptomatology and presentation of MRONJ can resemble endodontic disease and that timely and appropriate treatment requires eliciting an in-depth medical history, reaching a complete pulpal and periapical diagnosis, and remaining attentive to the presence of exposed bone on examination.

[Possibilities of using results of head computed tomography in victims with traumatic brain injuries]. / Vozmozhnosti ispol'zovaniya rezul'tatov komp'yuternoi tomografii golovy u poterpevshikh s cherepno-mozgovoi travmoi.

The constant increase in the number of neurotraumas in the country leads to an increase in forensic examinations of a persons. In Russia, about 600 thousand people receive craniocerebral injuries annually, of which 50 thousand die, others are potentially will be in forensic examination during or after treatment. With an increase in the total number of such examinations, the number of erroneous conclusions is expected to increase. If it is impossible for the radiologist included in the commission to review the results of computed tomography of the head performed in the hospital, the experts are forced to use the data that are recorded in the medical documents. The present study revealed the percentage of erroneous interpretations in such descriptions, systematized typical errors, calculated the sensitivity, specificity and accuracy of computed tomography in craniocerebral injury.

Explanatory argumentation in natural language for correct and incorrect medical diagnoses.

BACKGROUND: A huge amount of research is carried out nowadays in Artificial Intelligence to propose automated ways to analyse medical data with the aim to support doctors in delivering medical diagnoses. However, a main issue of these approaches is the lack of transparency and interpretability of the achieved results, making it hard to employ such methods for educational purposes. It is therefore necessary to develop new frameworks to enhance explainability in these solutions. RESULTS: In this paper, we present a novel full pipeline to generate automatically natural language explanations for medical diagnoses. The proposed solution starts from a clinical case description associated with a list of correct and incorrect diagnoses and, through the extraction of the relevant symptoms and findings, enriches the information contained in the description with verified medical knowledge from an ontology. Finally, the system returns a pattern-based explanation in natural language which elucidates why the correct (incorrect) diagnosis is the correct (incorrect) one. The main contribution of the paper is twofold: first, we propose two novel linguistic resources for the medical domain (i.e, a dataset of 314 clinical cases annotated with the medical entities from UMLS, and a database of biological boundaries for common findings), and second, a full Information Extraction pipeline to extract symptoms and findings from the clinical cases and match them with the terms in a medical ontology and to the biological boundaries. An extensive evaluation of the proposed approach shows the our method outperforms comparable approaches. CONCLUSIONS: Our goal is to offer AI-assisted educational support framework to form clinical residents to formulate sound and exhaustive explanations for their diagnoses to patients.

The discrepancy of antemortem clinical diagnosis and postmortem autopsy diagnosis of lung pathologies in under-five deaths and the reasons for discrepancies: a case series analysis.

BACKGROUND: Diagnostic autopsy is the most reliable approach to definitively ascertain the cause of death and evaluate the accuracy of antemortem clinical diagnoses. Identifying diagnostic discrepancies is vital to understanding common gaps in antemortem clinical diagnoses and modifying antemortem diagnostic approaches to increase the accuracy of clinical diagnosis. The objective of this study was to determine the frequency of diagnostic discrepancies between antemortem clinical diagnoses and postmortem autopsies on lung pathologies and to understand the reasons for diagnostic discrepancies among cases included in Child Health and Mortality Prevention Surveillance (CHAMPS) in Ethiopia. METHODS: A clinical case series study of deaths among children under-five in the CHAMPS study at three sites in Ethiopia between October 2019 and April 2022 was conducted. The antemortem clinical diagnoses and postmortem pathological diagnoses of the lung were compared for each case. Two senior physicians assessed the findings for both agreement and disagreement. McNemar's test was used to assess for statistically significant differences between antemortem and postmortem diagnoses. RESULTS: Seventy-five cases were included (73.3% male). Over half (54.7%) died between the 1st and 7th day of life. Sepsis (66.7%), pneumonia (6.7%), and meconium aspiration syndrome (5.0%) were the most common immediate causes of death. Half (52%) of cases were correctly diagnosed antemortem. The magnitude of diagnostic discrepancy was 35% (95% CI: 20-47%). The most common contributing factors to diagnostic discrepancy were gaps in knowledge (22/75, 35.5%) and problems in consultation and teamwork (22/75, 35.5%). CONCLUSIONS: Misdiagnoses were common among young children who died with positive lung pathology findings. In-service education initiatives and multidisciplinary collaboration are needed to mitigate high rates of diagnostic discrepancies among young children to potentially prevent future deaths.

Clinical distinctions in symptomatology and psychiatric comorbidities between misdiagnosed bipolar I and bipolar II disorder versus major depressive disorder.

BACKGROUND: To explore the demographic and clinical features of current depressive episode that discriminate patients diagnosed with major depressive disorder (MDD) from those with bipolar I (BP-I) and bipolar II (BP-II) disorder who were misdiagnosed as having MDD . METHODS: The Mini-International Neuropsychiatric Interview (MINI) assessment was performed to establish DSM-IV diagnoses of MDD, and BP-I and BP-II, previously being misdiagnosed as MDD. Demographics, depressive symptoms and psychiatric comorbidities were compared between 1463 patients with BP-I, BP-II and MDD from 8 psychiatric settings in mainland China. A multinomial logistic regression model was performed to assess clinical correlates of diagnoses. RESULTS: A total of 14.5% of the enrolled patients initially diagnosed with MDD were eventually diagnosed with BP. Broad illness characteristics including younger age, higher prevalence of recurrence, concurrent dysthymia, suicidal attempts, agitation, psychotic features and psychiatric comorbidities, as well as lower prevalence of insomnia, weight loss and somatic symptoms were featured by patients with BP-I and/or BP-I, compared to those with MDD. Comparisons between BP-I and BP-II versus MDD indicated distinct symptom profiles and comorbidity patterns with more differences being observed between BP-II and MDD, than between BP-I and MDD . CONCLUSION: The results provide evidence of clinically distinguishing characteristics between misdiagnosed BP-I and BP- II versus MDD. The findings have implications for guiding more accurate diagnoses of bipolar disorders.

Pulmonary artery sarcoma affecting the pulmonary valve mistaken as pulmonary vasculitis: a case report and comparative literature review.

Pulmonary arterial sarcomas (PAS) are rare aggressive tumours occurring mainly in the pulmonary trunk. We report a case of PAS involving the pulmonary trunk wall and valve, with uniform wall thickening which represents an atypical imaging manifestation of this tumour. A 63-year-old male presented with vague respiratory symptoms with rapid progression. CTPA showed low density filling defects in both pulmonary arteries and PET scan showed increased uptake in the pulmonary trunk, which along with raised ESR suggested Pulmonary Vasculitis. Echo imaging showed Right ventricular hypertrophy and pulmonary stenosis. Response to steroid therapy was minimal and his symptoms worsened. A referral for second opinion was made and he was diagnosed with PAS. He underwent Pulmonary thromboendarterectomy with Pulmonary valve replacement. Post-operative histopathology confirmed the diagnosis. PAS is rare and frequently misdiagnosed. Surgical resection is not curative, but together with chemotherapy can prolong survival.

Stakeholder perspectives on contributors to delayed and inaccurate diagnosis of cardiovascular disease and their implications for digital health technologies: a UK-based qualitative study.

OBJECTIVE: The aim of this study is to understand stakeholder experiences of diagnosis of cardiovascular disease (CVD) to support the development of technological solutions that meet current needs. Specifically, we aimed to identify challenges in the process of diagnosing CVD, to identify discrepancies between patient and clinician experiences of CVD diagnosis, and to identify the requirements of future health technology solutions intended to improve CVD diagnosis. DESIGN: Semistructured focus groups and one-to-one interviews to generate qualitative data that were subjected to thematic analysis. PARTICIPANTS: UK-based individuals (N=32) with lived experience of diagnosis of CVD (n=23) and clinicians with experience in diagnosing CVD (n=9). RESULTS: We identified four key themes related to delayed or inaccurate diagnosis of CVD: symptom interpretation, patient characteristics, patient-clinician interactions and systemic challenges. Subthemes from each are discussed in depth. Challenges related to time and communication were greatest for both stakeholder groups; however, there were differences in other areas, for example, patient experiences highlighted difficulties with the psychological aspects of diagnosis and interpreting ambiguous symptoms, while clinicians emphasised the role of individual patient differences and the lack of rapport in contributing to delays or inaccurate diagnosis. CONCLUSIONS: Our findings highlight key considerations when developing digital technologies that seek to improve the efficiency and accuracy of diagnosis of CVD.

The diagnosis and misdiagnosis of Sjögren disease.

Although one of the most common systemic autoimmune disorders, Sjögren disease (SjD) may be overlooked in patients presenting with non-specific symptoms or no complaints of sicca symptoms. SjD is not a condition to be missed as patients could present with serious extra-glandular manifestations, including lymphomas. In this article, we discuss the diagnostic pitfalls of this disorder and encourage physicians to consider carefully the 'non-textbook' presentations.