Curve Area Research Articles

Distinguishing glioblastoma from brain metastasis; a systematic review and meta-analysis on the performance of machine learning

Abstract Background The discrimination of glioblastoma and solitary metastasis brain tumor is challenging. Up now, several conventional and advanced imaging modalities were used for distinguishing between these tumors with different success rates. We systematically reviewed the studies reported the performance of machine learning (ML) algorithms for accurately discrimination of these two entities. Method The search was conducted from inception to 1 June, 2023, in PubMed/Medline, Embase, Scopus, and Web of Science to find out the studies investigated the performance of ML-based algorithm for differentiation of glioblastoma and metastatic brain tumor. Results This study included 28 studies comprising a total of 2,860 patients. The meta-analysis model results revealed a pooled sensitivity and specificity estimate of 0.83 [0.80–0.86] and 0.87 [0.83–0.90], respectively, indicating a commendable overall diagnostic accuracy across all the studies. ResNet50 and ResNet50-LSTM have shown promising results with single-study sensitivities of up to 88.9% and 88.2%, respectively. Furthermore, the integration of CNNs and RNNs has demonstrated improved performance compared to standalone models in a significant portion of the studies. The ROC curve area was 0.90, indicating high discriminative ability. The positive likelihood ratio was 6.2, and the negative likelihood ratio was 0.20, providing helpful information on how test results modified pretest probability. Conclusion ML applied to routine neuroimaging shows high diagnostic potential for glioblastoma detection. While more research is needed before clinical deployment, preliminary results are encouraging.

Validated Integration of Tumor Deposits in N Staging for Prognostication in Colon Cancer.

Tumor deposits have prognostic value in colon cancer, but the current American Joint Committee on Cancer (AJCC) staging only considers them if there are no concurrent positive lymph nodes. To devise a staging system for colon cancer by integrating counts of tumor deposits with positive lymph nodes while retaining the current AJCC staging framework. This retrospective cohort study examines data from a large-volume, tertiary care center database (January 2010 through March 2023 with follow-up until December 2023) and the population-based National Cancer Database (January 2010 through December 2020 with follow-up until December 2021). Participants were adults (age 18-75 years) with stage III colon adenocarcinoma who underwent chemotherapy, and had a specified positive lymph node count and tumor deposit count were selected. A real positive lymph nodes count was developed and used to derive Sassun-Mayo N/tumor, lymph node, and metastasis (TNM) stages that were compared with the AJCC N/TNM stages. Receiver operating characteristic (ROC) curves and Kaplan-Meier analyses for 3-year overall survival were performed to assess the efficiency of the 2 staging systems. The concordance index was used for validation using the National Cancer Database. From a total patient number of 11 162 (institutional) and 848 704 (national), the final patient numbers were 788 and 77 790, respectively. The institutional database patients had a mean (SD) age of 58.5 (11.5) years; there were 433 male patients (54.9%) and 355 female (45.1%). The national database patients had a mean (SD) age of 59.3 (10.6) years; there were 40 315 male patients (51.8%) and 37 475 female (48.2%). ROC curve areas were improved using the Sassun-Mayo stages (3-year death for AJCC TMN, 0.63 [95% CI, 0.57-0.69] vs 0.66 [95% CI, for 0.60-0.72] for Sassun-Mayo TNM). Kaplan-Meier curves revealed visible overlaps among AJCC N stages, which were absent in the Sassun-Mayo N stages. The concordance index in the Sassun-Mayo N/TNM stages was 0.611 and 0.616, respectively, while in the AJCC N/TNM stages, it was 0.598 and 0.606, respectively. Patients upstaged from N1 to N2 (n = 10 307; 13.2%) had a 3-year overall survival rate nearly identical to that of AJCC N2a patients. Additionally, 3001 patients (3.9%) were upstaged from N2a to N2b, indicating that 13 308 patients (17.1%) with stage III colon cancer across cohorts were understaged. This study found that Sassun-Mayo N/TNM staging provided superior overall survival stratification compared with the current AJCC staging, suggesting that their implementation could improve prognostication in colon cancer.

Echocardiographic evaluation of the size of the main pulmonary artery and right pulmonary artery in dogs with pulmonary hypertension.

Evaluating the size of the pulmonary artery (PA) is key for the echocardiographic assessment of pulmonary hypertension (PH) in dogs. To compare the diagnostic accuracy of the main PA (MPA) and right PA (RPA) sizes for the echocardiographic detection of PH in dogs, and to evaluate differences between precapillary and postcapillary PH dogs. Four hundred four dogs; 136 controls and 268 with PH. Prospective, multicenter, observational study. The MPA, maximum and minimum RPA diameter were normalized to body weight (MPA_N, RPAmax_N, and RPAmin_N). The MPA was also indexed to the ascending aorta (MPA/AO), while the RPA size was indexed to the aortic annulus (RPAmax/Aod and RPAmin/Aod). The right pulmonary artery distensibility index (RPADi) was also calculated. The diagnostic accuracy of PA parameters for PH was assessed through the receiver operating characteristic curve analysis and area under the curve (AUC). Measurement variability was assessed trough the coefficient of variation (CV). The RPADi, RPAmin_N, and RPAmin/Aod showed similar diagnostic accuracy for the detection of PH (AUC = 0.975, AUC = 0.971, and AUC = 0.953, respectively), higher than MPA/AO (AUC = 0.926), MPA_N (AUC = 0.880), RPAmax_N (AUC = 0.814), and RPAmax/Aod (AUC = 0.803; P < .05). Aside from RPAmax variables, no differences were found between precapillary and postcapillary PH. RPA size parameters showed lower CVs in comparison to MPA/AO and RPADi. Although MPA/AO showed an excellent sensitivity and specificity for the detection of PH, the RPAmin exhibited a higher diagnostic accuracy and less measurement variability, thus could represent a new useful parameter for the detection of PH in dogs.

The effects of blood lactate level on mortality in patients developing sepsis in intensive care unit

Aim: Sepsis is a serious condition with high mortality and morbidity in intensive care units (ICUs). Mortality decreases with early and appropriate antimicrobial treatment. We aimed to investigate the relationship between lactate levels and mortality in the ICU of our hospital. Methods: Patient records &gt; 18, hospitalized in the ICU of Meram State Hospital between January 2022 and January 2024, were retrospectively examined. All patients microbiologically confirmed to have positive blood culture results and diagnosed sepsis were included in the study. Age on admission, gender, diagnoses at hospitalization, Apache II, length of stay, and mortality in ICU were obtained from patients’ medical records. In the presence of suspicion of sepsis in a patient hospitalized in intensive care and in the first 72 hours after antibiotic treatment, the lactate level was recorded. Lactate clearance was defined as the percent decrease in lactate from ICU department presentation to hour 72. Mortality rates within the first 28 days were recorded. Lactate levels were compared in patients with and without mortality. The value of lactate in predicting mortality was evaluated statistically. Results: Of 56 patients included in the study, whose diagnoses of sepsis were microbiologically proven, 38 (67.9%) died. The area under a receiver operating characteristic (ROC) curve Area under curve (AUC) of lactate in predicting mortality was 0.738 [95% confidence interval (CI): 0.590 –0.886, (p=0.004)]. Threshold lactate value for mortality was 1.7 mmol/L (sensitivity: 73.7%, specificity: 61.1%). While lactate levels, lactate clearance, length of hospital stay, Acute Physiologic and Chronic Health Evaluation (APACHE II) score were statistically significant between sepsis patients with and without mortality (p=0,004, p = 0.03 p= 0,00 p=0.003). Baseline lactate was in survivors 2.05±1.37 and in nonsurvivors 1.33±0.98 mmol/L. Survivors compared with nonsurvivors had a lactate clearance of 48.2 ± 24.4 vs. 22.06 ± %, respectively (p = 0.007). It showed lactate clearance to have a significant relationship with mortality (p = 0.03). Conclusion: Here, we found that lactate level and, lactate clearance may be a significant place in the early treatment and follow-up of sepsis patients in ICUs.

P-1579. Prediction of Prognosis of Visceral and Subcutaneous Fat Areas in Pyelonephritis

Abstract Background Visceral fat accumulation has been regarded as a poor prognostic factor for coronary artery disease. Moderate overweight and mild obesity are associated with a lower mortality in patients with several infectious diseases on intensive care units, and this phenomenon is referred to as the obesity paradox. Pyelonephritis is one of the common infectious diseases, and although computed tomography (CT) imaging is frequently used in its localization, its prognostic value is limited. In this study, we analyze the relationship between the visceral and subcutaneous fat areas in CT scans and prognosis of patients with pyelonephritis.Fig. 1ROC curves using subcutaneous and visceral fat area to discriminating surviving pyelonephritis patients from deceased pyelonephritis patientsThe black line shows the curve using subcutaneous fat area and the gray line shows the curve using visceral fat area. Methods We included hospitalized patients with pyelonephritis who underwent computed tomography of the abdomen. Clinical data were obtained from the medical records. Subcutaneous and visceral fat aeras were analyzed at the umbilical level using the abdominal analysis (2D) function of the 3D image analysis system volume analyzer. Results 505 patients were included in the study. There were 497 survivors and 8 non-survivors, with both subcutaneous and visceral fat areas being lower in the non-survivors than in the survivors (subcutaneous fat area 49.3 ± 73.9 cm2 vs 123.7 ± 85.3 cm2, p=0.012; visceral fat area 42.2 ± 29.2 cm2 vs 98.4 ± 69.1 cm2, p&amp;lt; 0.01, respectively. ROC analysis using subcutaneous and visceral fat areas to discriminate survival and death showed that the areas under the curve of subcutaneous and visceral fat areas were 0.794 (p=0.002) and 0.770 (p&amp;lt; 0.001), respectively (Fig.1). Conclusion Patients with poor prognosis of pyelonephritis tended to have lower subcutaneous and visceral fat area at onset than patients with improved prognosis. The results suggest that both subcutaneous and visceral fat area using CT may have prognostic value for pyelonephritis. Disclosures All Authors: No reported disclosures

Free-form surface-based polar-axis rotational direct solar radiation spectrum measurements

Accurate measurements of direct solar radiation spectra are crucial for atmospheric science, climatology, agriculture, and solar energy. Existing systems depend on costly dual-axis tracking devices, leading to high maintenance and error rates. This study presents a free-form surface-based polar-axis rotating solar direct radiation spectrometer, enabling year-round measurements across all latitudes without mobile tracking. The system operates in the 380–780 nm range with a spectral resolution better than 2 nm. Simulation results demonstrate spectral curve area errors between 0.68% and 1.22%, and outdoor experiments in Changchun, China, confirm the accuracy of measurements against the AM1.5 G standard.

Clinical characteristics and prognosis of patients treated as invasive pulmonary aspergillosis outside of severe immunosuppression

This study aimed to identify clinical characteristics and develop a prognostic model for non-neutropenic patients with invasive pulmonary aspergillosis (IPA). A retrospective analysis of 151 IPA patients was conducted, with patients categorized into survival (n = 117) and death (n = 34) groups. Clinical data, including demographics, laboratory tests, and imaging, were collected. Multivariate Cox regression analysis identified glucocorticoid use (odds ratio [OR] = 30.223, 95% confidence interval [CI]: 2.676–341.306), intensive care unit admission (OR = 0.133, 95% CI: 0.023–0.758), and the arterial oxygen partial pressure/fractional inspired oxygen ratio (OR = 0.994, 95% CI: 0.990–0.999) as significant predictors of 28-day mortality. A prognostic model was developed based on these factors, showing high predictive accuracy (receiver operating characteristic curve area of 0.918). The model’s clinical applicability was validated through calibration curves, bootstrap internal validation, decision curve analysis, and clinical impact curves. Kaplan–Meier analysis further confirmed its utility, indicating a worse prognosis for high-risk patients within 50 days and the highest survival rate at 14 days. This novel model offers valuable insights for predicting survival in non-neutropenic IPA patients.

Triglyceride-glucose index in predicting the risk of new-onset diabetes in the general population aged 45 years and older: a national prospective cohort study

ObjectiveInsulin resistance (IR) is often present in diabetes, which imposes a heavy burden on the prevention and treatment of diabetes. Triglyceride glucose index (TyG) is simple, reliable and reproducible in detecting IR, and has great advantages in predicting the risk of diabetes. The aim of this study was to analyze the potential association between TyG and the risk of diabetes in Chinese middle-aged and older adults using a prospective cohort study design.MethodsThis study used longitudinal data from five waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, 2018, and 2020, involving 5886 participants. We used Cox proportional risk regression modeling to investigate the association between TyG index and the risk of new-onset diabetes, and decision tree analysis to identify high-risk groups for diabetes. Finally, ROC curves were applied in order to construct a predictive model for diabetes.ResultsA total of 1054 (17.9%) participants developed diabetes throughout the 9-year follow-up. Our study utilized a multivariate Cox proportional risk regression model and found a significant correlation between TyG index and diabetes risk. The analysis also revealed a nonlinear relationship between TyG index and diabetes risk.Receiver Operating Characteristic(ROC) curve analysis showed that the Area under the curve(AUC) area of TyG index in predicting the risk of new-onset diabetes was 0.652 (P < 0.05).ConclusionsTyG index can be used as a risk factor for predicting new-onset diabetes in the middle-aged and elderly population in China. In addition, there was a nonlinear relationship between TyG index and diabetes. Improving insulin resistance by regulating glucose and lipid metabolism plays an important role in the primary prevention of diabetes.

Studying the Behavior of Cast and Thermally Treated α + β -Titanium Alloys Using the Abbott Firestone Technique

Abstract Ti-6Al-4V and Ti-6Al-7Nb alloys were melted by an electric arc furnace, followed by tailored heat treatment routes in this study. The temperatures and cooling rates factors affecting the microstructural evolution, phase content and texture, and mechanical properties were evaluated. Thus far, the relationship between microstructure features, surface texture, and corresponding properties of as-cast and thermally treated alloys has not been completely understood. The results of this study revealed that the cooling rate and treatment temperatures significantly affect the properties and amount of phase transformation. Moreover, an approach utilizing bearing area curves (BAC) called Abbott Firestone curves were used to relate the surface texture to the phase content. Among the Ti67 alloys investigated, treatment at 1070 °C for 1 hour and water quenching followed by aging at 550 °C for 4 h followed by furnace cooling to 200 °C, then air cooling to room temperature exhibited the highest ultimate compressive strength (1423.7 MPa), consisting of ω phase along with α and β phases due to the precipitation hardening mechanism. Graphical Abstract

The value of local validation of a predictive model. A nomogram for predicting failure of non-invasive ventilation in patients with SARS-COV-2 pneumonia.

We aimed to determine predictors of non-invasive ventilation (NIV) failure and validate a nomogram to identify patients at risk of NIV failure. Observational, analytical study of a retrospective cohort from a single center, compared with an external cohort (March 2020 to August 2021). Two intensive care units (ICUs). Patients with pneumonia due to severe acute respiratory syndrome (SARS-CoV-2) and NIV>24h (154 and 229 in each cohort). The training cohort identified NIV failure predictors. A nomogram, created via logistic regression, underwent validation with the Hosmer-Lemeshow (HL), calibration curve and test and area under the curve (AUC). Its external validity was tested using AUC. Demographics, comorbidities, severity scores, NIV settings, vital signs, blood gases, and oxygenation at the start and 24h after NIV, NIV failure. NIV failure was 37.6% and 18% in the training and validation cohorts, respectively. Risk factors for NIV failure inluded age, obesity, sequential organ failure assessment (SOFA) score at admission, and heart rate (HR) and heart rate, acidosis, consciousness, oxygenation, respiratory rate (HACOR) 24h post-NIV. The model's HL test result was 0.861, with an AUC of 0.89 (confidence interval [CI] 0.839-0.942); validation AUC was 0.547 (CI 0.449-0.645). A predictive model using age, obesity, SOFA score, HR, and HACOR at 24h predicts NIV failure in our COVID-19 patients but may not apply to other ICUs.

Intratumoral and peritumoral radiomics for forecasting microsatellite status in gastric cancer: a multicenter study

ObjectiveThis investigation attempted to examine the effectiveness of CT-derived peritumoral and intratumoral radiomics in forecasting microsatellite instability (MSI) status preoperatively among gastric cancer (GC) patients.MethodsA retrospective analysis was performed on GC patients from February 2019 to December 2023 across three healthcare institutions. 364 patients (including 41 microsatellite instability-high (MSI-H) and 323 microsatellite instability-low/stable (MSI-L/S)) were stratified into a training set (n = 202), an internal validation set (n = 84), and an external validation set (n = 78). Radiomics features were obtained from both the intratumoral region (IR) and the intratumoral plus 3-mm peritumoral region (IPR) on preoperative contrast-enhanced CT images. After standardizing and reducing the dimensionality of these features, six radiomic models were constructed utilizing three machine learning techniques: Support Vector Machine (SVM), Linear Support Vector Classification (LinearSVC), and Logistic Regression (LR). The optimal model was determined by evaluating the Receiver Operating Characteristic (ROC) curve's Area Under the Curve (AUC), and the radiomics score (Radscore) was computed. A clinical model was developed using clinical characteristics and CT semantic features, with the Radscore integrated to create a combined model. Used ROC curves, calibration plots, and Decision Curve Analysis (DCA) to assess the performance of radiomics, clinical, and combined models.ResultsThe LinearSVC model using the IPR achieved the highest AUC of 0.802 in the external validation set. The combined model yielded superior AUCs in internal and external validation sets (0.891 and 0.856) in comparison to clinical model [(0.724, P = 0.193) and (0.655, P = 0.072)] and radiomics model [(0.826, P = 0.160) and (0.802, P = 0.068)]. Furthermore, results from calibration and DCA underscored the model's suitability and clinical relevance.ConclusionThe combined model, which integrates IPR radiomics with clinical characteristics, accurately predicts MSI status and supports the development of personalized treatment strategies.

Fabrication of Three‐Dimensional Net‐Structured Polyvinyl Alcohol Nanofibers Using Spray‐Freeze‐Drying Technique

ABSTRACTPolyvinyl alcohol (PVA) nanofibers have potential importance in industrial applications. In this study, three‐dimensional (3D) net‐structured PVA nanofibers are successfully fabricated using the spray‐freeze‐drying (SFD) technique for the first time. At first, different concentrations of PVA solutions from 0.001 to 5 wt% are applied to prepare PVA nanofibers using liquid nitrogen at −196°C by the SFD method. These nanofibers are characterized by scanning electron microscopy for morphological analysis, photo ruler software for diameter measurement, thermogravimetric analysis and differential scanning calorimetry for thermal stability and crystallinity, as well as nitrogen adsorption isotherms and pore size distribution curves for specific surface area and porous surface quality. Prepared SFD nanofibers with finer nano diameters, fewer beads, more regular 3D net‐structures and without any massive blocks are obtained from 0.05 to 1 wt%. These are compared with the nanofibers prepared by the freeze‐drying (FD) technique. The SFD method shows better results than the FD method in respect to fiber morphology, finer nanoscale diameter, crystallinity, specific surface area, and surface porous property. The best results are obtained from the nanofibers fabricated by the SFD method at 0.1 wt% concentration. Finally, the findings of this work open the opportunities for potential industrial applications and further development of PVA nanofibers.

Leveraging cancer mutation data to inform the pathogenicity classification of germline missense variants.

Innovative and easy-to-implement strategies are needed to improve the pathogenicity assessment of rare germline missense variants. Somatic cancer driver mutations identified through large-scale tumor sequencing studies often impact genes that are also associated with rare Mendelian disorders. The use of cancer mutation data to aid in the interpretation of germline missense variants, regardless of whether the gene is associated with a hereditary cancer predisposition syndrome or a non-cancer-related developmental disorder, has not been systematically assessed. We extracted putative cancer driver missense mutations from the Cancer Hotspots database and annotated them as germline variants, including presence/absence and classification in ClinVar. We trained two supervised learning models (logistic regression and random forest) to predict variant classifications of germline missense variants in ClinVar using Cancer Hotspot data (training dataset). The performance of each model was evaluated with an independent test dataset generated in part from searching public and private genome-wide sequencing datasets from ~1.5 million individuals. Of the 2,447 cancer mutations, 691 corresponding germline variants had been previously classified in ClinVar: 426 (61.6%) as likely pathogenic/pathogenic, 261 (37.8%) as uncertain significance, and 4 (0.6%) as likely benign/benign. The odds ratio for a likely pathogenic/pathogenic classification in ClinVar was 28.3 (95% confidence interval: 24.2-33.1, p < 0.001), compared with all other germline missense variants in the same 216 genes. Both supervised learning models showed high correlation with pathogenicity assessments in the training dataset. There was high area under precision-recall curve values (0.847 and 0.829) and area under the receiver-operating characteristic curve values (0.821 and 0.774) for logistic regression and random forest models, respectively, when applied to the test dataset. With the use of cancer and germline datasets and supervised learning techniques, our study shows that cancer mutation data can be leveraged to improve the interpretation of germline missense variation potentially causing rare Mendelian disorders.

Use of the oxygen reserve index/FiO2 as a non-invasive index to estimate venous admixture in anesthetized dogs.

The oxygen reserve index (ORi) is a novel, non-invasive parameter that estimates arterial oxygen partial pressure (PaO2) during hyperoxia when the fraction of inspired oxygen (FiO2) is elevated. This study aimed to assess the utility of the ORi/FiO2 ratio as an index for quantifying F-shunt, serving as an estimate of venous admixture. Anesthetic records were reviewed from 44 dogs undergoing general anesthesia and requiring arterial catheterization. ORi was measured via a CO-oximeter using a probe on the tongue. Paired measurements of PaO2, obtained by blood gas analysis, and ORi were taken at various FiO2 levels to achieve an ORi between 0 and 1. Venous admixture was quantified by F-shunt. Spearman's correlation coefficient assessed the relationship between ORi/FiO2 and F-shunt. Youden's index identified the optimal cut-off point to predict a physiological F-shunt (≤ 10%). A total of 77 paired observations were collected, revealing a moderate negative correlation between F-shunt and ORi/FiO2 (rho = -0.59, p < 0.001). An ORi/FiO2 cut-off of 1.2 demonstrated 80% sensitivity for identifying dogs with an F-shunt ≤10%, with a ROC curve area above 80%. However, the index was less effective at distinguishing dogs with higher shunt fractions. The ORi/FiO2 index identifies dogs with low F-shunt during anesthesia with strong sensitivity and predictive accuracy, potentially ruling out the occurrence of ventilation-perfusion inequality. However, it cannot replace blood gas analysis for quantifying venous admixture.

Screening of breast cancer in higher-risk Taiwanese women using contrast-enhanced mammography.

To assess the diagnostic performance of contrast-enhanced mammography (CEM) in screening higher-risk Taiwanese women for breast cancer. We conducted a prospective study at a Taiwanese medical center from 2019 to 2021. The study compared imaging techniques for breast cancer screening in women with a personal history of precancer or cancer, or a family history (first-degree relatives). The study included breast ultrasound (US) and the CEM combo, which consists of digital mammography (DM), digital breast tomosynthesis (DBT), and CEM. Diagnostic accuracy was compared using the receiver operating characteristic (ROC) curve. The study included 308 women, average age 52.1, with 86% having familial breast cancer history and 14% personal breast cancer or pre-cancerous histories. Approximately 19.5% had lesions rated BI-RADS 4 or 5. Biopsies were performed on 56 women based on lesions detected by the CEM combo. Additionally, 60 biopsies were due to abnormalities found via DM or DBT (n=20) or US (n=40). Breast cancer was confirmed in 8 women post-biopsy. The CEM combo showed a sensitivity of 87.5%, significantly higher than DM (50%), DBT (50%), and US (25%). The ROC curve area for CEM was 0.85, outperforming DM (0.65), DBT (0.63), and US (0.55), with all comparisons statistically significant (p<0.05). Lesions detected solely by DM, DBT, or US did not yield any cancer cases. CEM effectively detects breast cancer in higher-risk Taiwanese women, but further research is needed to refine biopsy recommendations.

Elevated plasma trimethyllysine is associated with incident atrial fibrillation.

Trimethyllysine (TML) is a methylated amino acid, which is linked to epigenetic regulation and can serve as a precursor of trimethylamine-N-oxide (TMAO). TMAO is a microbiota-derived metabolite and a potential risk factor of cardiovascular disease. TML has recently been linked to atherosclerosis, acute myocardial infarction and prevalent atrial fibrillation (AF). However, any association between circulating TML and incident AF has not yet been reported and was the aim of the current study in a large community based cohort. Information regarding AF was obtained by linking patient data to national health registries. Risk associations were explored by logistic regression. Potential improvements in risk reclassification were calculated by the continuous net reclassification index (NRI˃0) and the Receiver Operating Curve Area Under the Curve (ROC-AUC). At baseline 3117 patients were included. During a median (25th-75th percentile) follow-up of 10.8 (9.4 - 11.2) years, 492 patients (15.8 %) developed AF. Higher plasma TML was associated with incident AF per 1 SD log-transformed TML (OR (95 % CI) 1.30 (1.16-1.46) P < 0.01). Further analyses also showed an increase in NRI>0 (95 % CI) of 0.24 (0.14-0.33) P < 0.001 and ROC-AUC (95 % CI) of 0.013 (0.004-0.022) P = 0.006. TML was associated with, and improved risk classification of, new-onset AF in this large cohort of community dwelling adults. Our results motivate further studies on the association between TML and cardiac arrhythmias.

COMPUTER PROGRAM FOR MODELLING RAINFALL INTENSITY DURATION FREQUENCY (IDF) RELATIONSHIPS BY SHERMAN’S METHOD FOR ILORIN AREA IN NIGERIA

A computer program was developed for the modelling of rainfall data for a period of 30 years (1981-2010) for Ilorin area using a MATLAB software. The data was analyzed by sorting and ranking the maximum rainfall depths with their corresponding depths and their return periods. The rainfall depths were converted to rainfall intensities. An algorithm was developed in form of a flowchart which guided the development of computer program using Sherman’s method. Values of rainfall intensities with corresponding durations and return periods were exported to the MATLAB program for modelling of station constants and simulation of IDF curves for Ilorin area. The station constants were obtained as n = 0.5707, c = 131.0144, and m = 0.3425 for Ilorin area respectively. These were used to produce IDF curves and mathematical model for Ilorin area.

The Association Between Anthropometric Indices and Overactive Bladder (OAB): A Cross-Sectional Study From the NHANES 2005-2018.

The association between different anthropometric indices, including body mass index (BMI), a body shape index (ABSI), lipid accumulation product (LAP), visceral adiposity index (VAI), waist circumference-triglyceride index (WTI), weight-adjusted waist index (WWI), body roundness index (BRI) and the prevalence of overactive bladder (OAB) is unclear. This investigation aims to explore the association among different anthropometric indices and overactive bladder as well as confounding variables. Data were obtained from the USA National Health and Nutrition Examination Survey (NHANES) data set between 2005 and 2018, and 15231 participants were included in the study. Multivariable logistic regression was used to investigate the correlation among anthropometric indices mentioned in our study and overactive bladder. Subgroup analyses, smooth curve fitting and area under curve (AUC curve) were also performed. There was a positive correlation between BMI, LAP, WTI, WWI, BRI and overactive bladder. The results were significant even after taking into account every covariate (p < 0.05). Fitting smooth curves demonstrated that when anthropometric indices were used as a predictor to predict the occurrence of OAB, the probability of female patients suffering from OAB was higher than that of male patients. Additionally, WWI had better predictive power (AUC = 0.6780) and VAI had the worst predictive power (AUC = 0.5558). Our results suggest a substantial positive relationship between some of the anthropometric indices, including BMI, LAP, WTI, WWI, BRI, and overactive bladder.

The diagnostic value of prolactin adjustment in bilateral inferior petrosal sinus sampling for differentiating Cushing's disease from the ectopic ACTH syndrome: a systematic review and meta-analysis.

Adrenocorticotropin (ACTH)-dependent Cushing's syndrome can arise from a pituitary tumour (Cushing's disease) or an ectopic ACTH-secreting tumour, making precise differentiation essential for effective treatment. Bilateral inferior petrosal sinus sampling (BIPSS) is the gold standard for this differentiation, but false-negative results can limit its accuracy. Adding prolactin (PRL) measurement to BIPSS has been proposed to improve diagnostic precision. This meta-analysis evaluates how correction for prolactin levels ('prolactin adjustment') affects the diagnostic value of BIPSS in distinguishing Cushing's disease from ectopic ACTH syndrome. A systematic literature search was conducted in PubMed, Scopus, EMBASE, Web of Science, and Google Scholar up to July 2024. Studies were included if they provided data on BIPSS with and without PRL adjustment for ACTH-dependent Cushing's syndrome. Data extraction and quality assessment were performed, and diagnostic accuracy metrics were analysed using bivariate generalised linear mixed modelling. A total of 10 studies with 310 participants were included. The pooled sensitivity and specificity of BIPSS with PRL adjustment were 0.96 (95% CI: 0.93-0.98) and 0.68 (95% CI: 0.52-0.81), respectively. The diagnostic odds ratio (DOR) was 48.0 (95% CI: 19.0-123.0), with a positive likelihood ratio (LR) of 3.00 (95% CI: 1.9-4.7) and a negative LR of 0.06 (95% CI: 0.03-0.12). The area under the summary receiver operating characteristic (SROC) curve was 0.95 (95% CI: 0.93-0.97). For BIPSS without PRL adjustment, the pooled sensitivity was 0.90 (95% CI: 0.86-0.93) and specificity was 0.74 (95% CI: 0.59-0.85), with a DOR of 27.0 (95% CI: 13.0-59.0). The SROC curve area was 0.92 (95% CI: 0.89-0.94). Prolactin adjustment improved sensitivity (P < 0.01) without a significant change in specificity (P = 0.13). Prolactin adjustment in BIPSS slightly improves sensitivity for diagnosing Cushing's disease but does not enhance specificity for ectopic ACTH syndrome. This highlights the value of PRL measurement in improving diagnostic accuracy and reducing false negatives, while BIPSS remains crucial for ruling out EAS in clinical practice.

Prediction of Postoperative Survival Nomogram of Colorectal Cancer Patients based on Lymph Node Classification: a Study based on a SEER Population

Background: Lymph node metastases have a significant impact on the stage, treatment, and prognosis of patients with Colorectal cancer. Lymph node metastasis (LNM), log odds of positive lymph nodes (LODDS), and lymph node ratio (LNR) are independent prognostic factors for colon cancer. We are working to explore a more accurate prediction model and compare it with the staging predictions proposed by the American Joint Committee on Cancer (AJCC). Methods: A total of 15,957 patients with colorectal cancer who underwent surgical resection were included in the study, and they were randomly divided into training group (11,169 patients) and validation group (4,788 patients). Univariate Cox analysis, random forest regression analysis and Lasso analysis were performed on the training group. Based on the results of the analysis, the best independent prognostic factors were identified and integrated to construct a nomogram. The concordance index (C-index) and calibration curves were used to evaluate the nomograms of the training group and the validation group. Nomograms were compared to AJCC 8th edition TNM staging system using decision curve analysis (DCA) and area under curve (AUC). Results: N, LODDS, and LNR are independent prognostic factors for colorectal cancer. The C-index of nomogram predicting overall survival (OS) is higher than that of the AJCC 8th edition TNM staging system. Decision curve analysis (DCA) and ROC curve suggested that the nomogram was better than AJCC 8th TNM stage in terms of clinical practicability. Conclusions: We constructed a nomogram of the prognosis of patients with colorectal cancer, which may help clinicians provide individualized treatment.