Discriminatory Capacity Research Articles

Addressing racial disparities in prostate cancer pathology prediction models: external validation and comparison of four models of pathological outcome prediction before radical prostatectomy in the multiethnic SEARCH cohort.

Certain widely used pathological outcome prediction models that were developed in tertiary centers tend to overpredict outcomes in the community setting; thus, the Michigan Urological-Surgery Improvement Collaborative (MUSIC) model was developed in general urology practice to address this issue. Additionally, the development of these models involved a relatively small proportion of Black men, potentially compromising the accuracy of predictions in this patient group. We tested the validity of the MUSIC and three widely used nomograms to compare their overall and race-stratified predictive performance. We extracted data from 4139 (1138 Black) men from the Shared Equal Access Regional Cancer Hospital (SEARCH) database of the Veterans Affairs health system. The predictive performance of the MUSIC model was compared to the Memorial-Sloan Kettering (MSK), Briganti-2012, and Partin-2017 models for predicting lymph-node invasion (LNI), extra-prostatic extension (EPE), and seminal vesicle invasion (SVI). The median PSA of Black men was higher than White men (7.8 vs. 6.8 ng/ml), although they were younger by a median of three years and presented at a lower-stage disease. MUSIC model showed comparable discriminatory capacity (AUC:77.0%) compared to MSK (79.2%), Partin-2017 (74.6%), and Briganti-2012 (76.3%), with better calibration for LNI. AUCs for EPE and SVI were 72.7% and 76.9%, respectively, all comparable to the MSK and Partin models. LNI AUCs for Black and White men were 69.6% and 79.6%, respectively, while EPE and SVI AUCs were comparable between races. EPE and LNI had worse calibration in Black men. Decision curve analysis showed MUSIC superiority over the MSK model in predicting LNI, especially among Black men. Although the discriminatory performance of all models was comparable for each outcome, the MUSIC model exhibited superior net benefit to the MSK model in predicting LNI outcomes among Black men in the SEARCH population.

Exploring the influence of microbiota on gestational diabetes and its potential as a biomarker

Gestational diabetes mellitus (GDM) represents a significant health concern during pregnancy, impacting both maternal and fetal well-being. While conventional diagnostic protocols typically rely on blood glucose levels in the latter stages of pregnancy, there is a pressing need for early detection methods to mitigate potential risks. A plethora of glucose-based or non-glucose-based biomarkers have been investigated for their potential to predict GDM in early pregnancy. Though specific biomarkers showed promise in predicting GDM, their clinical usage has been constrained by the lack of validation and limitation in translating them into routine clinical use. This review aims to highlight and discuss the potential and practical utility of existing biomarkers and emergent biomarkers, such as microbiomes, in diagnosing GDM. A comprehensive analysis of recent studies reveals significant alterations in the composition and diversity of microbiota among women with GDM, suggesting their potential utility as predictive markers for this condition. For instance, distinct microbial profiles characterized by an increased abundance of Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136, alongside decreased levels of Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002, correlated with fasting blood glucose levels, hinting at their relevance in early GDM detection. Furthermore, proposed microbiota-targeted panels demonstrated promising predictive accuracy. Beyond gut microbiota, recent investigations have also explored the potential of oral microbiota as predictive biomarkers for GDM. Studies have highlighted the discriminatory capacity of specific oral microbes, such as Streptococcus in saliva and Leptotrichia in dental plaque, in distinguishing GDM from healthy pregnancies. Moreover, the examination of gut microbiota-derived metabolites has shown promising results in serum-based GDM prediction. These findings collectively underscore the potential of microbiota and its metabolites as valuable biomarkers for the early detection of GDM. However, further research is warranted to elucidate the mechanistic links between microbial dysbiosis and GDM pathogenesis, ultimately facilitating the development of targeted therapeutic interventions and personalized management strategies.

Molecular networking-based mass spectral identification of Brucea javanica (L.) Merr. metabolites and their selective binding affinities for dengue virus enzymes

Brucea javanica, a valued traditional medicinal plant in Malaysia, known for its fever-treating properties yet remains underexplored for its potential antiviral properties against dengue. This study aims to simultaneously identify chemical classes and metabolites within B. javanica using molecular networking (MN), by Global Natural Product Social (GNPS), and SIRIUS in silico annotation. Liquid chromatography-mass spectrometry (LC-MS2)-based MN explores chemical diversity across four plant parts (leaves, roots, fruits, and stem bark), revealing diverse metabolites such as tryptophan-derived alkaloids, terpenoids, and octadecadenoids. Simultaneous LC-MS2 and MN analyses reveal a discriminative capacity for individual plant components, with roots accumulating tryptophan alkaloids, fruits concentrating quassinoids, leaves containing fusidanes, and stem bark primarily characterised by simple indoles. Subsequently, extracts were evaluated for dengue antiviral activity using adenosine triphosphate (ATP) and plaque assays, indicates potent efficacy in the dichloromethane (DCM) extract from roots (EC50 = 0.3 μg/mL, SI = 10). Molecular docking analysis of two major compounds; canthin-6-one (264) and 1-hydroxy-11-methoxycanthin-6-one (275) showed potential binding interactions with active sites of NS5 RNA-dependent RNA polymerase (RdRp) of dengue virus (DENV) protein. Subsequent in vitro evaluation revealed compounds 264 and 275 had a promising dengue antiviral activity with SI value of 63 and 1.85. These identified metabolites emerge as potential candidates for further evaluation in dengue antiviral activities.

Resilience Scale (RS-14): Psychometric Study in a Population of Young People from Lima and Callao

The Resilience Scale (RS-14) instrument assesses an individual's level of resilience when facing adverse life situations. This study aimed to examine the psychometric properties of the RS-14 in a sample of young adults from Lima and Callao, aged 18 to 29 years old. Initially, a statistical analysis of the items was conducted, revealing satisfactory normality criteria and discriminative capacity. Subsequently, validity evidence was obtained through Confirmatory Factor Analysis (CFA), demonstrating a good fit (χ²/df = 1.47, CFI = .94, TLI = .92, SRMR = .04, and RMSEA = .04). Finally, reliability was assessed using both Alpha and Omega coefficients, yielding values of α = .91 and ω = .92, respectively, considered acceptable. In conclusion, the RS-14 is considered a valid and reliable scale for future research endeavors in this domain.

Comparison of two serological diagnosis tests for bovine paratuberculosis.

Mycobacterium avium subsp. paratuberculosis (MAP) is the causal agent of paratuberculosis (PTBC), a chronic infectious granulomatous enteritis of ruminants. The PTBC diagnosis with commercial ELISA has limitations in sensitivity and specificity, and its results depend on the state of progress of the disease. This research aimed to evaluate two different ELISAs: (a) an "in-house" ELISA with a sonicated antigen obtained from a MAP I47 strain, and (b) a commercial ELISA. In total, the evaluated sample consisted of 394 bovine serum samples from 12 farms in Argentina with high (5-9%) and low (≤ 0.05%) prevalence of PTBC. The evaluation of the new antigen (2.5µg/mL) was against a 1:50 dilution of the M. phlei faced sera. The cut-off point, sensitivity, and specificity determinations of both techniques were by ROC curve analysis. The area under the curve for the I47 ELISA was 0.9 (CI 95%, 0.93-0.97). With a cut-off point of 8.8%, the sensitivity was 84.3% and the specificity 96.6%. The agreement between both techniques was 0.7 (CI 95%, 0.6-0.8). These results indicate a high discriminative capacity to differentiate positive and negative bovine sera of MAP infection with the I47 ELISA. This result would represent an advantage to dispense with the imported kit.

Improving the ability to discriminate medical multiple-choice questions through the analysis of the competitive examination to assign residency positions in Spain

IntroductionPsychometrics plays a vital role in evaluating educational research, including the analysis of multiple-choice exams. This study aims to improve the discriminatory ability of the “Médico Interno Residente” (MIR) medical exam in Spain, used to rank candidates for specialized healthcare training, through psychometric analysis.MethodsWe analyzed 2,890 MIR exam questions from 2009 to 2021 (totaling 147,214 exams), categorizing them based on methodology and response type. Evaluation employed classical test theory and item response theory (IRT). Classical test theory determined difficulty and discrimination indices, while IRT assessed the relationship between knowledge levels and question performance.ResultsQuestion distribution varied across categories and years. Frequently addressed knowledge areas included various medical specialties. Non-image-associated clinical cases were the easiest, while case-based clinical questions exhibited the highest discriminatory capacity, differing significantly from image-based case or negative questions. High-quality questions without images had longer stems but shorter answer choices. Adding images reduced discriminatory power and question difficulty, with image-based questions being easier. Clinical cases with images had shorter stems and longer answer choices.ConclusionsFor improved exam performance, we recommend using a clinical case format followed by direct short-answer questions. Questions should be of low difficulty, providing clear and specific answers based on scientific evidence and avoiding ambiguity. Typical clinical cases with key characteristic features should be presented, excluding uncertain boundaries of medical knowledge. Questions should have lengthy stems and concise answer choices, minimizing speculation. If images are used, they should be typical, clear, consistent with the exam, and presented within clinical cases using clinical semiotics and propaedeutics.

Haplotype diversity of 17 Y-STR in the Iranian population

The current study aimed to evaluate Y chromosome haplotypes obtained from 1353 unrelated Iranian males using the AmpFlSTRTM YfilerTM kit; 1353 out of the 1353 identified haplotypes were unique. The haplotype diversity (HD) and discriminating capacity (DC) values were 1.00000 and 0.997, respectively. Analysis of genetic distance was performed using molecular variance (AMOVA) and multidimensional scaling plots (MDS), revealing a statistically significant difference between the study population and previous data reported for other Iranian populations and other neighboring countries. The present findings are likely to be useful for forensic casework analyses and kinship investigations.

Predictive effect of estimated glomerular filtrate rate by creatinine or cystatin C on mortality in patients with coronary artery disease

Background Renal dysfunction leads to poor prognosis of patients with coronary artery disease (CAD). Current studies have reported the prognosis or mortality of various diseases using different estimated glomerular filtrate rate (eGFR) formulas, while the performance of these equations is unclear in CAD patients. We aim to evaluate the predict effect of creatinine-based eGFR (eGFRcr), cystatin C-based eGFR (eGFRcys), and both creatinine and cystatin C-based eGFR (eGFRcr-cys) in CAD patients. Methods A total of 23,178 patients with CAD were included from CIN-II cohort study. The association of eGFRcr, eGFRcys and eGFRcr-cys with cardiovascular and all-cause mortality was detected by Cox regression analysis. The predictive effect of eGFRcr, eGFRcys and eGFRcr-cys on mortality was assessed. Results During a median follow up of 4.3 years, totally 2051 patients (8.8%) experience all-cause mortality, of which 1427 patients (6.2%) died of cardiovascular disease. For the detection of cardiovascular mortality among CAD patients, eGFRcr-cys had high discriminatory capacity with area under the curve (AUC) in receiver operator characteristic analysis of 0.730, which was significantly better than eGFRcr (AUC = 0.707, p < 0.001) and eGFRcys (AUC = 0.719, p < 0.001). Similar results were observed in all-cause mortality. Restricted cubic spline showed a U-shaped association between eGFRcr and all outcomes in patients with both reduced and supranormal eGFR levels, while a L-shaped association in eGFRcys and eGFRcr-cys. Conclusions Estimated GFR based on both creatinine and cystatin C has highest predictive effect for cardiovascular and all-cause mortality among CAD patients. Meanwhile, supranormal eGFRcr may indicate a higher risk of mortality.

Genetic Evaluation for Stability of Grain Yield and Yield Components in Foxtail Millet Using GGE Biplot in Foothills of Nagaland

Aims: Foxtail millet cultivation in India's North Eastern Hill region holds promise due to its adaptation to diverse environments and high-quality grain. Studying G x E interaction in this region will guide breeding programs to develop foxtail millet varieties adapted to local conditions. The objective of this study was to find out foxtail millet genotypes that produce high yield in diverse environments and to identify ideal mega-environments using GGE Biplot stability model analysis. Methods: The investigation was carried out during July 2022 to May 2023 for four different dates of sowing with twenty-five days interval. Two environments maintained under rained condition and the remaining two environments are maintained under irrigated condition. The experiment was conducted in randomized complete block design with three replications in all environments. Results: Analysis of variance revealed statistically significant differences (at 5%) among the 30 genotypes for all yield variables under evaluated. Genotype ‘G1’ exhibited superior performance for both yield and yield-related traits.In this study, four GGE biplots of GY, one is Discriminativeness and representativeness in GGE biplots revealed E4 is identified as the most representative environment. At the same time, E3 also stands out for its strong discriminative capacity. Another one is Which Own Where" biplots revealed that G19 and G27 displayed superior and stable performance in E1. Similarly, G25 and G1 excelled in E2, E3, and E4. while mean vs stability biplots revealed that G1 is stable and performs well. Conclusion: Genotypes, namely G1, G22, G25, and G21, exhibited stable and reliable performance across different conditions.

Quebec French Translation, Cultural Adaptation, and Validation of the Singing Voice Handicap Index-10 Questionnaire for Singers with Dysphonia

OBJECTIVES/HYPOTHESISDysphonia is a common voice disorder that can significantly impact a person’s life; it requires a collaborative evaluation by both speech-language pathologists and otolaryngologists that takes the patient’s perspective into account. The aim of this study was to translate and culturally adapt the Singing Voice Handicap Index questionnaire (SVHI-10), a reliable patient-reported outcome evaluation tool for dysphonia, for the Quebec French population. The result is the Singing Voice Handicap Index-10-QC (SVHI-10-QC). STUDY DESIGNThis study was a prospective translation and validation process. METHODSThe translation process complied with international recommendations and followed a standard forward-backward translation procedure and cognitive debriefing with ten singers. The Quebec French version was administered to two study samples: 30 vocal professionals with no dysphonia and 53 vocal professionals with dysphonia as one of their primary complaints. The SVHI-10-QC was assessed for construct validity, internal consistency, discriminatory capacity, and test-retest reliability. RESULTSThe SVHI-10-QC is valid, reliable, and ready for use with singer-patients suffering from dysphonia. CONCLUSIONSThe SVHI-10-QC is a reliable and valid tool for assessing the impact of dysphonia on French Quebec singers’ quality of life.

Longitudinal Assessment of ROX and HACOR Scores to Predict Non-Invasive Ventilation Failure in Patients with SARS-CoV-2 Pneumonia.

NIV (Non-invasive ventilation) and HFNC (High Flow nasal cannula) are being used in patients with acute respiratory failure. HACOR score has been exclusively calculated for patients on NIV, on other hand ROX index is being used for patients on HFNC. This is first study where ROX index has been used in patients on NIV to predict failure. This study investigates the comparative diagnostic performance of HACOR score and ROX index to predict NIV failure. We performed a retrospective cohort study of non-invasively ventilated COVID-19 patients admitted between 1st April 2020 to 15th June 2021 to ICU of a tertiary care teaching hospital located in Central India. We assessed factors responsible for NIV failure, and whether these scores HACOR/ROX index have discriminative capacity to predict risk of invasive mechanical ventilation. Of the 441 patients included in the current study, 179 (40.5%) recovered, while remaining 262 (59.4%) had NIV failure. On multivariable analysis, ROX index > 4.47 was found protective for NIV-failure (OR 0.15 (95% CI 0.03-0.23; p<0.001). Age > 60 years and SOFA score were other significant independent predictors of NIV-failure. The AUC for prediction of failure rises from 0.84 to 0.94 from day 1 to day 3 for ROX index and from 0.79 to 0.92 for HACOR score in the same period, hence ROX score was non-inferior to HACOR score in current study. DeLong's test for two correlated ROC curves had insignificant difference expect day-1 (D1: 0.03 to 0.08; p=3.191e-05, D2: -0.002 to 0.02; p = 0.2671, D3: -0.003 to 0.04; p= 0.1065). ROX score of 4.47 at day-3 consists of good discriminatory capacity to predict NIV failure. Considering its non-inferiority to HACOR score, the ROX score can be used in patients with acute respiratory failure who are on NIV.

Analysis of network expression and immune infiltration of disulfidptosis-related genes in chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a globally prevalent respiratory disease, and programmed cell death plays a pivotal role in the development of COPD. Disulfidptosis is a newly discovered type of cell death that may be associated with the progression of COPD. However, the expression and role of disulfidptosis-related genes (DRGs) in COPD remain unclear. The expression of DRGs was identified by analyzing RNA sequencing (RNA-seq) data in COPD. Further, COPD patients were classified into two subtypes by unsupervised cluster analysis to reveal their differences in gene expression and immune infiltration. Meanwhile, hub genes associated with disulfidptosis were screened by weighted gene co-expression network analysis. Subsequently, the hub genes were validated experimentally in cells and animals. In addition, we screened potential therapeutic drugs through the hub genes. We identified two distinct molecular clusters and observed significant differences in immune cell populations between them. In addition, we screened nine hub genes, and experimental validation showed that CDC71, DOHH, PDAP1, and SLC25A39 were significantly upregulated in cigarette smoke-induced COPD mouse lung tissues and bronchial epithelial cells (BEAS-2B) treated with cigarette smoke extract. Finally, we predicted 10 potential small molecule drugs such as Atovaquone, Taurocholic acid, Latamoxef, and Methotrexate. We highlighted the strong association between COPD and disulfidptosis, with DRGs demonstrating a discriminative capacity for COPD. Additionally, the expression of certain novel genes, including CDC71, DOHH, PDAP1, and SLC25A39, is linked to COPD and may aid in the diagnosis and assessment of this condition.

A Questionnaire of Artificial Intelligence Use Motives: A Contribution to Investigating the Connection between AI and Motivation

This study introduces the Questionnaire of AI Use Motives (QAIUM), an instrument designed to measure motivation levels in individuals using artificial intelligence (AI) applications. Building on a theoretical framework that emphasizes motivation over dispositions and defines motivation as expectancy/value, the QAIUM aims to fill a research gap in understanding the motivational factors that govern AI application use. Previous studies have often overlooked this human aspect, focusing instead on technological facets while failing to provide a robust theoretical foundation for measuring motivation. The QAIUM, administered to 1068 university students across various degree programs, was evaluated for its factorial structure, reliability, discriminatory capacity, and correlation with the General Attitudes to Artificial Intelligence Scale (GAAIS). The results demonstrate that the QAIUM aligns with the Eccles and Wigfield motivation model, boasts good reliability levels, discriminatory capacity, and a significant correlation with GAAIS, confirming its validation and reliability. Hence, the QAIUM provides an effective tool for investigating motivational factors affecting AI application utilization in academic instruction and intervention.

External Validation of the Oakland Score for Acute Lower Gastrointestinal Bleeding.

Introduction Acute lower gastrointestinal bleeding (LGIB) presents challenges in emergency settings, with incidence influenced by demographic shifts and anticoagulant usage. The Oakland score aids in risk stratification for safe discharge based on clinical and laboratory parameters. However, external validation remains limited. Methods This study validated the Oakland score in a French cohort of patients with acute LGIB and assessed the discriminatory value of the score using the area under the curve (AUC) and then its sensitivity and specificity. Results A retrospective examination of 343 patient records that satisfied the inclusion criteria showed a median score of 14 points and good discriminatory capacity (area under the receiver operating characteristic (AUROC) curve: 0.83). There was low sensitivity (20.9%) for safe discharge but good specificity (98.5%) when using an 8-point threshold. With a 9-point threshold, the sensitivity was increased to 36.5%, while the specificity remained at 95%. Conclusion Identifying low-risk LGIB patients is accomplished without sacrificing sensitivity by increasing the Oakland score threshold to 9 points. This modification improves patient safety and resource allocation in the emergency room and has been verified by other large series. For wider implementation, additional validation and long-term outcome evaluations are required.

Global semantic-guided graph attention network for Siamese tracking with ranking loss

Most Siamese trackers based on graph attention models focus on the topology between nodes when extracting features. These approaches ignore contextual information regarding the overall structure of the target, resulting in a diminished capacity for target discrimination. In this paper, to resolve this issue, we propose a global semantic-guided graph attention network for Siamese tracking. Firstly, in order to balance the node constraints with the overall information of the target, a global semantic awareness module (GSA) is proposed. It utilizes the attention strategy to focus on the overall characteristics of the target, aiming to mine the relationship of the target context. Incorporating it into the semantic-guided graph attention network through cross-correlation operations can avoid the problem of focusing only the information between nodes without being able to effectively characterize the target. Secondly, to enhance the accuracy of single-point feature regression results, a novel extreme point feature aggregation module (EPA) is proposed. We obtain feature information of the extreme points on the bounding box and combine them with single-point features for the bounding box feature representation to improve the regression accuracy. Finally, to establish a connection or bridge between the classification and regression subnetworks, a categorical regression alignment network is designed. An IOU-guided ranking loss is introduced to align the classification confidence with the IOU of the corresponding positive sample localization prediction to solve the problem of misalignment of the classification branch with the regression branch effectively. Experiments conducted on five challenging benchmarks datasets, namely GOT-10K, OTB-100, LaSOT, UAV123, and TC128, demonstrate that our approach exhibits superior performance compared to other tracking methods in terms of tracking accuracy and execution efficiency.

Combined use of QRISK3 and SCORE2 increases identification of ankylosing spondylitis patients at high cardiovascular risk: Results from the CARMA Project cohort after 7.5 years of follow-up

ObjectiveTo establish the predictive value of the QRESEARCH risk estimator version 3 (QRISK3) algorithm in identifying Spanish patients with ankylosing spondylitis (AS) at high risk of cardiovascular (CV) events and CV mortality. We also sought to determine whether to combine QRISK3 with another CV risk algorithm: the traditional SCORE, the modified SCORE (mSCORE) EULAR 2015/2016 or the SCORE2 may increase the identification of AS patients with high-risk CV disease. MethodsInformation of 684 patients with AS from the Spanish prospective CARdiovascular in ReuMAtology (CARMA) project who at the time of the initial visit had no history of CV events and were followed in rheumatology outpatient clinics of tertiary centers for 7.5 years was reviewed. The risk chart algorithms were retrospectively tested using baseline data. ResultsAfter 4,907 years of follow-up, 33 AS patients had experienced CV events. Linearized rate=6.73 per 1000 person-years (95 % CI: 4.63, 9.44). The four CV risk scales were strongly correlated. QRISK3 correctly discriminated between people with lower and higher CV risk, although the percentage of accumulated events over 7.5 years was clearly lower than expected according to the risk established by QRISK3. Also, mSCORE EULAR 2015/2016 showed the same discrimination ability as SCORE, although the percentage of predicted events was clearly higher than the percentage of actual events. SCORE2 also had a strong discrimination capacity according to CV risk. Combining QRISK3 with any other scale improved the model. This was especially true for the combination of QRISK3 and SCORE2 which achieved the lowest AIC (406.70) and BIC (415.66), so this combination would be the best predictive model. ConclusionsIn patients from the Spanish CARMA project, the four algorithms tested accurately discriminated those AS patients with higher CV risk and those with lower CV risk. Moreover, a model that includes QRISK3 and SCORE2 combined the best discrimination ability of QRISK3 with the best calibration of SCORE2.

Evaluation of metabolomics-based urinary biomarker models for recognizing major depression disorder and bipolar disorder

BackgroundMajor depressive disorder (MDD) and bipolar disorder (BD) are psychiatric disorders with overlapping symptoms, leading to high rates of misdiagnosis due to the lack of biomarkers for differentiation. This study aimed to identify metabolic biomarkers in urine samples for diagnosing MDD and BD, as well as to establish unbiased differential diagnostic models. MethodsWe utilized a metabolomics approach employing ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) to analyze the metabolic profiles of urine samples from individuals with MDD (n = 50), BD (n = 12), and healthy controls (n = 50). The identification of urine metabolites was verified using MS data analysis tools and online metabolite databases. ResultsTwo diagnostic panels consisting of a combination of metabolites and clinical indicators were identified—one for MDD and another for BD. The discriminative capacity of these panels was assessed using the area under the receiver operating characteristic (ROC) curve, yielding an area under the curve (AUC) of 0.9084 for MDD and an AUC value of 0.9017 for BD. ConclusionsHigh-resolution mass spectrometry-based assays show promise in identifying urinary biomarkers for depressive disorders. The combination of urine metabolites and clinical indicators is effective in differentiating healthy controls from individuals with MDD and BD. The metabolic pathway indicating oxidative stress is seen to significantly contribute to depressive disorders.

Impact of Molecular Subgroups on Prognosis and Survival Outcomes in Posterior Fossa Ependymomas: A Retrospective Study of 412 Cases.

Posterior fossa ependymomas (PFEs) are rare brain tumors classified as PF-EPN-A (PFA) and PF-EPN-B (PFB) subgroups. The study aimed to evaluate the prognosis and survival outcomes in PFEs, with a focus on the impact of molecular subgroups. A retrospective study was conducted on 412 patients with PFEs. Kaplan-Meier survival analyses were conducted to evaluate the overall survival (OS) and progression-free survival. Cox regression analyses were conducted to assess the prognostic factors. A nomogram was developed to predict the OS rates of PFEs. The study revealed significant differences between PFA and PFB in patient and tumor characteristics. PFAs were associated with poorer OS (hazard ratios [HR] 3.252, 95% CI 1.777-5.950, P < .001) and progression-free survival (HR 4.144, 95% CI 2.869-5.985, P < .001). World Health Organization grade 3 was associated with poorer OS (HR 2.389, 95% CI 1.236-4.617, P = .010). As for treatment patterns, gross total resection followed by radiotherapy or the combination of radiotherapy and chemotherapy yielded the most favorable OS for PFA ( P = .025 for both), whereas gross total resection followed by radiotherapy rather than observation showed improved OS for PFB ( P = .046). The nomogram demonstrated a high degree of accuracy and discrimination capacity for the prediction of OS rates for up to 10 years. In addition, 6 cases of PFA (3.51%) with H3K27M mutations were identified. PFAs demonstrate worse prognosis and survival outcomes compared with PFBs. Both PFAs and PFBs necessitate maximal resection followed by intensive adjuvant therapies in long-term effects.

Venous blood gases in the assessment of respiratory failure in patients undergoing sleep studies: a randomized study.

Venous blood gases (VBGs) are not consistently considered suitable surrogates for arterial blood gases (ABGs) in assessing acute respiratory failure due to variable measurement error. The physiological stability of patients with chronic ventilatory failure may lead to improved agreement in this setting. Adults requiring ABGs for sleep or ventilation titration studies had VBGs drawn before or after each ABG, in a randomized order. Veno-arterial correlation and agreement were examined for carbon dioxide tension (PCO2), pH, oxygen tension (PO2), and oxygen saturation (SO2). We analyzed 115 VBG-ABG pairs from 61 patients. Arterial and venous measures were correlated (P < .05) for PCO2 (r = .84) and pH (r = .72), but not for PO2 or SO2. Adjusted mean veno-arterial differences (95% limits of agreement) were +5.0 mmHg (-4.4 to +14.4) for PCO2; -0.02 (-0.09 to +0.04) for pH; -34.3 mmHg (-78.5 to +10.0) for PO2; and -23.9% (-61.3 to +13.5) for SO2. VBGs obtained from the dorsal hand demonstrated a lower mean PCO2 veno-arterial difference (P < .01). A venous PCO2 threshold of ≥ 45.8 mmHg was > 95% sensitive for arterial hypercapnia, so measurements below this can exclude the diagnosis without an ABG. A venous PCO2 threshold of ≥ 53.7 mmHg was > 95% specific for arterial hypercapnia, so such readings can be assumed diagnostic. The area under the receiver operating characteristic curve of 0.91 indicated high discriminatory capacity. A venous PCO2 < 45.8 mmHg or ≥ 53.7 mmHg would exclude or diagnose hypercapnia, respectively, in patients referred for sleep studies, but VBGs are poor surrogates for ABGs where precision is important. Registry: Australian New Zealand Clinical Trials Register; Name: A comparison of arterial and blood gas analyses in sleep studies; URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372717; Identifier: ACTRN12617000562370. Lindstrom SJ, McDonald CF, Howard ME, etal. Venous blood gases in the assessment of respiratory failure in patients undergoing sleep studies: a randomized study. J Clin Sleep Med. 2024;20(8):1259-1266.

Nomogram for customized recurrence prediction in primary non-muscle-invasive bladder cancer based on routine blood and urine parameters

PurposeA prevalent condition with a high probability of recurrence, non-muscle invasive bladder cancer (NMIBC) necessitates lifetime surveillance. In patients with pathologically confirmed NMIBC, our goal was to create a unique nomogram to predict recurrence after transurethral resection of bladder tumor (TURBT).MethodsOur institution’s 91 NMIBC patients with complete follow-up data between January 2017 and February 2021 were included in the retrospective analysis. The nomogram predicting the 0.5, 1, 2 and 3-year likelihood of recurrence was created using multivariate Cox proportional hazard models to find the significant determinants of recurrence. Using the concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curves, and decision curve analyses (DCA), we internally validated the nomogram.ResultsThe significant factors related to NMIBC recurrence were age, blood platelet count, especially for the urine leukocyte count and mucus filament. The constructed nomogram performed well in the customized prediction of NMIBC recurrence at 6th, 12th, 24th and 36th month, of which the C-index was 0.724. The calibration curve and the ROC curve both validated the prediction accuracy. On DCA, the nomogram presented good net benefit gains across a wide range of threshold probabilities. Furthermore, the Nomogram-related risk score was used to divide the patient population into two groups with significant recurrence disparities.ConclusionFor the prediction of NMIBC recurrence, our unique nomogram demonstrated a respectable degree of discriminative capacity, sufficient calibration, and considerable net benefit gain. There will be a need for additional internal and external validation.