Medical Diagnostic Tests Research Articles

Different view of the diagnostics test accuracy measures and optimal cut-off point selection procedure under tree or umbrella ordering

ABSTRACT In the realm of medical diagnostic testing, diagnostic tests can assume either binary forms, distinguishing between diseased and non-diseased states, or ordinal forms, categorizing states from non-diseased to various stages (1 to K). Another significant classification scheme for multi-class scenarios is tree or umbrella ordering, which entails several unordered sub-classes (subtypes) within a biomarker. Within tree or umbrella ordering, the classifier assesses whether the marker measurement for one class surpasses or falls below those for the other classes. Although Receiver Operating Characteristic (ROC) curves and summary measures have been adapted to accommodate tree and umbrella ordering, these approaches often yield cut-off points that generate highly sensitive tests for certain disease subtypes while compromising specificity for others. This may not be ideal for all diseases. Hence, in this investigation, we explore diverse measures of diagnostic test accuracy and optimal cut-off point selection procedures under tree or umbrella ordering to foster more specific tests. We present numerical examples and simulation studies and demonstrate the approach using real data on lung cancer.

Unnecessary diagnostic imaging requested by medical students during a first day of residency simulation: an explorative study

BackgroundPhysicians’ choice of appropriate tests in the diagnostic process is crucial for patient safety. The increased use of medical imaging has raised concerns about its potential overuse. How appropriately medical students order diagnostic tests is unknown. We explored their ordering behavior of diagnostic imaging during a simulated first day of residency.MethodsIn total, 492 undergraduate medical students participated in the simulation. After history taking with simulated patients, the students used an electronic system for requesting diagnostic tests. The analysis focused on 16 patient cases, each managed by at least 50 students. We calculated the total number of ordered images and unnecessary radiation exposure in millisievert per patient and performed one sample t-tests (one tailed) with an expected mean of zero on a Bonferroni-corrected alpha level of 0.003 for the independent variable of unnecessary radiation exposure.ResultsUnnecessary diagnostic imaging was ordered across all patient cases. Ultrasound, especially abdominal ultrasound, X-rays of the thorax, and abdominal CTs were notably overused in 90.9%, 80.0%, and 69.2% of all patient cases, respectively. Unnecessary requests of imaging related to radiation resulted in radiation over-exposure for nearly all patients, with 37.5% of all patients being exposed to a significant radiation overdose on average.ConclusionMedical students’ overuse of diagnostic imaging can be explained by patient-related factors like anxiety and medical factors like missing clinical information leading to cognitive biases in patient workup. This suggests the need for interventions to improve students’ clinical decision-making and reduce cognitive biases. Investigating student-specific factors being associated with overuse of diagnostic imaging would be of additional interest.

Comparing Point-of-Care Technology to ELISA Testing for Infliximab and Adalimumab Levels in Adult Inflammatory Bowel Disease Patients: A Prospective Pilot Study.

Introduction: Therapeutic drug monitoring (TDM) has proven to be a valuable strategy for optimizing biologic therapies, among which are anti-tumor necrosis factor (anti-TNF) treatments in inflammatory bowel disease (IBD). In particular, reactive TDM has been shown to manage treatment failures more cost-effectively than empirical dose adjustments for anti-TNF drugs. However, several challenges currently impede the widespread adoption of TDM in clinical practice, particularly addressing the delay between sample collection and result availability. To overcome this limitation, the use of point-of-care technology tests (POCTs) is a potential solution. Point-of-care technology tests are medical diagnostic tests performed at the site of patient care to provide immediate results, allowing for quicker decision-making and treatment. The current standard of care (SOC) for drug level measurement relies on the enzyme-linked immunosorbent assay (ELISA), a method that is time-consuming and requires specialized personnel. This study aims to evaluate a novel, user-friendly, and efficient POCT method (ProciseDx Inc.) and compare its performance with the SOC ELISA in assessing infliximab and adalimumab levels in blood samples from IBD patients. Methods: In this prospective, single-center study, we collected blood samples from IBD patients, both CD and UC, receiving infliximab (87 IBD patients; 50% UC and 50% CD) or adalimumab (60 patients; 14% UC and 48% CD) and we analyzed the blood's drugs levels using both the ProciseDx Analyzer POC and the SOC ELISA. We examined the correlation between the two methods using statistical analyses, including the Deming regression test. Additionally, we assessed the ease of use, turnaround time, and overall practicality of the POCT in a clinical setting. Results: The ProciseDx test demonstrated a strong correlation with the SOC ELISA for measuring both infliximab and adalimumab levels. In particular, the overall correlation between the ProciseDx POCT and the ELISA assessments showed an r coefficient of 0.83 with an R squared value of 0.691 (95% CI 0.717-0.902) for IFX measurements, and an r coefficient of 0.85 with an R squared value of 0.739 (95% CI 0.720-0.930). Conclusions: the ProciseDx POC test offers significantly faster turnaround times and is more straightforward to use, making it a viable alternative for routine clinical monitoring. Despite its promising potential, further refinement and validation of the ProciseDx test are necessary to ensure its effectiveness across diverse patient populations and clinical settings. Future research should focus on optimizing the POC tests' performance and evaluating its long-term impact on IBD management.

A mini-update on chronic rhinosinusitis

Chronic rhinosinusitis (CRS) is an inflammatory disorder of the paranasal sinuses and the nasal cavity lasting longer than 12 weeks. This disease is a common clinical syndrome with significant monetary burden due to the high costs of medical visits, diagnostic tests, medications, and surgical therapies. CRS without nasal polyposis (CRSsNP) is the most common subtype of CRS, accounting for about 70% of all patients. Other subtypes include CRS with nasal polyposis (CRSwNP) and allergic fungal rhinosinusitis (AFRS). CRSwNP has the worldwide prevalence of 2% to 4% and is often accompanied by type 2 inflammation and asthma as a comorbid condition. Pediatric chronic sinusitis is distinct from adult chronic sinusitis and is currently considered an infectious process, characterized by persistent inflammation representing an exaggerated immune response to an external stimulus. The medical and surgical management of CRS has been remarkably modified in the past two decades. The aim of this study was to present an update on CRS based on the recent years’ literature.

IS MY BALANCE DISORDER PATIENT IMPROVING WITH THIS REHABILITATION TREATMENT? RAPID STABILOMETRIC PLATFORM TEST

The aim of the present study is to compare the use and results of a rapid stabilometric platform test with traditional clinical scales to assess the individual clinical evolution of heterogeneous patients with balance disorders during rehabilitation treatment. The 67 participating vertigo patients underwent two assessment sessions, one before starting rehabilitation treatment and one after starting treatment. In each session, six static balance assessment tests with the stabilometric platform were accomplished. Then, the centre of pressure (COP) measured by the device, was processed using the MCQ-Balance method, that transforms the signal into clinical interpretable results. Additionally, in order to compare the results, three medical diagnostic tests were conducted and a methodical flag system to classify their results was proposed. The agreement rises until 85.71% with a contingency coefficient of 0.751 and a Kappa of 0.775. The platform showed a sensitivity of 100% with a specificity of 72.99%. Furthermore, it was not found false negatives in the platform. The stabilometric platform provided valuable assistance in the diagnosis of the evolution of balance pathology, involving less time and uncertainty than traditional tests.

Evaluation of Hi-C Sequencing for Detection of Gene Fusions in Hematologic and Solid Tumor Pediatric Cancer Samples.

Hi-C sequencing is a DNA-based next-generation sequencing method that preserves the 3D genome conformation and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate Hi-C as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens. Archived viable and non-viable frozen leukemic cells and formalin-fixed paraffin-embedded (FFPE) tumor specimens were analyzed. Pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to Hi-C to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases without known genomic rearrangements based on prior clinical diagnostic testing was evaluated to determine whether Hi-C could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, we observed 100% concordance between Hi-C and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study provides an institutional proof of principle evaluation of Hi-C sequencing to medical diagnostic testing as it identified several clinically relevant rearrangements, including those that were missed by current clinical testing workflows.

Impact of laboratory involvement in the characterization of B12 hypervitaminosis in clinical practice.

Unexplained B12 hypervitaminosis (HB12) in asymptomatic patients leads to a cascade of medical consultations and diagnostic tests aimed at determining its etiology. The objective of this study was to assess the efficacy of the laboratory getting involved in the detection and elimination of immune complexes with vitamin B12 in clinical practice and its economic impact. A retrospective longitudinal study was undertaken to assess the laboratory strategy of detecting B12macrovitamin (macro-B12) in patients with HB12 >1,000 pg/mL. The clinical characteristics of patients with HB12 referred to Internal Medicine (IM) in the pre- and post-implantation period of the new strategy were compared. Additionally, the healthcare costs of one-year follow-up were estimated. The prevalences of HB12 in the pre- and post-implantation period were 3.9 % and 3 %, respectively. Macro-B12 explained 25 % of the HB12 cases initially detected. A 41 % reduction was observed in the number of patients with HB12 after the implantation of the new strategy, thereby resulting in a cost reduction of 5,000 €. The laboratory intervention for the detection of macro-B12 provides clear economic and clinical benefits in clinical practice.

Epilepsy in inmate patients seen in a high complexity reference hospital in Colombia: A cross-sectional study.

To describe the sociodemographic and clinical characteristics of imprisoned patients with epilepsy seen at Samaritana University Hospital (HUS) in Bogotá D.C., between January 2017 and November 2020. Cross-sectional cohort study of inmate patients over 18 years of age seen at HUS between January 2017 and November 2020, with a discharge diagnosis of epilepsy. A descriptive univariate analysis of patient sociodemographic and clinical characteristics was carried out. Overall, 92 patients were included, 95.7% were males with a median age of 32 years (IQR: 26-44); 65% were assessed in the outpatient clinic; median hospital length of stay was 2 days (IQR: 0) and 7.6% required admission to the intensive care unit; 75% had focal onset epilepsy, 63.04% with undetermined etiology 31.52% with structural causes. Polytherapy was found in 53.3%, valproic acid being the most frequently used antiseizure medication in 59.78%; lack of adherence was reported in 15.22% and inadequate seizure control in 81.52%; status epilepticus occurred in 5.34%. A total of 31 EEG recordings and 53 brain images were performed, of which, 29% and 39.62%, respectively, were abnormal. Non-epileptic paroxysmal events were diagnosed in 5.34%, while organic or psychiatric comorbidities were found in 25%, and the use of psychoactive substances was documented in 17.39%. Upon discharge, 93.47% had no disability, and only 45.65% returned for outpatient follow-up. The clinical profile was of men in the fourth decade of life with focal onset epilepsy characterized by high seizure frequency, most of whom were receiving antiseizure medication, with a high proportion of polytherapy. The results are a point of departure for prospective studies designed to identify points to intervene and improve healthcare for inmates with epilepsy. Inmates are a vulnerable proportion of persons with epilepsy. In this group there are significant differences compared to the general population, especially with greater psychiatric comorbidity and worse control of epileptic seizures due to difficulties in accessing medical care, antiseizure medication and diagnostic tests. We found that the most characteristic population is made up of men in the fourth decade of life with a high frequency of seizures, most of whom were receiving multiple antiseizure medication This study is the first of its kind in Latin America and it is an initial approach to epilepsy in inmates.

Asparagus officinalis Herb-Derived Carbon Quantum Dots: Luminescent Probe for Medical Diagnostics.

The utilization of natural materials for the synthesis of highly fluorescent carbon quantum dots (CQDs) presents a sustainable approach to overcome the challenges associated with traditional chemical precursors. Here, we report the synthesis of novel S,N-self-doped CQDs (S,N@CQDs) derived from asparagus officinalis herb. These S,N@CQDs exhibit 16.7 % fluorescence quantum yield, demonstrating their potential in medical diagnostics. We demonstrate the efficacy of S,N@CQDs as luminescent probes for the detection of anti-pathogenic medications metronidazole (MTZ) and nitazoxanide (NTZ) over concentration ranges of 0.0-180.0 μM (with a limit of detection (LOD) of 0.064 μM) and 0.25-40.0 μM (LOD of 0.05 μM), respectively. The probes were successfully applied to determine MTZ and NTZ in medicinal samples, real samples, and spiked human plasma, with excellent recovery rates ranging from 99.82 % to 103.03 %. Additionally, S,N@CQDs demonstrate exceptional efficacy as diagnostic luminescent probes for hemoglobin (Hb) detection over a concentration range of 0-900 nM, with a minimal detectability of 9.24 nM, comparable to commercially available medical laboratory diagnostic tests. The eco-friendly synthesis and precise detection limits of S,N@CQDs meet necessary analytical requirements and hold promise for advancing diagnostic capabilities in clinical settings. This research signifies a significant step towards sustainable and efficient fluorescence-based medical diagnostics.

Iodide based electrochemical gold quantification method for lateral flow assays

The lateral flow assay (LFA) is an ideal technology for at-home medical diagnostic tests due to its ease of use, cost-effectiveness, and rapid results. Despite these advantages, only few LFAs, such as the pregnancy and COVID-19 tests, have been translated from the laboratory to the homes of patients. To date, the medical applicability of LFAs is limited by the fact that they only provide yes/no answers unless combined with optical readers that are too expensive for at-home applications. Furthermore, LFAs are unable to compete with the state-of-the-art technologies in centralized laboratories in terms of detection limits. To address those shortcomings, we have developed an electrochemical readout procedure to enable quantitative and sensitive LFAs. This technique is based on a voltage-triggered in-situ dissolution of gold nanoparticles, the conventional label used to visualize target-specific signals on the test line in LFAs. Following the dissolution, the amount of gold is measured by electroplating onto an electrode and subsequent electrochemical quantification of the deposited gold. The measured current has a low noise, which achieves superior detection limits compared to optical techniques where background light scattering is limiting the readout performance. In addition, the hardware for the readout was developed to demonstrate translatability towards low-cost electronics.

Chemiresistive Sensor for Enhanced CO2 Gas Monitoring.

Carbon dioxide (CO2) gas sensing and monitoring have gained prominence for applications such as smart food packaging, environmental monitoring of greenhouse gases, and medical diagnostic tests. Although CO2 sensors based on metal oxide semiconductors are readily available, they often suffer from limitations such as high operating temperatures (>250 °C), limited response at elevated humidity levels (>60% RH), bulkiness, and limited selectivity. In this study, we designed a chemiresistive sensor for CO2 detection to overcome these problems. The sensing material of this sensor consists of a CO2 switchable polymer based on N-3-(dimethylamino)propyl methacrylamide (DMAPMAm) and methoxyethyl methacrylate (MEMA) [P(D-co-M)], and diethylamine. The designed sensor has a detection range for CO2 between 103 and 106 ppm even at high humidity levels (>80% RH), and it is capable of differentiating ammonia at low concentrations (0.1-5 ppm) from CO2. The addition of diethylamine improved sensor performance such as selectivity, response/recovery time, and long-term stability. These data demonstrate the potential of using this sensor for the detection of food spoilage.

Peptic Ulcer: A review

Peptic ulcers, characterized by painful sores that develop on the lining of the stomach, small intestine, or esophagus, are a prevalent gastrointestinal condition affecting millions worldwide. This abstract provides an overview of the causes, symptoms, and treatment options for peptic ulcers. Peptic ulcers primarily stem from the imbalance between aggressive factors such as gastric acid secretion, pepsin, and Helicobacter pylori infection, and defensive mechanisms like mucosal barrier integrity and blood flow. Lifestyle factors such as excessive alcohol consumption, smoking, and stress, along with the use of nonsteroidal anti-inflammatory drugs (NSAIDs), also contribute to ulcer formation. Symptoms of peptic ulcers include burning pain in the abdomen, bloating, nausea, vomiting, and unintended weight loss. However, some individuals may remain asymptomatic or experience atypical symptoms. Diagnosis typically involves a combination of medical history assessment, physical examination, and diagnostic tests such as endoscopy, barium X-ray, and H. pylori testing. Treatment aims to alleviate symptoms, promote ulcer healing, and prevent recurrence. Proton pump inhibitors (PPIs), histamine receptor antagonists (H2RAs), and antibiotics are commonly prescribed to reduce gastric acid secretion, eradicate H. pylori infection, and promote ulcer healing. Lifestyle modifications including dietary changes, stress reduction techniques, and cessation of smoking and alcohol consumption are also integral components of ulcer management. In conclusion, peptic ulcers are a common gastrointestinal disorder with multifactorial etiology. Early recognition of symptoms, accurate diagnosis, and prompt initiation of appropriate treatment are essential to prevent complications and improve patient outcomes.

Review of Radiation Dose Metric Tracking for Patients: Ethical Implications of the “Do Not Disclose” Standard

Medical diagnostic imaging tests that produce ionizing radiation now deploy technology that captures an individual patient’s cumulative radiation dose. This raises the question of whether there is an imperative for regional health authorities to disclose this information to physicians who may then engage their patients in decisions about whether the potential harms are worth the benefits of subsequent diagnostic imaging. Currently, the advice of the professional bodies providing standards of practice for medical diagnostic imaging is to withhold this information from physicians. Their concern is that cumulative dose information is difficult to evaluate in terms of risk to individual patients; it is not easily applicable to clinical decision making about the appropriateness of a subsequent imaging exam; and referring clinicians will feel compelled to offer a patient a less efficacious non-ionizing test, which could negatively affect patient care. We present a critical analysis of several assumptions underlying the stance of non-disclosure. Working at the intersection of medical physics, medical anthropology, and clinical ethics, we offer an alternative framing of the discourse of risk that has shaped the recent scholarly debate on disclosure of individual cumulative radiation dose. We posit that a persuasive argument can be made against the stance of the professional bodies and for a policy of disclosure – provided that such a policy prioritizes patient-centred shared decision making, radiologists as risk-interpretation experts, and the authority of the prescribing physician.

Adversarial Detection from Derived Models

Deep Neural Networks (DNNs) can be easily fooled by inputs that are crafted by adversaries. For example, an adversarial image can be forged by adding to an image a tiny perturbation which is often unnoticeable by human eyes, though the semantic interpretations of the original image and the adversarial image, which are represented as outputs of a DNN, may be drastically different. This weakness can potentially lead to serious consequences in security-critical applications such as medical diagnostic tests and self-driving vehicles. Most existing approaches for adversarial detection only have satisfactory performance for specific types of attacks. These methods do not generalize their performances when applied to a broad range of attacks, models or datasets. In this work, we propose a new adversarial detection method called Adversarial Detection from Derived Models (ADDM), which applies derived models to “simulate” the functionality of a DNN, and analyzes the distribution for the neuron activation values in the derived models as indicators for adversarial inputs. In order to further enhance performance, we propose a heuristic that selects neurons from the derived models that are sensitive to perturbations. We compare our approach with six existing adversarial detection approaches of different methodologies, and the experimental result confirms that the proposed approach has generally better performance regarding stability over different types of adversarial attacks on a variety of tested DNN models and datasets.

Chinese expert consensus on multidisciplinary discussion of interstitial lung disease

Interstitial lung disease (ILD) is a group of heterogeneous diseases characterized by interstitial lung inflammation and fibrosis. Its causes are diverse, symptoms can be non-specific, and the associated imaging and pathologic patterns can vary widely. The diagnosis and management of these conditions often require input from multiple medical disciplines. Over the past few decades, the importance of multidisciplinary discussion (MDD) in the management of ILD has grown internationally, and MDD has gradually become a part of the gold standard for ILD diagnosis and an essential reference for disease management. Recognizing this, the Chinese Medical Association-Chinese Thoracic Society and the Chinese Association of Chest Physicians have collaborated with experts to standardize the ILD-MDD process in China.Key recommendations:1. Formation of teams: ILD centers should establish multidisciplinary teams (MDT) and integrate MDD into the ILD patient care process. (strong recommendation)2. Patient preparation: Prior to ILD-MDD, patients should undergo as thorough an ILD assessment as possible, including medical history, diagnostic tests, and functional evaluations. (strong recommendation)3. MDD frequency & logistics:(1) The frequency, duration and number of cases to be discussed in ILD-MDD should be based on the clinical needs of each center, but should be held at least monthly. (2) Consistent timing and location of ILD-MDD is recommended to improve attendance. (medium recommendation)4. Team composition: The MDT should include experts from a range of disciplines with experience of ILD. These should include specialists in Pulmonary and Critical Care Medicine, Radiology, and Pathology. Where appropriate, experts in Rheumatology, Hematology, Thoracic Surgery, and Respiratory Care and Rehabilitation should also be involved. (strong recommendation)5. Case presentation & goals:(1) The physician in charge should present clinical information, preferably using standardized slides. Real-time imaging and pathology data are encouraged. (2) The primary goals of ILD-MDD discussions should be disease diagnosis and management. (strong recommendation)6. Operational leadership: Assign a dedicated professional to manage the ILD-MDD operations and maintain the information discussed. (strong recommendation)7. Specific conditions:(1) Suspected idiopathic pulmonary fibrosis should be diagnosed by a standardized MDD process. (2) Suspected idiopathic interstitial pneumonia (IIP) should be classified by MDD. If IIP is indicated by imaging or pathology, prioritize identifying potential underlying causes such as connective tissue diseases (CTDs), certain medications, or aspiration.(3) Suspected hypersensitivity pneumonitis should also be diagnosed by MDD. (4) If an ILD patient shows signs suggestive of CTDs, the diagnosis should be made by ILD-MDD with the involvement of rheumatologists. (strong recommendation)8. Unclassifiable ILD: For ILD patients who cannot be clearly classified, create a tailored management plan based on the patient's specific disease features. (strong recommendation)9. Progressive pulmonary fibrosis: Use ILD-MDD to determine whether an ILD patient meets the criteria for progressive pulmonary fibrosis and to discuss a personalized care plan. (strong recommendation).

µPAD-based colorimetric nanogold aptasensor for CRP and IL-6 detection as sepsis biomarkers

Point-of-care testing is defined as medical diagnostic testing at or near the time and place of a patient. The integration of microfluidics with functionalized nanomaterials provides a rapid and sensitive detection method for biomarkers. Due to their optical characteristics, gold nanoparticles (GNPs) and aptamers can be used in a colorimetric technique. In this research, accurate and quick aptasensors were created using aptamers for two sepsis biomarkers, interleukin-6 (IL-6) and C-reactive protein (CRP). Aptamers were combined with GNPs to create aptasensors, which were then used to analyze various biomarker concentrations after aptamer-protein docking on the online HDOCK server to verify aptamer-protein interactions. To improve the results' stability and ease of use during the reaction time, microfluidic paper-based analytical devices (µPAD) was employed. The linear diagnostic ranges in this method were 50–1000 mg L−1 and 1–25 ng/L, and limit of detection values were 1.9 mg L−1 and 0.07 ng/L for CRP and IL-6, respectively; These values decreased when µPADs were used and became more suitable to diagnosis of sepsis. Two aptasensors were highly stable, reproducible, accurate, and recoverable. Our result suggests that colorimetric GNPs can be used to detect a specific analyte through color changes visible to the naked eye for monitoring purposes or as simple optical detectors for quantitative measurements.

Conventional Radiography of Grade III Knee Osteoarthritis: A Case Report

Introduction: Osteoarthritis (OA) is the most common form of inflammatory joint disease. It occurs most frequently in the knees, hips, the spine (vertebrae), and ankles. Radiological prevalence of knee OA in Indonesia reaches 15.5% in men and 12.7% in women aged between 40-60 years. X-ray imaging is routinely used in clinical practice to confirm knee OA diagnosis and in clinical research to monitor the progression of knee OA. Case report: A 62-year-old female patient presented with knee pain in both knees that had been ongoing for the past 6 months. The pain was described as throbbing and stabbing, the right knee worse affected than the left. Palpation elicited tenderness, crepitus in both joints and did not reveal any deformities. Radiological AP/Lateral X-ray of the right knee revealed evidence of osteophytes, sclerosis and narrowing joint space, leading to the impression of Grade III osteoarthritis in the right knee. Discussion: Joint pain is the chief complaint that leads patients with knee osteoarthritis to seek medical attention. Pain typically worsens with movement and decreases with rest. In diagnosing OA, an AP/Lateral radiographic examination of the right knee is conducted, revealing the presence of osteophytes, subchondral bone sclerosis and accompanied by slight joint narrowing. This impression aligns with the Grade III OA criteria according to the Kellgren-Lawrence grading system. Conclusion: Diagnosis of osteoarthritis involves a comprehensive approach combining medical history, physical examination, and diagnostic tests. Radiographic examinations including conventional radiography play a significant role in diagnosing OA. In the early stages of the disease, joint radiographs may still appear normal. The severity of knee OA can be evaluated using the Kellgren-Lawrence (KL) grading scheme which ranges from grade 0 to grade 4. Keywords: Knee Osteoarthritis, Conventional Radiography, The Kellgren-Lawrence Grading

Artificial intelligence-based image analysis in clinical testing: lessons from cervical cancer screening.

Novel screening and diagnostic tests based on artificial intelligence (AI) image recognition algorithms are proliferating. Some initial reports claim outstanding accuracy followed by disappointing lack of confirmation, including our own early work on cervical screening. This is a presentation of lessons learned, organized as a conceptual step-by-step approach to bridge the gap between the creation of an AI algorithm and clinical efficacy. The first fundamental principle is specifying rigorously what the algorithm is designed to identify and what the test is intended to measure (eg, screening, diagnostic, or prognostic). Second, designing the AI algorithm to minimize the most clinically important errors. For example, many equivocal cervical images cannot yet be labeled because the borderline between cases and controls is blurred. To avoid a misclassified case-control dichotomy, we have isolated the equivocal cases and formally included an intermediate, indeterminate class (severity order of classes: case>indeterminate>control). The third principle is evaluating AI algorithms like any other test, using clinical epidemiologic criteria. Repeatability of the algorithm at the borderline, for indeterminate images, has proven extremely informative. Distinguishing between internal and external validation is also essential. Linking the AI algorithm results to clinical risk estimation is the fourth principle. Absolute risk (not relative) is the critical metric for translating a test result into clinical use. Finally, generating risk-based guidelines for clinical use that match local resources and priorities is the last principle in our approach. We are particularly interested in applications to lower-resource settings to address health disparities. We note that similar principles apply to other domains of AI-based image analysis for medical diagnostic testing.

Situational Analysis of Healthcare and Medical Diagnostic Testing Facility Availability in Selected Blocks of Muzaffarpur District, Bihar, India: A Cross-Sectional Study.

This study presents a comprehensive assessment of healthcare facilities, focusing on workforce composition, operational dynamics, diagnostic laboratory services, and accessibility considerations. The comparison between government and private healthcare sectors provides insights into service delivery and potential disparities. The study's rationale, objectives, and methodology are explored in the context of the Indian healthcare landscape. A cross-sectional analysis was conducted in Muzaffarpur district, Bihar, targeting selected urban and rural blocks. The study employed geolocation data to analyze accessibility to healthcare facilities. Data collection involved on-site visits, structured questionnaires, and consultation of the Indian Council of Medical Research (ICMR)'s framework. The assessment concentrated on the availability of tests offered by the LaBike platform, and workforce compositions were compared. Government healthcare facilities exhibited a balanced distribution of doctors, nurses, and grassroot workers, reflecting comprehensive healthcare provisions. Private facilities, although featuring moderate doctor and nurse presence, lacked grassrootworkers. Diagnostic test prevalence was evident, with core tests, such as CBC and blood glucose, available in over 85% of facilities. Government facilities provided tests free of charge, while private facilities showcased a diverse cost spectrum. Proposed interventions received strong support from both sectors, indicating the potential for innovative healthcare solutions. Accessibility analysis: Urban intervention and control sites demonstrated comparable accessibility, with facilities located within 2 km. In rural intervention and control sites, distances varied significantly. Mushahari, a rural intervention site, required participants to travel 6 km to the nearest facility, impacting healthcare access. By contrast, Marwan, a rural control site, featured a shorter distance of 3 km. This study's comprehensive evaluation of healthcare facilities offers valuable insights into workforce dynamics, diagnostic services, and healthcare interventions in the context of government and private sectors. The findings underscore the significance of addressing workforce gaps and promoting equitable access to diagnostics. By informing evidence-based decision-making, this study contributes to the optimization of healthcare service delivery, aiming to enhance healthcare quality and accessibility for all.

Dysphagia in Neurological Disorders.

Dysphagia is a common symptom in many neurologic disorders. Patients with oropharyngeal dysphagia present with difficulties when they start to swallow, often with coughing and choking; whereas patients with esophageal dysphagia describe the feeling that swallowed food stops in the chest. Chronic neurologic diseases such stroke, Parkinson's disease, or dementia often have dysphagia as a symptom, particularly oropharyngeal dysphagia, and the term "neurogenic dysphagia" is often used. A disruption of the sophisticated, integrated sensorimotor swallowing system is usually the main reason behind dysphagia. Dysphagia can be associated with aspiration leading to aspiration pneumonia, and chronic dysphagia can lead to weight loss and malnutrition. Patients with dysphagia, when accurately and promptly diagnosed through medical history, physical examination, and diagnostic tests, often can be treated and experience improved quality of life. The pathophysiological mechanisms behind dysphagia, its diagnosis, and potential treatments are discussed in this manuscript.