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Extrathyroidal extension was related with worse survival for patients with papillary thyroid carcinoma. For its preoperative evaluation, we measured and compared the predicting value of sonographic method and ultrasonic radiomics method in nodules of papillary thyroid carcinoma. Data from 337 nodules were included and divided into training group and validation group. For ultrasonic radiomics method, a best model was constructed based on clinical characteristics and ultrasonic radiomic features. The predicting value was calculated then. For sonographic method, the results were calculated using all samples. For ultrasonic radiomics method, we constructed 9 models and selected the extreme gradient boosting model for its highest accuracy (0.77) and area under curve (0.813) in validation group. The accuracy and area under curve of sonographic method was 0.70 and 0.569. Meanwhile. We found that the top-6 important features of xgboost model included no clinical characteristics, all of whom were high-dimensional radiomic features. The study showed the superior value of ultrasonic radiomics method to sonographic method for preoperative detection of extrathyroidal extension in papillary thyroid carcinoma. Furthermore, high-dimensional radiomic features were more important than clinical characteristics. [ABSTRACT FROM AUTHOR]

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This article discusses the impact of artificial intelligence (AI) on the healthcare insurance industry. It highlights how AI is changing various aspects of healthcare insurance, including claims processing, personalized premiums, risk assessment, fraud detection, and underwriting. The integration of AI in these operations improves efficiency, reduces costs, and enhances patient care. However, there are concerns about data privacy, bias in AI algorithms, and transparency. The article emphasizes the need for strong data protection measures, transparency in AI usage, diverse team involvement, and evolving regulations. The future of AI in healthcare insurance is expected to bring more advanced predictive models, real-time insights, and personalized interventions. [Extracted from the article]

Aim: Geriatric patients are increasingly dominating the daily routine in emergency department (ED). The atypical clinical presentation of disease, multimorbidity, frailty and cognitive impairment of geriatric patients pose particular challenges for triage in the ED. Efficient and accurate emergency triage plays a key role in differentiating between geriatric patients who need timely treatment and those who can wait safely. The purpose of this study was to evaluate the performance of the modified Manchester Triage System (mMTS) in classifying geriatric patients. Design: An observational retrospective study. Methods: A retrospective study of 18,796 geriatric patients (≥65 years) attending the ED of a tertiary care hospital in Zhejiang province between 1 June 2020 and 30 June 2022. Baseline information on patients was collected and divided into two different study groups according to triage level: high priority (red/orange) and low priority (yellow/green). The sensitivity and specificity of the mMTS were estimated by verifying the triage classification received by the emergency geriatric patients and their survival at 7 days or the need for acute surgery within 72 h. Results: The study included a total of 17,764 geriatric patients with a median age of 72 years in ED. 10.7% (1896/17,764) of the geriatric patients were assigned to the high priority code group (red/orange) and 89.3% (15,868/17,764) were in the low priority code group (yellow/green). The sensitivity of the mMTS associated with death within 7 days was 85.7% (77.5–91.4), specificity was 89.8% (89.3–90.2), and accuracy was 89.8% (89.3–90.2). 1.8% of patients required surgery within 72 h. The sensitivity was 62.6% (57.0–67.9), specificity was 90.3% (89.8–90.7), and negative predictive value was 99.2% (99.0–99.4). Conclusions: The mMTS has good specificity, accuracy and negative predictive value for geriatric patients. However, its incorrect prediction of triage in high‐priority code patients results in lower sensitivity, which may serve as a protective strategy for these individuals. The current emergency triage system does not completely screen geriatric patients with severe acute illness who present to the ED, and it is necessary to add comprehensive assessment tools that match the characteristics of geriatric patients to improve triage outcomes. [ABSTRACT FROM AUTHOR]

When accidents occur, employees rely on the workers' compensation system to provide continuing wages and medical benefits. This study addresses a fundamental workers' compensation gap—the lack of an Employee Workers' Compensation Experience (EWCE) scale. While current metrics monitor direct costs, they often overlook the psycho-social impacts on employees. The study introduces a structured EWCE scale that encompasses dimensions of claim communication, psychological and emotional impacts, and uncertainty regarding the claim outcome. The EWCE scales relevance is emphasized by its ability to predict turnover intentions, burnout, and obligations to come to work sick outcomes. Discriminate, convergent, and predictive validity tests corroborate the scales' effectiveness. These findings allow employers, policymakers, and researchers to create a safer, more inclusive work environment by measuring and monitoring workers' compensation claim outcomes. This scale bridges the critical knowledge gap and offers an analytical tool to enhance workers' compensation policies and outcomes. [ABSTRACT FROM AUTHOR]

Introduction: A dynamic molecular biomarker that can identify early efficacy of immune checkpoint inhibitor (ICI) therapy remains an unmet clinical need. Here we evaluate if a novel circulating tumor DNA (ctDNA) assay, xM, used for treatment response monitoring (TRM), that quantifies changes in ctDNA tumor fraction (TF), can predict outcome benefits in patients treated with ICI alone or in combination with chemotherapy in a real-world (RW) cohort. Methods: This retrospective study consisted of patients with advanced cancer from the Tempus de-identified clinical genomic database who received longitudinal liquid-based next-generation sequencing. Eligible patients had a blood sample ≤ 40 days prior to the start of ICI initiation and an on-treatment blood sample 15–180 days post ICI initiation. TF was calculated via an ensemble algorithm that utilizes TF estimates derived from variants and copy number information. Patients with molecular response (MR) were defined as patients with a ≥ 50% decrease in TF between tests. In the subset of patients with rw-imaging data between 2 and 18 weeks of ICI initiation, the predictive value of MR in addition to rw-imaging was compared to a model of rw-imaging alone. Results: The evaluable cohort (N = 86) was composed of 14 solid cancer types. Patients received either ICI monotherapy (38.4%, N = 33) or ICI in combination with chemotherapy (61.6%, N = 53). Patients with MR had significantly longer rw-overall survival (rwOS) (hazard ratio (HR) 0.4, P = 0.004) and rw-progression free survival (rwPFS) (HR 0.4, P = 0.005) than patients with molecular non-response (nMR). Similar results were seen in the ICI monotherapy subcohort; HR 0.2, P = 0.02 for rwOS and HR 0.2, P = 0.01 for rwPFS. In the subset of patients with matched rw-imaging data (N = 51), a model incorporating both MR and rw-imaging was superior in predicting rwOS than rw-imaging alone (P = 0.02). Conclusions: xM used for TRM is a novel serial quantitative TF algorithm that can be used clinically to evaluate ICI therapy efficacy. [ABSTRACT FROM AUTHOR]

The article discusses a study by J. R. González and colleagues which examined the predictive value of Global-Positioning-System and multiomics data for noncontract injury occurrence in 24 female football players. Topics include finding on prognostic models developed with inadequate sample size and result of design analyses of any effect observed for the rate alleles of the target polymorphisms.

Aim: To investigate predicting factors for physical frailty development at hospital discharge in older patients admitted to the intensive care unit (ICU). Methods: This case–control study focused on ICU-admitted patients aged ≥ 65 years. This study assessed several independent variables, including functional status score for the ICU, Medical Research Council (MRC) sum score, and handgrip strength at ICU discharge. Physical frailty was the primary outcome of this study. Results: In total, 61 participants were included: 29 in the non-frailty group and 32 in the frailty group. Logistic regression analysis was used to extract only the MRC sum score at ICU discharge, with a cutoff score of 46 to predict physical frailty onset at hospital discharge. The functional status score for the ICU and handgrip strength were not extracted. Conclusions: An MRC sum score ≤46 at hospital discharge can predict physical frailty in critically ill older patients admitted to the ICU. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to evaluate the diagnostic accuracy (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)) of the PCR-based BioFire® Joint Infection Panel (BJI Panel) against microbiological culture growth for patients suspected of having a native or prosthetic joint infection. Methods: Synovial fluid and tissue biopsies were prospectively collected from patients from June 2022 to June 2023. The results of the BJI Panel were compared with those of culture growth. Results: 51 samples were included. Including all pathogens, the sensitivity was 69%, the specificity 89%, the PPV 73% and the NPV 86%. Including only pathogens in the BJI Panel, the sensitivity was 100%, the specificity 90%, the PPV 73% and the NPV 100%. Conclusion: The BJI Panel has a high accuracy for detecting the pathogens in its panel, but the absence of important common pathogens from the panel reduces its sensitivity and NPV. With a short turnaround time and precise pathogen detection, the BJI Panel has the potential to add value as a complementary diagnostic method. [ABSTRACT FROM AUTHOR]

Purpose: To develop a machine learning model that can predict dental implant failure and peri-implantitis as a tool for maximizing implant success. Materials and Methods: This study used a supervised learning model to retrospectively analyze 398 unique patients receiving a total of 942 dental implants presenting at the Philadelphia Veterans Affairs Medical Center from 2006 to 2013. Logistic regression, random forest classifiers, support vector machines, and ensemble techniques were employed to analyze this dataset. Results: The random forest model possessed the highest predictive performance on test sets, with receiver operating characteristic area under curves (ROC AUC) of 0.872 and 0.840 for dental implant failures and peri-implantitis, respectively. The five most important features correlating with implant failure were amount of local anesthetic, implant length, implant diameter, use of preoperative antibiotics, and frequency of hygiene visits. The five most important features correlating with peri-implantitis were implant length, implant diameter, use of preoperative antibiotics, frequency of hygiene visits, and presence of diabetes mellitus. Conclusion: This study demonstrated the ability of machine learning models to assess demographics, medical history, and surgical plans, as well as the influence of these factors on dental implant failure and peri-implantitis. This model may serve as a resource for clinicians in the treatment of dental implants. [ABSTRACT FROM AUTHOR]

Objective: The relationship between thyrotropin (TSH), free triiodothyronine (FT3), free thyroxine (FT4) and diabetic kidney disease (DKD) is still controversial, and this study analyzed the correlation between TSH, FT3, FT4 and DKD in patients with type 2 diabetes mellitus (T2DM). Methods: T2DM patients (1216) were divided into five groups based on serum TSH, FT3, and FT4 levels, differences in urinary albumin excretion rate (UACR), estimated glomerular filtration rate (eGFR) were compared. Binary logistic regression verified independent correlations among TSH, FT3, FT4 and UACR, eGFR. TSH and FT3 predictive values for DKD were analyzed using receiver operating characteristic (ROC) curves. Results: The prevalence of albuminuria with decreased eGFR was higher in T2DM patients with subclinical hypothyroidism and overt hypothyroidism than that in patients with normal thyroid function. TSH positively correlated with UACR (r = 0.133, p < 0.001) and positively correlated with eGFR (r = -0.218, p < 0.001), FT3 negatively correlated with UACR (r = -0.260, p < 0.001) and positively correlated with eGFR (r = 0.324, p < 0.001). With the change from the lower normal level to the increased level of TSH and the change from the higher normal level to the reduced level of FT3, the prevalence of albuminuria gradually increased, the prevalence of decreased eGFR gradually increased in TSH groups and FT3 groups. After adjusting for age, BMI, duration of diabetes, TPOAb, TGAb, smoking, drinking, hypertension, the use of anti-diabetic medications (metformin, sodium–glucose cotransporter 2 inhibitors), HbA1c, CRP, TC, TG, LDL-C, and HDL-C, both TSH and FT3 correlated with increased UACR (TSH: OR 1.253, p = 0.001; FT3: OR 0.166, p < 0.001) and decreased eGFR (TSH: OR 1.245, p < 0.001, FT3: OR 0.579, p < 0.001), but this correlation of TSH with eGFR < 60 mL/min/1.73 m2 was not found in male. The area under the ROC curve (AUC) for FT3 was greater than that for TSH (FT3: 0.64; TSH: 0.61). Conclusions: Increased TSH and reduced FT3 levels were associated with DKD in T2DM patients, but in a sex-dependent manner. FT3 had a higher predictive value for DKD. [ABSTRACT FROM AUTHOR]

Background: Understanding the relationship of social network use and addictive behaviors with adolescent psychosocial health is crucial in today's digital age. Aim: To verify the associations between social network use, messaging applications, and the addictive behaviors to social network with psychosocial health in Spanish adolescents. Methods: A cross-sectional study was developed with 632 adolescents, aged 12 to 17 years from the Region of Murcia, Spain. The assessment of social network use (Facebook, Twitter, Instagram, Snapchat, and TikTok) involved evaluating the frequency of use of each social network individually using a single-item scale with five response options. WhatsApp use (i.e., a messaging application) was evaluated in the same manner. The Short Social Networks Addiction Scale-6 Symptoms was employed to assess potential addictive behaviors to social network use. The psychosocial health was assessed using the Strengths and Difficulties Questionnaire. Generalized linear regression models were conducted, and predictive probabilities of having psychosocial health problems were calculated. Results: The predicted probability of presenting psychosocial health problems in the medium users and high users of social networks was 19.3% (95% confidence interval [CI] 13.0 to 27.7), and 16.2% (95% CI 10.2 to 24.6) higher compared to low users, respectively. High usage of Instagram, TikTok, Snapchat, and Facebook was associated with increased probabilities of psychosocial health problems, with Facebook showing the highest probabilities, at 31.3% (95% CI 14.8 to 54.2) for medium users and 51.9% (95% CI 26.5 to 76.3) for high users. Additionally, adolescents with addictive behaviors to social network use had from 19.0 to 25.2% probabilities of experiencing psychosocial health problems. Finally, the highest probabilities of having psychosocial health problems were identified in adolescents with high addictive behaviors when using social networks (28.9%; 95% CI 19.3 to 40.8%) and the lowest in those with low addictive behaviors (6.8%; 95% CI 3.3 to 13.6%). Conclusion: Adolescents who use social networks more frequently and exhibit more addictive behaviors related to their use are more likely to experience psychosocial health problems compared to those who do not. Facebook showed the strongest association, followed by Snapchat, Instagram, and TikTok. Our data also revealed that adolescents exhibit various signs of addictive behaviors to social network use. [ABSTRACT FROM AUTHOR]

Background: The CARDOT scores have been developed for prediction of respiratory complications after thoracic surgery. This study aimed to externally validate the CARDOT score and assess the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR) for postoperative respiratory complication. Methods: A retrospective cohort study of consecutive thoracic surgical patients at a single tertiary hospital in northern Thailand was conducted. The development and validation datasets were collected between 2006 and 2012 and from 2015 to 2021, respectively. Six prespecified predictive factors were identified, and formed a predictive score, the CARDOT score (chronic obstructive pulmonary disease, American Society of Anesthesiologists physical status, right-sided operation, duration of surgery, preoperative oxygen saturation on room air, thoracotomy), was calculated. The performance of the CARDOT score was evaluated in terms of discrimination by using the area under the receiver operating characteristic (AuROC) curve and calibration. Results: There were 1086 and 1645 patients included in the development and validation datasets. The incidence of respiratory complications was 15.7% (171 of 1086) and 22.5% (370 of 1645) in the development and validation datasets, respectively. The CARDOT score had good discriminative ability for both the development and validation datasets (AuROC 0.789 (95% CI 0.753–0.827) and 0.758 (95% CI 0.730–0.787), respectively). The CARDOT score showed good calibration in both datasets. A high NLR (≥ 4.5) significantly increased the risk of respiratory complications after thoracic surgery (P < 0.001). The AuROC curve of the validation cohort increased to 0.775 (95% CI 0.750–0.800) when the score was combined with a high NLR. The AuROC of the CARDOT score with the NLR showed significantly greater discrimination power than that of the CARDOT score alone (P = 0.008). Conclusions: The CARDOT score showed a good discriminative performance in the external validation dataset. An addition of a high NLR significantly increases the predictive performance of CARDOT score. The utility of this score is valuable in settings with limited access to preoperative pulmonary function testing. [ABSTRACT FROM AUTHOR]

In this registered report, we propose to stress-test existing models for predicting the ideology-prejudice association, which varies in size and direction across target groups. Previous models of this relationship use the perceived ideology, status, and choice in group membership of target groups to predict the ideology-prejudice association across target groups. These analyses show that models using only the perceived ideology of the target group are more accurate and parsimonious in predicting the ideology-prejudice association than models using perceived status, choice, and all of the characteristics in a single model. Here, we stress-test the original models by testing the models' predictive utility with new measures of explicit prejudice, a comparative operationalization of prejudice, the Implicit Association Test, and additional target groups. In Study 1, we propose to directly test the previous models using an absolute measure of prejudice that closely resembles the measure used in the original study. This will tell us if the models replicate with distinct, yet conceptually similar measures of prejudice. In Study 2, we propose to develop new ideology-prejudice models for a comparative operationalization of prejudice using both explicit measures and the Implicit Association Test. We will then test these new models using data from the Ideology 2.0 project collected by Project Implicit. We do not have full access to this data yet, but upon acceptance of our Stage 1 registered report, we will gain access to the complete dataset. Currently, we have access to an exploratory subset of the data that we use to demonstrate the feasibility of the study, but its limited number of target groups prevents conclusions from being made. [ABSTRACT FROM AUTHOR]

The purpose of this scoping review is to identify and evaluate studies that examine the effectiveness and implementation strategies of Electronic Health Record (EHR)-integrated digital technologies aimed at improving medication-related outcomes and promoting health equity among hospitalised adults. Using the Consolidated Framework for Implementation Research (CFIR), the implementation methods and outcomes of the studies were evaluated, as was the assessment of methodological quality and risk of bias. Searches through Medline, Embase, Web of Science, and CINAHL Plus yielded 23 relevant studies from 1,232 abstracts, spanning 11 countries and from 2008 to 2022, with varied research designs. Integrated digital tools such as alert systems, clinical decision support systems, predictive analytics, risk assessment, and real-time screening and surveillance within EHRs demonstrated potential in reducing medication errors, adverse events, and inappropriate medication use, particularly in older patients. Challenges include alert fatigue, clinician acceptance, workflow integration, cost, data integrity, interoperability, and the potential for algorithmic bias, with a call for long-term and ongoing monitoring of patient safety and health equity outcomes. This review, guided by the CFIR framework, highlights the importance of designing health technology based on evidence and user-centred practices. Quality assessments identified eligibility and representativeness issues that affected the reliability and generalisability of the findings. This review also highlights a critical research gap on whether EHR-integrated digital tools can address or worsen health inequities among hospitalised patients. Recognising the growing role of Artificial Intelligence (AI) and Machine Learning (ML), this review calls for further research on its influence on medication management and health equity through integration of EHR and digital technology. [ABSTRACT FROM AUTHOR]

Background: Deep vein thrombosis (DVT) of lower extremity is a common complications after total knee arthroplasty (TKA). The purpose of this study was to evaluate the risk factors for DVT after TKA and analyze the expression of miR-199b-5p and nitric oxide (NO) before and after TKA, as well as their predictive value for DVT. Methods: Basic clinical information of 121 patients with TKA was analyzed retrospectively. RT-qPCR was used to detect the relative expression level of miR-199b-5p in patients before and after TKA treatment. Based on the occurrence of DVT, patients were divided into DVT and non-DVT groups. Logistic regression analysis evaluated the risk factors of DVT. The receiver operating characteristic (ROC) curve assessed the predictive value of postoperative miR-199b-5p level, preoperative NO level, and their combination in DVT. The target genes of miR-199b-5p and their functions were predicted and annotated using bioinformatics analysis. Results: The level of miR-199b-5p after TKA was upregulated compared with that before TKA (P < 0.001). DVT occurred in 20 of 121 patients after TKA, with an incidence of 16.53%. Multivariate analysis showed that age, family history of DVT, decrease of NO and increase of miR-199b-5p were risk factors for DVT after TKA (P < 0.05). The ROC curve showed that both miR-199b-5p and NO had certain diagnostic value for DVT, but the combination of miR-199b-5p and NO had the highest diagnostic accuracy (P < 0.001). Conclusion: This study showed that the expression of miR-199b-5p was up-regulated after TKA, and miR-199b-5p levels were higher in DVT patients than in non-DVT patients. miR-199b-5p combined with NO is of great value in the diagnosis of DVT after TKA. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to evaluate the ability of the parasternal intercostal (PIC) thickening fraction during spontaneous breathing trial (SBT) to predict the need for reintubation within 48 h after extubation in surgical patients with sepsis. Methods: This prospective observational study included adult patients with sepsis who were mechanically ventilated and indicated for SBT. Ultrasound measurements of the PIC thickening fraction and diaphragmatic excursion (DE) were recorded 15 min after the start of the SBT. After extubation, the patients were followed up for 48 h for the need for reintubation. The study outcomes were the ability of the PIC thickening fraction (primary outcome) and DE to predict reintubation within 48 h of extubation using area under receiver characteristic curve (AUC) analysis. The accuracy of the model including the findings of right PIC thickening fraction and right DE was also assessed using the current study cut-off values. Multivariate analysis was performed to identify independent risk factors for reintubation. Results: We analyzed data from 49 patients who underwent successful SBT, and 10/49 (20%) required reintubation. The AUCs (95% confidence interval [CI]) for the ability of right and left side PIC thickening fraction to predict reintubation were 0.97 (0.88–1.00) and 0.96 (0.86–1.00), respectively; at a cutoff value of 6.5–8.3%, the PIC thickening fraction had a negative predictive value of 100%. The AUCs for the PIC thickening fraction and DE were comparable; and both measures were independent risk factors for reintubation. The AUC (95% CI) of the model including the right PIC thickening fraction > 6.5% and right DE ≤ 18 mm to predict reintubation was 0.99 (0.92–1.00), with a positive predictive value of 100% when both sonographic findings are positive and negative predictive value of 100% when both sonographic findings are negative. Conclusions: Among surgical patients with sepsis, PIC thickening fraction evaluated during the SBT is an independent risk factor for reintubation. The PIC thickening fraction has an excellent predictive value for reintubation. A PIC thickening fraction of ≤ 6.5–8.3% can exclude reintubation, with a negative predictive value of 100%. Furthermore, a combination of high PIC and low DE can also indicate a high risk of reintubation. However, larger studies that include different populations are required to replicate our findings and validate the cutoff values. [ABSTRACT FROM AUTHOR]

Background: Mental health in adolescence is critical in its own right and a predictor of later symptoms of anxiety and depression. To address these mental health challenges, it is crucial to understand the variables linked to anxiety and depression in adolescence. Methods: Here, we analyzed data of 278 adolescents that were collected in a nation-wide survey provided via a smartphone-based application during the COVID-19 pandemic. We used an elastic net regression machine-learning approach to classify individuals with clinically relevant self-reported symptoms of depression or anxiety. We then identified the most important variables with a combination of permutation feature importance calculation and sequential logistic regressions. Results: 40.30% of participants reported clinically relevant anxiety symptoms, and 37.69% reported depressive symptoms. Both machine-learning models performed well in classifying participants with depressive (AUROC = 0.77) or anxiety (AUROC = 0.83) symptoms and were significantly better than the no-information rate. Feature importance analyses revealed that anxiety and depression in adolescence are commonly related to sleep disturbances (anxiety OR = 2.12, depression OR = 1.80). Differentiating between symptoms, self-reported depression increased with decreasing life satisfaction (OR = 0.43), whereas self-reported anxiety was related to worries about the health of family and friends (OR = 1.98) as well as impulsivity (OR = 2.01). Conclusion: Our results show that app-based self-reports provide information that can classify symptoms of anxiety and depression in adolescence and thus offer new insights into symptom patterns related to adolescent mental health issues. These findings underscore the potentials of health apps in reaching large cohorts of adolescence and optimize diagnostic and treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: TIL scoring has been recommended as a biomarker in routine clinical practice in breast cancer patients. Currently, the standard of care for early breast cancer is neoadjuvant treatment. Recent studies have demonstrated the additional predictive value of TIL scoring to the residual cancer burden after neoadjuvant treatment. Although guidelines have been published, the reliability of this biomarker in treated tumor samples has not yet been evaluated. Here, we show that there is good inter-pathologist reproducibility for TIL scoring in patients with clear residual tumor tissue. However, in patients with a (near-)complete response, there is not. This is significant because this demonstrates that it could be a reliable biomarker and help guide adjuvant treatment decisions. Neoadjuvant chemotherapy (NAC) is now the standard of care for patients with locally advanced breast cancer (BC). TIL scoring is prognostic and adds predictive value to the residual cancer burden evaluation after NAC. However, NAC induces changes in the tumor, and the reliability of TIL scoring in post-NAC samples has not yet been studied. H&E- and dual CD3/CD20 chromogenic IHC-stained tissues were scored for stromal and intra-tumoral TIL by two experienced pathologists on pre- and post-treatment BC tissues. Digital TIL scoring was performed using the HALO® image analysis software (version 2.2). In patients with residual disease, we show a good inter-pathologist correlation for stromal TIL on H&E-stained tissues (CCC value 0.73). A good correlation for scoring with both staining methods (CCC 0.81) and the digital TIL scoring (CCC 0.77) was also observed. Overall concordance for TIL scoring in patients with a complete response was however poor. This study reveals there is good reliability for TIL scoring in patients with detectable residual tumors after NAC treatment, which is comparable to the scoring of untreated breast cancer patients. Based on the good consistency observed with digital TIL scoring, the development of a validated algorithm in the future might be advantageous. [ABSTRACT FROM AUTHOR]

Simple Summary: Regorafenib offers longer survival for patients with refractory metastatic colorectal cancer (mCRC). We aimed to identify biomarkers for regorafenib through preclinical and translational studies. In silico analysis identified matrix metalloproteinase (MMP)-14 and MMP-9 as key biomarkers. Validation in patients receiving regorafenib or FTD/TPI showed that high MMP-14 levels were correlated with a better response to regorafenib. Additionally, lower MMP-9 levels before the second cycle were linked to improved disease control and survival. These findings suggest that MMP-14 and MMP-9 could serve as prognostic markers for regorafenib efficacy. In identifying biomarkers for anticancer drugs, the lack of objectivity in selecting candidate factors makes interpretation difficult. We performed preclinical analysis and a translational validation study to identify candidate biomarkers for regorafenib efficacy in metastatic colorectal cancer (mCRC). Using in silico COMPARE analysis with a human cancer cell line panel, JFCR39, we selected candidate biomarkers whose expression correlates with regorafenib sensitivity. We validated predictive values in mCRC patients receiving regorafenib (discovery, n = 53) and FTD/TPI (control, n = 16). Blood samples were obtained at baseline (BL), before the second cycle (2nd), and at progressive disease (PD), and biomarker levels were measured using ELISA. Our analysis showed that high matrix metalloproteinase (MMP)-14 expression was associated with a high sensitivity to regorafenib. In the discovery cohort, high MMP-14 levels at BL and PD were correlated with tumor shrinkage and longer progression-free survival (PFS). A subsequent analysis of other related factors further indicated that the patients with decreased MMP-9 levels at the 2nd had higher disease control rates, tumor shrinkage, longer PFS, and overall survival than those with increased changes. These findings were not observed in the control cohort. Our study suggests MMP-14 and MMP-9 may serve as prognostic markers for regorafenib and provide insights into novel combination therapies with anti-MMP-9 agents or FTD/TPI. [ABSTRACT FROM AUTHOR]

Simple Summary: This pilot study aimed to highlight the value of spinal cord diffusion imaging and tractography in providing predictive factors for tumor resection in patients with intramedullary tumors. Tensor metrics provided predictive factors of spinal cord damage with a high correlation between fractional anisotropy, mean diffusivity, and radial diffusivity, and suggested changes in microstructural architecture, axonal density, and myelinated fibers of the spinal cord. Spinal cord tractography also provided predictive factors for tumor resection by helping to perform histological tumor differentiation and differentiating spinal tracts and, thus, defining relationships between spinal cord tissue and tumor; all these elements argue in favor of tumor resectability. This pilot study aimed to investigate the interest of high angular resolution diffusion imaging (HARDI) and tractography of the spinal cord (SC) in the management of patients with intramedullary tumors by providing predictive elements for tumor resection. Eight patients were included in a prospective study. HARDI images of the SC were acquired using a 3T MRI scanner with a reduced field of view. Opposed phase-encoding directions allowed distortion corrections. SC fiber tracking was performed using a deterministic approach, with extraction of tensor metrics. Then, regions of interest were drawn to track the spinal pathways of interest. HARDI and tractography added value by providing characteristics about the microstructural organization of the spinal white fibers. In patients with SC tumors, tensor metrics demonstrated significant changes in microstructural architecture, axonal density, and myelinated fibers (all, p < 0.0001) of the spinal white matter. Tractography aided in the differentiation of tumor histological types (SC-invaded vs. pushed back by the tumor), and differentiation of the spinal tracts enabled the determination of precise anatomical relationships between the tumor and the SC, defining the tumor resectability. This study underlines the value of using HARDI and tractography in patients with intramedullary tumors, to show alterations in SC microarchitecture and to differentiate spinal tracts to establish predictive factors for tumor resectability. [ABSTRACT FROM AUTHOR]

Simple Summary: Although the high mutation burden in small-cell lung cancer (SCLC) suggests that it should be responsive to immune checkpoint blockade (ICB), relatively few patients have shown durable clinical benefit (DCB). To identify biomarkers of responses, biopsies from 35 patients treated with ICB (21 first-line and 14 second-line) were subjected to transcriptomic analysis and gene signatures were studied. Patients with DCB were compared to those with no clinical benefit (NCB). The response to ICB in the second-line, but not the first-line, setting was associated with gene signatures of inflammation, antigen presentation, interferon responses, and increased CD8 T cells. Our data suggest that responses to ICB in the second-line setting can be predicted by the baseline inflammatory state of the tumor; however, this strong association with inflammation was not observed in the first-line setting, likely because chemotherapy alters the immune milieu allowing a response to ICB. Although immune checkpoint blockade (ICB) is currently approved for the treatment of extensive-stage small-cell lung cancer (SCLC) in combination with chemotherapy, relatively few patients have demonstrated durable clinical benefit (DCB) to these therapies. Biomarkers predicting responses are needed. Biopsies from 35 SCLC patients treated with ICB were subjected to transcriptomic analysis; gene signatures were assessed for associations with responses. Twenty-one patients were treated with ICB in the first-line setting in combination with platinum-based chemotherapy; fourteen patients were treated in the second-line setting with ICB alone. DCB after ICB in SCLC in the second-line setting (3 of 14 patients) was associated with statistically higher transcriptomic levels of genes associated with inflammation (p = 0.003), antigen presentation machinery (p = 0.03), interferon responses (p < 0.05), and increased CD8 T cells (p = 0.02). In contrast, these gene signatures were not significantly different in the first-line setting. Our data suggest that responses to ICB in SCLC in the second-line setting can be predicted by the baseline inflammatory state of the tumor; however, this strong association with inflammation was not seen in the first-line setting. We postulate that chemotherapy alters the immune milieu allowing a response to ICB. Other biomarkers will be needed to predict responses in first-line therapy patients. [ABSTRACT FROM AUTHOR]

Aim: To develop and internally validate risk prediction models for subsequent clinical deterioration, unplanned ICU admission and death among ward patients following medical emergency team (MET) review. Design: A retrospective cohort study of 1500 patients who remained on a general ward following MET review at an Australian quaternary hospital. Method: Logistic regression was used to model (1) subsequent MET review within 48 h, (2) unplanned ICU admission within 48 h and (3) hospital mortality. Models included demographic, clinical and illness severity variables. Model performance was evaluated using discrimination and calibration with optimism‐corrected bootstrapped estimates. Findings are reported using the TRIPOD guideline for multivariable prediction models for prognosis or diagnosis. There was no patient or public involvement in the development and conduct of this study. Results: Within 48 h of index MET review, 8.3% (n = 125) of patients had a subsequent MET review, 7.2% (n = 108) had an unplanned ICU admission and in‐hospital mortality was 16% (n = 240). From clinically preselected predictors, models retained age, sex, comorbidity, resuscitation limitation, acuity‐dependency profile, MET activation triggers and whether the patient was within 24 h of hospital admission, ICU discharge or surgery. Models for subsequent MET review, unplanned ICU admission, and death had adequate accuracy in development and bootstrapped validation samples. Conclusion: Patients requiring MET review demonstrate complex clinical characteristics and the majority remain on the ward after review for deterioration. A risk score could be used to identify patients at risk of poor outcomes after MET review and support general ward clinical decision‐making. Relevance to clinical practice: Our risk calculator estimates risk for patient outcomes following MET review using clinical data available at the bedside. Future validation and implementation could support evidence‐informed team communication and patient placement decisions. [ABSTRACT FROM AUTHOR]

Objective: The accurate diagnosis of thyroid nodules is crucial for effective management and the detection of malignancy. Fine-needle aspiration biopsy (FNAB) and fine-needle non-aspiration biopsy (FNNAB) are widely used techniques for evaluating thyroid nodules. In this study, we aimed to investigate the impact of anthropometric parameters and sonographic characteristics on the choice between FNAB and FNNAB in terms of diagnostic yield. Material and Methods: This retrospective and cross-sectional analysis involved 188 cases with a total of 225 thyroid nodules. Each nodule initially underwent either FNAB or FNNAB and if the initial biopsy did not yield a diagnostic result, the nodule was re-biopsied using the alternate technique. Ultrasound was used to evaluate the nodules, with a focus on echogenicity, calcifications, size, vascularity, and the presence of a halo sign. Both FNAB and FNNAB were performed using a 25-gauge needle, with the only difference being the application of suction. Results: FNAB demonstrated a higher diagnostic rate for nodules with a taller-than-wide shape (anteroposteriorto-transverse ratio ≥1), nodules sized 10–40 mm, nodules with volumes <0.5 cc, and hypoechoic nodules (P < 0.001 for all). FNAB also outperformed FNNAB in the assessment of the right-sided, inferior, and posterior nodules (P < 0.001), nodules with and without calcification (P = 0.041 and P = 0.020, respectively), and nodules with type 1 and type 2 vascularity patterns (P = 0.006 and P = 0.017, respectively). FNAB was effective in obese individuals (Body mass index ≥40 kg/m2), males with a waist circumference of <94 cm, females with a waist circumference of ≥80 cm, and females with a neck circumference of ≥34 cm (P = 0.011, P = 0.044, P = 0.029, and P = 0.008, respectively). Conclusion: Anthropometric parameters and sonographic characteristics influenced the diagnostic yield of FNAB and FNNAB, with FNAB generally demonstrating superior results. Given the importance of obtaining an accurate diagnostic result from fine-needle biopsy, clinicians should consider both the sonographic features of the nodule and the anthropometric measurements of the patient when selecting a biopsy technique. [ABSTRACT FROM AUTHOR]

Background: The characterization of pathologically enlarged mediastinal lymph nodes is clinically essential for effective disease management and accurate prognosis. Malignancy (metastases and lymphoma) and granulomatous conditions (sarcoidosis and tuberculosis) are the most common causes. Magnetic resonance imaging (MRI) is a good modality to characterize the mediastinal pathologically enlarged lymph nodes based on the excellent soft tissue contrast. It can save high-risk patients from radiation exposure and hazards of intervention such as general anesthesia and biopsy. Aim of the work: To estimate the accuracy of different advanced MRI quantitative parameters in the differentiation between benign and malignant mediastinal lymphadenopathy. This would involve the lesion-to-cord signal intensity ratio (SIR) in the T2-WI and diffusion weighted image (DWI), the lesion-to-chest wall muscle SIR in T2-WI and DWI, and the mean apparent diffusion coefficient (ADC) values. These values would be correlated with the prospective pathological data and the results of the positron emission tomography (PET-CT). Results: Prospectively, the study was conducted during the period between June 2022 and September 2023 on 45 patients with indeterminate or suspicious mediastinal lymphadenopathy identified by CT. MRI examination, PET-CT, and biopsy were applied for all patients. The intra-class correlation coefficient ranged between 0.89 and 0.95. (A) The lesion-to-cord SIR in T2-WI in the malignant group (1.49 ± 0.30) was higher than that in the benign group (0.83 ± 0.24) with P < 0.001. The statistically calculated cutoff value (> 1.2) estimated 90% sensitivity, 100% specificity, with AUC = 0.989. (B) The lesion-to-chest wall muscle SIR in T2-WI in malignant nodes (3.13 ± 0.84) was significantly higher than that in the benign nodes (1.90 ± 0.80) with P < 0.001. The statistically calculated cutoff value (> 2.4) estimated 86.67% sensitivity, 86.67% specificity, with AUC = 0.88. (C) The lesion-to-cord signal SIR in b500-DWI in the malignant node (1.80 ± 0.54) was higher than that in the benign group (0.75 ± 0.29) with P < 0.001. The statistically calculated cutoff value (> 1.2) estimated 100% sensitivity and specificity with AUC = 1.00. (D) The lesion-to-chest wall SIR in b500-DWI in the malignant node (6.43 ± 1.28) was higher than that in the benign node (2.63 ± 0.94) with P < 0.001. The statistically calculated cutoff value (> 4.1) estimated 96.67% sensitivity, 100% specificity, with AUC = 0.997. € The mean ADC values in the malignant nodes (0.83 ± 0.20 × 10–3 mm2/s) were significantly lower than that in the benign nodes (1.85 ± 0.19 × 10−3 mm2/s) with P < 0.001. The statistically calculated cutoff value (≤ 1.2) estimated 100% sensitivity and specificity with AUC = 1.00. Conclusions: Biopsy remains the main diagnostic modality for the characterization of mediastinal lymphadenopathy despite its hazards and limitations. This study proved that MRI could be accepted as an alternative non-invasive imaging tool that can overcome the PET-CT limitations. The lesion signal-to-cord and to-muscle ratios in both T2-WI and DWI-MRI side by side with the mean ADC value showed high statistical accuracy. [ABSTRACT FROM AUTHOR]

Background: Emerging biomarker technologies (e.g., MRI, EEG, digital phenotyping, eye-tracking) have potential to move the identification of autism into the first year of life. We investigated the perspectives of parents about the anticipated utility and impact of predicting later autism diagnosis from a biomarker-based test in infancy. Methods: Parents of infants were interviewed to ascertain receptiveness and perspectives on early (6-12 months) prediction of autism using emerging biomarker technologies. One group had experience parenting an older autistic child (n=30), and the other had no prior autism parenting experience (n=25). Parent responses were analyzed using inductive qualitative coding methods. Results: Almost all parents in both groups were interested in predictive testing for autism, with some stating they would seek testing only if concerned about their infant's development. The primary anticipated advantage of testing was to enable access to earlier intervention. Parents also described the anticipated emotions they would feel in response to test results, actions they might take upon learning their infant was likely to develop autism, attitudes towards predicting a child's future support needs, and the potential impacts of inaccurate prediction. Conclusion: In qualitative interviews, parents of infants with and without prior autism experience shared their anticipated motivations and concerns about predictive testing for autism in the first year of life. The primary reported motivators for testing—to have more time to prepare and intervene early—could be constrained by familial resources and service availability. Implications for ethical communication of results, equitable early intervention, and future research are discussed. [ABSTRACT FROM AUTHOR]

Background: Postoperative delirium (POD) is a usual neurological complication, often leading to poor prognoses. Early identification of high-risk patients is crucial for preventing POD. Sarcopenia is an age-related geriatric syndrome characterized by the loss of skeletal muscle mass and function, and previous studies indicated that preoperative low muscle mass might be a predictor for POD. However, the association between preoperative sarcopenia and POD remains to be fully elucidated. This study was to explore the correlation between preoperative sarcopenia and POD following gastrointestinal cancer surgery in older patients. Methods: Older patients (≥60 years) undergoing gastrointestinal cancer surgery were enrolled. Sarcopenia was defined based on the Special Interest Group on sarcopenia of the International Society of Physical and Rehabilitation Medicine (ISarcoPRM), which combined the loss of muscle mass (evaluated by ultrasound) and function (assessed by chair stand test and handgrip strength) before surgery. POD assessment was performed using the Confusion Assessment Method (CAM) or CAM for the intensive care unit (CAM-ICU) during the first 7 days after surgery or before discharge. Multivariate logistic regression analysis examined the correlation between preoperative sarcopenia and POD. Moreover, the receiver operator characteristic (ROC) curve was applied to analyze the predictive effect of the preoperative sarcopenia in POD. Results: One hundred and thirty patients were finally included, of which 43 patients presented with sarcopenia before surgery. Twenty-four patients ultimately developed POD, and the incidence was 18.5%. The results of the multivariate analyses demonstrated that preoperative sarcopenia was still independently associated with POD after adjusting for age ≥70 years, preoperative Mini-Mental State Examination score, and intraoperative blood transfusion. The area under the ROC curve of preoperative sarcopenia in predicting POD was 0.680 (95% confidence interval 0.557-0.804). Conclusion: Preoperative sarcopenia defined by ISarcoPRM criteria was independently associated with POD in geriatric patients after gastrointestinal cancer surgery. [ABSTRACT FROM AUTHOR]

Background/Objectives: To analyze the best noninvasive tests prognosis marker in patients with diabetic foot ulcer (DFU) who underwent endovascular revascularization based on clinical outcomes, such as healing rate, time to heal, and free amputation survival after at least a six-month follow-up. Methods: A multicentric prospective observational study was performed with 28 participants with ischemic or neuroischemic DFU who came to the participant centers and underwent endovascular revascularization between January 2022 and March 2023. Toe systolic pressure (TP), ankle systolic pressure (AP), the ankle brachial pressure index (ABPI), the toe brachial pressure index (TBPI), transcutaneous pressure of oxygen (TcPO2), and skin perfusion pressure (SPP) were evaluated using PeriFlux 6000 System, Perimed, Sweden, before (Visit 0) and four weeks after revascularization (Visit 1). The primary clinical outcome was an evaluation of the clinical evolution of noninvasive tests comparing Visit 0 and Visit 1, estimating the sensitivity for predicting wound healing of noninvasive tests at six months following initial recruitment. Results: After six months, 71.43% (n = 20) of DFU healed, four patients (14.3%) received major amputations, and one (3.5%) died. The two tests that best predicted wound healing after revascularization according to the ROC curve were TcPO2 and TP with sensitivities of 0.89 and 0.70 for the cut-off points of 24 mmHg and 46 mmHg, respectively. Conclusions: TcPO2 and TP were the two tests that best predicted wound healing in patients who underwent endovascular revascularization. Clinicians should consider the importance of the evaluation of microcirculation in the healing prognosis of patients with diabetic foot ulcers. [ABSTRACT FROM AUTHOR]

Background: The Lipid Accumulation Product (LAP) is a measure that indicates excessive fat accumulation in the body. LAP has been the focus of research in epidemiological studies aimed at forecasting chronic and metabolic diseases. This study aimed to evaluate the association between LAP and type 2 diabetes mellitus (T2DM) among adults in western Iran. Methods: The study involved 9,065 adults who participated in the initial phase of the Ravansar non-communicable diseases study (RaNCD) cohort. To investigate the association between LAP and T2DM, multiple logistic regressions were employed. Additionally, the receiver operating characteristic (ROC) curve was used to evaluate LAP's predictive ability concerning T2DM. Results: The participants had an average age of 47.24 ± 8.27 years, comprising 49.30% men and 50.70% women. The mean LAP was 53.10 ± 36.60 for the healthy group and 75.51 ± 51.34 for the diabetic group (P < 0.001). The multiple regression analysis revealed that the odds of T2DM in the second quartile of LAP were 1.69 (95% CI: 1.25, 2.29) times greater than in the first quartile. Furthermore, the odds in the third and fourth quartiles were 2.67 (95% CI: 2.01, 3.55) and 3.73 (95% CI: 2.83, 4.92) times higher, respectively. The ROC analysis for predicting T2DM showed that the LAP index had an area under the curve (AUC) of 0.66 (95% CI: 0.64, 0.68). Conclusion: A strong association was identified between elevated LAP levels and T2DM in the adult population of western Iran. LAP is recommended as a potential tool for screening diabetes susceptibility. [ABSTRACT FROM AUTHOR]

Background: This study aims to evaluate the effectiveness of ultrasound criteria, TI-RADS score, and elastography in distinguishing benign thyroid nodules from malignant ones, as a substitute for invasive diagnostic procedures. Although the minority of thyroid nodules is malignant, invasive diagnostic procedures are often necessary. Methods: In this prospective study, a total of 104 thyroid nodules were assessed using fine-needle aspiration cytology. The euthyroid state of the patients was ensured. Conventional ultrasound and shear wave elastography (SWE) were performed by a single experienced operator. Final postoperative histopathologic findings were compared to conventional ultrasound and elastography findings. Results: SWE elasticity indices (EIs) were found to be significantly higher in malignant nodules than benign ones (p < 0.05). Combined results of both TI-RADS and SWE increased the sensitivity of detection of malignant nodules. Conclusion: Combined SWE and TI-RADS could enhance the diagnostic accuracy in differentiating thyroid nodules by leveraging their complementary strengths. [ABSTRACT FROM AUTHOR]

Background: Frailty is a multifactorial syndrome; through this study, we aimed to investigate the physiological, psychological, and social factors associated with frailty and frailty worsening in community-dwelling older adults. Methods: We conducted a cross-sectional and longitudinal study using data from the "Community Empowerment and Well-Being and Healthy Long-term Care: Evidence from a Cohort Study (CEC)," which focuses on community dwellers aged 65 and above in Japan. The sample of the cross-sectional study was drawn from a CEC study conducted in 2014 with a total of 673 participants. After excluding those who were frail during the baseline assessment (2014) and at the 3-year follow-up (2017), the study included 373 participants. Frailty assessment was extracted from the Kihon Checklist, while social relationships were assessed using the Social Interaction Index (ISI). Variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression and their predictive abilities were tested. Factors associated with frailty status and worsening were identified through the Maximum-min Hillclimb algorithm applied to Bayesian networks (BNs). Results: At baseline, 14.1% (95 out of 673) participants were frail, and 24.1% (90 out of 373) participants experienced frailty worsening at the 3-years follow up. LASSO regression identified key variables for frailty. For frailty identification (cross-sectional), the LASSO model's AUC was 0.943 (95%CI 0.913–0.974), indicating good discrimination, with Hosmer–Lemeshow (H–L) test p = 0.395. For frailty worsening (longitudinal), the LASSO model's AUC was 0.722 (95%CI 0.656–0.788), indicating moderate discrimination, with H–L test p = 0.26. The BNs found that age, multimorbidity, function status, and social relationships were parent nodes directly related to frailty. It revealed an 85% probability of frailty in individuals aged 75 or older with physical dysfunction, polypharmacy, and low ISI scores; however, if their social relationships and polypharmacy status improve, the probability reduces to 50.0%. In the longitudinal-level frailty worsening model, a 75% probability of frailty worsening in individuals aged 75 or older with declined physical function and ISI scores was noted; however, if physical function and ISI improve, the probability decreases to 25.0%. Conclusion: Frailty and its progression are prevalent among community-dwelling older adults and are influenced by various factors, including age, physical function, and social relationships. BNs facilitate the identification of interrelationships among these variables, quantify the influence of key factors. However, further research is required to validate the proposed model. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate whether persistent human papillomavirus integration at the same loci (PHISL) before and after treatment can predict recurrent/residual disease in women with CIN2-3. Methods: A total of 151 CIN2-3 women treated with conization between August 2020 and September 2021 were included. To investigate the precision of HPV integration, we further analyzed HPV integration-positive patients. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and the Youden index for predicting recurrence/residual disease were calculated. Results: Among the 151 enrolled CIN2-3 women, 56 were HPV integration-positive and 95 had HPV integration-negative results. Six (10.7%) experienced recurrence among 56 HPV integration-positive patients, which was more than those in HPV integration-negative patients (one patient, 1.1%). In the 56 HPV integration-positive patients, 12 had positive HPV results after treatment, seven had PHISL, and two had positive cone margin. Among the seven patients who tested with PHISL, six (85.7%) had residual/recurrent disease. PHISL was a prominent predictor of persistent/recurrent disease. The HPV test, the HPV integration test, and PHISL all had a sensitivity of 100% and a NPV of 100% for residual/recurrent disease. PHISL showed better specificity (98.0% vs. 82.0%, p = 0.005) and PPV (85.7% vs. 40.0%, p = 0.001) than the HPV test for predicting recurrence. Conclusions: The HPV-integration-positive CIN2-3 women had much higher relapse rates than HPV-integration-negative CIN2-3 women. The findings indicate that PHISL derived from preoperative and postoperative HPV integration tests may be a precise biomarker for the identification of residual/recurrent CIN 2/3. [ABSTRACT FROM AUTHOR]

Introduction: Early identification of patients with sepsis at high risk of death remains a challenge, and whether brain natriuretic peptide (BNP) or N-terminal pro-B-type natriuretic peptide (NT-proBNP) has a prognostic effect on patients with sepsis is controversial. Here, we clarified the prognostic value of BNP and NT-proBNP and sought to establish suitable cutoff values and intervals. Methods: We searched five databases to identify studies that met the inclusion criteria. The primary outcomes were the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and corresponding 95% credible interval (95% CI) of BNP and NT-proBNP. The secondary outcomes were the sensitivity and specificity of BNP or NT-proBNP in subgroup analyses. Results: Forty-seven studies were included in our meta-analysis. The pooled sensitivity of NT-proBNP (0.77 [0.68, 0.84]) was weaker than that of BNP (0.82 [0.76, 0.87]), the pooled specificity of NT-proBNP (0.70 [0.60, 0.77]) was less than that of BNP (0.77 [0.71, 0.82]), and the AUC of BNP (0.87 [0.83–0.89]) was greater than that of NT-proBNP (0.80 (0.76–0.83]). The results of the subgroup analysis showed that the cutoff range of 400–800 pg/mL for BNP had high sensitivity (0.86 [0.74–0.98]) and specificity (0.87 [0.81–0.93]) and was probably the most appropriate cutoff range. Conclusions: Elevated levels of BNP and NT-proBNP were significantly related to the mortality of patients with sepsis and had a moderate prognostic value in predicting the mortality of patients with sepsis. In addition, our meta-analysis preliminarily established appropriate cutoff values for BNP and NT-proBNP. [ABSTRACT FROM AUTHOR]

Introduction: Significant hepatic steatosis affects the outcome of surgery when living donors are transplanted. The gold standard for diagnosing and evaluating hepatic steatosis is hepatic imaging-guided biopsy. Hepatic steatosis assessment using MR spectroscopy and the proton density fat fraction (MR-PDFF) method has produced positive findings. Objectives: Is to compare the pre-operative assessment of liver fat quantification using MRI-PDFF methods, a non-invasive method, with histopathology. Subjects and methods: A 42 potential donors were then operated surgically for liver transplantation, consequently, were available for the assessment of the efficiency and sensitivity of the radiological findings MRI-PDFF procedures and imaging-guided liver biopsy. This radiological workup of these donors was done through a period of 7 months. Results: In many liver transplantations centers, liver imaging-guided biopsy histopathological examination is the gold standard. The study examined the MR proton density fat fraction modality, a recently developed test for hepatic steatosis measurement. The findings indicate 86.8% sensitivity, 50% specificity, 94.2% PDV, 28.5% NPV, 83.3% accuracy, and 0.684 AUC. On analyzing the fat percent, we found that the recorded fat percent using liver imaging-guided biopsy ranges between 1 and 10% with a median of 3. On the other hand, the recorded fat percent using MRI ranged between 2 and 15% with a median of 5. Conclusion: The non-invasive magnetic resonance hepatic proton density fat fraction approach using IDEAL sequence is a reliable and accurate means of quantitatively evaluating hepatic steatosis with excellent sensitivity, specificity, and accuracy. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia is a prevalent psychiatric disorder that affects 1% of the global population. Schizophrenia frequently begins in late adolescence or early adulthood, causing significant educational, social, and economic costs for people and society. Functional neuroimaging research on schizophrenia physiopathology has been beneficial. Arterial spin labelling (ASL) is one of functional magnetic resonance imaging (fMRI) technologies that assess brain function without radiation. ASL uses magnetic resonance (MR) imaging to quantify tissue-level brain perfusion non-invasively. Arterial spin labelling (ASL) is one of the functional magnetic resonance imaging (fMRI) technologies that assess the brain function without radiation hazards. ASL uses magnetic resonance (MR) imaging to quantify tissue-level brain perfusion non-invasively. Many publications were performed on role of different advanced MRI techniques in schizophrenia, but our study insisted on the added value of combined ASL and MRS over the conventional MRI in schizophrenic Egyptian population sample. Aim of the work: The purpose of this work was to evaluate the added value of combined ASL-perfusion MRI and MRS in schizophrenic patients. Methods: This prospective case–control study was carried out on two groups: First group was 30 patients who were diagnosed clinically as schizophrenic patients, and second group was 20 healthy volunteers as a control group for comparison in the period from August 2021 till July 2022. Results: The majority of newly diagnosed cases had significant higher positive symptoms than chronic cases. According to arterial spin labelling (ASL) data, rCBF was noticed to be reduced in anterior cingulate, frontal lobe, and parietal lobe of both patients' subgroups but more significant in chronically ill patients. Convergent results of decreased rCBF were also found in the parietal lobe and occipital lobe. Magnetic resonance spectroscopic analysis showed that NAA was decreased in the anterior cingulate cortex, thalami and basal ganglia of the newly diagnosed cases more than chronic cases. The ASL-MRI perfusion accurately detected the hypo-perfusion of different brain regions with sensitivity 100%, specificity 66.67%, positive predictive value 96.43%, negative predictive value 100%, and accuracy 96.67%, while MR spectroscopy showed sensitivity 100%, specificity 33.33%, positive predictive value 93.10%, negative predictive value 100%, and accuracy 93.33% in evaluation of changes of brain metabolites. Conclusion: ASL is a promising functional MRI technique that can produce together with MRS quantitative information about the metabolites of different brain regions. The ASL-MRI appears as a reliable non-invasive technique to measure cerebral blood flow and identify decreased rCBF without any contrast administration, and it could be repeatable which helps in early diagnosis as well as follow-up of the progression of the disease. [ABSTRACT FROM AUTHOR]

Background: The urinary bladder neoplasm is considered the second most frequent kind of neoplasm globally, after prostate cancer. Bladder neoplasm clinical management strategies and prognosis depend on the extent of loco-regional disease. MRI is increasingly being employed for preoperative, local staging of BC. The aim of this study was to expose the mastery of bi-parametric MRI (MRDWI and T2WI conjunction) with signal intensity-based MR segmentation in evaluation of UB neoplasm mural invasion if unaccompanied by contrast-enhanced MRI with special concern to Vesical Imaging Reporting and Data System (VIRADS) score taking the histopathological diagnosis as a reference. Results: This prospective study was conducted on 99 patients (with 100 UB lesions), who were referred from the urology department with bladder neoplasm suspicion. The mean age of the patients was 64.8 years. About 66.6% of the cases were smokers. The most common pathology of the UB neoplastic lesions was urothelial carcinoma. ADC in muscle-invasive bladder cancer (MIBC) was significantly lower than in non-invasive bladder cancer (NMIBC), with the minimum to maximum value of the ADC in all cases about 0.01–2.0. Also, we have done DWI at different b values, where b 1000 turned out to be the most accurate in detection of muscle invasion. Sensitivity, specificity, PPV, NPV and accuracy were calculated for T2WI only VIRADS, DWI only VIRADS, bi-parametric MR (T2WI and DWI)-based VIRADS, signal intensity-based MR segmentation VIRADS and for bi-parametric and MR segmentation conjunction-based VIRADS. The diagnostic performance for the combination of the bi-parametric MRI and signal intensity-based MR segmentations attained the highest values in sensitivity, specificity, PPV and NPV as well as accuracy. Conclusions: Bi-parametric MRI (MRDWI with T2WI) and signal intensity MR segmentation conjunction have proven to be efficacious in accurately determining the UB neoplasm mural invasion allowing for the dispensability of CE-MRI in the event of contrast contraindications, unavailability or even its high cost. [ABSTRACT FROM AUTHOR]

Objective: To investigate the diagnostic efficacy of the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model based on ultrasonographic radiomics for the differentiation of small clear cell Renal Cell Carcinoma (ccRCC) and Renal Angiomyolipoma (RAML). Methods: The clinical, ultrasound, and contrast-enhanced CT(CECT) imaging data of 302 small renal tumors (maximum diameter ≤ 4cm) patients in Tianjin Medical University Cancer Institute and Hospital from June 2018 to June 2022 were retrospectively analyzed, with 182 patients of ccRCC and 120 patients of RAML. The ultrasound images of the largest diameter of renal tumors were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from ROI segmented images. The patients were randomly divided into training and internal validation cohorts in the ratio of 7:3. The Random Forest algorithm of the Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model. The efficacy of the prediction models was verified in an independent external validation cohort consisting of 69 patients, from 230 small renal tumor patients in two different institutions. The Delong test compared the predictive ability of three models and CECT. Calibration Curve and clinical Decision Curve Analysis were applied to evaluate the model and determine the net benefit to patients. Results: 491 ultrasonographic radiomics features were extracted from 302 small renal tumor patients, and 9 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. In the internal validation cohort, the area under the curve (AUC), sensitivity, specificity, and accuracy of the clinical ultrasound imaging model, ultrasonographic radiomics model, comprehensive model, and CECT were 0.75, 76.7%, 60.0%, 70.0%; 0.80, 85.6%, 61.7%, 76.0%; 0.88, 90.6%, 76.7%, 85.0%and 0.90, 92.6%, 88.9%, 91.1%, respectively. In the external validation cohort, AUC, sensitivity, specificity, and accuracy of the three models and CECT were 0.73, 67.5%, 69.1%, 68.3%; 0.89, 86.7%, 80.0%, 83.5%; 0.90, 85.0%, 85.5%, 85.2% and 0.91, 94.6%, 88.3%, 91.3%, respectively. The DeLong test showed no significant difference between the clinical ultrasound imagingmodel and the ultrasonographic radiomics model (Z=-1.287, P=0.198). The comprehensive model showed superior diagnostic performance than the ultrasonographic radiomics model (Z=4. 394, P<0.001) and the clinical ultrasound imaging model (Z=4. 732, P<0.001). Moreover, there was no significant difference in AUC between the comprehensive model and CECT (Z=-0.252, P=0.801). Both in the internal and external validation cohort, the Calibration Curve and Decision Curve Analysis showed a better performance of the comprehensive model. Conclusion: It is feasible to construct an ultrasonographic radiomics model for distinguishing small ccRCC and RAML based on ultrasound images, and the diagnostic performance of the comprehensive model is superior to the clinical ultrasound imaging model and ultrasonographic radiomics model, similar to that of CECT. [ABSTRACT FROM AUTHOR]

The Breast Reconstruction Risk Assessment (BRA) score is a tool for the prediction of the risk of complications in breast surgery, elaborated in 2014. This score assesses the risk of surgical complications related to each type of breast reconstruction technique. The purpose of this study was to evaluate the effectiveness of using the calculator on patients who underwent prosthetic breast reconstruction with submuscular tissue expander or prepectoral prosthesis. Our retrospective study analyzed 92 patients whose data was entered into the calculator. The predicted and observed 1-year rates of overall surgical complications were compared, separately for both cohorts. Subsequently, the accuracy, the applicability, and the discrimination ability of the BRA score were assessed using statistical analysis. In the two-stage subpectoral reconstruction group, Mann–Whitney U test showed a statistically significant difference in BRA-score values between the patients who developed complications compared to the patients who had no complications (p-value < 0.02). Moreover, the score has an excellent discrimination ability (AUC = 0.9), and a cutoff of overall surgical complication rate was found to be between 17 and 18%. For the one-stage prepectoral prosthetic reconstruction group, the BRA score tool was unable to discriminate between patients with complications and patients without complication. Our results suggest that the BRA score can accurately identify patients with risk of complications following two-stage subpectoral breast reconstruction. Moreover, we believe it is possible to identify a risk rate cutoff of overall surgical complications that may potentially help physicians select the safest surgical strategy. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews are potentially less biased and provide more precise estimates than primary studies of diagnostic test accuracy. Their use to inform evidence-based diagnosis is rapidly expanding. However, the extent, scope and methodologies of systematic reviews of studies of the accuracy of diagnostic tests relevant to physical therapy have not yet been described. Information about methods used in these systematic reviews could inform future reviews and subsequently improve evidence-based diagnosis in physical therapy. Objectives: To describe the systematic review methodology of diagnostic test accuracy studies relevant to physical therapy. Methods: All systematic reviews indexed on DiTA (Diagnostic Test Accuracy database) were included. Data on methodology, reporting characteristics, and review topics were extracted. A random sample was assessed for risk of bias using the Risk Of Bias In Systematic Reviews (ROBIS) tool. Results: The review included 241 reviews published between 1995 and 2022, covering all 10 major physical therapy subdisciplines, although 90% related to musculoskeletal physical therapy. In 72% of reviews, QUADAS and QUADAS-2 were used to assess the risk of bias. In a random sample of included reviews, 47% of reviews displayed a 'high' risk of bias. Conclusions: Systematic reviews of diagnostic test accuracy studies relevant to physical therapists are becoming more prevalent. There is a relatively large number of these reviews however a large proportion use methods that expose them to bias. This makes the interpretation of their results more difficult. Future research could focus on publishing methodology guidelines for physical therapy-relevant diagnostic test accuracy reviews. [ABSTRACT FROM AUTHOR]

Fricatives, and especially sibilants, are very frequently misarticulated by speakers with hearing loss. Misarticulations can result in phonemic contrast weakening or loss, compromising intelligibility. The present study focuses on the examination of acoustic characteristics of the Greek alveolar fricative /s/, an articulatorily demanding sound, produced by young adult speakers with profound hearing impairment and with normal hearing. An array of variables was examined using mixed-effects and random forest models aiming to assess the effectiveness of various measures in differentiating hearing-impaired and normal-hearing /s/ production. Significant differences were found in spectral and amplitude measures, but not in temporal measures. In hearing-impaired speech, spectral slope and RMS amplitude had significantly lower values, indicating a more distributed spectrum, suggestive of decreased flow velocity through the fricative constriction. Also, a trend for concentration of energy at lower frequencies was observed suggesting more posterior fricative articulation than normal. Moreover, measures capturing the variation of frequency and amplitude over time revealed different patterns of sibilance development across time than normal, denoting the production of a less well-formed or less sibilant /s/ by speakers with hearing impairment. The investigation of contextual effects on /s/ in hearing-impaired speech showed increased spectral variance, negative skewness and lower kurtosis in the labial (rounded) context /u/ in relation to the nonlabial contexts /i/ and /a/, indicating a more diffuse, less compact spectrum with concentration at high frequencies. Findings are discussed in relation to previous literature on fricative production by speakers with hearing impairment and normal hearing in Greek and other languages. [ABSTRACT FROM AUTHOR]

The human tongue has been long believed to be a window to provide important insights into a patient's health in medicine. The present study introduced a novel approach to predict patient age, gender, and weight inferences based on tongue images using pretrained deep convolutional neural networks (CNNs). Our results demonstrated that the deep CNN models (e.g., ResNeXt) trained on dorsal tongue images produced excellent results for age prediction with a Pearson correlation coefficient of 0.71 and a mean absolute error (MAE) of 8.5 years. We also obtained an excellent classification of gender, with a mean accuracy of 80% and an AUC (area under the receiver operating characteristic curve) of 88%. ResNeXt model also obtained a moderate level of accuracy for weight prediction, with a Pearson correlation coefficient of 0.39 and a MAE of 9.06 kg. These findings support our hypothesis that the human tongue contains crucial information about a patient. This study demonstrated the feasibility of using the pretrained deep CNNs along with a large tongue image dataset to develop computational models to predict patient medical conditions for noninvasive, convenient, and inexpensive patient health monitoring and diagnosis. [ABSTRACT FROM AUTHOR]

Background: Nurses provide care to meet the complex needs of patients in the increasing workload in the health system and are at risk of compassion fatigue. The concept of compassion fatigue has begun drawing attention in the last decade, as it negatively affects nurses' physical and mental health, job performance and satisfaction, and therefore patient care quality. Objectives: This study was to examine compassion fatigue and predictive factors in paediatric surgery nurses. Participants and research context: The study was cross-sectional, predictive and quantitative. It was conducted with the 135 paediatric surgery nurses. The data were sent to the email addresses of the members via Google Survey. Research data were collected with the Nurse Information Form, Compassion Fatigue Scale, Life Satisfaction Scale and Multidimensional Perceived Social Support Scale. Ethical considerations: After obtaining the approval of the University's ethics committee, the study was carried out after obtaining participants' informed written and verbal consent. Results: There was a difference between the level of compassion fatigue according to the paediatric surgery unit that worked the longest and the thought of changing their profession. Burn unit nurses and nurses who were considering changing professions have higher compassion fatigue scores. When the predictors of compassion fatigue were examined, the thought of changing the nursing profession and life satisfaction were significant predictors of compassion fatigue. The thought of changing the nursing profession and life satisfaction explained 22% of compassion fatigue. The same variables and the longest working period of the paediatric surgery unit were the estimators of the level of occupational burnout; explaining 29% of occupational burnout. Conclusions: Compassion fatigue, life satisfaction and perceived social support of paediatric surgery nurses are moderate. Compassion fatigue is affected by working time, the thought of changing the profession, life satisfaction and perceived social support. [ABSTRACT FROM AUTHOR]

Introduction: Atezolizumab plus bevacizumab (Atez/Bev) is the preferred treatment for advanced hepatocellular carcinoma (HCC). However, biomarkers of therapeutic efficacy have remained unclear. We took a retrospective approach to explore the role of prognostic nutritional index (PNI) for predicting the outcomes of Atez/Bev treatment. Methods: One hundred 25 HCC patients were enlisted; these patients received Atez/Bev treatment and underwent dynamic computerized tomography/magnetic resonance imaging to determine the treatment response on at least one occasion between October 2020 and January 2023, and their PNI before treatment and at the beginning of the second cycle (PNI-2c) was evaluated. Results: During the initial evaluation, 2 (2%), 28 (22%), 70 (56%), and 25 (20%) patients exhibited a complete response, partial response, stable disease, and progressive disease (PD), respectively. Patients with non-PD tended to have higher PNI at baseline and PNI-2c than those with PD (p = 0.245 and 0.122, respectively), with optimal baseline PNI and PNI-2c cut-off values of 42.6 and 40.4, respectively. PNI at baseline could not be used to predict overall survival (OS) or progression-free survival (PFS). However, PNI-2c predicted OS and PFS (PNI-2c ≥ 40.4 vs. < 40.4: 25.3 vs. 16.2 months, p = 0.008 for OS; 12.7 vs. 8.4 months, p = 0.036 for PFS). A multivariate analysis showed a significant association between PNI-2c and OS. Conclusions: PNI-2c is a predictor of prognosis in HCC patients treated with Atez/Bev therapy. Plain Language Summary: Atezolizumab plus bevacizumab (Atez/Bev) is the preferred treatment for advanced hepatocellular carcinoma (HCC). However, biomarkers of therapeutic efficacy have remained unclear. We took a retrospective approach to explore the role of prognostic nutritional index (PNI) for predicting the outcomes of Atez/Bev treatment. 125 HCC patients were enlisted; these patients received Atez/Bev treatment and underwent dynamic computerized tomography/magnetic resonance imaging to determine the treatment response on at least one occasion between October 2020 and January 2023, and their PNI before treatment and at the beginning of the second cycle (PNI-2c) was evaluated. During the initial evaluation, 2 (2%), 28 (22%), 70 (56%), and 25 (20%) patients exhibited a complete response, partial response, stable disease, and progressive disease (PD), respectively. Patients with non-PD tended to have higher PNI at baseline and PNI-2c than those with PD (p = 0.245 and 0.122, respectively), with optimal baseline PNI and PNI-2c cut-off values of 42.6 and 40.4, respectively. PNI at baseline could not be used to predict overall survival (OS) or progression-free survival (PFS). However, PNI-2c predicted OS and PFS (PNI-2c ≥ 40.4 vs. < 40.4: 25.3 vs. 16.2 months, p = 0.008 for OS; 12.7 vs. 8.4 months, p = 0.036 for PFS). A multivariate analysis showed a significant association between PNI-2c and OS. Therefore, PNI-2c is a predictor of prognosis in HCC patients treated with Atez/Bev therapy. [ABSTRACT FROM AUTHOR]

Background: Sepsis is still one of the leading causes of mortality and morbidity in children worldwide. Consumptive coagulopathy and suppression of thrombopoiesis in the bone marrow resulting from immune dysregulation are pathological mechanisms that cause thrombocytopenia in sepsis. Platelet count (PLT) and indices, such as mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) are markers of platelet activation and are strongly influenced by platelet morphology and proliferation kinetics. We aimed to study the use of platelet count and indices as predictors of mortality in children with sepsis. Methods: This is a cross-sectional study of 45 children diagnosed with sepsis on admission at Haji Adam Malik Hospital, Medan, North Sumatra, Indonesia, between October and November 2022. Blood samples were drawn upon admission, and platelet count and indices were then determined for all children. Subjects were followed up till discharge from hospital or death. Receiver Operating Characteristic (ROC) curve analysis of platelet parameters was done to determine the area under the curve (AUC), optimal cut-off value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in predicting mortality in children with sepsis. Using the cut-off values from ROC curve analysis, the odds ratio with 95% confidence interval was calculated using multiple logistic regression analyses. A P value less than 0.05 was considered statistically significant. Results: MPV, PDW, and PDW/PLT were significantly higher in non-survivors than survivors (P=0.04, P=0.02, and P=0.04, respectively). ROC curve analysis showed that PDW had the largest AUC (0.708 [95% CI=0.549-0.866]) with a cut-off value of 14.1%, sensitivity of 63.6%, and specificity of 82.6%. PDW was also the only parameter that significantly affected the outcome of children with sepsis. PDW≥14.1% at admission increases the risk of mortality by 5.7 times. Conclusion: Admission PDW is a fast and specific tool to predict the outcome of children with sepsis. [ABSTRACT FROM AUTHOR]

The variability in outcomes among adult cochlear implant (CI) users poses challenges for clinicians in accurately predicting the benefits of the implant for individual candidates. This study aimed to investigate the accuracy and confidence of clinicians in predicting speech perception outcomes for adult CI users one-year post-implantation. Participants were presented with comprehensive information on pre-implantation, one-month post-implantation, and six-month post-implantation data for 10 case studies. The cases encompassed a range of one-year post-implantation phoneme scores, from low performers (27%) to high performers (92%). Participants were tasked with predicting the speech perception outcomes for these cases one year after implantation. Forty-one clinicians completed the full outcome prediction survey. Our findings revealed a significant over-prediction of low performance by clinicians. Interestingly, clinicians tended to predict average performance (73–76% phoneme score) even when provided with information suggesting lower-than-average performance. Most clinicians expressed confidence in their predictions, irrespective of their accuracy. Identifying signs of low performance, particularly in the early post-implantation period, can enable clinicians to implement early interventions. Further research into accurate outcome prediction is essential for managing expectations, providing counselling, increasing CI adoption, and optimising clinical care for both high and low performers. [ABSTRACT FROM AUTHOR]

The QuantiFERON CMV (QCMV) test evaluates specific adaptive immune system activity against CMV by measuring IFN-γ released by activated CD8+ T lymphocytes. We aimed to evaluate the QCMV test as a predictive tool for CMV manifestations and acute or chronic lung allograft rejection (AR and CLAD) in lung transplant (LTx) patients. A total of 73 patients were divided into four groups based on donor and recipient (D/R) serology for CMV and QCMV assay: group A low-risk for CMV infection and disease (D−/R−); group B and C at intermediate-risk (R+), group B with non-reactive QCMV and group C with reactive QCMV; group D at high-risk (D+/R−). Group D patients experienced higher viral replication; no differences were observed among R+ patients of groups B and C. D+/R− patients had a higher number of AR events and group C presented a lower incidence of AR. Prevalence of CLAD at 24 months was higher in group B with a higher risk of CLAD development (OR 6.33). The QCMV test allows us to identify R+ non-reactive QCMV population as the most exposed to onset of CLAD. This population had a higher, although non-significant, susceptibility to AR compared to the R+ population with reactive QCMV. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Adherence to medications is important for the management of chronic diseases. Although the proportion of days covered (PDC) is a common metric for measuring adherence, it may be insufficient to distinguish relevant differences in medication-taking behavior. Group-based trajectory models (GBTMs) have been used to better represent adherence over time. This study aims to examine adherence patterns 1 year after initiation among users of sodium-glucose cotransporter 2 (SGLT2) inhibitors using GBTMs and evaluate the ability of baseline characteristics to predict adherence trajectory. STUDY DESIGN: SGLT2 inhibitor new-user cohort study from 2014 to 2018. METHODS: We calculated 12-month PDC and categorized patients with PDC of 80% or greater as adherent. We performed multivariable logistic regression on adherence status controlling for baseline covariates. GBTMs were fit to identify adherence patterns 12 months following SGLT2 inhibitor initiation. Five multinomial logistic regression models including different subsets of predictors were used to predict adherence trajectory group assignment. RESULTS: In a cohort of 228,363 SGLT2 inhibitor users, the mean PDC was 57%, with 36% of the cohort being adherent. Overall, women and patients with anxiety or depression were less likely to be adherent. Six patterns of SGLT2 inhibitor adherence were identified with GBTMs: 1 fill (PDC = 0.08), early discontinuation (PDC = 0.22), consistently low adherence (PDC = 0.35), moderate adherence (PDC = 0.48), high adherence (PDC = 0.79), and near-perfect adherence (PDC = 0.95). All prediction models showed poor predictive accuracy (0.35). CONCLUSIONS: We found wide variation in adherence patterns among SGLT2 inhibitor users in a national cohort. Predictors from a health care claims database were unable to accurately predict adherence trajectory. [ABSTRACT FROM AUTHOR]

This paper describes some statistical tests for comparing the predictive performance of two or more prediction rules. It covers the cases of both quantitative and qualitative predictions, that is, both regression and classification problems. Worked examples are included for both cases. This paper describes some statistical tests for comparing the predictive performance of two or more prediction rules. It covers the cases of both quantitative and qualitative predictions, that is, both regression and classification problems. [ABSTRACT FROM AUTHOR]

Introduction: New tools have been developed to distinguish the COVID‐19 diagnosis from other viral infections presenting similar symptomatology and mitigate the lack of sensitivity of molecular testing. We previously identified a specific "sandglass" aspect on the white blood cells (WBC) scattergram of COVID‐19 patients, as a highly reliable COVID‐19 screening test (sensitivity: 85.9%, specificity: 83.5% and positive predictive value: 94.3%). We then decided to validate our previous data in a multicentric study. Methods: This retrospective study involved 817 patients with flu‐like illness, among 20 centers, using the same CBC instrument (XN analyzer, SYSMEX, Japan). After training, one specialist per center independently evaluated, under the same conditions, the presence of the "sandglass" aspect of the WDF scattergram, likely representing plasmacytoid lymphocytes. Results: Overall, this approach showed sensitivity: 59.0%, specificity: 72.9% and positive predictive value: 77.7%. Sensitivity improved with subgroup analysis, including in patients with lymphopenia (65.2%), patients presenting symptoms for more than 5 days (72.3%) and in patients with ARDS (70.1%). COVID‐19 patients with larger plasmacytoid lymphocyte cluster (>15 cells) more often have severe outcomes (70% vs. 15% in the control group). Conclusion: Our findings confirm that the WBC scattergram analysis could be added to a diagnostic algorithm for screening and quickly categorizing symptomatic patients as either COVID‐19 probable or improbable, especially during COVID‐19 resurgence and overlapping with future influenza epidemics. The observed large size of the plasmacytoid lymphocytes cluster appears to be a hallmark of COVID‐19 patients and was indicative of a severe outcome. Furthers studies are ongoing to evaluate the value of the new hematological parameters in combination with WDF analysis. [ABSTRACT FROM AUTHOR]