Diagnostic Method Research Articles

Seizure Outcome After Intraoperative Electrocorticography-Tailored Epilepsy Surgery: A Systematic Review and Meta-Analysis.

Tailoring epilepsy surgery using intraoperative electrocorticography (ioECoG) has been debated, and modest number of epilepsy surgery centers apply this diagnostic method. We assessed the current evidence to use ioECoG-tailored epilepsy surgery for improving postsurgical outcome. PubMed and Embase were searched for original studies reporting on ≥10 cases who underwent ioECoG-tailored surgery for epilepsy, with a follow-up of at least 6 months. We used a random-effects model to calculate the overall rate of patients achieving favorable seizure outcome (FSO), defined as Engel class I, ILAE class 1, or seizure-free status. Meta-regression was used to investigate potential sources of heterogeneity. We calculated the odds ratio (OR) for estimating variables on FSO:ioECoG vs non-ioECoG-tailored surgery (if included studies contained patients with non-ioECoG-tailored surgery), ioECoG-tailored epilepsy surgery in children vs adults, temporal (TL) vs extratemporal lobe (eTL), MRI-positive vs MRI-negative, and complete vs incomplete resection of tissue that generated interictal epileptiform discharges (IEDs). A Bayesian network meta-analysis was conducted for underlying pathologies. We assessed the evidence certainty using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Eighty-three studies (82 observational studies, 1 trial) comprising 3,631 patients with ioECoG-tailored surgery were included. The overall pooled rate of patients who attained FSO after ioECoG-tailored surgery was 74% (95% CI 71-77) with significant heterogeneity, which was predominantly attributed to pathologies and seizure outcome classifications. Twenty-two studies contained non-ioECoG-tailored surgeries. IoECoG-tailored surgeries reached a higher rate of FSO than non-ioECoG-tailored surgeries (OR 2.10 [95% CI 1.37-3.24]; p < 0.01; very low certainty). Complete resection of tissue that displayed IEDs in ioECoG predicted FSO better compared with incomplete resection (OR 3.04 [1.76-5.25]; p < 0.01; low certainty). We found insignificant difference in FSO after ioECoG-tailored surgery in children vs adults, TL vs eTL, or MRI-positive vs MRI-negative. The network meta-analysis showed that the odds of FSO was lower for malformations of cortical development than for tumors (OR 0.47 95% credible interval 0.25-0.87). Although limited by low-quality evidence, our meta-analysis shows a relatively good surgical outcome (74% FSO) after epilepsy surgery with ioECoG, especially in tumors, with better outcome for ioECoG-tailored surgeries in studies describing both and better outcome after complete removal of IED areas.

Novel picture fuzzy distance measure [formula omitted] and its application in medical diagnosis

In this research work, we introduced novel distance measure in picture fuzzy sets and prove all the triangle inequality associated with it. There is an introduction to the use of the distance measure in medical diagnostics. In addition to this, we have shown a comparison between two distance functions ρ and ρ∗ in this research work. Our observation indicates that the novel fuzzy distance measure ρ∗ exhibits greater efficacy in the context of disease diagnosis compared to the conventional measure ρ.

Prior function designs for X-ray reconstructions from limited angular views

The objectivity of three-dimensional imaging has placed X-ray Computed Tomography (CT) into an indispensable diagnostic method in clinical and industrial applications. Despite the advances in the X-ray CT imaging, high- resolution three-dimensional reconstruction of small details in objects with large in-plane dimensions has been a fundamental challenge for the conventional X-ray CT method. An alternative scanning geometry, where X-ray source and a detector move synchronously irradiating a specimen at an inclined angle, has been proposed to address this challenge. This work presents new designs of prior (or penalty) functions developed for reconstructing the radiography data obtained under the limited angular conditions. The new prior targets reduction of shape distortion artifacts, common for laminographic reconstructions, as well as preservation of small features, such as voids, edge details, and high-density inclusions. The novel prior function designs are demonstrated on the computational phantom of a specimen scanned under tilted planar CT geometry simulating large planar dimensions of a specimen. To accommodate physical CT scanning of such specimens, a novel microfocus X-ray CT scanning device that rotates X-ray source and moves the detector synchronously while staying on the same side of the test specimen (Inclined CT), is introduced. This device allows scanning of critical areas of up to 3-meter-wide and potentially unlimited length specimens with high resolution required for identification of manufacturing and structural defects typical for modern composite structural elements used in the aerospace industry.

Validation and optimization of the loop-mediated isothermal amplification (LAMP) technique for rapid detection of wheat stripe mosaic virus, a wheat-infecting pathogen

BackgroundWheat stripe mosaic virus (WhSMV) is a significant wheat pathogen that causes substantial yield losses in Brazil and other countries. Although several detection methods are available, reliable and efficient tools for on-site WhSMV detection are currently lacking. In this study, a Loop-Mediated Isothermal Amplification (LAMP) method was developed for rapid and reliable field detection of WhSMV. We designed WhSMV-specific primers for the LAMP assay and optimized reaction conditions for increased sensitivity and specificity using infected plant samples. ResultsWe have developed a diagnostic method utilizing the Loop-Mediated Isothermal Amplification (LAMP) technique capable of rapidly and reliably detecting WhSMV. The LAMP assay has been optimized to enhance sensitivity, specificity, and cost-effectiveness. ConclusionThe LAMP assay described here represents a valuable tool for early WhSMV detection, serving to mitigate the adverse economic and social impacts of this viral pathogen. By enabling swift and accurate identification, this assay can significantly improve the sustainability of cereal production systems, safeguarding crop yields against the detrimental effects of WhSMV.

Parasite-derived microRNA let-7-5p detection for metacestodiasis based on rolling circular amplification-assisted CRISPR/Cas9.

Metacestodiasis is an infectious disease caused by the larval stage of cestode parasites. This disease poses a serious health hazard to wildlife, livestock, and humans, and it incurs substantial economic losses by impacting the safety of the livestock industry, the quality of meat production, and public health security. Unfortunately, there is currently no available molecular diagnostic method capable of distinguishing cysticercus- and Echinococcus-derived microRNAs (miRNAs) from other helminthes and hosts in the plasma of metacestode-infected animals. This study aims to develop a specific, sensitive, and cost-efficient molecular diagnostic method for cysticercosis and echinococcosis, particularly for early detection. The study developed a rolling circular amplification (RCA)-assisted CRISPR/Cas9 detection method based on parasite-derived miRNA let-7-5p. Using a series of dilutions of the let-7 standard, the limit of detection (LOD) of the qPCR, RCA, and RCA-assisted CRISPR/Cas9 methods was compared. The specificity of qPCR and CRISPR/Cas9 was evaluated using four artificially synthesized let-7 standards from different species. A total of 151 plasma samples were used to evaluate the diagnostic performance. Additionally, the study also assessed the correlation between plasma levels of let-7-5p, the number of Taenia pisiformis cysticerci, and the weight of Echinococcus multilocularis cysts. The results demonstrated that the RCA-assisted CRISPR/Cas9 assay could significantly distinguish let-7 from cestodes and other species, achieving a LOD of 10 aM; the diagnostic sensitivity and specificity for rabbit cysticercosis and mouse E. multilocularis were 100% and 97.67%, and 100% and 100%, respectively. Notably, let-7-5p gradually increased in the plasma of T. pisiformis-infected rabbits from 15 days post infection (dpi), peaked at 60 dpi, and persisted until 120 dpi. In E. multilocularis-infected mice, let-7-5p gradually increased from 15 dpi and persisted until 90 dpi. Furthermore, the expression of let-7-5p positively correlated with the number of cysticerci and cyst weight. These results indicated that the let-7-5p-based RCA-assisted CRISPR/Cas9 assay is a sensitive and specific detection method that can be used as a universal diagnostic method for metacestodiasis, particularly for early diagnosis (15 dpi).

Artificial Intelligence: A Quick Overview of Speech Recognition System

Abstract: The study of intelligent behaviour is known as artificial intelligence. Wagner said, "We build intelligent machines in science." By this, he implied that the primary goal is to teach these sophisticated devices, such as computers, to examine and comprehend human conduct. numerous believed that human intelligence might be understood through the construction of several programmes, while other researchers believed that numerous basics should be required in order to accomplish the intended objective. We can carry out or replicate any type of task we conduct using a computer. Therefore, computers are the ideal devices for developing artificial intelligence. In the hopes that they will outperform computers in several other areas, some researchers created additional computing devices. Billions of dollars were invested in creating new devices that surpassed the speed of the computer used to simulate software. However, the computers and the code both need to be extremely quick. As you learn about artificial intelligence, you may wonder, what really is intelligence? How is intelligence measured? Turn become something quite significant. In this case, the programme that evaluates its surroundings acts as the intelligent agent. Modern digital computers and human minds are comparable to one other in ways such as symbolic information processing systems. Both use symbolic data as input, change it in accordance with predetermined guidelines, and then use the results to solve issues. In order to mechanically replicate intelligent human activity, artificial intelligence researchers have programmed some algorithms to recognise intelligent human behaviour. Human conduct in language processing, chess, and other games, as well as medical diagnostics, may be used to monitor this activity. Voice recognition is a key component of AI. A certain voice may be recognised using voice recognition technology. The cornerstone for speaker identification is voice signals. Voice targeting is applicable to a wide range of applications, including voice mail, database access, phone banking, and phone purchasing. The ability to enter one's voice for verification is among the most potent uses of voice recognition for security. The fundamental means of interpersonal communication is speech. The technique of translating voice sounds into appropriate text is known as speech recognition. Over the past few years, speech recognition technology has advanced significantly. Nonetheless, there are other significant study obstacles, such as variations in speaker and language, ambient sound, word size, etc. This study aims to give a comprehensive overview of speech acceptance by summarising the several approaches utilised in the standard speech system and describing the numerous processes involved

Epitope mapping and establishment of a blocking ELISA for mAb targeting the p72 protein of African swine fever virus.

The African swine fever virus (ASFV) has the ability to infect pigs and cause a highly contagious acute fever that can result in a mortality rate as high as 100%. Due to the viral epidemic, the pig industry worldwide has suffered significant financial setbacks. The absence of a proven vaccine for ASFV necessitates the development of a sensitive and reliable serological diagnostic method, enabling laboratories to effectively and expeditiously detect ASFV infection. In this study, four strains of monoclonal antibodies (mAbs) against p72, namely, 5A1, 4C4, 8A9, and 5E10, were generated through recombinant expression of p72, the main capsid protein of ASFV, and immunized mice with it. Epitope localization was performed by truncated overlapping polypeptides. The results indicate that 5A1 and 4C4 recognized the amino acid 20-39 aa, 8A9 and 5E10 are recognized at 263-282 aa, which is consistent with the reported 265-280 aa epitopes. Conserved analysis revealed 20-39 aa is a high conservation of the epitopes in the ASFV genotypes. Moreover, a blocking ELISA assay for detection ASFV antibody based on 4C4 monoclonal antibody was developed and assessed. The receiver-operating characteristic (ROC) was performed to identify the best threshold value using 87 negative and 67 positive samples. The established test exhibited an area under the curve (AUC) of 0.9997, with a 95% confidence interval ranging from 99.87 to 100%. Furthermore, the test achieved a diagnostic sensitivity of 100% (with a 95% confidence interval of 95.72 to 100%) and a specificity of 98.51% (with a 95% confidence interval of 92.02 to 99.92%) when the threshold was set at 41.97%. The inter- and intra-batch coefficient of variation were below 10%, demonstrating the exceptional repeatability of the method. This method can detect the positive standard serum at a dilution as high as 1:512. Subsequently, an exceptional blocking ELISA assay was established with high diagnostic sensitivity and specificity, providing a novel tool for detecting ASFV antibodies. KEY POINTS: • Four strains of ASFV monoclonal antibodies against p72 were prepared and their epitopes were identified. • Blocking ELISA method was established based on monoclonal antibody 4C4 with an identified conservative epitope. • The established blocking ELISA method has a good effect on the detection of ASFV antibody.

Why Are Explainable AI Methods for Prostate Lesion Detection Rated Poorly by Radiologists?

Deep learning offers significant advancements in the accuracy of prostate identification and classification, underscoring its potential for clinical integration. However, the opacity of deep learning models presents interpretability challenges, critical for their acceptance and utility in medical diagnosis and detection. While explanation methods have been proposed to demystify these models, enhancing their clinical viability, the efficacy and acceptance of these methods in medical tasks are not well documented. This pilot study investigates the effectiveness of deep learning explanation methods in clinical settings and identifies the attributes that radiologists consider crucial for explainability, aiming to direct future enhancements. This study reveals that while explanation methods can improve clinical task performance by up to 20%, their perceived usefulness varies, with some methods being rated poorly. Radiologists prefer explanation methods that are robust against noise, precise, and consistent. These preferences underscore the need for refining explanation methods to align with clinical expectations, emphasizing clarity, accuracy, and reliability. The findings highlight the importance of developing explanation methods that not only improve performance but also are tailored to meet the stringent requirements of clinical practice, thereby facilitating deeper trust and a broader acceptance of deep learning in medical diagnostics.

An efficient computational framework for gastrointestinal disorder prediction using attention-based transfer learning

Diagnosing gastrointestinal (GI) disorders, which affect parts of the digestive system such as the stomach and intestines, can be difficult even for experienced gastroenterologists due to the variety of ways these conditions present. Early diagnosis is critical for successful treatment, but the review process is time-consuming and labor-intensive. Computer-aided diagnostic (CAD) methods provide a solution by automating diagnosis, saving time, reducing workload, and lowering the likelihood of missing critical signs. In recent years, machine learning and deep learning approaches have been used to develop many CAD systems to address this issue. However, existing systems need to be improved for better safety and reliability on larger datasets before they can be used in medical diagnostics. In our study, we developed an effective CAD system for classifying eight types of GI images by combining transfer learning with an attention mechanism. Our experimental results show that ConvNeXt is an effective pre-trained network for feature extraction, and ConvNeXt+Attention (our proposed method) is a robust CAD system that outperforms other cutting-edge approaches. Our proposed method had an area under the receiver operating characteristic curve of 0.9997 and an area under the precision-recall curve of 0.9973, indicating excellent performance. The conclusion regarding the effectiveness of the system was also supported by the values of other evaluation metrics.

Management of disseminated histoplasmosis in a high-complexity clinic in Cali, Colombia.

Histoplasmosis presents a substantial clinical challenge globally, with a particular prevalence in South America, especially among patients with concurrent Human Immunodeficiency Virus (HIV) infection. Despite itraconazole's established efficacy, investigating alternative therapeutic approaches remains imperative. This is the largest study in our region to date, assessing the effectiveness of the less explored posaconazole treatment. This observational study, conducted at Fundación Valle del Lili (FVL) from 2016 to 2022, encompassed adults with disseminated histoplasmosis. Patients (n = 31) were treated with liposomal amphotericin B as an initial treatment, followed by consolidation treatment with posaconazole or itraconazole. Patients with single-organ cases, those lacking microbiological diagnosis, those who received initial treatment with antifungals other than liposomal Amphotericin B. and those with <6 months follow-up were excluded (Figure 1)Analyses considered population characteristics, treatments, and outcomes. Patients (average age: 45.6; 58.1% female) had common comorbidities (HIV 38.7%, solid organ transplantation 29% and oncologic disease 12.9%). Lungs (48.4%) and lymph nodes (16.1%) were commonly affected. Biopsy (64.5%) was the primary diagnostic method. Initial treatment with liposomal amphotericin B (100%) was given for 14 days on average. Follow-up indicated 71% completion with 19.4% requiring treatment modifications. Notably, 70.9% concluded a posaconazole consolidation regimen over 350 days on average. Drug interactions during consolidation (80.6%) were common. No relapses occurred, and three deaths unrelated to histoplasmosis were reported. Traditionally, itraconazole has been the prevalent initial treatment; however, in our cohort, 55.9% of patients received posaconazole as the primary option. Encouragingly, posaconazole showed favorable tolerance, infection resolution, suggesting its potential as an effective and well-tolerated alternative for consolidation treatment. This finding prompts further exploration of posaconazole, potentially leading to more effective patient care and better outcomes.

Colistin, the last resort antibiotic: challenges in the implementation of its routine susceptibility testing

Background: colistin has become a critical antibiotic for lifethreatening multidrug resistance Gram-negative infections, particularly carbapenemase-producing bacteria. Detecting colistin resistance in routine microbiology laboratories is crucial for combating these fatal infections poses a challenge. Especially in developing countries, there is a need for a cost-effective, rapid, and user-friendly diagnostic method. Objective: implementing the various available methods for colistin testing is a significant challenge in resource-limited settings due to logistic difficulties and the need for technical expertise. Materials and Methods: this study shares experiences and insights gained while implementing in-vitro colistin susceptibility testing in a high-load bacteriology laboratory of a tertiary care center in Delhi, India. The following test methods for colistin susceptibility testing were incorporated in the routine antimicrobial susceptibility testing of our laboratory: Colistin Agar Test, Colistin Broth Disk Elution Test, Broth Microdilution susceptibility testing. Results: inconsistent growth patterns were observed in the colistin agar dilution Minimum Inhibitory Concentration (MIC) method, which could be resolved only after the preparation of fresh plates containing that specific concentration of colistin. The contamination issue of plates on use over a few days was addressed by pouring agar containing various concentrations of colistin in cottonplugged glass tubes. In the colistin broth disk elution test, due to the non-availability of screw-capped 10 mL glass tubes, MacCornety bottles (30 mL) were used. Subcultures were performed from the turbid wells to rule out the growth of contaminants when encountering discordant MIC values or skipped wells on the colistin broth microdilution test. Conclusions: despite several technical issues in in-vitro colistin susceptibility testing, we have successfully implemented it in our laboratory. Our experiences can offer guidance to laboratories that are still in the process of implementing it.

Social acceptance of artificial intelligence (AI) application for improving medical service diagnostics

Social acceptance of artificial intelligence (AI) application for improving medical service diagnostics

Reviewing the Impact of Machine Learning on Disease Diagnosis and Prognosis: A Comprehensive Analysis

Aim This study aimed to explore how machine learning algorithms can enhance medical diagnostics through the analysis of illness imagery and patient data, assessing their effectiveness and potential to improve diagnostic accuracy and early disease detection. Background This study highlights the critical role of machine learning in healthcare, particularly in medical diagnostics. By leveraging advanced algorithms to analyse medical data and images, machine learning enhances disease detection and diagnosis, contributing significantly to improved patient outcomes and the advancement of precision medicine. Objective The objective of this study was to thoroughly analyse and evaluate the efficacy of machine learning algorithms in medical diagnostics, focusing on their application in interpreting illness images and patient data. The goal was to ascertain the algorithms' accuracy in disease diagnosis and prognosis, aiming to demonstrate their potential in revolutionizing healthcare through improved diagnostic precision and early disease detection. Methods A systematic approach has been used in this study to evaluate machine learning algorithms' effectiveness in diagnosing diseases from medical images and data. It involved selecting pertinent datasets, applying and comparing models, like SVM and K-nearest neighbors, and assessing their diagnostic accuracy and performance, aiming to identify the most effective methodologies in medical diagnostics. Results The results have highlighted the varying accuracy of machine learning algorithms in medical diagnostics, with a focus on the performance of models, such as SVM and K-nearest neighbors. A comparative analysis has illustrated the differential effectiveness of these algorithms across various diseases and datasets, underscoring their potential to enhance healthcare diagnostics. Conclusion The study has concluded that machine learning algorithms have significantly improved medical diagnostics, offering varied effectiveness across different conditions. Their potential to revolutionize healthcare is evident, with enhanced diagnostic accuracy and efficiency. Ongoing research and clinical application are essential to harness these technologies' full benefits.

Risk Factors for Deterioration Events in the Pediatric Acute Care Setting.

Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event. For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events. Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event. Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.

Endoscopic versus surgical treatment for the management of oesophageal fistula after atrial fibrillation ablation - a subanalysis of the worldwide POTTER-AF study

Abstract Background Oesophageal fistula (OF) is considered the most dreadful complication of atrial fibrillation (AF) catheter ablation. The endoscopic and surgical treatment of OF has been proposed to improve the prognosis of these patients, but the data on the individual impact of each treatment technique are scarce. Methods The POTTER-AF study is a worldwide, multi-centre registry conducted under the auspices of the Working Group of Cardiac Electrophysiology of the German Cardiac Society (AGEP, DGK) which evaluated the incidence, management, and outcome of post-procedural OF following catheter ablation of AF [1]. A total of 553 729 patients underwent ablation procedures for AF or atrial tachycardia (AT) in 214 electrophysiological centres from 35 countries between 1996 and 2022. Of them, 138 (0.025%) patients experienced postprocedural OF and data regarding the therapeutical approach were available in 116 patients. Of them, 78 underwent surgical or interventional treatment. Herein we conducted a therapy- based analysis of the patients exhibiting OF. Purpose To assess the impact of each therapeutical approach on the prognosis of patients developing OF after AF or AT ablation. Results A total of 23 (29.5%) patients were treated using endoscopic interventions only (Endoscopy group), while 55 (70.5%) patients underwent surgical procedures (Surgery group). Of the latter, 8 (14.5%) underwent previous endoscopic treatment. The endoscopic therapy consisted of oesophageal stenting (n = 28), clipping (n = 2), or vacuum-assisted-closure therapy (n = 1). There was no difference between the Endoscopy and Surgery groups regarding the demographic characteristics and comorbidities. The energy sources used were also similar between the groups (Figure 1). There was a trend towards a higher use of an oesophageal thermal probe in the Endoscopy group (43.5% vs. 21.8%; p=0.096). The duration until symptoms onset was 10 (5.5; 18.5) days in the Endoscopy group and 18.0 (10.0; 22.0) days in the Surgery group (p=0.081), while the time to OF diagnosis was 18.0 (10.0; 26.0) days and 20.0 (15.0; 29.25) days respectively (p=0.10; Figure 2). The symptoms at presentation were similar between the two groups. Endoscopy was the diagnostic method in 45.5% of the patients in the Endoscopy group and in 16.7% in the Surgery group (p=0.017). The subsequent complications of the OF were also similar between groups. The mortality was 56.5% in the Endoscopy group and 51.9% in the Surgery group (p=0.805), while minor sequalae occurred in 8.7% patients in the former group and 16.7% in the latter (p=0.490) and major sequalae in 4.3% and 16.7% respectively (p=0.266). Conclusion There was no clinical or paraclinical parameter associated with the choice of the therapeutical approach. Patients diagnosed by means of endoscopy were more likely to undergo exclusively endoscopic interventions. The mortality, incidence of minor and major sequalae were similar between the groups.

Impact of gender on the management and prognosis of oesophageal fistula after atrial fibrillation ablation - a subanalysis of the worldwide POTTER-AF study

Abstract Background Oesophageal fistula (OF) is a rare but devastating complication following atrial fibrillation (AF) ablation. The data regarding the impact of gender on the management and prognosis of OF are scarce. Methods The POTTER-AF study is a worldwide, multi-centre registry conducted under the auspices of the Working Group of Cardiac Electrophysiology of the German Cardiac Society (AGEP, DGK) which evaluated the incidence, management, and outcome of post-procedural OF following catheter ablation of AF. A total of 553 729 patients underwent ablation procedures for AF or atrial tachycardia (AT) in 214 electrophysiological centres from 35 countries between 1996 and 2022. Of them, 138 (0.025%) patients experienced postprocedural OF and data regarding the gender, management and prognosis were available in 117 patients. Herein we conducted a gender- based analysis of the patients exhibiting OF. Purpose To evaluate the impact of gender on the management and prognosis of OF. Results Females represented 47% of the study population, which is a notable finding considering that the female population represents only a minority of the patients receiving AF/AT ablation. They were less likely to have atrioesophageal fistula (90.9% vs. 100%; p=0.021). Oesophageal-pericardial fistula occurred solely in females (7.3% vs. 0%; p=0.046). Congestive heart failure was significantly less frequent in the female population (7.4% vs. 26.7%; p=0.012). No other difference was seen between genders regarding the baseline characteristics and comorbidities (Table1). The energy source, ablation technique and utilization of oesophageal temperature probes were similar for males and females. Significantly less women received proton pump inhibitors (PPI) postprocedural (64.8% vs. 84.7%; p=0.017). The median duration until onset of symptoms was 20 days for women and 16.5 days for men (p=0.14), while the median duration until OF diagnosis was 22.5 days and 19.5 days respectively (p=0.217). Significantly more women underwent echocardiography (36.4% vs. 15%; p=0.01) as diagnostic method. More women exhibited stroke (32.7% vs. 14.8%; p=0.040), while there was no significant difference regarding the incidence of septic shock, coma, cardiac arrest, cardiac tamponade, and gastro-intestinal bleeding. Significantly more women than men presented no complications other than OF (9.6% vs. 0%; p=0.026). The females were more likely to undergo endoscopic treatment (35.8% vs. 17.7%; p=0.034), but less likely to undergo direct surgical treatment, without stenting (28.3% vs. 51.6%; p=0.014) (Figure1). The mortality was 63.6% for women and 67.2% for men (p=0.70), with no difference in terms of major and minor sequelae. Conclusion Approximatively half of the patients exhibiting postprocedural OF are females. Women showed a higher rate of endoscopic treatment and a lower rate of direct surgical treatment. The survival, as well as the incidence of minor and major sequelae were similar between genders.

Does ChatGPT-4 succeed in the ECG interpretation: friend or foe to cardiologists?

Abstract Background/Introduction Artificial intelligence (AI) and large language models (LLMs) are increasingly being tested for medical purposes, especially in clinical settings and one of the most well-known LLMs is OpenAI’s ChatGPT-4. Recent explorations have considered using ChatGPT to answer medical questions, and the new ChatGPT-4 also allows graphical inputs, which could aid medical doctors in interpreting electrocardiograms (ECGs) in everyday practice. AI-powered ECG interpretation has shown promising results, improving the detection of arrhythmias, ST-segment changes, QT prolongation, and other ECG abnormalities. However, whether ChatGPT4’s interpretation of ECGs is comparable to that of experienced cardiologists has yet to be established. Purpose We sought to test whether ChatGPT-4 could analyze and interpret ECGs similarly to experienced cardiologists. Methods We tasked ChatGPT-4 with interpreting, for scientific purposes, 12-lead ECGs, from 150 patients included in our prospective CaRD registry, presenting with various cardiac pathologies, including acute coronary syndrome, arrhythmias (primarily atrial fibrillation), conduction abnormalities, pacemaker rhythms and normal ECGs. Four experienced cardiologists reviewed the ECG interpretations provided by ChatGPT-4. The model provided information on rate, rhythm, axis, P-wave, PR interval, QRS complex, ST segment, T wave, differential diagnoses, most likely diagnosis and further diagnostic step. Results In this observational study, ChatGPT-4 demonstrated low overall accuracy in interpreting ECGs, with only 24% of the most likely diagnosis being correct. ChatGPT-4 performed the best when interpreting normal ECGs with sinus rhythm, achieving 62% accuracy rate, followed by 17%, 10% and 7.3% for ECGs with arrhythmias, acute ischemic changes, and conduction abnormalities or pacing rhythms, respectively. Conclusion ChatGPT-4 exhibited very low accuracy in interpreting different categories of pathology in 12-lead ECG, yielding less than 20% success rate. While the use of AI in medical diagnostics is an appealing concept in theory, the results suggest that, in its current state, ChatGPT-4 would not provide significant aid to experienced cardiologists in clinical settings.

Fluorophore multimerization on a PEG backbone as a concept for signal amplification and lifetime modulation

Fluorescent labels have strongly contributed to many advancements in bioanalysis, molecular biology, molecular imaging, and medical diagnostics. Despite a large toolbox of molecular and nanoscale fluorophores to choose from, there is still a need for brighter labels, e.g., for flow cytometry and fluorescence microscopy, that are preferably of molecular nature. This requires versatile concepts for fluorophore multimerization, which involves the shielding of dyes from other chromophores and possible quenchers in their neighborhood. In addition, to increase the number of readout parameters for fluorescence microscopy and eventually also flow cytometry, control and tuning of the labels’ fluorescence lifetimes is desired. Searching for bright multi-chromophoric or multimeric labels, we developed PEGylated dyes bearing functional groups for their bioconjugation and explored their spectroscopic properties and photostability in comparison to those of the respective monomeric dyes for two exemplarily chosen fluorophores excitable at 488 nm. Subsequently, these dyes were conjugated with anti-CD4 and anti-CD8 immunoglobulins to obtain fluorescent conjugates suitable for the labeling of cells and beads. Finally, the suitability of these novel labels for fluorescence lifetime imaging and target discrimination based upon lifetime measurements was assessed. Based upon the results of our spectroscopic studies including measurements of fluorescence quantum yields (QY) and fluorescence decay kinetics we could demonstrate the absence of significant dye-dye interactions and self-quenching in these multimeric labels. Moreover, in a first fluorescence lifetime imaging (FLIM) study, we could show the future potential of this multimerization concept for lifetime discrimination and multiplexing.

Advancements and Prospects of Electronic Nose in Various Applications: A Comprehensive Review

An electronic nose, designed to replicate human olfaction, captures distinctive ‘fingerprint’ data from mixed gases or odors. Comprising a gas sensing system and an information processing unit, electronic noses have evolved significantly since their inception in the 1980s. They have transitioned from bulky, costly, and energy-intensive devices to today’s streamlined, economical models with minimal power requirements. This paper presents a comprehensive and systematic review of the electronic nose technology domain, with a special focus on advancements over the last five years. It highlights emerging applications, innovative methodologies, and potential future directions that have not been extensively covered in previous reviews. The review explores the application of electronic noses across diverse fields such as food analysis, environmental monitoring, and medical diagnostics, including new domains like veterinary pathology and pest detection. This work aims to underline the adaptability of electronic noses and contribute to their continued development and application in various industries, thereby addressing gaps in current literature and suggesting avenues for future research.

Core needle biopsy for thyroid nodules assessment-a new horizon?

Ultrasound-guided fine-needle aspiration is the standard for evaluating thyroid nodules with a high safety profile and a relatively low number of non-diagnostic cytological findings. Nevertheless, this diagnostic method traditionally has its weak points. Several diagnostic categories such as Bethesda I, III and IV are not reliable for thyroid carcinoma risk assessment. Recent advancements in a core needle biopsy made it possible to use this tool as a new method for thyroid nodules evaluation. The main feature of this method is the use of thin needles (18-21G) and guns with an automatic trigger mechanism. The histological material collected with the use of a core needle biopsy is usually superior to cytological. Therefore, the core needle biopsy can be used as a complementary technique to a standard fine needle aspiration in difficult and dubious cases of thyroid neoplasia with uncertain malignant potential.