Accuracy Of Clinical Diagnosis Research Articles

Pulmonary microbial spectrum in late-stage SARS-CoV-2 infection: a case series.

Coronavirus disease 2019 (COVID-19), a kind of respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), primarily spreads through the respiratory tract from human to human. Its extensive and rapid spread has led to a global pandemic, causing great harm to human health and economic development all over the world. Current known evidence indicates that SARS-CoV-2 has evolved accumulating multiple mutations, with altered infectivity and viral replication capacity. A better understanding of the complications of COVID-19 and its relationship with underlying diseases is crucial for the prevention and treatment of SARS-CoV-2. This case series reviewed case data of our 4 recent patients with severe or critical COVID-19, including treatment plan, status of pulmonary infection and their microbiology workup with metagenomic next-generation sequencing with bronchoalveolar lavage fluid. This report shed light on the significance of rapid and accurate clinical diagnosis and treatment on COVID-19.

Diagnostic ability of Peptidase S8 gene in the Arthrodermataceae causing dermatophytoses: A metadata analysis.

An unambiguous identification of dermatophytes causing dermatophytoses is necessary for accurate clinical diagnosis and epidemiological implications. In the current taxonomy of the Arthrodermataceae, the etiological agents of dermatophytoses consist of seven genera and members of the genera Trichophyton are the most prevalent etiological agents at present. The genera Trichophyton consists of 16 species that are grouped as clades, but the species borderlines are not clearly delimited. The aim of the present study was to determine the discriminative power of subtilisin gene variants (SUB1-SUB12) in family Arthrodermataceae, particularly in Trichophyton. Partial and complete reads from 288 subtilisin gene sequences of 12 species were retrieved and a stringent filtering following two different approaches for analysis (probability of correct identification (PCI) and gene gap analysis) conducted to determine the uniqueness of the subtilisin gene subtypes. SUB1 with mean PCI value of 60% was the most suitable subtilisin subtype for specific detection of T.rubrum complex, however this subtype is not reported in members of T. mentagrophytes complex which is one of the most prevalent etiological agent at present. Hence, SUB7 with 40% PCI value was selected for testing its discriminative power in Trichophyton species. SUB7 specific PCR based detection of dermatophytes was tested for sensitivity and specificity. Sequences of SUB7 from 42 isolates and comparison with the ITS region showed that differences within the subtilisin gene can further be used to differentiate members of the T. mentagrophytes complex. Further, subtilisin cannot be used for the differentiation of T. benhamiae complex since all SUB subtypes show low PCI scores. Studies on the efficiency and limitations of the subtilisin gene as a diagnostic tool are currently limited. Our study provides information that will guide researchers in considering this gene for identifying dermatophytes causing dermatophytoses in human and animals.

Qualitative evaluation of a molecular point-of-care testing study for influenza in UK primary care.

Influenza contributes to the surge in winter infections and the consequent winter pressures on the health service. Molecular point-of-care testing(POCT) for influenza might improve patient management by providing rapid and accurate clinical diagnosis to inform the timely initiation of antiviral therapy and reduce unnecessary admissions and antibiotics use. To explore factors that influence the adoption or non-adoption of POCT in English general practices and provide insights to enable its integration into routine practice workflows. A qualitative implementation evaluation was conducted in ten general practices within the English national sentinel network (Oxford-RCGP Research and Surveillance Centre), from April to July 2023. Using the nonadoption, abandonment, scale-up, spread, and sustainability framework, data collection and analysis were conducted across ten practices. We made ethnographic observations of the POCT workflow and surveyed the practice staff for their perspectives on POCT implementation. Data were analysed using a mix of descriptive statistics, graphical modelling techniques and framework approach. Ethnographic observations identified two modes of POCT integration into practice workflow: 1) clinician POCT workflow - typically involving batch testing due to time constraints, 2) research nurse/healthcare assistant POCT workflow - characterised by immediate testing of individual patients. Survey indicated that most primary care staff considered the POCT training offered was sufficient, and these practices were ready for change and had the capacity and resources to integrate POCT in workflows. General practices should demonstrate flexibility in the workflow and workforce they deploy to integrate POCT into routine clinical workflow.

Qualitative evaluation of a molecular point-of-care testing study for influenza in UK primary care.

Influenza contributes to the surge in winter infections and the consequent winter pressures on the health service. Molecular point-of-care testing(POCT) for influenza might improve patient management by providing rapid and accurate clinical diagnosis to inform the timely initiation of antiviral therapy and reduce unnecessary admissions and antibiotics use. To explore factors that influence the adoption or non-adoption of POCT in English general practices and provide insights to enable its integration into routine practice workflows. A qualitative implementation evaluation was conducted in ten general practices within the English national sentinel network (Oxford-RCGP Research and Surveillance Centre), from April to July 2023. Using the nonadoption, abandonment, scale-up, spread, and sustainability framework, data collection and analysis were conducted across ten practices. We made ethnographic observations of the POCT workflow and surveyed the practice staff for their perspectives on POCT implementation. Data were analysed using a mix of descriptive statistics, graphical modelling techniques and framework approach. Ethnographic observations identified two modes of POCT integration into practice workflow: 1) clinician POCT workflow - typically involving batch testing due to time constraints, 2) research nurse/healthcare assistant POCT workflow - characterised by immediate testing of individual patients. Survey indicated that most primary care staff considered the POCT training offered was sufficient, and these practices were ready for change and had the capacity and resources to integrate POCT in workflows. General practices should demonstrate flexibility in the workflow and workforce they deploy to integrate POCT into routine clinical workflow.

Accuracy of clinical diagnosis of behavioural variant frontotemporal dementia: a protocol for a systematic review and meta-analysis

IntroductionBehavioural variant frontotemporal dementia (bvFTD) characterisation has evolved, but diagnosis remains challenging, relying on clinical diagnostic criteria that have undergone revisions over time. In this systematic review, our aims are...

P-528 Establishing sequencing coverage depth for preimplantation genetic testing for monogenic disorders (PGT-M) using a specific targeted next generation sequencing (tNGS)

Abstract Study question What is the sufficient sequencing coverage read depth (RD) for direct variant analysis for PGT-M using a specific tNGS assay? Summary answer Downsampling modelling experiments identified a minimum sequencing depth of 50X that is recommended for PGT-M with this specific tNGS assay. What is known already Properly developed and validated multiplex PCR amplification and NGS-based analysis reliably produces PGT-M diagnoses with low allele and amplification failure at RD of hundreds of reads when analyzing a 3-10 cell trophectoderm (TE) biopsy. However, the RD can be affected by amplification efficiency in a specific genomic region and therefore affect the reproducibility of variant detection: the higher the number of aligned reads, the higher the confidence of base calling at a particular position. Downsampling is a powerful bioinformatics tool for modelling comparisons between samples or between replicates, identifying analytical sequencing depth limits for accurate clinical diagnosis. Study design, size, duration This is a retrospective comparative diagnostic test accuracy (DTA) and verification study. Twenty-three embryos from 8 patients that had undergone PGT-M with clinically established Taqman qPCR genotyping were used as positive controls. The primary outcome was to establish the lowest RD point of down sampling where allelic frequency is reliably detected at heterozygosity between 20-80% in known positive controls. A further 30 PGT-M clinical cases were used to verify analytical performances under clinical conditions. Participants/materials, setting, methods Embryo biopsies were pre-amplified with a multiplex primer pool for PGT-M and PGT-A, using a two-step PCR strategy. Sequencing was performed on Illumina NextSeq550. Reads were aligned to a human reference genome (GRCh37/hg19) and processed with an in house bioinformatic pipeline. The RD and alternative allele frequencies (AAF) for PGT-M was calculated. The reads for the heterozygous variants were downsampled to 10X, 20X, 30X, 50X, 100X, 200X, 300X, 500X, and 1000X to establish the cutoff. Main results and the role of chance One or two TE biopsies (N = 44) of 23 embryos that were 100% concordant with previous PGT-M results were tested for 1 to 3 of the 12 variants (MLH1 c.199G>A, RB1 c.1589A>G, SLC16A2 c.604G>A, GNPTAB c.1123C>T, GNPTAB c.3314A>G, WFS1 c.1391C>G, USH2A c.10073G>A, USH2A del exons 5-11, F5 c.1601G>A, GAA c.693-1G>C, GAA c.875A>G, and HEXA c.1274_1277dupTATC). PGT-A analysis of multiple biopsies from the same embryo demonstrated consistent karyotypes (N = 44). The 19 heterozygous variants from 17 biopsies exhibited average RD of 763X (238X -1980X) with average AAF of 50% (44%- 56%). The reads for the heterozygous variants were downsampled to different levels (100,000 replicates). The distribution of the AAF were compared among the different depth levels. At a RD of 50X, the AAF displayed an interquartile range (IQR) of 8% (46%-54%) between the maximum and minimum values from 20% to 78%. Compared to 30X (IQR: 43%-57%, with minimum 13% and maximum 90%), and 100X (IQR: 47%-54%, with minimum 30% and maximum 71%), the RD at 50X generated reliable heterozygous calls with minimum depth requirement. 245 biopsies from 30 clinic cases were analyzed by tNGS-based PGT-M. 90 samples with heterozygous variant calls showed average RD of 979X (57X-5803X) with average AAF of 47% (29%-585). Limitations, reasons for caution The 50X cutoff is based on the heterozygous variants with theoretical 50% AFF and is specific for this PGT-A assay. This evaluation should be corroborated for complicated variants with homologous genes, which might require different thresholds. The aneuploidy at specific chromosome can cause the deviation of AFF from 50%. Wider implications of the findings This specific tNGS-based PGT-M can provide direct variant analysis at a 50X read depth with a high level of consistency compared to established methodologies while allowing for simultaneous aneuploidy screening using the same biopsy and procedural optimization. Trial registration number not applicable

An ensemble model for assisting early Alzheimer's disease diagnosis based on structural magnetic resonance imaging with dual-time-point fusion

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder. Due to the subtlety of symptoms in the early stages of AD, rapid and accurate clinical diagnosis is challenging, leading to a high rate of misdiagnosis. Current research on early diagnosis of AD has not sufficiently focused on tracking the progression of the disease over an extended period in subjects. To address this issue, this paper proposes an ensemble model for assisting early diagnosis of AD that combines structural magnetic resonance imaging (sMRI) data from two time points with clinical information. The model employs a three-dimensional convolutional neural network (3DCNN) and twin neural network modules to extract features from the sMRI data of subjects at two time points, while a multi-layer perceptron (MLP) is used to model the clinical information of the subjects. The objective is to extract AD-related features from the multi-modal data of the subjects as much as possible, thereby enhancing the diagnostic performance of the ensemble model. Experimental results show that based on this model, the classification accuracy rate is 89% for differentiating AD patients from normal controls (NC), 88% for differentiating mild cognitive impairment converting to AD (MCIc) from NC, and 69% for distinguishing non-converting mild cognitive impairment (MCInc) from MCIc, confirming the effectiveness and efficiency of the proposed method for early diagnosis of AD, as well as its potential to play a supportive role in the clinical diagnosis of early Alzheimer's disease.

Are invasive postmortem examinations still the ‘gold standard’ in diagnosing the cause of death?

For many years, the foundations of both its art and science in medicine grew from the observations made at the autopsy table. The observations of the pathologists formed the pathologic basis and manifestations of disease, which further advanced the development of therapeutics. For most of the 18th and 19th centuries, morbid anatomy (autopsy pathology) was considered the science of medicine. Today, the autopsy and the knowledge that derives from it do not hold the position they once did in the profession’s history. There is a belief among the medical community a complete autopsy is necessary to find out the answers when someone dies. In some jurisdictions, the forensic pathology community is reluctant to follow the targeted or minimally invasive approach in postmortem examinations due to a lack of understanding of the process. With a complete external examination, trace evidence collection, total body computed tomography (CT) scan, and minimally invasive/targeted dissection with a collection of samples for further analysis, almost all answers can be provided in hospital and medicolegal autopsy settings. We must collaborate with sister disciplines, such as experts in radiology and the legal community, to educate them on the importance of this new approach using advanced technology.Continuously evolving modern radiological imaging has remarkably increased the accuracy of clinical diagnosis. Conventionally, when you hear the word postmortem examination, people think it includes an external examination and dissection of all body cavities. In the 21st century, most questions raised by the family, clinicians, the coroner (medical examiner), courts, and law enforcement agencies can be answered with a complete external examination of the body, total body CT scan +/- magnetic resonance imaging, and targeted dissection or minimally invasive approach incorporated with sample collection for further testing. This is cost-effective and can produce reviewable data.

Frontotemporal lobar degeneration in the "Annual of the Pathological Autopsy Cases in Japan".

Good accuracy for the clinical diagnosis of frontotemporal lobar degeneration (FTLD) by specialists in an early onset dementia clinic has been reported. To assess the diagnostic accuracy of FTLD in an entire population, without restrictions related to patient age or diagnosing physician. Volumes of the "Annual of the Pathological Autopsy Cases in Japan," with reports of 130,105 autopsies throughout Japan from 2007 to 2016, were descriptively analyzed. There were 219 patients with clinical and/or pathological diagnoses of FTLD. The sensitivity and specificity were 24.5% and 76.9%, respectively. Age at death for pathologically confirmed patients was 76.3 ± 11.6years (mean ± standard deviation). Overlooked patients died significantly older than patients with an accurate clinical diagnosis. Clinical diagnoses of FTLD had low sensitivity. Furthermore, the age at death of pathologically confirmed patients suggests that FTLD affects a wide age range and is not restricted to presenile individuals.

Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images

BackgroundNasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm for computer-aided diagnosis of nasal endoscopic images, which may provide a more accurate clinical diagnosis before pathologic confirmation of the nasal masses.MethodsBy performing deep learning of nasal endoscope images, we evaluated our computer-aided diagnosis system’s assessment ability for nasal polyps and inverted papilloma and the feasibility of their clinical application. We used curriculum learning pre-trained with patches of nasal endoscopic images and full-sized images. The proposed model’s performance for classifying nasal polyps, inverted papilloma, and normal tissue was analyzed using five-fold cross-validation.ResultsThe normal scores for our best-performing network were 0.9520 for recall, 0.7900 for precision, 0.8648 for F1-score, 0.97 for the area under the curve, and 0.8273 for accuracy. For nasal polyps, the best performance was 0.8162, 0.8496, 0.8409, 0.89, and 0.8273, respectively, for recall, precision, F1-score, area under the curve, and accuracy. Finally, for inverted papilloma, the best performance was obtained for recall, precision, F1-score, area under the curve, and accuracy values of 0.5172, 0.8125, 0.6122, 0.83, and 0.8273, respectively.ConclusionAlthough there were some misclassifications, the results of gradient-weighted class activation mapping were generally consistent with the areas under the curve determined by otolaryngologists. These results suggest that the convolutional neural network is highly reliable in resolving lesion locations in nasal endoscopic images.

Enhancing early breast cancer diagnosis through automated microcalcification detection using an optimized ensemble deep learning framework

Background Breast cancer remains a pressing global health concern, necessitating accurate diagnostics for effective interventions. Deep learning models (AlexNet, ResNet-50, VGG16, GoogLeNet) show remarkable microcalcification identification (>90%). However, distinct architectures and methodologies pose challenges. We propose an ensemble model, merging unique perspectives, enhancing precision, and understanding critical factors for breast cancer intervention. Evaluation favors GoogleNet and ResNet-50, driving their selection for combined functionalities, ensuring improved precision, and dependability in microcalcification detection in clinical settings. Methods This study presents a comprehensive mammogram preprocessing framework using an optimized deep learning ensemble approach. The proposed framework begins with artifact removal using Otsu Segmentation and morphological operation. Subsequent steps include image resizing, adaptive median filtering, and deep convolutional neural network (D-CNN) development via transfer learning with ResNet-50 model. Hyperparameters are optimized, and ensemble optimization (AlexNet, GoogLeNet, VGG16, ResNet-50) are constructed to identify the localized area of microcalcification. Rigorous evaluation protocol validates the efficacy of individual models, culminating in the ensemble model demonstrating superior predictive accuracy. Results Based on our analysis, the proposed ensemble model exhibited exceptional performance in the classification of microcalcifications. This was evidenced by the model’s average confidence score, which indicated a high degree of dependability and certainty in differentiating these critical characteristics. The proposed model demonstrated a noteworthy average confidence level of 0.9305 in the classification of microcalcification, outperforming alternative models and providing substantial insights into the dependability of the model. The average confidence of the ensemble model in classifying normal cases was 0.8859, which strengthened the model’s consistent and dependable predictions. In addition, the ensemble models attained remarkably high performances in terms of accuracy, precision, recall, F1-score, and area under the curve (AUC). Conclusion The proposed model’s thorough dataset integration and focus on average confidence ratings within classes improve clinical diagnosis accuracy and effectiveness for breast cancer. This study introduces a novel methodology that takes advantage of an ensemble model and rigorous evaluation standards to substantially improve the accuracy and dependability of breast cancer diagnostics, specifically in the detection of microcalcifications.

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

BackgroundDiagnostic 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.MethodsA 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.ResultsSeventy-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%).ConclusionsMisdiagnoses 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.

A Hybrid CNN-TransXNet Approach for Advanced Glomerular Segmentation in Renal Histology Imaging

In the specialized field of renal histology, precise segmentation of glomeruli in microscopic images is crucial for accurate clinical diagnosis and pathological analysis. Facing the challenge of discerning complex visual features, such as shape, texture, and size within these images, we introduce a novel segmentation model that innovatively combines convolutional neural networks (CNNs) with the advanced TransXNet block, specifically tailored for glomerular segmentation. This innovative model is designed to capture the intricate details and broader contextual features within the images, ensuring a comprehensive and precise segmentation process. The model's architecture unfolds in two primary phases: the down-sampling phase, which utilizes CNNs structures within the TransXNet block for meticulous extraction of detailed features, and the up-sampling phase, which employs CNNs deconvolution techniques to restore spatial resolution and enhance macroscopic feature representation. A critical innovation in our model is the implementation of residual connections between these two phases, which facilitate the seamless integration of features and minimize loss of precision during image reconstruction. Experimental results demonstrate a significant improvement in our model’s performance compared to existing medical image segmentation methods. We report enhancements in mean Pixel Accuracy (mPA) and mean Intersection over Union (mIoU), with increases of approximately 3–5% and 3–8%, respectively. Additionally, the segmented outputs exhibit higher subjective visual quality with fewer noise artifacts. These findings suggest that our model offers promising applications in the segmentation of medical microscopic images, marking a significant contribution to the domain.

Intra-operative dermoscopy (onychoscopy) of the nail unit-A systematic review.

Dermoscopy of the nail unit (onychoscopy) is a method which allows for non-invasive observation of the nail structures, increasing the accuracy of clinical diagnosis. Currently, it is used in evaluation of both inflammatory and neoplastic conditions of the nail unit. However, in contrast to the skin, the anatomy of the nail unit prevents direct observation of nail bed or nail matrix structure during classic onychoscopy. Intra-operative onychoscopy is a variant of the technique which uses direct visualization of the nail unit structures after nail plate avulsion. The aim of this systematic review was to summarize the current state of knowledge on intra-operative onychoscopy. The MEDLINE, EMBASE and Cochrane databases were systematically searched in January 2024. All types of study designs assessing intra-operative dermoscopy of the nail unit were included in this study. The risk of bias in included studies was assessed using the Joanna Briggs Institute critical appraisal tools. The qualitative synthesis of 19 studies totalling a number of 218 cases in 217 patients included the following entities: melanoma, nevus, hypermelanosis (melanocytic activation), melanocytic hyperplasia, melanophages accumulation, squamous cell carcinoma, glomus tumour, lichen planus, onychomatricoma, onychomycosis and subungual exostosis. The main limitation of the study was a relatively low number of identified studies, most with low levels of evidence. Intra-operative onychoscopy does not replace histologic examination, though it may be useful in determining the modality of surgical diagnostic procedures.

Evaluation of The Effectiveness of Abdominal and Vaginal B-Ultrasound in The Diagnosis of Acute Abdomen in Obstetrics and Gynecology

Objective: To explore the clinical effect of the combined application of abdominal and vaginal B-ultrasound in the diagnosis of acute abdomen in obstetrics and gynecology. Methods: Eighty patients admitted to our hospital from March 2023 to March 2024 were selected, all of whom were acute abdomen patients admitted to the Department of Obstetrics and Gynecology. In this study, the patients were divided into two groups. One group of 40 patients was given a simple abdominal B-ultrasound diagnosis (control group). The other group of 40 patients was given both abdominal and vaginal B-ultrasound examinations (experimental group). The diagnostic accuracy between the two groups was compared. Results: Patients in the experimental group had higher consistency rates with pathological diagnosis results in ectopic pregnancy rupture, embryonic arrest, acute pelvic inflammation, corpus luteum rupture, and intrauterine adhesions as compared to the control group. At the same time, the inspection accuracy rate of the experimental group (92.50%) was higher than that of the control group (70.00%) (P < 0.05). Conclusion: The combined application of abdominal and vaginal B-ultrasound in the diagnosis of acute abdomen was of great significance in improving the accuracy of clinical diagnosis and guiding doctors to provide effective treatment.

Simultaneous determination of methanol, ethanol, and formic acid in human serum by HSGC-MS: Method development, validation, and application

The concurrent assessment of methanol, ethanol, and formic acid is imperative for accurate clinical toxicology diagnosis in cases of methanol poisoning. Here, we reported a very simple and reliable headspace gas chromatography coupled with mass spectrometry (HSGC-MS) method for simultaneous quantitative determination of methanol, ethanol and formic acid in blood samples. The derivatization variables for formic acid were optimized. The method exhibits high sensitivity, good selectivity and effective separation factor for methanol (6.51 min), ethanol (8.29 min), and formic acid (11.41 min). The method demonstrates excellent reproducibility and accuracy. The limit of detection (LOD) and the limit of quantification (LOQ) were determined to be 3.14–5.83 μg/mL and 10.47–19.34 μg/mL, respectively. Finally, this method was successfully used for measuring the levels of methanol, ethanol, and formic acid in the serum of patients involved in actual methanol poisoning incidents.

Endogenous AND Logic DNA Nanomachine for Highly Specific Cancer Cell Imaging.

Intracellular cancer-related biomarker imaging strategy has been used for specific identification of cancer cells, which was of great importance to accurate cancer clinical diagnosis and prognosis studies. Localized DNA circuits with improved sensitivity showed great potential for intracellular biomarkers imaging. However, the ability of localized DNA circuits to specifically image cancer cells is limited by off-site signal leakage associated with a single-biomarker sensing strategy. Herein, we integrated the endogenous enzyme-powered strategy with logic-responsive and localized signal amplifying capability to construct a self-assembled endogenously AND logic DNA nanomachine (EDN) for highly specific cancer cell imaging. When the EDN encountered a cancer cell, the overexpressed DNA repairing enzyme apurinic/apyrimidinic endonuclease 1 (APE1) and miR-21 could synergistically activate a DNA circuit via cascaded localized toehold-mediated strand displacement (TMSD) reactions, resulting in amplified fluorescence resonance energy transfer (FRET) signal. In this strategy, both endogenous APE1 and miR-21, served as two "keys" to activate the AND logic operation in cancer cells to reduce off-tumor signal leakage. Such a multiplied molecular recognition/activation nanomachine as a powerful toolbox realized specific capture and reliable imaging of biomolecules in living cancer cells.

Application of the Universal Definition of Myocardial Infarction in Clinical Practice in Scotland and Sweden

Whether the diagnostic classifications proposed by the universal definition of myocardial infarction (MI) to identify type 1 MI due to atherothrombosis and type 2 MI due to myocardial oxygen supply-demand imbalance have been applied consistently in clinical practice is unknown. To evaluate the application of the universal definition of MI in consecutive patients with possible MI across 2 health care systems. This cohort study used data from 2 prospective cohorts enrolling consecutive patients with possible MI in Scotland (2013-2016) and Sweden (2011-2014) to assess accuracy of clinical diagnosis of MI recorded in hospital records for patients with an adjudicated diagnosis of type 1 or type 2 MI. Data were analyzed from August 2022 to February 2023. The main outcome was the proportion of patients with a clinical diagnosis of MI recorded in the hospital records who had type 1 or type 2 MI, adjudicated by an independent panel according to the universal definition. Characteristics and risk of subsequent MI or cardiovascular death at 1 year were compared. A total of 50 356 patients were assessed. The cohort from Scotland included 28 783 (15 562 men [54%]; mean [SD] age, 60 [17] years), and the cohort from Sweden included 21 573 (11 110 men [51%]; mean [SD] age, 56 [17] years) patients. In Scotland, a clinical diagnosis of MI was recorded in 2506 of 3187 patients with an adjudicated diagnosis of type 1 MI (79%) and 122 of 716 patients with an adjudicated diagnosis of type 2 MI (17%). Similar findings were observed in Sweden, with 970 of 1111 patients with adjudicated diagnosis of type 1 MI (87%) and 57 of 251 patients with adjudicated diagnosis of type 2 MI (23%) receiving a clinical diagnosis of MI. Patients with an adjudicated diagnosis of type 1 MI without a clinical diagnosis were more likely to be women (eg, 336 women [49%] vs 909 women [36%] in Scotland; P < .001) and older (mean [SD] age, 71 [14] v 67 [14] years in Scotland, P < .001) and, when adjusting for competing risk from noncardiovascular death, were at similar or increased risk of subsequent MI or cardiovascular death compared with patients with a clinical diagnosis of MI (eg, 29% vs 18% in Scotland; P < .001). In this cohort study, the universal definition of MI was not consistently applied in clinical practice, with a minority of patients with type 2 MI identified, and type 1 MI underrecognized in women and older persons, suggesting uncertainty remains regarding the diagnostic criteria or value of the classification.

Hematological and Biochemical Profiles of Patients with Dengue Virus Infection in Lalitpur, Nepal

Dengue viral infection is a disease transmitted by mosquitoes of the Aedes genus, and it arises as a result of being bitten by mosquitoes that are carrying the virus. This infection induces a wide range of changes in the body’s immune system. Thus serological evaluation together with hematological and biochemical parameters in cases of dengue viral infection make an accurate clinical diagnosis. The main objective of this study was to study the serological, hematological, and biochemical parameters among patients infected with Dengue virus. A total of 102 blood samples were collected at Asrik Diagnostic Lab, Lalitpur during the period of August to October 2022. Samples were analyzed by following methods: hematological tests were done by coulter counter, Biochemical tests were done by fully automated analyzer and serological tests were done by ELISA. Of the 102 blood samples NS1 antigen was detected in 62 (60.9%) whereas anti-dengue IgM antibody was detected in 10 (9.8%). Leukopenia and thrombocytopenia were present in 33 (53.1%) and 32 (51.6%) of the 62 NS1 positive samples, respectively. Of the 62 cases, only 16 samples were tested for the alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Out of 16 samples, ALT and AST level were significantly higher in 11 (68.8%) and 14 (87.5%) positive cases, respectively. The statistical analysis showed that there was no significant association between NS1 and IgM. It can be concluded that the investigation of leukocytes, thrombocytes, ALT, and AST helps to diagnose the dengue efficiently.

(405) - Accuracy of Clinical Diagnosis in Advanced Heart Failure Patients Undergoing Transplantation and Impact of Genetic Testing

(405) - Accuracy of Clinical Diagnosis in Advanced Heart Failure Patients Undergoing Transplantation and Impact of Genetic Testing