Diagnostic Accuracy Research Articles

Malaria Rapid Tests, Febrile Illness Management, and Child Mortality Across Sub-Saharan African Countries

A prompt malaria diagnosis is crucial for the management of children with febrile illness in sub-Saharan African countries, where malaria remains a leading cause of mortality among children younger than 5 years of age. The development and distribution of point-of-care rapid diagnostic tests (RDTs) for malaria has transformed practice, but limited systematic evidence exists on how malaria RDTs have affected the management of febrile illness and mortality for children younger than 5 years of age across sub-Saharan Africa countries. To evaluate the association between the distribution of malaria RDTs and the management of febrile illness and mortality among children younger than 5 years of age in sub-Saharan African countries. This quasi-experimental study used a novel dataset linking malaria RDT distribution to 165 nationally representative household surveys across 35 sub-Saharan African countries with mortality data. The sample comprised approximately 3.9 million child-year observations and approximately 260 000 febrile illness episodes in children younger than 5 years of age between 2000 and 2019. Fixed-effects linear probability models were used to analyze the association between variation in malaria RDTs distributed per child younger than 5 years of age (by country per year) and blood testing, antimalarial drug use, antibiotic use, use of symptomatic treatments, and mortality rates. Variation in the effects of testing and treatment was also assessed across the sub-Saharan African countries that had varying prevalence of malaria. The mortality sample included 1 317 866 children and the fever sample included 256 292 children. The mean age of the children with febrile illness was 2.4 years (SD, 1.3 years) and 49% were female. Each additional malaria RDT distributed per child younger than 5 years of age was associated with an increase of 3.5 percentage points (95% CI, 3.2-3.8 percentage points) in blood testing, an increase of 1.5 percentage points (95% CI, 1.2-1.8 percentage points) in the use of antimalarial drugs, an increase of 0.4 percentage points (95% CI, 0.1-0.6 percentage points) in antibiotic use, and a decrease of 0.4 percentage points (95% CI, 0.1-0.8 percentage points) in the use of treatments for symptoms. Each additional malaria RDT distributed per child younger than 5 years of age was associated with a reduction in child mortality of 0.34 deaths per 1000 child-years (95% CI, 0.15-0.52 deaths per 1000 child-years). The effects of malaria RDT distribution on medication use and child mortality varied across prevalence settings (low vs high) for malaria; there were survival improvements only in areas that had a high prevalence of malaria. Increasing distribution of malaria RDTs was associated with increased blood testing, increased use of antimalarial drugs, and modestly improved survival in children younger than 5 years of age in sub-Saharan African countries. However, malaria RDTs were associated with increases in the rates of antibiotic use that were already high, suggesting that more comprehensive approaches to case management of febrile illness are needed.

Natural Frequencies Improve Public Understanding of Medical Test Results: An Experimental Study on Various Bayesian Inference Tasks with Multiple Scoring Methods and Non-Bayesian Reasoning Strategies.

It is well established that the natural frequencies (NF) format is cognitively more beneficial for Bayesian inference than the conditional probabilities (CP) format. However, empirical studies have suggested that the NF facilitation effect might be limited to specific groups of individuals. Unlike previous studies that focused on a limited number of Bayesian inference problems evaluated by a single scoring method, it was essential to examine multiple Bayesian problems using various scoring metrics. This study also explored the impact of numeracy on Bayesian inference and assessed non-Bayesian cognitive strategies using the numerical information in problem solving. In a Web-based experimental survey, 175 South Korean adults were randomly assigned to 1 of 2 format groups (NF v. CP). After completing numeracy scales, participants were asked to estimate 4 Bayesian inference problems and document the numerical information used in their problem-solving process. Four scoring methods-strict rounding, loose rounding, absolute deviation, and 50-Split-were used to evaluate participants' estimations. The NF format generally outperformed the CP format across all problems, except in a chorionic villus sampling test problem when evaluated using the 50-Split method. In addition, numeracy levels significantly influenced Bayesian inference; participants with higher numeracy demonstrated better performance. In addition, participants used various non-Bayesian strategies influenced by the format and the nature of the problems. The NF facilitation effect was consistently observed across multiple Bayesian problems and scoring methods. Individuals with higher numeracy levels benefited more from the NF format. The use of various non-Bayesian strategies varied with the formats and nature of specific tasks. The natural frequencies (NF) format is known to foster understanding of medical test results compared with the conditional probabilities (CP) format, but some studies have reported that this benefit is either nonexistent or limited to specific groups.This study aims to replicate previous empirical studies using various Bayesian problems using multiple scoring methods.The NF format fosters understanding of medical test results across all Bayesian problems by all scoring methods, except in the CVS problem when using a 50-Split scoring method.Participants with high numeracy perform better Bayesian inference than those with lower numeracy. Particularly, higher numerates benefit more in the NF format than lower numerates do. In addition, the public tend to use various non-Bayesian reasoning strategies depending on the format and the nature of the tasks.

Endoscopic ultrasound-guided fine needle biopsy using macroscopic on-site evaluation technique reduces the number passes yet maintains a high diagnostic accuracy: A randomized study.

Although rapid on-site cytological evaluation (ROSE) for endoscopic ultrasound (EUS)-guided tissue acquisition (EUS-TA) may increase diagnostic yield, it is not widely available. Macroscopic on-site evaluation (MOSE) is an alternative modality although it is not standardized for EUS-guided fine-needle biopsy (FNB). We evaluated diagnostic performance of MOSE compared with conventional technique of EUS-TA using core biopsy needle. Consecutive patients undergoing EUS-FNA for solid lesions were randomized to MOSE or conventional arms. The primary and secondary outcome measures were diagnostic accuracy, diagnostic yield, sensitivity, specificity, positive and negative predictive values, and the number of passes, respectively. The optimum parameters for macroscopic visible core (MVC, i.e., length, number) by MOSE to achieve accurate diagnosis were evaluated. Ninety-six patients (48 conventional and 48 MOSE) were enrolled. Mean lesion size was larger in MOSE arm (32.67±7.22 vs 29.31±6.98mm, P=0.023). Diagnostic accuracy (95.8% vs 91.6%), diagnostic yield (97.9% vs 95.8%), procedure duration, and adverse events of the two methods were similar. Median number of passes with MOSE was less (2 vs 3 P=0.000). Area under the receiver operating characteristic curve showed that with MOSE, obtaining a total MVC length of 11.5mm had 93.3% sensitivity, and 2.5 MVC cores (each 4mm) had 86.7% sensitivity for malignancy diagnosis. EUS-FNB with MOSE, a simple reliable technique, can achieve a high and comparable diagnostic accuracy with lesser number of passes. Obtaining longer length and greater number of MVC increase the sensitivity to diagnose malignancy with MOSE.

Accuracy of convex probe EBUS-TBNA versus FDG-PET/CT imaging in diagnosis and mediastinal staging of lung cancer patients; an Egyptian Experience

BackgroundAppropriate staging of lung cancer is of paramount importance, as it customizes treatment and predicts prognosis. Both Fludeoxyglucose-18 (FDG) positron emission tomography (PET) combined with contrast computed tomography (CT) and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) are two widely used diagnostic modalities in the field of staging & diagnosis of lung malignancies, the former depends on image analysis while the later enables real-time sampling of lymph nodes under sonographic guidance.ObjectiveTo compare the diagnostic and staging accuracy of convex probe EBUS-TBNA versus FDG – PET/CT as two modalities in diagnosis & mediastinal staging of lung cancer patients.MethodsThis prospective, observational (daignostic accuracy) research was performed on 40 cases with lung malignancies. All cases were examined via FDG-PET/CT followed by convex probe EBUS-TBNA for diagnosis & staging of concurrent mediastinal lymphadenopathy (MLN).ResultsThe diagnostic yield of EBUS-TBNA reached 92.5% (37/40) compared to 70% (28/40) for FDG-PET/CT. There was poor agreement between EBUS-TBNA & FDG-PET/CT regarding (MLN) staging (k = 0.043), in 16/40 patients (40%), EBUS MLN staging matched that of FDG-PET/CT, while in 24/40(60%) there were discrepancies between the two diagnostic modalities; 18/40(45%) were up-staged after EBUS while 6/40(15%) were down staged after EBUS. In addition, EBUS-TBNA confirmed occult mediastinal nodal involvement in 9/10 FDG-PET/CT negative scans (N0). The overall diagnostic accuracy of EBUS-TBNA was significantly greater than FDG-PET/CT in staging of lung cancer (97.37% & 70% respectively, p < 0.001).ConclusionEBUS-TBNA is a minimally invasive procedure that we currently recommend as a first choice for MLN staging.Trial registrationClinicalTrials.gov, NCT06479798. Registered 26 June 2024—Retrospectively registered, https://clinicaltrials.gov/study/NCT06479798.

Педиатрическая рентгенография: проблемы и решения

Background: Because of children's distinct physiological and anatomical features, pediatric radiography necessitates particular techniques. Recent advances in medical physics have considerably improved the accuracy and safety of pediatric radiological procedures. However, these developments bring new obstacles. Objective: This article evaluates the most recent advances in medical physics relevant to pediatric radiography, highlights the accompanying problems, and provides feasible solutions to improve clinical results and patient safety. Methods: A thorough literature analysis focused on current research and technology advancements in pediatric radiology. The main advances in imaging technology, radiation dose control, and diagnostic accuracy were examined. Expert comments and case studies were also analyzed for common issues and solutions. Results: Low-dose imaging methods, such as digital radiography, pediatric-specific computed tomography (CT), and magnetic resonance imaging (MRI), have advanced significantly. These enhancements have resulted in better image quality and lower radiation exposure. However, patient size heterogeneity, motion artifacts, and the necessity for age-specific procedures remain common. Conclusion: Medical physics advancements have significantly enhanced pediatric radiology, allowing for higher diagnostic capabilities while reducing hazards. To address the remaining difficulties, radiologists must continue research, adopt standardized methods, and get continual education. Future advances should focus on lowering radiation exposure and enhancing imaging technologies' flexibility to meet pediatric patients' demands.

Impact of neutrophil‐activating protein conservation on diagnostic tests and vaccine design

AbstractBACKGROUNDThe neutrophil activating protein (NAP) is a highly immunogenic and virulence factor of Helicobacter pylori, presenting inflammatory and immunomodulatory activity. Consequently, NAP has been explored as a diagnostic and therapeutic target. However, when evaluating a target protein to design diagnostic methods or vaccines, it is critical to determine the protein conservation among the bacterial population, as well the impact of alterations of amino acid residues on the protein antigenic profile.RESULTSIn the present work, NAP conservation and theoretical antigenicity were determined among 51 sequences from H. pylori isolated from patients worldwide. A high NAP conservation (83%) was observed, where 17 amino acid residues, among the 144 residues of the protein, were polymorphic. Alterations at these polymorphic sites had a theoretically low impact on predicted antigenicity, where only 5 NAPs out of 51 NAPs presented a slightly different antigenic profile in relation to the consensus sequence. According to that, it was possible to recognize in western blotting 93% of NAP from different bacteria (n = 15) using polyclonal antibodies developed against a specific NAP.CONCLUSIONSIt was predicted that when working with polyclonal antibodies or large NAP fragments for diagnostic and vaccine design, slight variation in protein sequence will have a minimal impact on NAP recognition. However, if a NAP monoclonal antibody or small NAP epitopes are considered, it is critical to select the most conserved and antigenic NAP regions, to maximize the coverage of NAP variants. © 2024 Society of Chemical Industry (SCI).

Causal Associations of Sleep Apnea With Alzheimer Disease and Cardiovascular Disease: A Bidirectional Mendelian Randomization Analysis.

Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular, or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization. Using summary statistics from 4 recent, large genome-wide association studies of SA (n=523 366), AD (n=94 437), CAD (n=1 165 690), and stroke (n=1 308 460), we conducted bidirectional 2-sample Mendelian randomization analyses. Our primary analytic method was fixed-effects inverse variance-weighted (IVW) Mendelian randomization; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. We identified a significant causal effect of SA on the risk of CAD (odds ratio [ORIVW]=1.35 per log-odds increase in SA liability [95% CI=1.25-1.47]) and stroke (ORIVW=1.13 [95% CI=1.01-1.25]). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (ORIVW=1.26 [95% CI=1.15-1.39] for CAD risk; ORIVW=1.08 [95% CI=0.96-1.22] for stroke risk). SA was not causally associated with a higher risk of AD (ORIVW=1.14 [95% CI=0.91-1.43]). We did not find causal effects of AD, CAD, or stroke on risk of SA. These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by body mass index. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.

The GFAP proteoform puzzle: How to advance GFAP as a fluid biomarker in neurological diseases.

Glial fibrillary acidic protein (GFAP) is a well-established biomarker of reactive astrogliosis in the central nervous system because of its elevated levels following brain injury and various neurological disorders. The advent of ultra-sensitive methods for measuring low-abundant proteins has significantly enhanced our understanding of GFAP levels in the serum or plasma of patients with diverse neurological diseases. Clinical studies have demonstrated that GFAP holds promise both as a diagnostic and prognostic biomarker, including but not limited to individuals with Alzheimer's disease. GFAP exhibits diverse forms and structures, herein referred to as its proteoform complexity, encompassing conformational dynamics, isoforms and post-translational modifications (PTMs). In this review, we explore how the proteoform complexity of GFAP influences its detection, which may affect the differential diagnostic performance of GFAP in different biological fluids and can provide valuable insights into underlying biological processes. Additionally, proteoforms are often disease-specific, and our review provides suggestions and highlights areas to focus on for the development of new assays for measuring GFAP, including isoforms, PTMs, discharge mechanisms, breakdown products, higher-order species and interacting partners. By addressing the knowledge gaps highlighted in this review, we aim to support the clinical translation and interpretation of GFAP in both CSF and blood and the development of reliable, reproducible and specific prognostic and diagnostic tests. To enhance disease pathology comprehension and optimise GFAP as a biomarker, a thorough understanding of detected proteoforms in biofluids is essential.

Detection rate of gastrin-releasing peptide receptor (GRPr) targeted tracers for positron emission tomography (PET) imaging in primary prostate cancer: a systematic review and meta-analysis.

The gastrin-releasing peptide receptor (GRPr) has gained recognition as a promising target for both diagnostic and therapeutic applications in a variety of human cancers. This study aims to explore the primary tumor detection capabilities of [68Ga] Ga-GRPr PET imaging, specifically in newly diagnosed intra-prostatic prostate cancer lesions (PCa). Following PRISMA-DTA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies) guidelines, a systematic literature search was conducted using the Medline, Embase, Scopus, and Web of Science databases. Data regarding patient characteristics and imaging procedure details-including the type of radiotracer used, administered activity, image acquisition time, scanner modality, criteria, and detection rate of index test-were extracted from the included studies. The pooled patient-and lesion-based detection rates, along with their corresponding 95% confidence intervals (CI), were calculated using a random effects model. The final analysis included 9 studies involving 291 patients and 350 intra-prostatic lesions with [68Ga] Ga-GRPr PET imaging in primary PCa. In per-patient-based analysis of [68Ga] Ga-GRPr PET imaging, the pooled detection rates of overall and patients with Gleason score ≥ 7 were 87.09% (95% CI 74.98-93.82) and 89.01% (95% CI 68.17-96.84), respectively. In per-lesion-based analysis, the pooled detection rate [68Ga] Ga-GRPr PET imaging was 78.54% (95% CI 69.8-85.29). The pooled detection rate mpMRI (multiparametric magnetic resonance imaging) in patient-based analysis was 91.85% (95% CI 80.12-96.92). The difference between the detection rates of the mpMRI and [68Ga] Ga-GRPr PET imaging was not statistically significant (OR 0.90, 95% CI 0.23-3.51). Our findings suggest that [68Ga] Ga-GRPr PET imaging has the potential as a diagnostic target for primary PCa. Future research is needed to determine the effectiveness of [68Ga] Ga-GRPr PET in delivering additional imaging data and guiding therapeutic decisions.

How to detect affect recognition alterations in amyotrophic lateral sclerosis.

To define the clinical usability of an affect recognition (AR) battery-the Comprehensive Affect Testing System (CATS)-in an Italian sample of patients with amyotrophic lateral sclerosis (ALS). 96 ALS patients and 116 healthy controls underwent a neuropsychological assessment including the AR subtests of the abbreviated version of the CATS (CATS-A). CATS-A AR subtests and their global score (CATS-A AR Quotient, ARQ) were assessed for their factorial, convergent, and divergent validity. The diagnostic accuracy of each CATS-A AR measure in discriminating ALS patients with cognitive impairment from cognitively normal controls and patients was tested via receiver-operating characteristics analyses. Optimal cut-offs were identified for CATS-A AR measures yielding an acceptable AUC value (≥ .70). The ability of CATS-A ARQ to discriminate between different ALS cognitive phenotypes was also tested. Gray-matter (GM) volumes of controls, ALS with normal (ALS-nARQ), and impaired ARQ score (ALS-iARQ) were compared using ANCOVA models. CATS-A AR subtests and ARQ proved to have moderate-to-strong convergent and divergent validity. Almost all considered CATS-A measures reached acceptable accuracy and diagnostic power (AUC range = .79-.83). ARQ showed to be the best diagnostic measure (sensitivity = .80; specificity = .75) and discriminated between different ALS cognitive phenotypes. Compared to ALS-nARQ, ALS-iARQ patients showed reduced GM volumes in the right anterior cingulate, right middle frontal, left inferior temporal, and superior occipital regions. The AR subtests of the CATS-A, and in particular the CATS-A ARQ, are sound measures of AR in ALS. AR deficits may be a valid marker of frontotemporal involvement in these patients.

Artificial Intelligence Tools in Pediatric Urology: A Comprehensive Review of Recent Advances

Artificial intelligence (AI) is providing novel answers to long-standing clinical problems, and it is quickly changing pediatric urology. This thorough analysis focuses on current developments in AI technologies that improve pediatric urology diagnosis, treatment planning, and surgery results. Deep learning algorithms help detect problems with previously unheard-of precision in disorders including hydronephrosis, pyeloplasty, and vesicoureteral reflux, where AI-powered prediction models have demonstrated promising outcomes in boosting diagnostic accuracy. AI-enhanced image processing methods have significantly improved the quality and interpretation of medical images. Examples of these methods are deep-learning-based segmentation and contrast limited adaptive histogram equalization (CLAHE). These methods guarantee higher precision in the identification and classification of pediatric urological disorders, and AI-driven ground truth construction approaches aid in the standardization of and improvement in training data, resulting in more resilient and consistent segmentation models. AI is being used for surgical support as well. AI-assisted navigation devices help with difficult operations like pyeloplasty by decreasing complications and increasing surgical accuracy. AI also helps with long-term patient monitoring, predictive analytics, and customized treatment strategies, all of which improve results for younger patients. However, there are practical, ethical, and legal issues with AI integration in pediatric urology that need to be carefully navigated. To close knowledge gaps, more investigation is required, especially in the areas of AI-driven surgical methods and standardized ground truth datasets for pediatric radiologic image segmentation. In the end, AI has the potential to completely transform pediatric urology by enhancing patient care, increasing the effectiveness of treatments, and spurring more advancements in this exciting area.

Diagnostic Capability of Ultrasonography in Evaluating Peripheral Nerve Injuries of the Brachial Plexus.

The purpose of this study is to determine the diagnostic capability of ultrasonography (US) in patients with suspected brachial plexus injury (BPI) to the terminal nerves by comparing physical examination (PE) findings with US, electromyography (EMG), and magnetic resonance imaging (MRI) reports. All patients at a single institution who underwent US for peripheral nerve injury of the brachial plexus and terminal nerves resulting in sensory-motor deficits from October 1, 2017 to October 31, 2023 were identified. A retrospective chart review was performed. Each PE, US, EMG, and MRI reports were given an overall rating: "normal" or "abnormal." Terminal nerves (musculocutaneous, axillary, radial, ulnar, medial) were individually assessed as "normal" or "abnormal." The interobserver agreement between reports was calculated using Cohen kappa. Specificity and sensitivity analyses were performed to determine diagnostic accuracy and were reported with 95% confidence intervals (CI). A total of 120 patients were included. Most injuries were traumatic in nature (78.8%) and were low-energy (53.8%). When each imaging modality was compared with the PE findings, EMG had the highest interobserver agreement (Cohen kappa = 0.18), followed by US (Cohen kappa = 0.10), and last MRI (Cohen kappa = 0.07). The US had the highest sensitivity (0.92, CI = 0.85, 0.96) among the 3 imaging modalities (Table 2). On US, the ulnar nerve was most commonly abnormal (n = 84, 70.0%). Ultrasonography serves as a useful adjunct in the workup of patients with suspected peripheral BPI and is reliable in localizing the pathology of injured terminal nerves in the brachial plexus.

Update on Whole-body MRI Surveillance for Pediatric Cancer Predisposition Syndromes.

Whole-body MRI (WBMRI) is an integral part of screening infants, children and adolescents for pre-symptomatic neoplasms in certain cancer predisposition syndromes (CPS). This includes Li-Fraumeni and Constitutional Mismatch Repair Deficiency syndromes, among others. The list of syndromes where WBMRI adds value, as part of a comprehensive surveillance protocol, continues to evolve in response to new evidence, growing experience and more widespread adoption of WBMRI. In July 2023, the American Association of Cancer Research (AACR) reconvened an international, multidisciplinary panel to revise and update recommendations stemming from the 2016 AACR Special Workshop on Childhood Cancer Predisposition. That initial meeting resulted in a series of publications in Clinical Cancer Research in 2017, including "Pediatric Cancer Predisposition Imaging: Focus on Whole Body MRI". This 2024 review of WBMRI in CPS updates the 2017 WBMRI publication, the revised recommendations derived from the 2023 AACR Childhood Cancer Predisposition Workshop based on available data, societal guidelines and expert opinion. Different aspects of acquiring and interpreting WBMRI including diagnostic accuracy are discussed. Application of WBMRI in resource poor environments, as well as integration of whole-body imaging techniques with emerging technologies such as cell-free DNA, or liquid biopsies, and artificial intelligence/machine learning are also considered.

Enhancing Pap Smear Image Classification: Integrating Transfer Learning and Attention Mechanisms for Improved Detection of Cervical Abnormalities

Abstract Cervical cancer remains a major global health challenge, accounting for significant morbidity and mortality among women. Early detection through screening, such as Pap smear tests, is crucial for effective treatment and improved patient outcomes. However, traditional manual analysis of Pap smear images is labor-intensive, subject to human error, and requires extensive expertise. To address these challenges, automated approaches using deep learning techniques have been increasingly explored, offering the potential for enhanced diagnostic accuracy and efficiency. This research focuses on improving cervical cancer detection from Pap smear images using advanced deep-learning techniques. Specifically, we aim to enhance classification performance by leveraging Transfer Learning (TL) combined with an attention mechanism, supplemented by effective preprocessing techniques. Our preprocessing pipeline includes image normalization, resizing, and the application of Histogram of Oriented Gradients (HOG), all of which contribute to better feature extraction and improved model performance. The dataset used in this study is the Mendeley Liquid-Based Cytology (LBC) dataset, which provides a comprehensive collection of cervical cytology images annotated by expert cytopathologists. Initial experiments with the ResNet model on raw data yielded an accuracy of 63.95%. However, by applying our preprocessing techniques and integrating an attention mechanism, the accuracy of the ResNet model increased dramatically to 96.74%. Further, the Xception model, known for its superior feature extraction capabilities, achieved the best performance with an accuracy of 98.95%, along with high precision (0.97), recall (0.99), and F1-Score (0.98) on preprocessed data with an attention mechanism. These results underscore the effectiveness of combining preprocessing techniques, TL, and attention mechanisms to significantly enhance the performance of automated cervical cancer detection systems. Our findings demonstrate the potential of these advanced techniques to provide reliable, accurate, and efficient diagnostic tools, which could greatly benefit clinical practice and improve patient outcomes in cervical cancer screening.

Harmonizing Insights: LR-FFT Feature Extraction for Alzheimer’s and Autism Spectrum Disorder Detection in EEG Signals

Alzheimer’s Disease (AD) and Autism Spectrum Disorder (ASD) represent two distinct but equally impactful challenges in the field of neurology and cognitive health. AD is a degenerative neurological condition characterized by its progressive nature, typically affecting individuals in later stages of life. The hallmark features include cognitive impairment, mem- ory deterioration, and alterations in behavior. In contrast, ASD is a developmental disorder typically diagnosed in childhood, marked by difficulties in social interaction, communication, and repetitive behaviors. This paper explores the potential of the time-frequency feature extraction model known as the Left-Right Fast Fourier Transform (LR-FFT) in the context of these two disorders. While AD and ASD differ significantly in their onset, presentation, and demographic affected, both necessitate early and accurate diagnosis to enable timely intervention and tailored treatment strategies. Our research yields promising results, with classification accuracies reaching 88.26% for AD and 99.86% for ASD, demonstrating the LR-FFT’s potential to enhance diagnostic accuracy. By contributing to improved differentiation between these complex neurological conditions, this work aims to advance our understanding and management of AD and ASD, ultimately benefiting patients, their families, and healthcare practitioners.

Artificial intelligence in psychiatric diagnosis: challenges and opportunities in the era of machine learning

The integration of artificial intelligence (AI) into psychiatric diagnosis heralds a new era in mental health care, offering unprecedented opportunities to enhance diagnostic accuracy, personalize treatment, and streamline clinical workflows. A systematic approach was utilized, adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. This literature review explores the current state of AI in psychiatric diagnosis, highlighting key technologies such as machine learning, natural language processing, and deep learning. We discuss the application of these technologies across various psychiatric disorders, including depression, anxiety, and schizophrenia. While AI holds immense promise, significant challenges remain, including issues of data privacy, model bias, and the clinical validation of AI tools. Furthermore, ethical and regulatory considerations must be addressed to ensure responsible implementation. This review also examines the potential future directions of AI in psychiatry, emphasizing the importance of collaboration between AI systems and human clinicians. As the field evolves, AI has the potential to transform psychiatric practice, offering new avenues for early detection, personalized care, and therapeutic monitoring.

The value of SDC2 and Septin9 combined with serum tumor markers in early diagnosis of colorectal cancer

ObjectiveThe aim of this study is to evaluate the significance of combined detection of Septin9 and syndecan-2 (SDC2) methylation markers and serum tumor markers for the early diagnosis of colorectal cancer.MethodsA total of 116 patients diagnosed with colorectal cancer between December 2022 and February 2024 were designated as the colorectal cancer group. Additionally, 31 patients with colorectal adenoma were assigned to the adenoma group, while 44 individuals undergoing routine physical examinations were included in the control group. Concentrations of Septin9, SDC2, fecal occult blood (FOB), and four tumor markers—carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), carbohydrate antigen 125 (CA125), and carbohydrate antigen 724 (CA724)—were measured. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves for Septin9, SDC2, the four tumor markers, FOB, the combination of Septin9 and SDC2, and the combined use of all seven indicators (CEA, CA19-9, CA125, CA72-4, FOB, Septin9, and SDC2).ResultsThe colorectal cancer group exhibited the highest positive rates for Septin9, SDC2, the four tumor markers, the combined detection of Septin9 and SDC2, and the combined detection of all seven indicators, compared to both the adenoma and control groups (P < 0.05). The adenoma group also showed higher positive rates than the control group (P < 0.05). For patients with stage I–III colorectal cancer, the positive rates for the combined detection of Septin9 and SDC2 were 81.3%, 78.9%, and 90.2%, respectively, surpassing those for the combined detection of the four tumor markers (43.8%, 55.3%, and 61.0%). Additionally, the positive rates for the two-gene combination in stage III colorectal cancer were higher than those for FOB (P < 0.05). The sensitivity and area under the curve (AUC) for SDC2 were 73.3% and 0.855, respectively, exceeding the sensitivity and AUC for the combined four tumor markers, which were 60.3% and 0.734 (P < 0.05). The combined detection of the two methylated genes demonstrated a sensitivity of 86.2% and an AUC of 0.908, outperforming both FOB and the combined detection of the four tumor markers (P < 0.05).ConclusionThe detection of SDC2 exhibits high sensitivity for colorectal cancer, and when combined with Septin9, it significantly enhances the diagnostic accuracy for early-stage colorectal cancer, offering substantial clinical value.

Performance of ParaHIT® HRP2-Based Rapid Diagnostic Test and Proportions of Plasmodium falciparum Histidine-Rich Protein 2/3 Gene Deletions in Togo.

In areas where malaria is endemic and microscopes are unavailable, rapid diagnostic tests (RDTs) are essential tools for early diagnosis and prompt and effective treatment. However, HRP2-based RDTs are threatened by the emergence of Plasmodium falciparum parasites that do not carry the pfhrp2 or pfhrp3 gene, leading to false-negative results. Therefore, the aim of this study was to evaluate the performance of the ParaHIT RDT together with the proportion of pfhrp2/3 gene-deleted P. falciparum parasites in Togo. The performance of RDTs compared with microscopy and polymerase chain reaction (PCR) was determined using capillary blood collected by finger prick during a cross-sectional study conducted from September 2021 to January 2022 in children aged 6-59 months at two sentinel sites. Blood spots were collected for molecular analysis. Amplicons from the target regions (exon 2 of hrp2 and hrp3 genes) were generated by multiplex nested PCR and sequenced using Illumina's MiSeq protocol. A total of 278 samples were analyzed for ParaHIT RDT evaluation. The sensitivity and specificity of the RDT test compared with microscopy were 96.4% and 85.7%, respectively, which increased to 97.9% and 90.7%, respectively, when compared with PCR. Of the microscopically and PCR-positive P. falciparum samples, 138 were sequenced to detect pfhrp2/3 deletions. None of the parasites had a single pfhrp2 deletion or a single pfhrp3 deletion. The ParaHIT RDT demonstrated an acceptable level of performance in this evaluation, confirming the use of HRP2-based RDTs for the detection of P. falciparum infection in areas where microscopy is not available in Togo.

PCR enables rapid detection of dermatophytes in practice.

Dermatophytes cause superficial infections of skin, hair, and nails. Even though they rarely cause severe infections, they are relatively common, particularly in primary health care. Diagnosis of dermatophyte infections has relied on relatively slow culture-based methods. Nucleic acid-based detection (PCR) methods might provide results more rapidly. Here, we describe the transition from culture-based methods into PCR-based methods in Northern Finland with a catchment area of approximately 720,000 mostly Caucasian people. This study included 14,330 samples collected between 2019 and 2022. Our results showed that the PCR-based method has become the diagnostic test of choice for these infections in this area. Commercial real-time PCR assay DermaGenius 2.0 complete multiplex test detected more positive results than culture and covered the most important dermatophytes, Candida albicans, and few less common species. With PCR, the mean turn-around-time from sample request to results decreased from 19 days to 16 hours.IMPORTANCESuperficial fungal infections, dermatophytosis, are remarkably common worldwide, affecting an estimated 20%-25% of the global population. In the diagnosis of these infections, fast and accurate results by PCR shorten the time to diagnosis and help clinicians to avoid unnecessary antifungal treatments.

Documentation of shared decision-making in diagnostic testing for dementia in Dutch general practice: A retrospective study in electronic patient records

ObjectiveTo explore (1) documentation of shared decision-making (SDM) in diagnostic testing for dementia in electronic patient records (EPR) in general practice and (2) study whether documentation of SDM is related to specific patient characteristics. MethodsIn this retrospective observational study, EPRs of 228 patients in three Dutch general practices were explored for the documentation of SDM elements using Elwyn’s model (team talk, option talk, decision talk). Patient characteristics (gender, age, comorbidities, chronic polypharmacy, the number of consultations on memory complaints) and decision outcome (wait-and-see, GP diagnostics, referral) were also extracted. ResultsIn EPRs of most patients (62.6 %), at least one SDM element was documented. Most often this concerned team talk (61.6 %). Considerably less often option talk (4.3 %) and decision talk (12.8 %) were documented. SDM elements were more frequently documented in patients with lower comorbidity scores and patients with a relatively high number of consultations. Decision talk was more frequently documented in referred patients. ConclusionPatients' and significant others’ needs, goals, and wishes on diagnostic testing for dementia are often documented in EPRs. Practice implicationsLimited documentation of option and decision talk stresses the need for future SDM interventions to facilitate timely dementia diagnosis.