Abnormal performance of peroral endoscopic myotomy (POEM): a case misdiagnosed as achalasia of cardia.

BACKGROUND: Pseudoachalasia is a rare disease that behaves similarly to achalasia (AC), making it sometimes difficult to differentiate. CASE PRESENTATION: We report a case of 49-year-old male with adenocarcinoma of the gastroesophageal junction misdiagnosed as achalasia. No obvious abnormalities were found in his initial examinations including upper digestive endoscopy, upper gastrointestinal imaging and chest computed tomography (CT). During the subsequent introduced-peroral endoscopic myotomy (POEM), it was found that the mucosal layer and the muscular layer had severe adhesion, which did not receive much attention, delayed the clear diagnosis and effect treatment, and ultimately led to a poor prognosis for the patient. CONCLUSIONS: This case suggests that when patients with AC found mucosal and muscular adhesions during POEM surgery, the possibility should be considered that the lesion may be caused by a malignant lesion.

Influence of initial misdiagnosis on mortality in patients with bacteraemia: propensity score matching and propensity score weighting analyses.

BACKGROUND: The diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding. METHODS: Data from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting. RESULTS: Data of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results. CONCLUSION: Thus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.

Demographic bias in misdiagnosis by computational pathology models.

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas. For example, when using common modeling approaches, we observed performance gaps (in area under the receiver operating characteristic curve) between white and Black patients of 3.0% for breast cancer subtyping, 10.9% for lung cancer subtyping and 16.0% for IDH1 mutation prediction in gliomas. We found that richer feature representations obtained from self-supervised vision foundation models reduce performance variations between groups. These representations provide improvements upon weaker models even when those weaker models are combined with state-of-the-art bias mitigation strategies and modeling choices. Nevertheless, self-supervised vision foundation models do not fully eliminate these discrepancies, highlighting the continuing need for bias mitigation efforts in computational pathology. Finally, we demonstrate that our results extend to other demographic factors beyond patient race. Given these findings, we encourage regulatory and policy agencies to integrate demographic-stratified evaluation into their assessment guidelines.

Inaccurate diagnosis of diabetes type in youth: prevalence, characteristics, and implications.

Classifying diabetes at diagnosis is crucial for disease management but increasingly difficult due to overlaps in characteristics between the commonly encountered diabetes types. We evaluated the prevalence and characteristics of youth with diabetes type that was unknown at diagnosis or was revised over time. We studied 2073 youth with new-onset diabetes (median age [IQR] = 11.4 [6.2] years; 50% male; 75% White, 21% Black, 4% other race; overall, 37% Hispanic) and compared youth with unknown versus known diabetes type, per pediatric endocrinologist diagnosis. In a longitudinal subcohort of patients with data for ≥ 3 years post-diabetes diagnosis (n = 1019), we compared youth with steady versus reclassified diabetes type. In the entire cohort, after adjustment for confounders, diabetes type was unknown in 62 youth (3%), associated with older age, negative IA-2 autoantibody, lower C-peptide, and no diabetic ketoacidosis (all, p < 0.05). In the longitudinal subcohort, diabetes type was reclassified in 35 youth (3.4%); this was not statistically associated with any single characteristic. In sum, among racially/ethnically diverse youth with diabetes, 6.4% had inaccurate diabetes classification at diagnosis. Further research is warranted to improve accurate diagnosis of pediatric diabetes type.

Paracoccidioidomycosis manifested by sarcoid-like cutaneous lesions with severe systemic disease: a rare and challenging diagnosis.

Cutaneous involvement in paracoccidioidomycosis (PCM) can exhibit a highly polymorphic spectrum. The infiltrative pattern corresponds to up to 26.6% of observed skin lesions, including sarcoid-like plaques, a rare presentation of cutaneous lesions in PCM. This clinical expression is almost exclusively cutaneous, and its histology reveals a tuberculoid granuloma with a scarcity of fungi, leading to misdiagnosis as other granulomatous diseases. Here, we report a rare form of chronic multifocal paracoccidioidomycosis manifesting as sarcoid-like skin lesions misdiagnosed as granulomatous rosacea in a patient with severe systemic disease.

Utilizing adaptive deformable convolution and position embedding for colon polyp segmentation with a visual transformer.

Polyp detection is a challenging task in the diagnosis of Colorectal Cancer (CRC), and it demands clinical expertise due to the diverse nature of polyps. The recent years have witnessed the development of automated polyp detection systems to assist the experts in early diagnosis, considerably reducing the time consumption and diagnostic errors. In automated CRC diagnosis, polyp segmentation is an important step which is carried out with deep learning segmentation models. Recently, Vision Transformers (ViT) are slowly replacing these models due to their ability to capture long range dependencies among image patches. However, the existing ViTs for polyp do not harness the inherent self-attention abilities and incorporate complex attention mechanisms. This paper presents Polyp-Vision Transformer (Polyp-ViT), a novel Transformer model based on the conventional Transformer architecture, which is enhanced with adaptive mechanisms for feature extraction and positional embedding. Polyp-ViT is tested on the Kvasir-seg and CVC-Clinic DB Datasets achieving segmentation accuracies of 0.9891 ± 0.01 and 0.9875 ± 0.71 respectively, outperforming state-of-the-art models. Polyp-ViT is a prospective tool for polyp segmentation which can be adapted to other medical image segmentation tasks as well due to its ability to generalize well.

Potential Serological Misdiagnosis of Barmah Forest Virus and Ross River Virus Diseases as Chikungunya Virus Infections in Australia: Comparison of ELISA with Neutralization Assay Results.

To evaluate the frequency of errors in the diagnosis of medical laboratory-diagnosed Chikungunya virus (CHIKV) infections in Australia, we studied 42 laboratory-diagnosed CHIKV serum samples from one Queensland medical laboratory by ELISA IgG/IgM and measured the specific neutralization antibodies (Nab) against Barmah Forest virus (BFV), CHIKV and Ross River virus (RRV). The sero-positivity rates for the sera were as follows: anti-BFV IgG+ 19% (8/42), IgM+ 2.4% (1/42) and Nab+ 16.7% (7/42); anti-CHIKV IgG+ 90.5% (38/42), IgM+ 21.4% (9/42) and Nab+ 90.5% (38/42); anti-RRV IgG+ 88.1% (37/42), IgM+ 28.6% (12/42) and Nab+ 83.2% (35/42), respectively. Among the samples with multiple antibody positivity, 2.4% (1/42) showed triple ELISA IgM+, and 14.3% (6/42) exhibited double IgM RRV+CHIKV+; 9.5% (4/42) showed triple IgG+, 76.2% (32/42) displayed double IgG RRV+CHIKV+, 4.8% (2/42) showed IgG BFV+RRV+ and 4.8% (2/42) showed IgG BFV++CHIKV+; and 9.5% (4/42) showed triple Nab+ and 69% (29/42) exhibited double Nab RRV+CHIKV+, respectively. Our analysis of the single-virus infection control Nab results suggested no cross-neutralization between RRV and BFV, and only mild cross-neutralization between CHIKV and RRV, BFV and CHIKV, all with a ≥4-fold Nab titre ratio difference between the true virus infection and cross-reactivity counterpart virus. Subsequently, we re-diagnosed these 42 patients as 1 BFV+, 8 CHIKV+ and 23 RRV+ single-virus infections, along with five RRV+/BFV+ and four RRV+/CHIKV+ double infections, and one possible RRV+/BFV+ or RRV+CHIKV+, respectively. These findings suggests that a substantial proportion of medically attended RRV and BFV infections were misdiagnosed as CHIKV infections, highlighting the imperative need for diagnostic laboratory tests capable of distinguishing between CHIKV infections and actively co-circulating RRV and BFV. For a correct diagnosis, it is crucial to consider reliable diagnostic methods such as the neutralization assay to exclude RRV and BFV.

Imaging of Visceral Vessels.

The visceral vasculature is inextricably intertwined with abdominopelvic disease staging, spread, and management in routine and emergent cases. Comprehensive evaluation requires specialized imaging techniques for abnormality detection and characterization. Vascular pathology is often encountered on nondedicated routine imaging examinations, which may obscure, mimic, or confound many vascular diagnoses. This review highlights normal arterial, portal venous, and systemic venous anatomy and clinically relevant variants; diagnostic pitfalls related to image-acquisition technique and disease mimics; and characteristics of common and rare vascular diseases to empower radiologists to confidently interpret the vascular findings and avoid misdiagnosis.

Endolymphatic sac tumor misdiagnosed as metastatic renal cell carcinoma: Pitfalls in morphology and immunohistochemistry.

Endolymphatic sac tumor (ELST) is a rare disease that originates from the endolymphatic sac system of the inner ear. Being a low-grade malignant tumor, ELST has a mild morphology and is characterized by a slow but aggressive growth. Most clinicians and pathologists are unfamiliar with this disease. ELST can be misdiagnosed as metastatic renal cancer because of the similarity in morphology and expression of nephrogenic markers such as PAX8. The presented case of a 27-year-old man revealed that observing the characteristic location and confirming the absence of renal neoplasm to rule out the possibility of metastasis are critical for obtaining an accurate final diagnosis.

Tips and tricks for a correct interpretation of contrast-enhanced ultrasound.

Although contrast-enhanced ultrasound (CEUS) is a widespread and easily manageable technique, image interpretation errors can occur due to the operator's inexperience and/or lack of knowledge of the frequent pitfalls, which may cause uncertain diagnosis and misdiagnosis. Indeed, knowledge of the basic physical and technical principles of ultrasound is needed both to understand sonographic image findings and to evaluate the potential and limits of the method. Like the B-mode ultrasound, the quality of the CEUS examination is also subject not only to the adequate manual skill of the operator but also to his/her deep knowledge of the technique which improves the quality of the image helping avoid misleading artifacts. In this review, the main parameters influencing a CEUS examination will be described by taking into account the most common errors and pitfalls and their possible solutions.

Angioimmunoblastic T-cell lymphoma involving the nasopharynx: An easily misdiagnosed disease with atypical histopathological features.

OBJECTIVES: To explore the clinicopathologic features, treatment, and survival outcomes of angioimmunoblastic T-cell lymphoma (AITL) involving the nasopharynx. METHODS: We retrospectively analyzed 73 cases of AITL. Among them, 64 cases with complete pre-treatment 18F-FDG positron emission tomography/computed tomography (PET/CT) images were integrated into the analysis of clinical characteristics and PET/CT findings of AITL involving the nasopharynx; 14 cases with both biopsies from lymph node and nasopharynx were included in the comparison of pathological characteristics of AITL in the two areas. Forty-six of the 73 patients who received first-line systemic treatment at our institute were included in the treatment efficacy and survival analyses. RESULTS: Nasopharyngeal involvement was seen in 44/64 (68.8%) patients. Histologically, lymph node and nasopharyngeal biopsies in 14 patients both showed small to medium-sized tumor cells, complex inflammatory infiltration, and Reed-Sternberg-like cells or B immunoblasts. However, tumor cells with clear cytoplasm, significant high endothelial venule (HEV) hyperplasia, and perivascular infiltration were observed in 5/14, 3/14, and 2/14 nasopharyngeal biopsies, respectively, but in all fourteen lymph node biopsies (P < 0.05). Immunophenotypic profiles and gene rearrangements were highly concordant. Treatment efficacy and survival were similar between patients with nasopharyngeal involvement and those without (P > 0.05), indicating nasopharyngeal involvement is not a prognostic factor for AITL patients. CONCLUSIONS: Nasopharyngeal involvement is common in AITL but can be easily misdiagnosed because of its atypical pathologic pattern, especially when a lymph node biopsy is unavailable. However, the patient's clinical presentation, PET/CT manifestations, the typical immunophenotype, and gene rearrangements help the diagnosis.

Exploring the causes of COPD misdiagnosis in primary care: A mixed methods study.

BACKGROUND: Within primary care there exists a cohort of patients misdiagnosed with Chronic Obstructive Pulmonary Disease (COPD). Misdiagnosis can have a detrimental impact on healthcare finances and patient health and so understanding the factors leading to misdiagnosis is crucial in order to reduce misdiagnosis in the future. The objective of this study is to understand and explore the perceived causes of COPD misdiagnosis in primary care. METHODS: A sequential mixed methods study, quantifying prevalence and features of patients misdiagnosed with COPD in primary care followed by a qualitative analysis to explore perceived causes of misdiagnosis. Quantitative data was collected for 206 patients identified as misdiagnosed with COPD within the INTEGR COPD study (NCT03482700). Qualitative data collected from 21 healthcare professionals involved in providing COPD care and 8 misdiagnosed patients who were recruited using a maximum variation purposive sampling. RESULTS: Misinterpretation of spirometry results was the prevailing factor leading to patients initially being misdiagnosed with COPD, affecting 59% of misdiagnosed patients in this cohort. Of the 99 patients who were investigated for their underlying diagnosis; 41% had normal spirometry and 40% had asthma. Further investigation through qualitative methodology uncovered reluctance to challenge historical misdiagnoses and challenges in differential diagnosis as the underlying explanations for COPD misdiagnosis in this cohort. CONCLUSIONS: Patients historically diagnosed with COPD without spirometric evidence are at risk of remaining labelled and treated for COPD despite non-obstructive respiratory physiology, leading to a persistent cohort of patients misdiagnosed with COPD in primary care. The lack of spirometry services during and after the COVID19 pandemic in primary care risks adding to the cohort of misdiagnosed patients. Support from respiratory specialists can potentially help to reduce the prevalence of COPD misdiagnosis in primary care. TRIAL REGISTRATION: NCT03482700.