Meta-analysis of machine learning models for the diagnosis of central precocious puberty based on clinical, hormonal (laboratory) and imaging data.

Background: Central precocious puberty (CPP) is a common endocrine disorder in children, and its diagnosis primarily relies on the gonadotropin-releasing hormone (GnRH) stimulation test, which is expensive and time-consuming. With the widespread application of artificial intelligence in medicine, some studies have utilized clinical, hormonal (laboratory) and imaging data-based machine learning (ML) models to identify CPP. However, the results of these studies varied widely and were challenging to directly compare, mainly due to diverse ML methods. Therefore, the diagnostic value of clinical, hormonal (laboratory) and imaging data-based ML models for CPP remains elusive. The aim of this study was to investigate the diagnostic value of ML models based on clinical, hormonal (laboratory) and imaging data for CPP through a meta-analysis of existing studies. Methods: We conducted a comprehensive search for relevant English articles on clinical, hormonal (laboratory) and imaging data-based ML models for diagnosing CPP, covering the period from the database creation date to December 2023. Pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve, and area under the curve (AUC) were calculated to assess the diagnostic value of clinical, hormonal (laboratory) and imaging data-based ML models for diagnosing CPP. The I2 test was employed to evaluate heterogeneity, and the source of heterogeneity was investigated through meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test. Results: Six studies met the eligibility criteria. The pooled sensitivity and specificity were 0.82 (95% confidence interval (CI) 0.62-0.93) and 0.85 (95% CI 0.80-0.90), respectively. The LR+ was 6.00, and the LR- was 0.21, indicating that clinical, hormonal (laboratory) and imaging data-based ML models exhibited an excellent ability to confirm or exclude CPP. Additionally, the SROC curve showed that the AUC of the clinical, hormonal (laboratory) and imaging data-based ML models in the diagnosis of CPP was 0.90 (95% CI 0.87-0.92), demonstrating good diagnostic value for CPP. Conclusion: Based on the outcomes of our meta-analysis, clinical and imaging data-based ML models are excellent diagnostic tools with high sensitivity, specificity, and AUC in the diagnosis of CPP. Despite the geographical limitations of the study findings, future research endeavors will strive to address these issues to enhance their applicability and reliability, providing more precise guidance for the differentiation and treatment of CPP.

CT Cadaveric dataset for Radiomics features stability assessment in lumbar vertebrae.

Radiomics features (RFs) studies have showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. The provided CadAIver dataset has the aims of evaluating how CT scanner parameters effect radiomics features on cadaveric donor. The dataset comprises 112 unique CT acquisitions of a cadaveric truck acquired on 3 different CT scanners varying KV, mA, field-of-view, and reconstruction kernel settings. Technical validation of the CadAIver dataset comprises a comprehensive univariate and multivariate GLM approach to assess stability of each RFs extracted from lumbar vertebrae. The complete dataset is publicly available to be applied for future research in the RFs field, and could foster the creation of a collaborative open CT image database to increase the sample size, the range of available scanners, and the available body districts.

Reliability of thoracolumbar burst fracture classification in the Swedish Fracture Register.

BACKGROUND: The Swedish Fracture Register (SFR) is a national quality register for all types of fractures in Sweden. Spine fractures have been included since 2015 and are classified using a modified AOSpine classification. The aim of this study was to determine the accuracy of the classification of thoracolumbar burst fractures in the SFR. METHODS: Assessments of medical images were conducted in 277 consecutive patients with a thoracolumbar burst fracture (T10-L3) identified in the SFR. Two independent reviewers classified the fractures according to the AOSpine classification, with a third reviewer resolving disagreement. The combined results of the reviewers were considered the gold standard. The intra- and inter-rater reliability of the reviewers was determined with Cohen's kappa and percent agreement. The SFR classification was compared with the gold standard using positive predictive values (PPV), Cohen's kappa and percent agreement. RESULTS: The reliability between reviewers was  high (Cohen's kappa 0.70-0.97). The PPV for correctly classifying burst fractures in the SFR was high irrespective of physician experience (76-89%), treatment (82% non-operative, 95% operative) and hospital type (83% county, 95% university). The inter-rater reliability of B-type injuries and the overall SFR classification compared with the gold standard was low (Cohen's kappa 0.16 and 0.17 respectively). CONCLUSIONS: The SFR demonstrates a high PPV for accurately classifying burst fractures, regardless of physician experience, treatment and hospital type. However, the reliability of B-type injuries and overall classification in the SFR was found to be low. Future studies on burst fractures using SFR data where classification is important should include a review of medical images to verify the diagnosis.

A novel dual-channel cassava starch/polyvinyl alcohol-based film for visual monitoring of shrimp freshness.

In this study, the polyvinylpyrrolidone-alizarin nanoparticles (PVP-AZ NPs) with favorable water dispersion and the carbon quantum dots (RQDs) with aggregate induced emission effect were synthesized to construct an eco-friendly film for food freshness monitoring. The introduction of PVP-AZ NPs and RQDs enhanced the network structure and thermal stability of the cassava starch/polyvinyl alcohol film, and reduced its crystallinity and light transmittance via non-covalent binding with the film-forming matrix. The developed film exhibited visually recognizable colorimetric and fluorescent responses to ammonia at 0.025-25 mg/mL, and it can be reused at least 6 times. Practical application experiment proved that the film, as an indicator label, can achieve accurate, real-time, and visual dynamic monitoring of the freshness of shrimp stored at 25 °C, 4 °C, and - 20 °C under daylight (orange yellow to purple) and UV light (red to blue). The integration of multivariate detection technology can eliminate the interference of external factors by self-correction to improve sensitivity and reliability, which provides a reference for the development of other food quality and safety monitoring platforms.

Intravoxel incoherent motion (IVIM)-derived perfusion fraction mapping for the visual evaluation of MR-guided high intensity focused ultrasound (MR-HIFU) ablation of uterine fibroids.

BACKGROUND: A method for periprocedural contrast agent-free visualization of uterine fibroid perfusion could potentially shorten magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) treatment times and improve outcomes. Our goal was to test feasibility of perfusion fraction mapping by intravoxel incoherent motion (IVIM) modeling using diffusion-weighted MRI as method for visual evaluation of MR-HIFU treatment progression. METHODS: Conventional and T2-corrected IVIM-derived perfusion fraction maps were retrospectively calculated by applying two fitting methods to diffusion-weighted MRI data (b = 0, 50, 100, 200, 400, 600 and 800 s/mm2 at 1.5 T) from forty-four premenopausal women who underwent MR-HIFU ablation treatment of uterine fibroids. Contrast in perfusion fraction maps between areas with low perfusion fraction and surrounding tissue in the target uterine fibroid immediately following MR-HIFU treatment was evaluated. Additionally, the Dice similarity coefficient (DSC) was calculated between delineated areas with low IVIM-derived perfusion fraction and hypoperfusion based on CE-T1w. RESULTS: Average perfusion fraction ranged between 0.068 and 0.083 in areas with low perfusion fraction based on visual assessment, and between 0.256 and 0.335 in surrounding tissues (all p < 0.001). DSCs ranged from 0.714 to 0.734 between areas with low perfusion fraction and the CE-T1w derived non-perfused areas, with excellent intraobserver reliability of the delineated areas (ICC 0.97). CONCLUSION: The MR-HIFU treatment effect in uterine fibroids can be visualized using IVIM perfusion fraction mapping, in moderate concordance with contrast enhanced MRI. IVIM perfusion fraction mapping has therefore the potential to serve as a contrast agent-free imaging method to visualize the MR-HIFU treatment progression in uterine fibroids.

Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants.

Background: Scalp-related symptoms such as dandruff and itching are common with diverse underlying etiologies. We previously proposed a novel classification and scoring system for scalp conditions, called the scalp photographic index (SPI); it grades five scalp features using trichoscopic images with good reliability. However, it requires trained evaluators.Aim: To develop artificial intelligence (AI) algorithms for assessment of scalp conditions and to assess the feasibility of AI-based recommendations on personalized scalp cosmetics.Methods: Using EfficientNet, convolutional neural network (CNN) models (SPI-AI) ofeach scalp feature were established. 101,027 magnified scalp images graded according to the SPI scoring were used for training, validation, and testing the model Adults with scalp discomfort were prescribed shampoos and scalp serums personalized according to their SPI-AI-defined scalp types. Using the SPI, the scalp conditions were evaluated at baseline and at weeks 4, 8, and 12 of treatment.Results: The accuracies of the SPI-AI for dryness, oiliness, erythema, folliculitis, and dandruff were 91.3%, 90.5%, 89.6%, 87.3%, and 95.2%, respectively. Overall, 100 individuals completed the 4-week study; 43 of these participated in an extension study until week 12. The total SPI score decreased from 32.70 ± 7.40 at baseline to 15.97 ± 4.68 at week 4 (p < 0.001). The efficacy was maintained throughout 12 weeks.Conclusions: SPI-AI accurately assessed the scalp condition. AI-based prescription of tailored scalp cosmetics could significantly improve scalp health.

Establishment of an Animal Model of Dog Bite Injuries.

Nowadays dog bite is becoming a world public health problem. Therefore, the study aimed to develop a dog bite animal model that is helpful to solve these problems. In this study, the skull of an adult dog was scanned. The three-dimensional model of the dog maxillofacial bones and dentition was built by MIMICS. Next, the model was printed with Co-Cr alloy by using selective laser sintering technology to develop the dog bite simulation pliers. Then, to simulate dog bite to most, the maximum bite force of the pliers was measured and actions contained in dog bite process was analyzed. Afterwards, according to action analysis results, rabbits were bitten by the prepared instrument in actions that simulate dog's bite. Finally, the reproducibility and controllability of this animal model of dog bite injuries was validated in an in vivo study. The results showed a reliable animal model of dog bite injuries has been developed in this study. The sites and severities of the injuries could be adjusted as the operator wishes and the animal model of dog bite injuries was highly repeatable. This study also indicates the feasibility of using digital technology in establishing animal bite models.

Assessing the quality and reliability of YouTube videos as a source of information on inflammatory back pain.

Background: Inflammatory back pain is a chronic condition with localized pain, particularly in the axial spine and sacroiliac joints, that is associated with morning stiffness and improves with exercise. YouTube is the second most frequently used social media platform for accessing health information. This study sought to investigate the quality and reliability of YouTube videos on inflammatory back pain (IBP). Methods: The study design was planned as cross-sectional. A search was conducted using the term "inflammatory back pain," and the first 100 videos that met the inclusion criteria were selected on October 19, 2023. The data of the videos selected according to the inclusion and exclusion criteria in the study settings were examined. Videos with English language, with audiovisual content , had a duration >30 s, non-duplicated and primary content related to IBP were included in the study. A number of video parameters such as the number of likes, number of views, duration, and content categories were assessed. The videos were assessed for reliability using the Journal of the American Medical Association (JAMA) Benchmark criteria and the DISCERN tool. Quality was assessed using the Global Quality Score (GQS). Continuous variables were checked for normality of distribution using Shapiro-Wilk test and Kolmogorov-Smirnov test. Kruskal-Wallis test and Mann-Whitney U test were used to analyze the continuous data depending on the number of groups. Categorical data were analyzed using Pearson's chi-square test. Results: Reliability assessment based on JAMA scores showed 21% of the videos to have high reliability. Quality assessment based on GQS results showed 19% of the videos to have high quality. JAMA, DISCERN, and GQS scores differed significantly by source of video (p < 0.001, < 0.001, and = 0.002, respectively). Video duration had a moderate positive correlation with scores from the GQS (r = 0.418, p < 0.001), JAMA (r = 0.484, p < 0.001), and modified DISCERN (r = 0.418, p < 0.001). Conclusion: The results of the present study showed that YouTube offers videos of low reliability and low quality on inflammatory back pain. Health authorities have a responsibility to protect public health and should take proactive steps regarding health information shared on social media platforms.

Artificial Intelligence in Cataract Surgery: A Systematic Review.

Purpose: The purpose of this study was to assess the current use and reliability of artificial intelligence (AI)-based algorithms for analyzing cataract surgery videos. Methods: A systematic review of the literature about intra-operative analysis of cataract surgery videos with machine learning techniques was performed. Cataract diagnosis and detection algorithms were excluded. Resulting algorithms were compared, descriptively analyzed, and metrics summarized or visually reported. The reproducibility and reliability of the methods and results were assessed using a modified version of the Medical Image Computing and Computer-Assisted (MICCAI) checklist. Results: Thirty-eight of the 550 screened studies were included, 20 addressed the challenge of instrument detection or tracking, 9 focused on phase discrimination, and 8 predicted skill and complications. Instrument detection achieves an area under the receiver operator characteristic curve (ROC AUC) between 0.976 and 0.998, instrument tracking an mAP between 0.685 and 0.929, phase recognition an ROC AUC between 0.773 and 0.990, and complications or surgical skill performs with an ROC AUC between 0.570 and 0.970. Conclusions: The studies showed a wide variation in quality and pose a challenge regarding replication due to a small number of public datasets (none for manual small incision cataract surgery) and seldom published source code. There is no standard for reported outcome metrics and validation of the models on external datasets is rare making comparisons difficult. The data suggests that tracking of instruments and phase detection work well but surgical skill and complication recognition remains a challenge for deep learning. Translational Relevance: This overview of cataract surgery analysis with AI models provides translational value for improving training of the clinician by identifying successes and challenges.

Unilateral Sacral Erector Spinae Plane Block for Thigh Amputation: Case Report.

Selection of anesthetic technique for thigh amputation is complicated by patients' comorbid conditions. The sacral erector spinae plane block (ESPB) is an emerging technique with potential as a primary anesthetic for thigh amputation. We detail a case involving a 79-year-old undergoing thigh amputation, where sacral ESPB proved insufficient, prompting a shift to spinal anesthesia. This instance underscores the necessity for further investigation into the reliability of the sacral ESPB for lower limb surgeries. Until such evidence is established, caution is advised in relying solely on the sacral ESPB for thigh amputations, and consideration of alternative techniques is recommended.

Rapid Detection of Bacterial Pathogens Causing Lower Respiratory Tract Infections via Microfluidic-Chip-Based Loop-Mediated Isothermal Amplification.

Respiratory tract infections (RTIs) are among the most common problems in clinical settings. Rapid and accurate identification of bacterial pathogens will provide practical guidelines for managing and treating RTIs. This study describes a method for rapidly detecting bacterial pathogens that cause respiratory tract infections via multi-channel loop-mediated isothermal amplification (LAMP). LAMP is a sensitive and specific diagnostic tool that rapidly detects bacterial nucleic acids with high accuracy and reliability. The proposed method offers a significant advantage over traditional bacterial culturing methods, which are time-consuming and often require greater sensitivity for detecting low levels of bacterial nucleic acids. This article presents representative results of K. pneumoniae infection and its multiple co-infections using LAMP to detect samples (sputum, bronchial lavage fluid, and alveolar lavage fluid) from the lower respiratory tract. In summary, the multi-channel LAMP method provides a rapid and efficient means of identifying single and multiple bacterial pathogens in clinical samples, which can help prevent the spread of bacterial pathogens and aid in the appropriate treatment of RTIs.

Reliability and measurement error of exercise-induced hypoalgesia in pain-free adults and adults with musculoskeletal pain: A systematic review.

OBJECTIVES: We systematically reviewed the reliability and measurement error of exercise-induced hypoalgesia (EIH) in pain-free adults and in adults with musculoskeletal (MSK) pain. METHODS: We searched EMBASE, PUBMED, SCOPUS, CINAHL, and PSYCINFO from inception to November 2021 (updated in February 2024). In addition, manual searches of the grey literature were conducted in March 2022, September 2023, and February 2024. The inclusion criteria were as follows: adults - pain-free and with MSK pain - a single bout of exercise (any type) combined with experimental pre-post pain tests, and assessment of the reliability and/or measurement error of EIH. Two independent reviewers selected the studies, assessed their Risk of Bias (RoB) with the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) RoB tool, and graded the individual results (COSMIN modified Grading of Recommendations Assessment, Development, and Evaluation). RESULTS: We included five studies involving pain-free individuals (n = 168), which were deemed to have an overall "doubtful" RoB. No study including adults with MSK pain was found. The following ranges of parameters of reliability and measurement error of EIH were reported: intraclass correlation coefficients: 0-0.61; kappa: 0.01-0.46; standard error of measurement: 30.1-105 kPa and 10.4-21%; smallest detectable changes: 83.54-291.1 kPa and 28.83-58.21%. CONCLUSIONS: We concluded, with a very low level of certainty, that the reliability and measurement error of EIH is, in pain-free adults, respectively, "insufficient" and "indeterminate." Future studies should focus on people with MSK pain and could consider using tailored exercises, other test modalities than pressure pain threshold, rater/assessor blinding, and strict control of the sources of variations (e.g., participants' expectations).

Integrating bulk and single-cell sequencing data to construct a Scissor+ dendritic cells prognostic model for predicting prognosis and immune responses in ESCC.

Esophageal squamous cell carcinoma (ESCC) is characterized by molecular heterogeneity with various immune cell infiltration patterns, which have been associated with therapeutic sensitivity and resistance. In particular, dendritic cells (DCs) are recently discovered to be associated with prognosis and survival in cancer. However, how DCs differ among ESCC patients has not been fully comprehended. Recently, the advance of single-cell RNA sequencing (scRNA-seq) enables us to profile the cell types, states, and lineages in the heterogeneous ESCC tissues. Here, we dissect the ESCC tumor microenvironment at high resolution by integrating 192,078 single cells from 60 patients, including 4379 DCs. We then used Scissor, a method that identifies cell subpopulations from single-cell data that are associated bulk samples with genomic and clinical information, to stratify DCs into Scissorhi and Scissorlow subtypes. We applied the Scissorhi gene signature to stratify ESCC scRNAseq patient, and we found that PD-L1, TIGIT, PVR and IL6 ligand-receptor-mediated cell interactions existed mainly in Scissorhi patients. Finally, based on the Scissor results, we successfully developed a validated prognostic risk model for ESCC and further validated the reliability of the risk prediction model by recruiting 40 ESCC clinical patients. This information highlights the importance of these genes in assessing patient prognosis and may help in the development of targeted or personalized therapies for ESCC.

A new classification for surgical NEC during exploratory laparotomy: introduction and reproducibility assessment.

PURPOSE: Variability in necrosis patterns and operative techniques in surgical necrotizing enterocolitis (NEC) necessitates a standardized classification system for consistent assessment and comparison. This study introduces a novel intraoperative reporting system for surgical NEC, focusing on reliability and reproducibility. METHODS: Analyzing surgical NEC cases from January 2018 to June 2023 at two tertiary neonatal and pediatric surgery units, a new classification system incorporating anatomical details and intestinal involvement extent was developed. Its reproducibility was quantified using kappa coefficients (κ) for interobserver and intraobserver reliability, assessed by four specialists. Furthermore, following surgery, the occurrence of mortality and enteric autonomy were evaluated on the basis of surgical decision-making of the novel intraoperative classification system for surgical NEC. RESULTS: In total, 95 patients with surgical NEC were included in this analysis. The mean κ value of the intra-observer reliability was 0.889 (range, 0.790-0.941) for the new classification, indicating excellent agreement and the inter-observer reliability was 0.806 (range, 0.718-0.883), indicating substantial agreement. CONCLUSION: The introduced classification system for surgical NEC shows high reliability, deepening the understanding of NEC's intraoperative exploration aspects. It promises to indicate operative strategies, enhance prognosis prediction, and substantially facilitate scholarly communication in pediatric surgery. Importantly, it explores the potential for a standardized report and may represent a step forward in classifying surgical NEC, if pediatric surgeons are open to change.

The development, evaluation, performance, and validation of micro-PCR and extractor for the quantification of HIV-1 &-2 RNA.

HIV infection has been a global public health threat and overall reported ~ 40 million deaths. Acquired immunodeficiency syndrome (AIDS) is attributed to the retroviruses (HIV-1/2), disseminated through various body fluids. The temporal progression of AIDS is in context to the rate of HIV-1 infection, which is twice as protracted in HIV-2 transmission. Q-PCR is the only available method that requires a well-developed lab infrastructure and trained personnel. Micro-PCR, a portable Q-PCR device, was developed by Bigtec Labs, Bangalore, India. It is simple, accurate, fast, and operationalised in remote places where diagnostic services are inaccessible in developing countries. This novel micro-PCR determines HIV-1 and HIV-2 viral load using a TruePrep™ extractor device for RNA isolation. Five ml blood samples were collected at the blood collection centre at AIIMS, New Delhi, India. Samples were screened for serology, and a comparison of HIV-1/2 RNA was done between qPCR and micro-PCR in the samples. The micro-PCR assay of HIV-RNA has compared well with those from real-time PCR (r = 0.99, i < 0.002). Micro-PCR has good inter and intra-assay reproducibility over a wide dynamic range (1.0 × 102-1.0 × 108 IU/ml). The linear dynamic range was 102-108 IU/ml. The clinical and analytical specificity of the assay was comparable, i.e., 100%. Intra-assay and inter-assay coefficients of variation ranged from 1.17% to 3.15% and from 0.02% to 0.46%, respectively. Moreover, due to the robust, simple, and empirical method, the Probit analysis has also been done for qPCR LODs to avoid uncertainties in target recoveries. The micro-PCR is reliable, accurate, and reproducible for early detection of HIV-1 and HIV-2 viral loads simultaneously. Thus, it can easily be used in the field and in remote places where quantification of both HIV-1/2 is not reachable.

Adverse childhood experiences among black sexually minoritized men and Black transgender women in Chicago.

BACKGROUND: Adverse childhood experiences (ACE) are important predictors of mental health outcomes in adulthood. However, commonly used ACE measures such as the Behavioural Risk Factor Surveillance System (BRFSS) have not been validated among Black sexually minoritized men (SMM) nor transgender women (TW), whom are known to have higher rates of ACE and poorer mental health outcomes. Assessing the psychometric properties of the measure is important for health equity research, as measurements that are not valid for some populations will render uninterpretable results. METHODS: Data are drawn from the Neighborhoods and Networks (N2) study, a longitudinal cohort of Black SMM and TW living in Southern Chicago. We conducted confirmatory factor analysis, correlation analysis and a two-parameter Item Response Theory (IRT) on the BRFSS ACE measure, an 11-item measure with 8 domains of ACE. RESULTS: One hundred forty seven participants (85% cisgender male) completed the BRFSS ACE measurement in the N2 study with age ranges from 16-34. The cohort were from a low socioeconomic background: about 40% of the cohort were housing insecure and made than $10,000 or less annually. They also have a high number of ACEs; 34% had endorsed 4 or more ACE domains. The three-factor structure fit the BRFSS ACE measure best; the measurement consisted of three subscales: of "Household Dysfunction", "Emotional / Physical", and "Sexual Abuse" (CFI = 0.975, TLI = 0.967, and RMSEA = 0.051). When the 8 domains of ACE were summed to one score, the total score was is correlated with depressive symptoms and anxiety scores, establishing concurrent validity. Item Response Theory model indicated that the "parental separation" domain had a low discrimination (slope) parameter, suggesting that this domain does not distinguish well between those with and without high ACE. CONCLUSIONS: The BRFFS ACE measure had adequate reliability, a well-replicated structure and some moderate evidence of concurrent validity among Black SMM and TW. The parental separation domain does not discriminate between those with high and low ACE experiences in this population. With changing population demographics and trends in marriage, further examination of this item beyond the current study is warranted to improve health equity research for all.

Comparison of the Predictive Validity of Norton and Braden Scales in Determining the Risk of Pressure Injury in Elderly Patients.

AIM: To compare the reliability and predictive validity of Norton and Braden scales in determining the risk of pressure injury in elderly patients. DESIGN: This research used a comparative design. One hundred thirty elderly patients participated in the study. METHODS: The daily pressure injury risk of participants was evaluated by a researcher using both the Norton and Braden scales in a consecutive manner. RESULTS: The mean age of patients was 75.1 ± 8.5 years, and that for those without and with pressure injury development was 75.0 ± 8.3 years and 76.1 ± 9.7 years (P < .001), respectively. The reliability coefficients of the Norton and Braden scales were .82 and .89, respectively. The sensitivity, specificity, and positive and negative predictive values of the Norton Scale were 100%, 40.7%, 20.2%, and 100%, and those of the Braden Scale were 100%, 32.7%, 18.3%, and 100%, respectively. CONCLUSIONS: The reliability of both scales for elderly patients was found to be high, and their ability to differentiate patients at risk was comparable. However, both scales had low specificity. Further research is needed to develop scales that have higher predictive validity for the elderly population, taking into account other risk factors that influence total scale scores.

Assessing Laboratory Method Validations for Informing Inference Across Survey Cycles in the National Health and Nutrition Examination Survey.

Background and objectives Laboratory tests conducted on survey respondents' biological specimens are a major component of the National Health and Nutrition Examination Survey. The National Center for Health Statistics' Division of Health and Nutrition Examination Surveys performs internal analytic method validation studies whenever laboratories undergo instrumental or methodological changes, or when contract laboratories change. These studies assess agreement between methods to evaluate how methodological changes could affect data inference or compromise consistency of measurements across survey cycles. When systematic differences between methods are observed, adjustment equations are released with the data documentation for analysts planning to combine survey cycles or conduct a trend analysis. Adjustment equations help ensure that observed differences from methodological changes are not misinterpreted as population changes. This report assesses the reliability of statistical methods used by the Division of Health and Nutrition Examination Surveys when conducting method validation studies to address concerns that adjustment equations are being overproduced (recommended too frequently). Methods Public-use 2017-2018 National Health and Nutrition Examination Survey laboratory data were used to simulate "new" measurements for 120 analytic method validation studies. Blinded studies were analyzed to determine the final adjustment recommendation for each study using difference plots, descriptive statistics, t-tests, and Deming regressions. Final recommendations were compared with simulated difference types to assess how often spurious results were observed. Concordance estimates (concordance, misclassification, sensitivity, specificity, and positive and negative predictive values) informed assessments. Results Adjustment equations were appropriately recommended for 75.0% of the studies, over-recommended for 5.8%, under-recommended for 15.8%, and recommended with an inappropriate technique for 3.3%. Across simulated difference types, sensitivity ranged from 65.9% to 84.4% and specificity from 74.7% to 97.5%. Conclusions Findings from this report suggest that the current methodology used by the Division of Health and Nutrition Examination Surveys performs moderately well. Based on these data and analyses, underadjustment was more prevalent than overadjustment, suggesting that the current methodology is conservative.

Development of a scale to gain insight into the experience of living with chronic heart failure: The UNAV-Experience of Living with Chronic Heart Failure Scale.

BACKGROUND: To date, there are no tools for the nursing staff to gain systematic insight on the experience lived by patients with chronic heart failure. The objective of this study was to develop a scale for this purpose. METHODS: The study was conducted between January 2018 and December 2020 in three Spanish hospitals. The process described by DeVellis was used for the development of the scale. The items were built based on a phenomenological study and a systematic review of the literature. Next, feedback from a panel of experts was obtained, the scale was administered to a sample of patients with chronic heart failure, and a cognitive interview and an observational study were conducted to create the final version of the scale. RESULTS: The first version of the scale had in seven domains and 76 items. After its evaluation by a panel of experts, it was reduced to a second version with six domains and 55 items. Following the administration of Version 2 to 17 patients (58.8% male, mean age 59.53, 70.6% classified as NYHA functional class II), five items were modified and two eliminated. Thus, the third version of the UNAV-CHF Experience Scale was composed of six domains and 53 items. CONCLUSIONS: This study presents the development of the UNAV-experience of living with chronic heart failure scale. It is an original and novel instrument that allows systematically explore this experience. A larger-scale study is necessary to confirm the validity of our scale.

Graphene quantum dots on TiO2 nanotubes as a light-assisted peroxidase nanozyme.

Hybrid nanozyme graphene quantum dots (GQDs) deposited TiO2 nanotubes (NTs) on titanium foil (Ti/TiO2 NTs-GQDs) were manufactured by bestowing the hybrid with the advantageous porous morphology, surface valence states, high surface area, and copious active sites. The peroxidase-like activity was investigated through the catalytic oxidation of chromogenic substrate 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of H2O2, which can be visualized by the eyes. TiO2 NTs and GQDs comprising oxygen-containing functional groups can oxidize TMB in the presence of H2O2 by mimicking peroxidase enzymes. The peroxidase-mimicking activity of hybrid nanozyme was significantly escalated by introducing light illumination due to the photosensitive features of the hybrid material. The peroxidase-like activity of Ti/TiO2 NTs-GQDs enabled H2O2 determination over the linear range of 7 to 250 µM, with a LOD of 2.1 µM. The satisfying peroxidase activity is possibly due to the unimpeded access of H2O2 to the catalyst's active sites. The porous morphology provides the easy channeling of reactants and products. The periodic structure of the material also gave rise to acceptable reproducibility. Without material functionalization, the Ti/TiO2 NTs-GQDs can be a promising substitute for peroxidases for H2O2 detection.