Integrated neural network and evolutionary algorithm approach for liver fibrosis staging: Can artificial intelligence reduce patient costs?

Background and Aim: Staging liver fibrosis is important, and liver biopsy is the gold standard diagnostic tool. We aim to design and evaluate an artificial neural network (ANN) method by taking advantage of the Teaching Learning-Based Optimization (TLBO) algorithm for the prediction of liver fibrosis stage in blood donors and hepatitis C patients. Methods: We propose a method based on a selection of machine learning classification methods including multilayer perceptron (MLP) neural network, Naive Bayesian (NB), decision tree, and deep learning. Initially, the synthetic minority oversampling technique (SMOTE) is performed to address the imbalance in the dataset. Afterward, the integration of MLP and TLBO is implemented. Results: We propose a novel algorithm that reduces the number of required patient features to seven inputs. The accuracy of MLP using 12 features is 0.903, while that of the proposed MLP with TLBO is 0.891. Besides, the diagnostic accuracy of all methods, except the model designed with the Bayesian network, increases when the SMOTE balancer is applied. Conclusion: The decision tree-based deep learning methods show the highest levels of accuracy with 12 features. Interestingly, with the use of TLBO and seven features, MLP reached an accuracy rate of 0.891, which is quite satisfactory when compared with those of similar studies. The proposed model provides high diagnostic accuracy, while reducing the required number of properties from the samples. The results of our study show that the recruited algorithm of our study is more straightforward, with a smaller number of required properties and similar accuracy.

Ultra-low-dose vs. standard-of-care-dose CT of the chest in patients with post-COVID-19 conditions-a prospective intra-patient multi-reader study.

OBJECTIVES: To conduct an intrapatient comparison of ultra-low-dose computed tomography (ULDCT) and standard-of-care-dose CT (SDCT) of the chest in terms of the diagnostic accuracy of ULDCT and intrareader agreement in patients with post-COVID conditions. METHODS: We prospectively included 153 consecutive patients with post-COVID-19 conditions. All participants received an SDCT and an additional ULDCT scan of the chest. SDCTs were performed with standard imaging parameters and ULDCTs at a fixed tube voltage of 100 kVp (with tin filtration), 50 ref. mAs (dose modulation active), and iterative reconstruction algorithm level 5 of 5. All CT scans were separately evaluated by four radiologists for the presence of lung changes and their consistency with post-COVID lung abnormalities. Radiation dose parameters and the sensitivity, specificity, and accuracy of ULDCT were calculated. RESULTS: Of the 153 included patients (mean age 47.4 ± 15.3 years; 48.4% women), 45 (29.4%) showed post-COVID lung abnormalities. In those 45 patients, the most frequently detected CT patterns were ground-glass opacities (100.0%), reticulations (43.5%), and parenchymal bands (37.0%). The accuracy, sensitivity, and specificity of ULDCT compared to SDCT for the detection of post-COVID lung abnormalities were 92.6, 87.2, and 94.9%, respectively. The median total dose length product (DLP) of ULDCTs was less than one-tenth of the radiation dose of our SDCTs (12.6 mGy*cm [9.9; 15.5] vs. 132.1 mGy*cm [103.9; 160.2]; p < 0.001). CONCLUSION: ULDCT of the chest offers high accuracy in the detection of post-COVID lung abnormalities compared to an SDCT scan at less than one-tenth the radiation dose, corresponding to only twice the dose of a standard chest radiograph in two views. CLINICAL RELEVANCE STATEMENT: Ultra-low-dose CT of the chest may provide a favorable, radiation-saving alternative to standard-dose CT in the long-term follow-up of the large patient cohort of post-COVID-19 patients.

Grammatical correction and morphological productivity tasks as potential identifiers of developmental language disorder in Spanish-Catalan bilingual children: a pilot study.

A critical problem for Catalan-Spanish bilinguals is the lack of assessment tools to conduct valid and accurate oral language evaluations. The purpose of this preliminary study was to provide pilot data for a new potential assessment tool in Catalan. We examined the possibility that two novel tasks, a grammatical correction (GramCorr) and morphological productivity (MP; nonword and word subtasks), could differentiate between Catalan-speaking children with and without developmental language disorder (DLD) with good diagnostic accuracy. Twenty-seven school-aged children with DLD (Mage = 9;1 years) and twenty-seven age/sex-matched typically developing (TD) children (Mage = 9;0 years) participated in the study. Group differences and diagnostic accuracy analyses (sensitivity and specificity and likelihood ratios) were conducted. Results showed that the overall accuracy of children with DLD was significantly poorer than that of the TD controls in the two tasks. The preliminary diagnostic accuracy results suggested that the overall test (GramCorr+MP) could be useful in identifying children with DLD (cut-off point 62.1%; sensitivity (.929)/specificity (.893); +LH (8.67)/-LH (0.80). Moreover, the overall MP task (nonword + word subtasks; cut-off point 60%; sensitivity (.897)/specificity (.931), +LH (13.00)/-LH (0.111)) appears to provide adequate information to help in detecting DLD. The nature of both tasks, their usefulness for practitioners and future steps in the design of valid tools for the identification of Catalan speaking children with DLD are discussed.

Diagnostic accuracy of contrast-enhanced computed tomography in assessing bone invasion in patients with oral squamous cell carcinoma.

OBJECTIVES: This study aimed to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) in detecting bone invasion in oral squamous cell carcinoma (OSCC) patients and to explore clinicopathological factors associated with its reliability. MATERIALS AND METHODS: 417 patients underwent preoperative contrast-enhanced CT followed by radical surgery. The presence or absence of bone invasion served as the outcome variable, with histopathologic examination of the resection specimen considered the gold standard. Statistical analyses, comprising correlation analyses and the determination of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were conducted. RESULTS: CT exhibited 76.85% sensitivity, 82.20% specificity, 47.14% PPV, and 89.67% NPV. False-positive and false-negative rates were 11.27% and 5.99%, respectively. Artifacts affected assessment in 44 patients, but not in those with bone invasion. Tumor size, depth of invasion (DOI), tumor localization at the upper jaw, lymphatic invasion, and perineural invasion correlated with incorrect identification of bone invasion (Chi-square, p < 0.05). CONCLUSIONS: Despite utilizing thin-section CT, notable false-positive and false-negative results persisted. Patients with T3 tumors, DOI ≥ 10 mm, or upper jaw tumors are at higher risk for misidentification of bone invasion. Combining multiple methods may enhance diagnostic accuracy, and the integration of artificial intelligence or tracking electrolyte disturbances by tumor depth profiling shows promise for further assessment of bone invasion before histopathology. CLINICAL RELEVANCE: Surgeons should consider these insights when planning tumor resection. Supplementary imaging may be warranted in cases with high risk factors for misidentification. Further methodological advancements are crucial for enhancing diagnostic precision.

Estimation of diagnostic sensitivity and specificity of abattoir registrations and bulk tank milk ELISA as herd-level tests for Fasciola hepatica using Bayesian latent class modelling.

The common liver fluke, Fasciola hepatica, is a trematode parasite found worldwide, typically with a focal distribution due to its requirement for suitable climatic and environmental conditions to complete its lifecycle. Bovine fasciolosis causes suboptimal production and economic losses, including liver condemnation at slaughter. The lack of reliable diagnostic methods is a disadvantage to the increasing demand for surveillance and control. The aim of this study was to evaluate the diagnostic accuracy of bulk tank milk (BTM) antibody testing and aggregated abattoir registrations (AAR) of liver fluke as herd-level tests for F. hepatica infection using Bayesian latent class models. Data from the abattoirs in 2019-2021 and BTM, sampled in the winter of 2020/2021, were collected from 437 herds on the southwest coast of Norway. The BTM samples were analysed with the SVANOVIR® F. hepatica-Ab ELISA test, with results given as an optical density ratio (ODR), and later dichotomized using the recommended cut-off value from the test manufacturer (ODR ≥0.3). Based on the BTM ELISA test, 47.8% of the herds tested positive. The AAR test was defined as the herd-level proportion of female slaughtered animals registered with liver fluke infection during the study period. For this test, three cut-offs were used (a proportion of 0.05, 0.1 and 0.2). The herds were split into two subpopulations ("Coastal" and "Inland"), which were expected to differ in true prevalence of F. hepatica infection based on climate-related and geographical factors. The diagnostic accuracies of both tests were estimated using Bayesian latent class models with minimally informative priors. Post-hoc analysis revealed that the maximum sum of sensitivity (Se) and specificity (Sp) of the tests was achieved with a herd-level proportion of ≥0.1 registered with liver fluke as the AAR test. Using this cut-off, the median estimate for the diagnostic accuracy of the BTM ELISA was 90.4% (84.0-96.2 95% Posterior Credible Interval (PCI)) for Se and 95.3% (90.6-100% PCI) for Sp, while the median estimate of Se for AAR was 87.5% (81.4-93.1% PCI) and the median estimate of Sp for AAR was 91.0% (85.2-96.5% PCI). The cut-off evaluation of the SVANOVIR® F. hepatica-Ab ELISA test for BTM confirmed the manufacturer's recommended cut-off of ODR ≥0.3 to denote positive and negative herds. This study suggests that AAR and BTM ELISA test can be used as herd-level tools to monitor liver fluke infection, so that appropriate interventions against infection can be implemented as necessary.

Diagnostic accuracy of cognitive screening tools validated for older adults in Iran: a systematic review and meta-analysis.

BACKGROUND: This systematic review aims to comprehensively assess the diagnostic accuracy of cognitive screening tools validated for older adults in Iran, providing evidence-based recommendations for clinicians and researchers. METHODS: A comprehensive search in March 2023 across Web of Science, PubMed, Scopus, ScienceDirect, SID, IranMedex, and IranDoc, enhanced by hand-searching references and Google Scholar, identified cross-sectional studies on cognitive screening in Iranian seniors. We assessed diagnostic accuracy, cognitive domains, and test strengths and weaknesses. A bivariate random-effects meta-analysis provided summary estimates and 95% confidence intervals, illustrated in forest plots. RESULTS: Our review, derived from an initial screening of 38 articles, focused on 17 studies involving 14 cognitive screening tools and participant counts from 60 to 350, mostly from specialized clinics. The MMSE was the only tool examined in at least three studies, prompting a meta-analysis revealing its sensitivity at 0.89 and specificity at 0.77 for dementia detection, albeit amidst significant heterogeneity (I^2 > 80%). ACE-III demonstrated the highest diagnostic accuracy for MCI and dementia, while MoCA's performance was deemed adequate for MCI and excellent for dementia. High bias risk in studies limits interpretation. CONCLUSION: This review identifies key cognitive tools for dementia and MCI in Iranian older adults, tailored to educational levels for use in primary and specialized care. It emphasizes the need for further validation to enhance diagnostic precision across diverse settings, within a concise framework prioritizing brevity and accuracy for clinical applicability.

Deep Learning-Enabled Quantification of 99mTc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis.

Transthyretin cardiac amyloidosis (ATTR CA) is increasingly recognized as a cause of heart failure in older patients, with 99mTc-pyrophosphate imaging frequently used to establish the diagnosis. Visual interpretation of SPECT images is the gold standard for interpretation but is inherently subjective. Manual quantitation of SPECT myocardial 99mTc-pyrophosphate activity is time-consuming and not performed clinically. We evaluated a deep learning approach for fully automated volumetric quantitation of 99mTc-pyrophosphate using segmentation of coregistered anatomic structures from CT attenuation maps. Methods: Patients who underwent SPECT/CT 99mTc-pyrophosphate imaging for suspected ATTR CA were included. Diagnosis of ATTR CA was determined using standard criteria. Cardiac chambers and myocardium were segmented from CT attenuation maps using a foundational deep learning model and then applied to attenuation-corrected SPECT images to quantify radiotracer activity. We evaluated the diagnostic accuracy of target-to-background ratio (TBR), cardiac pyrophosphate activity (CPA), and volume of involvement (VOI) using the area under the receiver operating characteristic curve (AUC). We then evaluated associations with the composite outcome of cardiovascular death or heart failure hospitalization. Results: In total, 299 patients were included (median age, 76 y), with ATTR CA diagnosed in 83 (27.8%) patients. CPA (AUC, 0.989; 95% CI, 0.974-1.00) and VOI (AUC, 0.988; 95% CI, 0.973-1.00) had the highest prediction performance for ATTR CA. The next highest AUC was for TBR (AUC, 0.979; 95% CI, 0.964-0.995). The AUC for CPA was significantly higher than that for heart-to-contralateral ratio (AUC, 0.975; 95% CI, 0.952-0.998; P = 0.046). Twenty-three patients with ATTR CA experienced cardiovascular death or heart failure hospitalization. All methods for establishing TBR, CPA, and VOI were associated with an increased risk of events after adjustment for age, with hazard ratios ranging from 1.41 to 1.84 per SD increase. Conclusion: Deep learning segmentation of coregistered CT attenuation maps is not affected by the pattern of radiotracer uptake and allows for fully automatic quantification of hot-spot SPECT imaging such as 99mTc-pyrophosphate. This approach can be used to accurately identify patients with ATTR CA and may play a role in risk prediction.

Performance evaluation of loop-mediated isothermal amplification, polymerase chain reaction and real-time polymerase chain reaction methods to detect Neisseria gonorrhoeae among symptomatic patients from India.

Background: Neisseria gonorrhoeae is one of the most important causative organisms in causing sexually transmitted infections. The clinical presentation of gonorrhoea mimics the symptoms of other sexually transmitted infections, and a proper diagnosis of the same is therefore crucial in patient management. The current study intended to compare different in-house molecular methods: that is, conventional PCR, real-time PCR, and LAMP assay for detection of N. gonorrhoeae. Methods: A total of 163 samples were collected from 145 patients who presented with urethral and vaginal discharge. Collected samples were processed for culture on GC agar base, and three different molecular diagnostic tests (conventional PCR, real-time PCR, and LAMP assay) were performed simultaneously on all the samples. Results: Culture of N. gonorrhoeae was positive in 17 out of 21 (80.9%) swab samples. With culture as the gold standard method, conventional and real-time PCR had a sensitivity of 94.1%, whereas the sensitivity of the LAMP assay was found to be 88.2%. All three methods had a specificity of 100%. In addition to swab samples, evaluation of urine samples by different molecular methods yielded a good concordance with a kappa value of 0.85 by conventional PCR and real-time PCR showing a perfect level of agreement, while the LAMP assay was found to have a substantial level of agreement. Conclusion: LAMP assay had a comparable diagnostic accuracy to other molecular methods for the detection of N. gonorrhoeae and can be used as a point-of-care test in resource-limited settings.

Agreement of Fractional Flow Reserve Estimated by Computed Tomography With Invasively Measured Fractional Flow Reserve: A Systematic Review and Meta-Analysis.

BACKGROUND: Fractional flow reserve (FFR) is the ratio of blood pressure measured distal to a stenosis and pressure proximal to a stenosis. FFR can be estimated noninvasively using computed tomography (CT) although the usefulness of this technique remains controversial. This meta-analysis evaluated the agreement of FFR estimated by CT (FFR-CT) with invasively measured FFR. The study also evaluated the diagnostic accuracy of FFR-CT, defined as the ability of FFR-CT to classify lesions as hemodynamically significant (invasive FFR ≤0.8) or insignificant (invasive FFR >0.8). METHODS AND RESULTS: Forty-three studies reporting on 7291 blood vessels from 5236 patients were included. A moderate positive linear relationship between FFR-CT and invasively measured FFR was observed (Spearman correlation coefficient: 0.67). Agreement between the 2 measures increased as invasively measured FFR values approached 1. The overall diagnostic accuracy, sensitivity and specificity of FFR-CT were 82.2%, 80.9%, and 83.1%, respectively. Diagnostic accuracy of 90% could be demonstrated for FFR-CT values >0.90 and <0.49. The diagnostic accuracy of off-site tools was 79.4% and the diagnostic accuracy of on-site tools was 84.1%. CONCLUSIONS: The agreement between FFR-CT and invasive FFR is moderate although agreement is highest in vessels with FFR-CT >0.9. Diagnostic accuracy varies widely with FFR-CT value but is above 90% for FFR-CT values >0.90 and <0.49. Furthermore, on-site and off-site tools have similar performance. Ultimately, FFR-CT may be a useful adjunct to CT coronary angiography as a gatekeeper for invasive coronary angiogram.

From diagnosis to intervention: a review of telemedicine's role in skin cancer care.

Skin cancer treatment is a core aspect of dermatology that relies on accurate diagnosis and timely interventions. Teledermatology has emerged as a valuable asset across various stages of skin cancer care including triage, diagnosis, management, and surgical consultation. With the integration of traditional dermoscopy and store-and-forward technology, teledermatology facilitates the swift sharing of high-resolution images of suspicious skin lesions with consulting dermatologists all-over. Both live video conference and store-and-forward formats have played a pivotal role in bridging the care access gap between geographically isolated patients and dermatology providers. Notably, teledermatology demonstrates diagnostic accuracy rates that are often comparable to those achieved through traditional face-to-face consultations, underscoring its robust clinical utility. Technological advancements like artificial intelligence and reflectance confocal microscopy continue to enhance image quality and hold potential for increasing the diagnostic accuracy of virtual dermatologic care. While teledermatology serves as a valuable clinical tool for all patient populations including pediatric patients, it is not intended to fully replace in-person procedures like Mohs surgery and other necessary interventions. Nevertheless, its role in facilitating the evaluation of skin malignancies is gaining recognition within the dermatologic community and fostering high approval rates from patients due to its practicality and ability to provide timely access to specialized care.

A systematic review and meta-analysis of diagnostic test accuracy of chest ultrasound in diagnosing pediatric pulmonary tuberculosis.

INTRODUCTION: Despite medical advancement, pediatric pulmonary tuberculosis (PTB) still has high morbidity and mortality, due to challenging detection in clinical practice. Ultrasound has been touted as the next best diagnostic tool but currently, this claim is unfounded. Therefore, this study aims to systematically review the diagnostic parameters of chest ultrasound in diagnosing pediatric PTB. METHODS: The literature search started and ended on December 23, 2023. We searched MEDLINE, Cochrane Library, Pubmed, Science Direct, and Google Scholar. Our research question could be formulated as "In pediatric patients who present with signs and symptoms of PTB such as fever, cough, and poor weight gain, how accurate is chest ultrasound in ruling in and ruling out pediatric PTB when the diagnosis is compared to culture, PCR or CXR?" This systematic review adhered to the PRISMA-DTA guidelines while the meta-analysis was conducted with STATA program using the "midas" and "metandi" commands. RESULTS: There are five studies included with 137 positive PTB children. The combined sensitivity is 84% (95% confidence interval [CI]: 76-89), specificity of 38% (95% CI: 24-54), and summary receiver operating curve yields an area under the curve of 0.83 (95% CI: 0.80-0.86). The I2 value is 24% (95% CI: 0-100) with a p-value of 0.13. The combined negative predictive value is 0.68 (95% CI: 0.58-0.79), and the positive predictive value is 0.57 (95% CI: 0.51-0.63). The positive likelihood ratio is 1 with a 6% increase from the baseline while the negative likelihood ratio is 0.43 with a 12% decrease from the baseline. CONCLUSION: Chest ultrasound is sensitive but currently could neither exclude nor confirm pediatric PTB.

Diagnostic Accuracy of a Computed Tomography-Guided Transthoracic Needle Biopsy for Ground-Glass Opacities and Subsolid Pulmonary Nodules.

Purpose The increasing use of computed tomography (CT) imaging has led to the detection of more ground-glass nodules (GGNs) and subsolid nodules (SSNs), which may be malignant and require a biopsy for proper diagnosis. Approximately 75% of persistent GGNs can be attributed to adenocarcinoma in situ or minimally invasive adenocarcinoma. A CT-guided biopsy has been proven to be a reliable procedure with high diagnostic performance. However, the diagnostic accuracy and safety of a CT-guided biopsy for GGNs and SSNs with solid components ≤6 mm are still uncertain. The aim of this study is to assess the diagnostic accuracy of a CT-guided core needle biopsy (CNB) for GGN and SSNs with solid components ≤6 mm. Methods This is a retrospective study of patients who underwent CT-guided CNB for the evaluation of GGNs and SSNs with solid components ≤6 mm between February 2020 and January 2023. Biopsy findings were compared to the final diagnosis determined by definite histopathologic examination and clinical course. Results A total of 22 patients were enrolled, with a median age of 74 years (IQR: 68-81). A total of 22 nodules were assessed, comprising 15 (68.2%) SSNs with a solid component measuring ≤6 mm and seven (31.8%) pure GGNs. The histopathological examination revealed that 12 (54.5%) were diagnosed as malignant, nine (40.9%) as benign, and one (4.5%) as non-diagnostic. The overall diagnostic accuracy and sensitivity for malignancy were 86.36% and 85.7%, respectively. Conclusion A CT-guided CNB for GGNs and SSNs with solid components measuring ≤6 mm appears to have a high diagnostic accuracy.

Utilization of Point-of-Care Ultrasound as an Imaging Modality in the Emergency Department: A Systematic Review and Meta-Analysis.

Point-of-care ultrasound (POCUS) is an imaging modality that has become a fundamental part of clinical care provided in the emergency department (ED). The applications of this tool in the ED have ranged from resuscitation, diagnosis, and therapeutic to procedure guidance. This review aims to summarize the evidence on the use of POCUS for diagnosis and procedure guidance. To achieve this, CrossRef, PubMed, Cochrane Library, Web of Science, and Google Scholar databases were extensively searched for studies published between January 2000 and November 2023. Additionally, the risk of bias assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies 2 (for studies on the diagnostic role of POCUS) and Cochrane Risk of Bias tool (for studies on the use of POCUS for procedure guidance). Furthermore, diagnostic accuracy outcomes were pooled using STATA 16 software (StatCorp., College Station, TX, USA), while outcomes related to procedure guidance were pooled using the Review Manager software. The study included 81 articles (74 evaluating the diagnostic application of POCUS and seven evaluating the use of POCUS in guiding clinical procedures). In our findings sensitivities and specificities for various conditions were as follows: appendicitis, 65% and 89%; hydronephrosis, 82% and 74%; small bowel obstruction, 93% and 82%; cholecystitis, 75% and 96%; retinal detachment, 94% and 91%; abscess, 95% and 85%; foreign bodies, 67% and 97%; clavicle fractures, 93% and 94%; distal forearm fractures, 97% and 94%; metacarpal fractures, 94% and 92%; skull fractures, 91% and 97%; and pleural effusion, 91% and 97%. A subgroup analysis of data from 11 studies also showed that the two-point POCUS has a sensitivity and specificity of 89% and 96%, while the three-point POCUS is 87% sensitive and 92% specific in the diagnosis of deep vein thrombosis. In addition, the analyses showed that ultrasound guidance significantly increases the overall success rate of peripheral venous access (p = 0.02) and significantly reduces the number of skin punctures (p = 0.01) compared to conventional methods. In conclusion, POCUS can be used in the ED to diagnose a wide range of clinical conditions accurately. Furthermore, it can be used to guide peripheral venous access and central venous catheter insertion.

Poor evidence for poor R wave progression in coronary disease: A scoping review.

BACKGROUND: Poor R wave progression (PRWP) and reversed R wave progression (RRWP) have long been noted in electrocardiograms as potential indicators of anterior wall fibrosis or chronic coronary artery disease; however, the quantity and quality of evidence supporting these associations warrants closer examination. OBJECTIVE: The aim of this scoping review is to assess the breadth of evidence regarding the diagnostic significance of PRWP and RRWP, explore the extent of research, study populations and methodologies, and the presence of gaps in knowledge regarding these electrocardiographic phenomena and their association with coronary diseases. DESIGN: We conducted a comprehensive search across PubMed, Web of Science, and Scopus, covering literature on PRWP or RRWP in the context of myocardial infarction, ischemia, or fibrosis from any time period and in any language. RESULTS: A total of 20 studies were included in this review, highlighting the severe paucity of data. No high-quality accuracy studies have been identified, and existing research suffers from methodological issues, in particular selection bias. Prevalence and prognostic studies showed significant heterogeneity in terms of definitions and outcomes, which contributes to an alarming risk of bias. CONCLUSIONS: The lack of solid evidence for PRWP and RRWP as diagnostic markers for acute and chronic coronary artery disease necessitates caution in clinical interpretation. Future research should focus on well-designed case-control studies to clarify the diagnostic accuracy of these markers. Until robust evidence is available, the reliance on PRWP/RRWP for diagnosing anterior infarction should be discouraged, reflecting a gap between clinical practice and evidence-based medicine.

Role of ultrasonography (USG) and color Doppler in the evaluation of thyroid nodules and its association with USG-guided FNAC - A cross-sectional study.

Introduction: Thyroid diseases affect approximately 42 million people in India. The majority (15%-40%) of these cases remain asymptomatic and benign and warrant special investigations such as ultrasonography (USG) and fine-needle aspiration cytology (FNAC) for diagnosis. Early diagnosis and management of thyroid disorders determine the disease course in many patients. Objective: To determine the role of USG and color Doppler in the evaluation of thyroid nodules and its association with USG-guided FNAC. Methods: We did a cross-sectional analytical study over 2 years, where we recruited 108 patients with thyroid swelling attending the OPD. We used a semi-structured data collection proforma that captured information on sociodemographic details, clinical symptoms, physical examination, and all ne cessary laboratory investigations. All patients underwent USG, color Doppler, and FNAC as a part of the investigation of thyroid nodules. The diagnostic value of ultrasound and Doppler parameters was assessed in terms of sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for detection of malignancy in comparison to FNAC. Results: Approximately 155 nodules were identified from the selected 108 cases, and the prevalence of malignancy among the selected thyroid nodule patients was found to be 9.1%. We observed that malignant tumors were likely to be solitary with lobulated margins, >2 cm in size with <50% peripheral halo, with markedly hypoechoic, predominantly solid, with nodal involvement and extrathyroidal extension, microcalcifications, and central vascularity. We also observed that tumors that had USG characteristics of being taller than wide (91%), poorly defined margins (92%), marked hypoechoic (95%), and microcalcifications (96%) had the highest diagnostic accuracy in detecting malignancy when compared to FNAC. Conclusion: Thus, through our study findings, we conclude that USG and color Doppler can serve as vital tools for the evaluation of thyroid nodules with high sensitivity and specificity.

Diagnostic accuracy of transvaginal ultrasonography and hysterosalpingography in the detection of uterine cavity pathologies among infertile women.

Background: Uterine cavity pathology may affect the endometrium or myometrium, resulting in distortion of the uterine cavity, and is responsible for 2%-5% of infertility. The methods for its assessment usually involve imaging modalities like pelvic ultrasonography, often transvaginal-(TVS), and hysterosalpingography-(HSG), with hysteroscopy-(HSC) as the gold standard. However, HSC is not readily available in resource-poor-settings. Purpose: To determine and compare the diagnostic accuracy of TVS and HSG in detecting uterine cavity pathology using HSC as a gold standard. Materials and Methods: A cross-sectional analytical study of consenting infertile women for evaluation of the uterine cavity using transvaginal-ultrasonography, hysterosalpingogram, and hysteroscopy. The primary-outcome-measures were the sensitivity, specificity, and accuracy of TVS and HSG in detecting uterine cavity abnormalities using HSG as the gold standard. Results: Eighty-eight participants were analysed for this study. The lesions confirmed on HSC were intrauterine-adhesions (43.1%), endometrial polyps (14.8%), submucous fibroids (18.2%), intrauterine-septum (13.6%), and cavity distortion (14.8%). The overall sensitivity with TVS was 57.7%, with a specificity of 97.6%, a positive-predictive-value (PPV) of 88.2%, and a negative-predictive-value (NPV) of 88.2%, giving a percentage-accuracy of 88.2%. In comparison, HSG had a sensitivity of 72.1%, a specificity of 99.4%, a PPV of 97.4%, and an NPV of 92.0%, giving an overall accuracy of 92.9%. The detection rates of TVS and HSG in this category were: fibroids (97.7% vs 89.8%; p = .0004) and adhesions (73.9% vs 87.5%; p = .0002), respectively. Conclusion: HSG appears to be the superior modality for detection of obliterative uterine cavity pathologies, while TVS is better suited for myometrium and endometrial lesions.

BC-QNet: A quantum-infused ELM model for breast cancer diagnosis.

The timely and accurate diagnosis of breast cancer is pivotal for effective treatment, but current automated mammography classification methods have their constraints. In this study, we introduce an innovative hybrid model that marries the power of the Extreme Learning Machine (ELM) with FuNet transfer learning, harnessing the potential of the MIAS dataset. This novel approach leverages an Enhanced Quantum-Genetic Binary Grey Wolf Optimizer (Q-GBGWO) within the ELM framework, elevating its performance. Our contributions are twofold: firstly, we employ a feature fusion strategy to optimize feature extraction, significantly enhancing breast cancer classification accuracy. The proposed methodological motivation stems from optimizing feature extraction for improved breast cancer classification accuracy. The Q-GBGWO optimizes ELM parameters, demonstrating its efficacy within the ELM classifier. This innovation marks a considerable advancement beyond traditional methods. Through comparative evaluations against various optimization techniques, the exceptional performance of our Q-GBGWO-ELM model becomes evident. The classification accuracy of the model is exceptionally high, with rates of 96.54 % for Normal, 97.24 % for Benign, and 98.01 % for Malignant classes. Additionally, the model demonstrates a high sensitivity with rates of 96.02 % for Normal, 96.54 % for Benign, and 97.75 % for Malignant classes, and it exhibits impressive specificity with rates of 96.69 % for Normal, 97.38 % for Benign, and 98.16 % for Malignant classes. These metrics are reflected in its ability to classify three different types of breast cancer accurately. Our approach highlights the innovative integration of image data, deep feature extraction, and optimized ELM classification, marking a transformative step in advancing early breast cancer detection and enhancing patient outcomes.

Pediatric blood cultures-turning up the volume: a before and after intervention study.

The major determinant of blood culture (BC) diagnostic performance is blood volume, and pediatric sample volumes are frequently low. We aimed to assess BC volumes in our institution, design an intervention to increase volumes, and assess its impact. All pediatric BCs submitted over a 7-month period to the microbiology laboratory in a university hospital (including emergency department, pediatric ward, and neonatal unit) were included. A pre-intervention period assessed current practice. A multi-faceted intervention (education, guideline introduction, active feedback strategies) was collaboratively designed by all stakeholders. Impact was assessed in a post-intervention period. The main outcome measures included the percentage of samples adequately filled using three measures of sample adequacy (1) manufacturer-recommended minimum validated volume-> 0.5 ml, (2) manufacturer-recommended optimal minimum volume-> 1.0 ml, (3) newly introduced age-specific recommendations. Three hundred ninety-eight pre-intervention and 388 post-intervention samples were included. Initial volumes were low but increased significantly post-intervention (median 0.77 ml vs. 1.52 ml), with multivariable regression analysis estimating volumes increased 89% post-intervention. There were significant increases in all measures of volume adequacy, including an increase in age-appropriate filling (20.4-53.1%), with less improvement in those aged > 3 years. Overall, 68.4% of pathogens were from adequately filled cultures, while 76% of contaminants were from inadequately filled cultures. A pathogen was detected in a higher proportion of adequately filled than inadequately filled cultures (9.4% vs. 2.2%, p < 0.001).  Conclusion: Blood volume impacts BC sensitivity, with lower volumes yielding fewer pathogens and more contaminants. Focused intervention can significantly improve volumes to improve diagnostic performance. What is Known: • Blood volume is the major determinant of blood culture positivity, and yet pediatric blood culture volumes are frequently low, resulting in missed pathogens and increased contamination. What is New: • Adequately filled (for age) blood cultures have a pathogen detection rate three times higher than inadequately filled blood cultures. • This interventional study shows that collaboratively designed multi-modal interventions including focus on accurate volume measurement can lead to significant increases in blood volumes and improve blood culture diagnostic performance.

Assessing ChatGPT 4.0's test performance and clinical diagnostic accuracy on USMLE STEP 2 CK and clinical case reports.

While there is data assessing the test performance of artificial intelligence (AI) chatbots, including the Generative Pre-trained Transformer 4.0 (GPT 4) chatbot (ChatGPT 4.0), there is scarce data on its diagnostic accuracy of clinical cases. We assessed the large language model (LLM), ChatGPT 4.0, on its ability to answer questions from the United States Medical Licensing Exam (USMLE) Step 2, as well as its ability to generate a differential diagnosis based on corresponding clinical vignettes from published case reports. A total of 109 Step 2 Clinical Knowledge (CK) practice questions were inputted into both ChatGPT 3.5 and ChatGPT 4.0, asking ChatGPT to pick the correct answer. Compared to its previous version, ChatGPT 3.5, we found improved accuracy of ChatGPT 4.0 when answering these questions, from 47.7 to 87.2% (p = 0.035) respectively. Utilizing the topics tested on Step 2 CK questions, we additionally found 63 corresponding published case report vignettes and asked ChatGPT 4.0 to come up with its top three differential diagnosis. ChatGPT 4.0 accurately created a shortlist of differential diagnoses in 74.6% of the 63 case reports (74.6%). We analyzed ChatGPT 4.0's confidence in its diagnosis by asking it to rank its top three differentials from most to least likely. Out of the 47 correct diagnoses, 33 were the first (70.2%) on the differential diagnosis list, 11 were second (23.4%), and three were third (6.4%). Our study shows the continued iterative improvement in ChatGPT's ability to answer standardized USMLE questions accurately and provides insights into ChatGPT's clinical diagnostic accuracy.

Diagnostic Accuracy of Abdominal Point of Care Ultrasound in Primary Care: Study Design and Protocol.

The aim of this study is to estimate the diagnostic accuracy of abdominal point of care ultrasound (POCUS) performed by family physicians (FPs) in primary care (PC), in comparison with the findings in the medical record (MR) at 12 months of follow-up. This study is conducted entirely in PC healthcare centers in Spain. Abdominal ultrasound scans performed by FPs (selected on the basis of their ultrasound knowledge and experience) are compared with the findings, or not, in the patient's MR after a 12-month follow-up period. The study will involve 100 FPs in Spain and an estimated sample size of 1334 patients who are to undergo abdominal POCUS at the indication of their physician. The results of the abdominal POCUS will be collected and compared with the findings of the MR. This comparison will be performed by another physician of the research team, different from their FP after one year of follow-up. The diagnostic accuracy of abdominal POCUS has been addressed in the hospital setting but not in PC. This lack of evidence can begin to be resolved with studies such as the one we present, designed for unselected populations such as those treated in PC and taking the patient's MR as the gold standard, which will allow us to make comparisons with the patient's clinical course.