High Level Of Reliability Research Articles

The relationship between serum anion gap levels and short-, medium-, and long-term all-cause mortality in ICU patients with congestive heart failure: a retrospective cohort study

Background There hasn’t been research done on the connection between serum anion gap (AG) levels and long-, medium-, and short-term all-cause mortality in congestive heart failure (CHF) patients. This study aims to investigate the association between serum anion gap levels and all-cause mortality in CHF patients after adjusting for other covariates. Methods For each patient, we gather demographic information, comorbidities, laboratory results, vital signs, and scoring data using the ICU (Intensive Care Unit) Admission Scoring System from the MIMIC-III database. The connection between baseline AG and long-, medium-, and short-term all-cause mortality in critically ill congestive heart failure patients was investigated using Kaplan-Meier survival curves, subgroup analysis, restricted cubic spline, and Cox proportional risk analysis. Results 4840 patients with congestive heart failure in total were included in this study. With a mean age of 72.5 years, these patients had a gender split of 2567 males and 2273 females. After adjusting for other covariates, a multiple regression analysis revealed that, in critically ill patients with congestive heart failure, all-cause mortality increased significantly with rising AG levels. In the fully adjusted model, we discovered that AG levels were strongly correlated with 4-year, 365-day, 90-day, and 30-day all-cause mortality in congestive heart failure patients with HRs (95% CI) of 1.06 (1.04, 1.08); 1.08 (1.05, 1.10); and 1.08 (1.05, 1.11) (p-value < 0.05). Our subgroup analysis’s findings demonstrated a high level of consistency and reliability. K-M survival curves demonstrate that high serum AG levels are associated with a lower survival probability. Conclusion Our research showed the association between CHF patients’ all-cause mortality and anion gap levels was non-linear. Elevated anion gap levels are associated with an increased risk of long-, medium-, and short-term all-cause death in patients with congestive heart failure. Continuous monitoring of changes in AG levels may have a clinical predictive role.

A Universal Image Compression Sensing–Encryption Algorithm Based on DNA-Triploid Mutation

With the fast growth of information technology (IT), the safety of image transmission and the storing of images are becoming increasingly important. Traditional image encryption algorithms have certain limitations in transmission and security, so there is an urgent need for a secure and reliable image encryption algorithm. A universal compression sensing (CS) image encryption (IE) algorithm based on DNA-triploid mutation (DTM) is presented in this paper. Firstly, by using the CS algorithm, an image is compressed while obtaining a range of chaotic sequences by iteration of a chaotic map. Then, DNA sequences are generated by encoding the image and, based on the DTM, new mutant DNA sequences are generated according to specific rules. Next, the chaotic sequences are operated at the DNA level to perform confusion and diffusion operations on the image to ensure the security of the data. Finally, DNA decoding is carried out to obtain the compressed encrypted image. The simulation results show that the algorithm can effectively complete encryption and decryption of images. The performance test results show that the algorithm has a sufficiently large key space of 10587. The information entropy of the cipher image is close to 8. In summary, both simulation experiments and performance tests fully show that a high level of security and reliability for the proposed algorithm in protecting image privacy is achieved.

Разработка и апробация методики диагностики способности студентов к инновационной предпринимательской деятельности «СИНПРЕД»

Due to the need to ensure economic growth and improving competitiveness of the Russian economy, the development of youth innovative entrepreneurship is relevant for our country. This requires not only the implementation of appropriate educational programs, but also selection of young people for admission on the basis of an effective assessment of their abilities and readiness to create an innovative business. The goal of the investigation is to design and test psychodiagnostic method that solves the problem of prompt assessment of students’ ability to innovative entrepreneurship. The test SINPRED is elaborated on the basis of the authored by Prokhorova and Belokon model of psychic determinants of effective entrepreneurial activity, connected with innovations. The test contains: instruction, 56 statements, the agreement with which the testee expresses on a seven-rank scale; key of primary data processing; normalized points (stens), worked out for two groups of testees (women and men); manual on processing and interpretation of diagnostics results. For empirical foundation of the methodics indices of students’ behavior, singled out by 5 experts, are used. Verification of discriminatory power, internal consistency, reliability of the test is carried out on the sampling of 180 students. 152 students comprise the sampling for evaluating of methodics validity. For defining the test factor structure and its standardization the results of 308 students questioning are utilized. It is revealed that the created test possesses a high level of discriminatory power and test-retest reliability. All test assignments are correlated with each other. The scales of the methodics have a sufficient level of validity. During the test approbation significant differences between women and men are unveiled on four primary scales: leadership, creativity, nonconformity, early entrepreneurial experience. The acquired differences additionally confirm discriminatory power and criteria validity of the test, and also indicate perspective of scientific investigations, that uncover peculiarities of determination and molding ability to innovative entrepreneurship, conditioned by sex.

FINANCIAL ANALYSIS OF THE SUSTAINABILITY OF INSURANCE COMPANIES

The article examines the essence of the concept of financial stability of an insurer, conducts a financial analysis of insurance companies. The role of financial sustainability for insurers is determined, which is special because it determines the importance of ensuring a high level of financial stability and reliability of the insurer's activities. It is proved that the key factors in assessing the competitiveness of an insurance company are profitability, stability, financial strength and level of service. The factors influencing the financial stability of the insurer and the main criteria for ensuring the financial stability of the insurer are analyzed. It is found that an important criterion for ensuring the financial stability of an insurer is the availability of a balanced insurance portfolio, the formation of which is aimed at maximizing profit with minimal risk. The role of reinsurance in ensuring the financial stability of the insurer is substantiated. The investment activities of the insurer to accumulate significant financial resources are analyzed

The Stirling Antenatal Anxiety Scale (SAAS): Turkish validity and reliability study

AimsTo examine the psychometric properties of the Stirling Antenatal Anxiety Scale (SAAS), developed by Sinesi et al., which assesses the level of anxiety of pregnant women in the prenatal period, in the Turkish culture, and to conduct a validity and reliability study. MethodsThis study had a methodological approach, with a cross-sectional and descriptive research design. Reporting was in accordance with the STROBE checklist. The sample included 160 pregnant women who were followed up in the maternity outpatient clinics of a public hospital and a private hospital in Istanbul. Data were collected face-to-face using a personal information form, the Turkish version of the SAAS, and the Generalized Anxiety Disorder-7 scale between June and August 2023. In the data analysis, validity analyses were performed with content and construct validity and multiple fit indices for confirmatory factor analysis. Item-total score analysis was conducted using Cronbach's alpha coefficient and Pearson's correlation analysis to assess reliability. Descriptive and reliability analyses were undertaken using SPSS v.28.0.1.0, and validity analyses were performed using SPSS AMOS v.26.0.0.0. FindingsBased on expert opinions on the items in the Turkish version of the SAAS, the content validity ratio was 0.96. The decision was made to exclude Item 9 from the Turkish version because the item factor load was low. The Turkish version had a single factor, as did the original version. The Cronbach alpha coefficient was 0.87, so the Turkish version was determined to have high reliability. ConclusionThe Turkish version of the SAAS, originally produced in English, has high levels of validity and reliability. In addition, it is short and easy to apply in clinical and research settings. As such, the Turkish version of the SAAS is recommended for use to evaluate the level of anxiety in pregnant women.

ToPick: Time-of-Pickup Measurement for the Elderly using Wearables.

The ability to pick up objects off the floor can degrade over time with elderly individuals, leading to a reduced quality of life and an increase in the risk of falling. Healthcare professionals have expressed an interest in monitoring the decline in pickup ability of a subject over extended periods of time and intervening when it becomes hazardous to the subject's health. The current means of evaluating pickup ability involving in-clinic patient visits is both time and financially expensive. There is a clear need for a cost-effective, remote means of pickup evaluation to ease the burden on both patients and physicians. To address these challenges, we introduce a Time-of-Pickup (ToP) solution, called ToPick, designed for the automatic assessment of pickup ability over time. The practical performance of ToPick is evident, demonstrated by a minimal median error of approximately 100 milliseconds in evaluating 20 pickup events among 10 elderly individuals. Furthermore, ToPick exhibits a high level of reliability, achieving perfect accuracy, precision, and recall scores for pickup event detection. We actualize our research findings by designing an application intended for adoption by both healthcare practitioners and elderly individuals. The app aims to reduce both time and financial costs while enabling mobile treatment for users.

An index of the economic dependence on Tourism

This study proposes a methodology to construct a Tourism Economic Dependence Index for a sample of 144 countries spanning the period 1995–2019. This index aims to serve as a summary measure of countries’ dependence on tourism while controlling for differences in economic development levels across countries. Findings suggest that an index value of 20% may be considered a threshold for identifying highly tourism-dependent countries. Furthermore, the results of the index indicate that economies have experienced a slight trend toward higher levels of dependence on tourism since the global financial crisis. However, estimates from a panel convergence model suggest that the hypothesis of convergence toward a common long-run equilibrium in index levels across countries can be rejected. Instead, different groups of countries converging toward the same long-run equilibrium level of the index have been identified.

Improving prediction accuracy of laser-induced shock wave velocity prediction using neural networks

The velocity of laser-induced shock waves affects the efficiency and efficacy of laser-based processes. The ability to accurately estimate shock wave velocity is critical for optimizing experimental combinations, creating laser-based systems, and assuring desired results. Traditional approaches to predict shock wave velocity involve empirical equations and analytical models based on simplified assumptions. However, these methods often lack accuracy and fail to capture the complex dynamics of laser-matter interactions. To overcome these limitations, we used a combination of an artificial neural network and a genetic algorithm to predict shock wave velocity. In this method, the neural network structure is dynamically designed. The optimization method does this by modifying the neural network's weights and figuring out the network's structure on our behalf. Based on the findings, our suggested technique worked very well; it surpassed other comparison methods by achieving the lowest average errors in terms of RMSE and MAE, which are 4.38 and 3.74, respectively. Moreover, the analysis has shown that our proposed method has a high level of reliability in predicting impulsive wave velocity using a neural network.

Fatigue, Internet Addiction and Symptoms of Long COVID-A Cross-Sectional Study of Polish Students.

Introduction: Fatigue is the most persistent symptom in patients with long COVID. Moreover, Internet addiction itself has become a pandemic long-term effect. The aim of this study was to investigate the degree of fatigue and Internet addiction in a group of students with COVID-19 and to determine the relationship between fatigue and addiction in students with and without long COVID symptoms. Material and methods: A cross-sectional study was conducted among 402 Polish students aged 19-26. The 183 students who had COVID-19 signaled the presence of long COVID symptoms, which corresponded to 45.5% of the surveyed group. The Modified Fatigue Impact Scale was used to assess the level of fatigue, and the Kimberly Young questionnaire was used to assess the level of Internet addiction. Results: 19.7% (95% c.i.: 15.9-23.9%) of the students surveyed had a moderate level of Internet dependence (Internet addiction measure value of 50 points or more). Most of them did not complain of high levels of fatigue. Higher levels of dependence and fatigue were observed in subjects with long COVID symptoms (MFIS mean value was 26.5 in this group vs. 17.7 in the others; p = 0.0000 ***). The higher the respondents' level of dependence, the more they tended to feel tired (correlations were stronger in those with long COVID symptoms: rS = 0.23; p = 0.0017 **). Conclusions: In view of the results obtained, the study presented here has the potential to contribute to the international debate on the long-term health consequences of the COVID-19 pandemic and strategies to address them. The study provides data that may be useful in the development of educational and health policies that target the psychophysical well-being of patients with long COVID symptoms. This process should be considered as a long-term endeavor.

A Cu2+-modulated UCNPs@RBD sensor for sensitive detection of tetracyclines in food based on the spirolactam open-loop reaction

Abuse of tetracycline (TC) leads to the development of drug-resistant bacterial strains that threaten public health. This paper proposed a novel Cu2+-modulated UCNPs@RBD sensor for detecting TC. The sensor utilizes rhodamine B derivatives (RBD) that bind to Cu2+, forming RBD-Cu through a spirolactam open-loop reaction. The fluorescence of upconversion nanoparticles (UCNPs) is quenched by RBD-Cu via the inner filter effect (IFE). Upon addition of TC, TC-Cu forms due to electron-donor groups in TC, which decreases the generation of RBD-Cu, thereby enhancing the fluorescence of UCNPs. Under optimized conditions, the sensor exhibits remarkable accuracy across a concentration range of 50–50000 µg L−1, with a limit of detection (LOD) of 1.72 µg L−1. Moreover, the sensor demonstrates high selectivity for TC, validated by its application in food samples. The relative standard deviation (RSD) in real sample analysis was below 4.17 %, and the results were consistent with the HPLC method (P > 0.05). Hence, the sensor exhibited a high level of sensitivity and reliability, making it suitable for the detection of TC in food.

Utilizing large language models for EFL essay grading: An examination of reliability and validity in rubric‐based assessments

AbstractThis study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student essays of varying quality. The grading scale comprised five domains: grammar, content, organization, style &amp; expression and mechanics. The results revealed that fine‐tuned ChatGPT model demonstrated a very high level of reliability with an intraclass correlation (ICC) score of 0.972, Default ChatGPT model exhibited an ICC score of 0.947 and Bard showed a substantial level of reliability with an ICC score of 0.919. Additionally, a significant overlap was observed in certain domains when comparing the grades assigned by LLMs and human raters. In conclusion, the findings suggest that while LLMs demonstrated a notable consistency and potential for grading competency, further fine‐tuning and adjustment are needed for a more nuanced understanding of non‐objective essay criteria. The study not only offers insights into the potential use of LLMs in grading student essays but also highlights the need for continued development and research. Practitioner notesWhat is already known about this topic Large language models (LLMs), such as OpenAI's ChatGPT and Google's Bard, are known for their ability to generate text that mimics human‐like conversation and writing. LLMs can perform various tasks, including essay grading. Intraclass correlation (ICC) is a statistical measure used to assess the reliability of ratings given by different raters (in this case, EFL instructors and LLMs). What this paper adds The study makes a unique contribution by directly comparing the grading performance of expert EFL instructors with two LLMs—ChatGPT and Bard—using an analytical grading scale. It provides robust empirical evidence showing high reliability of LLMs in grading essays, supported by high ICC scores. It specifically highlights that the overall efficacy of LLMs extends to certain domains of essay grading. Implications for practice and/or policyThe findings open up potential new avenues for utilizing LLMs in academic settings, particularly for grading student essays, thereby possibly alleviating workload of educators.The paper's insistence on the need for further fine‐tuning of LLMs underlines the continual interplay between technological advancement and its practical applications.The results lay down a footprint for future research in advancing the use of AI in essay grading.

Robust Prediction of Relative Binding Energies for Protein–Protein Complex Mutations Using Free Energy Perturbation Calculations

Computational free energy-based methods have the potential to significantly improve throughput and decrease costs of protein design efforts. Such methods must reach a high level of reliability, accuracy, and automation to be effectively deployed in practical industrial settings in a way that impacts protein design projects. Here, we present a benchmark study for the calculation of relative changes in protein–protein binding affinity for single point mutations across a variety of systems from the literature, using free energy perturbation (FEP+) calculations. We describe a method for robust treatment of alternate protonation states for titratable amino acids, which yields improved correlation with and reduced error compared to experimental binding free energies. Following careful analysis of the largest outlier cases in our dataset, we assess limitations of the default FEP+ protocols and introduce an automated script which identifies probable outlier cases that may require additional scrutiny and calculates an empirical correction for a subset of charge-related outliers. Through a series of three additional case study systems, we discuss how Protein FEP+ can be applied to real-world protein design projects, and suggest areas of further study.

Flood Mapping and Impact Assessment in Agricultural Land in Hoa Vang, Da Nang Using Remote Sensing and Google Earth Engine

: Hoa Vang district in Da Nang city, is frequently affected by floods. This research was conducted to generate a flood map in Hoa Vang District, Da Nang City, during the peak flooding period in 2022, using Sentinel 1 imagery on the Google Earth Engine (GEE) cloud computing platform. The research also aims to assess the impact of this flooding event on the productivity of agricultural land in the district. Based on the Sentinel 1 imagery's backscattering coefficient, the study utilizes the Otsu algorithm for thresholding to determine the flood inundated areas. The results indicated that the optimal Otsu threshold value range from -16.003 to -10.631 dB. In addition, to assess the reliability of the flood mapping results, the study utilizes the in-situ flood inventory data to calculate the overall error and Kappa index. The research findings indicate a high level of reliability with an overall accuracy of 0.89 and a Kappa index of 0.79. Based on this analysis, the study successfully established a flood map for the peak flooding period 2022 in the study area. Furthermore, the study assessed the impact of floods on agricultural land productivity in the communes of Hoa Vang District. The findings showed that the flooded agricultural land area was 1,979.8 hectares, accounting for 77.3% of the total flooded area and 2.7% of the total natural area, primarily concentrated in the southern communes of the district such as Hoa Tien, Hoa Chau, Hoa Phuoc, and Hoa Phong. These findings serve as scientific background for assessing further impacts of flooding on agricultural land in Hoa Vang District, Da Nang City.

Cross-Cultural Adaptation, Translation, and Validation of the Victorian Institute of Sport Assessment-Achilles Questionnaire (VISA-A) for Use With Arabic-Speaking Patients With Achilles Tendinopathy.

The Victorian Institute of Sport Assessment-Achilles (VISA-A) questionnaire is a validated instrument for assessing symptoms of Achilles tendinopathy (AT). However, there is a need to validate the Arabic version of the VISA-A (VISA-A-AR) in Arabic-speaking patients with AT. To validate the VISA-A-AR in Arabic patients with AT and evaluate its reliability and validity. Cohort study (diagnosis); Level of evidence, 3. The translation and cultural adaptation of the VISA-A questionnaire into Arabic followed international guidelines. A total of 81 participants were recruited, including 45 patients diagnosed with AT and 36 healthy individuals. The AT group comprised male and female native Arabic speakers aged ≥18 years who were diagnosed with and had symptoms of AT. The inclusion criteria for the healthy group were the same, except that they must not have had AT at the time of the study or previously. The exclusion criteria were individuals with a partial or complete Achilles tendon rupture or prior Achilles tendon surgery. The internal consistency of the VISA-A-AR was assessed using the Cronbach α coefficient. Test-retest reliability was evaluated using the intraclass correlation coefficient (ICC[3,1]). Construct validity was assessed through correlation analysis between VISA-A-AR scores and the Arabic versions of the Short Form-36 Health Survey (SF-36-AR) and the Numeric Pain Rating Scale (ANPRS). Differences in VISA-A-AR scores between patients with AT and healthy controls were analyzed using appropriate statistical tests. The VISA-A-AR demonstrated a high level of internal consistency (Cronbach α = 0.935) and excellent test-retest reliability (ICC[3,1] = 0.985). Significant positive correlations were observed between VISA-A-AR scores and SF-36-AR (r(43) = 0.838, P < .001), indicating good construct validity. In addition, VISA-A-AR scores showed a significant negative correlation with ANPRS (rS(43) = -0.835, P < .001). Furthermore, VISA-A-AR scores exhibited a significant difference between patients with AT (mean, 45.82 ± 16.65) and healthy controls (mean, 99.94 ± 0.33) (P < .001). The findings of this study validate the VISA-A-AR as a reliable and valid tool for assessing symptoms of AT in Arabic-speaking patients.

Vaginal irritation testing-prospects of human organotypic vaginal tissue culture models.

Personal lubricants intended for local or systemic delivery via the vaginal route can induce vaginal irritation, damage the vaginal epithelial barrier which can enhance microbial entry, induce inflammation, and alter the microbiome of the vaginal ecosystem. Therefore, manufacturers of personal lubricants and medical devices are required to show biocompatibility and safety assessment data to support regulatory decision-making within a specified context of use. Furthermore, due to ethical concerns and the introduction of the 7th amendment of the European Council Directive which bans animal testing for cosmetic ingredients and products coupled with the Food and Drug Administration modernization Act 2.0 guidelines, there is a wave of drive to develop alternative test methods to predict human responses to chemical or formulation exposure. In this framework, there is a potential to use three-dimensional organotypic human vaginal-ectocervical tissue models as a screening tool to predict the vaginal irritation potential of personal lubricants and medicaments. To be physiologically relevant, the in vitro tissue models need to be reconstructed using primary epithelial cells of the specific organ or tissue and produce organ-like structure and functionality that recapitulate the in vivo-like responses. Through the years, progress has been made and vaginal tissue models are manufactured under controlled conditions with a specified performance criterion, which leads to a high level of reproducibility and reliability. The utility of vaginal tissue models has been accelerated in the last 20years with an expanded portfolio of applications ranging from toxicity, inflammation, infection to drug safety, and efficacy studies. This article provides an overview of the state of the art of diversified applications of reconstructed vaginal tissue models and highlights their utility as a tool to predict vaginal irritation potential of feminine care products.

Development of an Infrared Marker based Encoder System as a Non-Contact Positioning System for Ultrasonic Probes

The digitalization of testing procedures is one of the challenges in the development of modern non-destructive testing systems. In order to guarantee a high level of inspection reliability, the assignment of measurement data to the measurement position plays an important role as well as the optimal inspection hardware. In a cooperative research and development project, an optical tracking system has been developed with which it is possible to determine the positions of different ultrasonic probes in space without contact. Thus, the position of the measurement is linked to the measurement results directly. Infrared LED markers attached to the ultrasonic probes are used for this purpose. The position of the markers are tracked in space with a camera. By linking several cameras and trackers, a positional accuracy of a few millimeters can be achieved for a camera specimen distance of 2 m. The more cameras are used the bigger the investigated part can be. For the tracking system, an existing optical camera system is coupled with a conventional of the shelve ultrasonic phased array device by means of a newly developed universal encoder. Different single transducer probes or phased array probes can be used. The costly and time consuming use of mechanical encoders is thus eliminated. This combination enables the further digitalization of hand-guided ultrasonic testing precisely in those areas where robot-based testing is not feasible. Additionally, a much easier way of documentation is possible. Due to the exact position determination a better evaluation of the measurement data can be carried out via a subsequent 3D display of the ultrasound data.

Full Outline of UnResponsiveness (FOUR) Scale: a Multicenter Validation Study of the Psychometric Properties of the Approved Russian Version

Assessment of the individual level of consciousness on admission of a patient with brain injury to the intensive care unit (ICU) is a priority task and a mandatory step in the overall assessment of neurological status. The Full Outline of UnResponsiveness (FOUR) scale, developed at the Mayo Clinic (USA) in 2005, is a widely used tool for comprehensive assessment of patients with altered state of consciousness. The lack of a validated Russian-language version of the FOUR scale has hindered its widespread use in clinical practice. Therefore, the official Russian version of the FOUR scale was developed and adapted for use in Russia after the first stage of the validation study (linguistic and cultural adaptation).Aim. To evaluate the psychometric properties of the Russian version of the FOUR scale for comprehensive assessment of patients in altered state of consciousness.Materials and Methods. As part of a prospective multicenter validation study, the psychometric properties of the scale (reliability, validity, and sensitivity) were evaluated in a group of 171 adult patients with altered conscious state of various etiologies, such as ischemic and hemorrhagic stroke, neuroinflammatory conditions, and traumatic brain injury. Patients’ responses were assessed on the first day of ICU stay and 2-3 days later by two ICU neurologists with at least three years of experience.Results. High levels of validity and reliability were obtained for the Russian version of the FOUR scale for comprehensive assessment of unresponsive patients, including Spearman’s rank correlation coefficient r=0.99 (P&lt;0.0001), Cohen’s κ=0.77 (P&lt;0.001), Cronbach’s α=0.87 (P&lt;0.0001). Regarding the sensitivity of the FOUR scale, no significant changes were found after comprehensive assessment of unresponsive patients on day 1 in the ICU and 2-3 days later (Wilcoxon test, P=0.906). There was a good correlation between the FOUR and Glasgow Coma Scale scores used to assess patients with altered state of consciousness, confirming the validity of the test with r=0.91 (P&lt;0.0001).Conclusion. The Russian version of the FOUR scale for comprehensive assessment of unresponsive patients is a valid, reliable, and sensitive clinical tool. Sufficiently verified level of psychometric properties allows its authorized use in Russia and other Russian-speaking countries. The scale is available for download via QR code and at the website of the International Scales and Questionnaires Validation Group at the Scientific Center of Neurology.

Enhanced reliability and time efficiency of deep learning-based posterior tibial slope measurement over manual techniques.

Multifaceted factors contribute to inferior outcomes following anterior cruciate ligament (ACL) reconstruction surgery. A particular focus is placed on the posterior tibial slope (PTS). This study introduces the integration of machine learning and artificial intelligence (AI) for efficient measurements of tibial slopes on magnetic resonance imaging images as a promising solution. This advancement aims to enhance risk stratification, diagnostic insights, intervention prognosisand surgical planning for ACL injuries. Images and demographic information from 120 patients who underwent ACL reconstruction surgery were used for this study. An AI-driven model was developed to measure the posterior lateral tibial slope using the YOLOv8 algorithm. The accuracy of the lateral tibial slope, medial tibial slopeand tibial longitudinal axis measurements was assessed, and the results reached high levels of reliability. This study employed machine learning and AI techniques to provide objective, consistentand efficient measurements of tibial slopes on MR images. Three distinct models were developed to derive AI-based measurements. The study results revealed a substantial correlation between the measurements obtained from the AI models and those obtained by the orthopaedic surgeon across three parameters: lateral tibial slope, medial tibial slopeand tibial longitudinal axis. Specifically, the Pearson correlation coefficients were 0.673, 0.850and 0.839, respectively. The Spearman rank correlation coefficients were 0.736, 0.861and 0.738, respectively. Additionally, the interclass correlation coefficients were 0.63, 0.84and 0.84, respectively. This study establishes that the deep learning-based method for measuring posterior tibial slopes strongly correlates with the evaluations of expert orthopaedic surgeons. The time efficiency and consistency of this technique suggest its utility in clinical practice, promising to enhance workflow, risk assessmentand the customization of patient treatment plans. Level III, cross-sectional diagnostic study.

Enhancing clinical decision-making: A novel nomogram for stratifying cancer-specific survival in middle-aged individuals with follicular thyroid carcinoma utilizing SEER data

BackgroundThyroid cancer (TC) is the most common malignant tumor in the endocrine system, is also one of the head and neck tumor. Follicular Thyroid Carcinoma (FTC) plays an important role in the pathological classification of thyroid cancer. This study aimed to develop an innovative predictive tool, a nomogram, for predicting cancer specific survival (CSS) in middle-aged FTC patients. MethodsWe collected patient data from the Surveillance, Epidemiology, and End Results (SEER) database. The data from patients between 2004 and 2015 were used as the training set, and the data from patients between 2016 and 2018 were used as the validation set. To identify independent risk factors affecting patient survival, univariate and multivariate Cox regression analyses were performed. Based on this, we developed a nomogram model aimed at predicting CSS in middle-aged patients with FTC. The consistency index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration curve were used to evaluate the accuracy and confidence of the model. ResultsA total of 2470 patients were enrolled in this study, in which patients from 2004 to 2015 were randomly assigned to the training cohort (N = 1437) and validation cohort (N = 598), and patients from 2016 to 2018 were assigned to the external validation cohort (N = 435) in terms of time. Univariate and multivariate Cox regression analysis showed that marriage, histological grade and TNM stage were independent risk factors for survival. The C-index for the training cohort was 0.866 (95 % CI: 0.805–0.927), for the validation cohort it was 0.944 (95 % CI: 0.903–0.985), and for the external validation cohort, it reached 0.999 (95 % CI: 0.997–1.001). Calibration curves and AUC suggest that the model has good accuracy. ConclusionsWe developed an innovative nomogram to predict CSS in middle-aged patients with FTC. Our model after a rigorous internal validation and external validation process, based on the time proved that the high level of accuracy and reliability. This tool helps healthcare professionals and patients make informed clinical decisions.

Sensitivity, Specificity, and Reliability of the CTS-6 for Carpal Tunnel Syndrome Administered by Medical Assistants

The CTS-6 can be used clinically to diagnose carpal tunnel syndrome (CTS) and has demonstrated high levels of interrater reliability when administered by nonexpert clinicians. Our purpose was to assess sensitivity (Sn), specificity (Sp), and interrater reliability of the CTS-6 when administered by medical assistants (MAs). A series of patients presenting to an academic, upper-extremity surgery clinic were screened using CTS-6 between May and June of 2023. The CTS-6 was first administered by one of seven MAs and then by one of four fellowship-trained upper-extremity surgeons. In addition to recording baseline demographics, the results of each of the six history and examination components of the CTS-6 were recorded, as was the cumulative CTS-6 score (0-26). Surgeons were blinded to the scores obtained by the MAs. Interrater reliability (Cohen's kappa) was determined between the groups with respect to the diagnosis of CTS and the individual CTS-6 items. Sensitivity/specificity was calculated for the MA-administered CTS-6, using the score obtained by the surgeon as the reference standard. A CTS-6 score >12 was considered diagnostic of CTS. Two hundred eighteen patients were included, and 26% had a diagnosis of CTS. The MA group demonstrated a Sn/Sp of 84%/91% for the diagnosis of CTS. Interrater reliability was substantial (Cohen's kappa: 0.72, 95% confidence interval: 0.62-0.83) for MAs compared with hand surgeons for the diagnosis of CTS. For individual CTS-6 components, agreement was lowest for the assessment of two-point discrimination (fair) and highest for the assessment of subjective numbness (near perfect). The CTS-6 demonstrates substantial reliability and high Sn/Sp when administrated by MAs in an upper-extremity clinic. These data may be used to inform the development of CTS screening programs and future investigations in the primary care setting. Diagnostic II.