Characteristic Curve Analysis Research Articles

Nerve ultrasound in CANVAS-spectrum disease: Reduced nerve size distinguishes genetically confirmed CANVAS from other axonal polyneuropathies.

Ultrasound nerve cross-sectional area (CSA) of patients affected with axonal neuropathy usually shows normal value. Cerebellar ataxia, neuropathy and vestibular areflexia syndrome (CANVAS) seems to represent an exception, showing smaller CSA, but previous reports did not test for biallelic RFC1 gene repeat expansions. We compared nerve CSA from CANVAS patients (tested positive for biallelic RFC1 gene repeat expansions) with the CSA from a group of patients with chronic idiopathic axonal polyneuropathy (CIAP) who tested negative for RFC1 gene repeat expansions, hereditary axonal neuropathy (Charcot-Marie-Tooth type 2, CMT2), and Friedreich ataxia (FRDA). We enrolled 15 CANVAS patients (eight men, mean age 66.3 ± 11.5 years, mean disease duration 9.3 ± 4.1 years), affected with sensory axonal neuronopathy. Controls consisted of 13 CIAP (mean age 68.5 ± 12.8 years, seven men), seven CMT2 (mean age 47.9 ± 18.1 years, four men), 12 FRDA (mean age 33.7 ± 8.8, five men). Nerve ultrasound was performed at median, ulnar, sciatic, sural, and tibial nerves and brachial plexus, bilaterally. The nerve CSA from CANVAS patients was significantly smaller than the one from the other cohorts at several sites with significant and high accuracy at Receiver-operating characteristic (ROC) curve analyses. RFC1 AAGGG pentanucleotide expansion, disease duration, and disability did not correlate with CSA at any site, after Bonferroni correction. Decreased sonographic nerve sizes, in arms and legs, in patients with sensory neuropathy and normal motor conduction studies could point to CANVAS-spectrum disease and help guide appropriate genetic testing.

Fecal short-chain fatty acids level and pediatric relapsing nephrotic syndrome

Background The gut microbiota has a potential role in the development of nephrotic syndrome. Fecal short-chain fatty acid (SCFA) levels are representative of gut microbiota activity. Objective To assess for potential associations of fecal short-chain fatty acid levels in pediatric relapsing nephrotic syndrome. Methods This cross-sectional study was done on patients at the Pediatric Nephrology Subdivision of Prof. Dr. R.D. Kandou General Hospital, a referral hospital in Manado, Indonesia. Subjects were 25 patients aged less than 18 years with nephrotic syndrome (NS). We compared the levels of fecal acetic acid, propionic acid, butyric acid percentage, absolute butyric acid, and total short-chain fatty acid between children with relapsing and non-relapsing NS. A receiver operating characteristic (ROC) curve analysis was conducted to determine the significant SCFA cut-off level to diagnose NS. Results Comparison of fecal SCFAs between relapsing and non-relapsing NS groups showed significantly lower butyric acid percentages, absolute butyric acid level, and total SCFAs levels in the relapsing NS group, but not in acetic acid or propionic acid levels. Further multivariate analysis did not show a significant difference in total SCFA levels between relapsing and non-relapsing NS. Absolute butyric acid level had the strongest association with relapsing NS, with the highest predictive score. The absolute butyric acid cut-off value of 0.85 mg/mL had a high sensitivity (90%) and high specificity (93.3%) for predicting relapsing nephrotic syndrome. Conclusion Fecal acetic acid, propionic acid, and total short-chain fatty acid in stool are not associated with relapsing NS in children. However, fecal butyric acid measurements are inversely associated with relapsing NS.

A comparative study of histotripsy parameters for the treatment of fibrotic ex-vivo human benign prostatic hyperplasia tissue

Histotripsy is a noninvasive focused ultrasound therapy that mechanically fractionates tissue to create well-defined lesions. In a previous clinical pilot trial to treat benign prostatic hyperplasia (BPH), histotripsy did not result in consistent objective improvements in symptoms, potentially because of the fibrotic and mechanically tough nature of this tissue. In this study, we aimed to identify the dosage required to homogenize BPH tissue by different histotripsy modalities, including boiling histotripsy (BH) and cavitation histotripsy (CH). A method for histotripsy lesion quantification via entropy (HLQE) analysis was developed and utilized to quantify lesion area of the respective treatments. These data were correlated to changes in mechanical stiffness measured by ultrasound shear-wave elastography before and after treatment with each parameter set and dose. Time points corresponding to histologically observed complete lesions were qualitatively evaluated and quantitatively measured. For the BH treatment, complete lesions occurred with > = 30 s treatment time, with a corresponding maximum reduction in stiffness of −90.9 ± 7.2(s.d.)%. High pulse repetition frequency (PRF) CH achieved a similar reduction to that of BH at 288 s (−91.6 ± 6.0(s.d.)%), and low-PRF CH achieved a (−82.1 ± 5.1(s.d.)%) reduction in stiffness at dose > = 144 s. Receiver operating characteristic curve analysis showed that a > ~ 75% reduction in stiffness positively correlated with complete lesions observed histologically, and can provide an alternative metric to track treatment progression.

Avoidance of negative emotional contrasts as a diagnostic feature of OCD: A receiver-operator characteristic curve analysis of the contrast avoidance questionnaires

BackgroundModels focusing on transdiagnostic mechanisms, such as repetitive negative thinking, may be of additive value to existing conceptualizations of obsessive-compulsive disorder (OCD). One such model is the Contrast Avoidance Model (CAM), which posits that individuals with generalized anxiety disorder (GAD) are sensitive to sharp increases in emotions, and use worry to maintain heightened states of negative arousal to avoid these emotional shifts. The current study used receiver operator characteristic (ROC) curve analyses to examine the predictive utility of two contrast avoidance questionnaires in detecting probable OCD. MethodsUndergraduate students with probable OCD (N = 431) and a non-OCD group (N = 433) completed measures of contrast avoidance (CAQ-GE and CAQW) and obsessive-compulsive symptoms. ResultsResults showed significant differences in total CAQ-GE and CAQ-W scores between the probable OCD group and the non-OCD group. Area under the curve values demonstrated excellent accuracy in predicting probable OCD on the CAQ-GE and CAQW, (0.87 and 0.88, respectively). Correlation analyses revealed that certain OC symptom dimensions (e.g., Unacceptable Thoughts; Responsibility for Harm) were more closely associated with the CAQ-GE and the CAQ-W relative to other symptom dimensions. LimitationsThe study had a cross-sectional design and relied on an undergraduate sample. ConclusionIdentifying shared mechanisms across OCD and its comorbidities is an important and novel approach to understanding the etiology and maintenance of symptoms.

Quantitative Assessment of Early Caries Lesion Activity Using Novel Dye-Enhanced Fluorescence Imaging

ObjectivesThis study aimed to evaluate the validity of the dye-enhanced quantitative light-induced fluorescence (DEQLF) method for assessing early enamel caries activity. MethodsSeventy extracted human teeth with early enamel caries on smooth surfaces were included. Two dentists evaluated the caries activity using the Nyvad system followed by the DEQLF method. The teeth were hydrated with distilled water for 60 s, dehydrated with compressed air for 10 s, and stained with 100 μM fluorescein sodium solution for 10 s. White and fluorescent images were captured using a QLF-D 2+ Billuminator. The change in fluorescence (ΔΔG) was calculated using an image analysis software. Independent-sample t-tests were performed to evaluate the difference in ΔΔG between active and inactive lesions for both DEQLF and conventional quantitative light-induced fluorescence (QLF) methods. Receiver operating characteristic (ROC) curve analysis was used to assess the validity of ΔΔG for distinguishing lesion activity using the area under the ROC curve (AUROC). ResultsAmong 70 caries lesions, 33 were active and 37 were inactive. Using the DEQLF method, the ΔΔG for active lesions (3.8 ± 5.6) was significantly higher than that for inactive lesions (1.0 ± 2.5) (P < 0.05). With the conventional QLF method, there was no significant difference in ΔΔG between active (-1.1 ± 1.7) and inactive (-1.3 ± 1.7) lesions. DEQLF-derived ΔΔG demonstrated an AUROC of 0.72, a sensitivity of 0.67, and a specificity of 0.76. ConclusionsApplying the DEQLF method to human teeth enabled the quantitative assessment of lesion activity based on dye penetration. DEQLF-derived ΔΔG values showed significant differences based on lesion activity status and demonstrated high validity in distinguishing lesion activity. Clinical significanceClinicians can use the DEQLF method, which involves applying a fluorescent dye for 10 s prior to conventional QLF, to objectively quantify and distinguish the activity status of early enamel caries, potentially replacing the traditional reliance on subjective visual assessments.

Expansion of a Novel Subset of L-Selectin+ Classical Monocytes in Kawasaki Disease.

Kawasaki disease (KD) is an acute systemic vasculitis that is associated with dysregulated immune responses. Monocytes play a central role in innate immunity. Our previous single-cell RNA sequencing of peripheral blood mononuclear cells (PBMC) revealed a new subset of monocytes in children with KD called L-Selectin+ classical monocytes (SELL+ CM). Therefore, we aimed to investigate the correlation between KD and SELL+ CM. Peripheral blood samples were collected from 81 KD patients, 18 febrile patients and 36 healthy children before treatment. Among them, ten KD patients were followed up, and samples were obtained before and after intravenous immunoglobulin (IVIG) treatment. Analysis of SELL+ CM was performed using flow cytometry. Additionally, ROC curve analysis was conducted to assess the diagnostic value of SELL+ CM for KD. Classical monocytes (CM) expressed the highest levels of L-selectin in children with KD. The ratio of SELL+ CM in CM was significantly higher in KD patients than in febrile and healthy children. Following IVIG treatment, the ratio of SELL+ CM in CM showed a downward trend. The receiver operating characteristic (ROC) curve analysis (the area under the curve, AUC = 0.71) indicated the potential diagnostic value of SELL+ CM in KD. The correlation analysis suggested that SELL+ CM may serve as a new clinical index for patients with KD. In KD, the ratio of SELL+ CM in CM significantly increases during the acute phase, which may become a potential biomarker and help facilitate KD diagnosis based on clinical features.

Diagnostic value of serum GDF-15 in patients with pseudomyxoma peritonei

Background and aimsPseudomyxoma peritonei (PMP) is a rare malignancy that lacks a highly sensitive and specific biomarker for its diagnosis. Identifying reliable serum markers is crucial for improving the diagnostic accuracy and management of PMP. This study aims to explore the diagnostic value of serum growth differentiation factor 15 (GDF-15) in patients with PMP. Material and methodsWe carried on a 1:1 matched case-control study. 44 patients with PMP hospitalized in Aerospace Center Hospital were recruited as cases, and 44 sex- and age-matched apparently healthy participants were selected as controls. The serum GDF-15 concentrations were tested using an ELISA method. The diagnostic value of GDF-15 in PMP patients was assessed by receiver operating characteristic (ROC) curve analysis. ResultsThe median serum GDF-15 level in PMP patients was 1192.77 (843.03–1879.06) pg/mL, notably higher than that in healthy controls [533.27 (410.46–641.47) pg/mL] (P<0.001). The area under the curve (AUC) of serum GDF-15 for PMP diagnosis was 0.907, the optimal diagnostic threshold value was 644.58 pg/mL, the sensitivity was 93.18 %, and the specificity was 77.27 %. The AUC of GDF-15 combined with carbohydrate antigen 125 (CA125) was larger than that of GDF-15 alone (P=0.027), and the sensitivity and specificity achieved 86.36 % and 95.45 %. GDF-15 levels showed a significant correlation with age (P=0.042), with younger PMP patients exhibiting notably lower concentrations of GDF-15 compared to older patients. ConclusionSerum GDF-15 could become a new marker for the PMP diagnosis. The combination of GDF-15 and CA125 demonstrated superior diagnostic performance for PMP compared to GDF-15 alone, achieving a sensitivity of 86.36% and a specificity of 95.45%.

The Mayo Adhesive Probability Score as a Predictor of Postoperative Renal Function in Robot-assisted Partial Nephrectomy.

The aim of this study was to evaluate the Mayo Adhesive Probability (MAP) score as a predictor of split renal function deterioration after robot-assisted partial nephrectomy (RAPN). A total of 30 patients who underwent RAPN were identified retrospectively. The parameters evaluated included patient characteristics, tumor diameter, MAP score, warm ischemic time (WIT), and renal function. Split renal function was evaluated using Tc-99m DTPA renal scintigraphy before and six months after surgery. Univariate and multivariate logistic regression analyses were performed. Nine patients (30.0%) showed more than 90% preservation of split renal function on the operated side. The MAP score (p=0.015), cT1b tumor (p=0.0002), and WIT (p=0.044) were associated with preservation of split renal function six months after surgery on univariate analysis. The MAP score was the strongest predictor of preservation of split renal function six months after surgery on multivariable analysis (p=0.007). On receiver-operating characteristic (ROC) curve analysis, the MAP score (cutoff value 3.0; p=0.01) was a significant predictor of split renal function six months after surgery. The MAP score was significantly associated with postoperative split renal function six months after RAPN on the operated kidney side. The MAP score is useful for predicting split renal function after RAPN.

Risk factors and nomograms for diagnosis and early death in patients with combined small cell lung cancer with distant metastasis: a population-based study.

Combined small cell lung cancer (CSCLC) with distant metastasis (DM) is an aggressive disease with a poor prognosis. Effective nomograms are needed to predict DM and early death in patients with CSCLC and DM. This retrospective study included patients with CSCLC from the Surveillance, Epidemiology, and End Results database between 2004 and 2015. Risk factors for DM and early death were analyzed by univariate and multivariate logistic regression. Nomograms were constructed based on the results in a training cohort and confirmed in a validation cohort, and their performances were assessed by concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). A total of 788 patients with CSCLC were selected, including 364 patients with metastatic CSCLC. Sex, tumor site, T stage, and N stage were independent risk factors for DM, while age, surgery, chemotherapy, and liver metastasis were independent risk factors for early death. C-index, ROC, calibration, and DCA curve analyses all showed good predictive performances for both nomograms. These nomograms could reliably predict DM risk in CSCLC patients and early death in CSCLC patients with DM, and may thus help clinicians to assess these risks and implement individualized therapies.

PREDICTING RISK OF EMPLOYEE INJURY IN A PEDIATRIC HOSPITAL

PURPOSEHealthcare has one of the highest rates of non-fatal occupational injury as compared to other industries. Yet, evaluation of risk determinants and prediction algorithms in hospital settings remains limited. METHODSThis study examines risk factors for employee injuries in a large pediatric hospital and evaluates prediction algorithms using hospital surveillance data, incident reports, and work unit measures such as patient density and employee workload. We employed multiple statistical models and machine learning tools, including logistic regression (LR), random forest (RF), penalized logistic regression (PLR), Naïve Bayes, neural network (NN), XGBoost (XG), and mixed-effects logistic regression (GLMER) to predict employee injury risk for specific time periods. We used cross-validation and receiver-operator characteristic (ROC) curve analyses to assess model performance. RESULTSGLMER, LR, and PLR were superior to other models, with higher AUC values (∼0.76), indicating good discrimination ability, though accuracy and specificity varied across models. RF showed high accuracy and specificity and comparable AUC with the top performing models. Further analyses using GLMER revealed variability in employee injury risk across months, days, and hospital units, identifying peaks on Tuesdays and Saturdays and in April and July, with lows in March and June. CONCLUSIONOur findings highlight the significance of monitoring specific risk factors within pediatric hospital settings and pairing them with appropriate predictive algorithms to effectively predict and mitigate employee injuries. These insights indicate that continuous monitoring may help enhance employee safety. Future work should evaluate additional predictors that may be obtained from individual hospital units, which may inform targeted prevention strategies.

Validity of estimated aortic pulse wave velocity measured during the 6-min walk test to predict anaerobic fitness before major non-cardiac surgery

BackgroundThis study aimed to assess the efficacy of estimated preoperative aortic pulse wave velocity (AoPWV) to discriminate between low and high 6 min walk test (6MWT) distance in patients awaiting major non-cardiac surgery. MethodsProspective observational study in 133 patients undergoing non cardiac surgery. AoPWV and the distance walked during a 6MWT were assessed. Receiver operating characteristic (ROC) curve analysis was used to determine two different AoPWV cut-points for predicting a distance of 427 m in the 6MWT. We also calculated lower and upper AoPWV cut-points (probability ≥ 0.75) for predicting a distance of < 427 m, ≥427 m, and also 563 m in the 6MWT. ResultsThe ROC curve analysis for the < 427 m distance revealed an area under the curve (AUC) of 0.68 (95% confidence interval 0.56–0.79) and an AUC of 0.72 (95% confidence interval 0.61–0.83) for >563 m. Patients with AoPWV > 10.97 m/s should be considered high risk, while those with <9.42 m/s can be considered low risk. ConclusionsAoPWV is a simple, non-invasive, useful clinical tool for identifying and stratifying patients awaiting major non-cardiac surgery. In situations of clinical uncertainty, additional measures should be taken to assess the risk.

Expression of Interleukin-8, Interleukin-12 and Interleukin-13 in Esophageal Squamous Cell Carcinoma: Biomarker Potentiality and Prognostic Significance.

Interleukin-8 (IL8), Interleukin-12 (IL12) and Interleukin-13 (IL13) are cytokines that play regulatory role in cancer pathogenesis. We analysed their expression profile to evaluate as molecular biomarkers of esophageal squamous cell carcinoma (ESCC) and their association with different parameters and patient survival. Expression analysis was performed by Real time quantitative polymerase chain reaction and receiver operating characteristic (ROC) curve analysis was done. The expression profiles were associated with different clinicopathological and dietary factors. Survival and hazard analysis were also performed. IL8 expression showed upregulation in tissue (p = 0.000) and blood samples (p = 0.481), IL12 expression showed downregulation in tissue samples (p = 0.064) and upregulation in blood samples (p = 0.689) and IL13 expression showed upregulation in tissue (p = 0.000) and blood samples (p = 0.006). IL13 expression in tissue showed the highest area under the curve (AUC) value (0.773) for ESCC diagnosis, followed by IL8 expression in tissue (0.704) and IL13 expression in blood (0.643). This study also reveals the correlation of studied cytokines in tissue and blood level. Different clinicopathological and dietary factors showed significant association (p < 0.05) with IL8, IL12 and IL13 expression and with survival of ESCC patients. IL8 expression in blood and IL12 expression in tissue and blood showed significant association (p < 0.05) with patient survival. Altered expression of IL8, IL12 and IL13 may be associated with ESCC progression. Overexpression of IL8 and IL13 in tissue samples may be potential biomarkers for ESCC screening. Additionally, both survival and hazard analysis data indicate the effects of different parameters on the prognosis of ESCC patients.

Clinical and Diagnostic Value of High-Density Lipoprotein-Based Inflammatory Indices and Lipid Ratios in Young Adults with Schizophrenia.

This study aimed to assess High-density Lipoprotein (HDL)-based Inflammatory Indices and lipid profile changes in antipsychotic-naive first-episode schizophrenia (AN-FES) patients, chronic schizophrenia (CS) patients, and explore the clinical and predictive value of these parameters for schizophrenia. The study cohort included 52 AN-FES patients, 46 CS patients, and 52 healthy controls (HCs), with an average age of 24 years. Upon admission, patients underwent complete blood count and lipid profile analyses. Various ratios were calculated, including neutrophil-to-HDL (NHR), monocyte-to-HDL (MHR), lymphocyte-to-HDL (LHR), and platelet-to-HDL (PHR), as well as lipid ratios like triglycerides/HDL, non-HDL/HDL, total cholesterol/HDL, and low-density lipoprotein/HDL. For the AN-FES group, these evaluations were repeated after two months of treatment with atypical antipsychotics. Statistical analyses included correlation analysis, Receiver Operating Characteristic (ROC) curve analysis, and univariate and multivariate regression. Compared to HCs, CS patients exhibited significantly higher MHR and NHR values, while AN-FES patients showed elevated levels of PHR, MHR, and NHR. No significant differences were observed in LHR or lipid ratios across the three groups. In the AN-FES cohort, MHR correlated positively with neutrophil counts, and NHR with monocyte counts. Additionally, white blood cell counts were positively associated with both MHR and NHR. Following treatment, NHR levels decreased, whereas TG/HDL ratios increased, with MHR and PHR remaining elevated. ROC analysis highlighted NHR as the most diagnostically valuable parameter (AUC = 0.799), with 86.5% specificity at an optimal cutoff of 3.534, outperforming MHR and PHR. Regression analyses recognized NHR (OR=2.225) as an independent risk factor for schizophrenia, even after adjusting for confounders. HDL-based inflammatory indices, particularly NHR, may serve as valuable diagnostic and prognostic markers in young adults with schizophrenia, even though significant alterations in lipid ratios were not observed in this demographic.

The value of predicting the invasiveness and degree of infiltration of pulmonary ground-glass nodules based on computed tomography features and enhanced quantitative analysis.

The incidence and mortality rate of lung cancer are the highest in the world among all malignant tumors. Accurate assessment of ground-glass nodules (GGNs) is crucial in reducing lung cancer mortality. This study aimed to explore the value of computed tomography (CT) features and quantitative parameters in predicting the invasiveness and degree of infiltration of GGNs. Lesions were classified into three groups based on pathological types: the precursor glandular lesion (PGL) group, including atypical adenomatoid hyperplasia and adenocarcinoma in situ; the minimally invasive adenocarcinoma group; and the invasive adenocarcinoma group. Quantitative and qualitative data of the nodules were compared, and receiver operating characteristic (ROC) curve analysis was performed for each quantitative parameter. Binary logistic regression analysis was used to evaluate independent predictors of GGN invasiveness. There were significant differences in lesion size, morphology, nodule type, bronchial abnormality, internal vascular sign and pleural retraction among the three groups (P<0.05). There were significant differences in all CT quantitative parameters (CT attenuation value in the plain phase, CT attenuation value in the arterial phase, CT attenuation value in the venous phase, arterial phase enhancement difference, venous phase enhancement difference, arterial phase enhancement index and venous phase enhancement index) among the three groups (P<0.001). The ROC curve analysis showed that the CT attenuation value in the plain phase, CT attenuation value in each enhanced phase, enhancement difference and enhancement index had good discriminatory power. Binary logistic regression analysis revealed that nodule type and internal vascular sign were independent risk factors for GGN invasiveness. CT features combined with enhanced scanning and quantitative analysis have important value in predicting the invasiveness of GGNs. The type of pulmonary nodule detected on CT (pure GGN or mixed GGN) and the presence of internal vascular signs are independent risk factors for GGN invasiveness.

Development and Validation of Radiomics-Based Models for Predicting the Parametrial Invasion in Stage IB1 to IIA2 Cervical Cancer.

To develop an early warning system that enables accurate parametrial invasion (PMI) risk prediction in cervical cancer patients with early-stage. We retrospectively collected 218 early-stage cervical cancer patients who were treated in Jingzhou Central Hospital from January 31, 2015, to January 31, 2023, and diagnosed with early stage cervical cancer by pathology. The prediction model training is achieved by randomly dividing 70% of the training queue population, with the remaining 30% used as the testing queue. Then, a prediction model based on machine learning algorithms (including random forest, generalized linear regression, decision tree, support vector machine, and artificial neural network) is constructed to predict the risk of PMI occurrence. Ultimately, the analysis of receiver operating characteristic curve (ROC) and decision curve analysis (DCA) is used to evaluate the predictive ability of various prediction models. We finally included radiomics-based candidate variables that can be used for PMI model. Multivariate logistic regression analysis showed that energy, correlation, sum entropy (SUE), entropy, mean sum (MES), variance of differences (DIV), and inverse difference (IND) were independent risk factors for PMI occurrence. The predictive performance AUC of five types of machine learning ranges from 0.747 to 0.895 in the training set and can also reach a high accuracy of 0.905 in the testing set, indicating that the predictive model has ideal robustness. Our ML-based model incorporating GLCM parameters can predict PMI in cervical cancer patients with stage IB1 to IIA2, particularly the RFM, which could contribute to distinguishing PMI before surgery, especially in assisting decision-making on surgical scope.

Value of the red blood cell distribution width (RDW) and neutrophil lymphocyte ratio (NLR) in the prediction of functional recovery and 3-month mortality following endovascular treatment for acute anterior circulation ischemic stroke

ObjectivesThe red blood cell distribution width (RDW) and neutrophil to lymphocyte ratio (NLR) have been linked to poor prognosis in patients with ischaemic stroke. However, no study has yet evaluated the prognostic role of RDW and NLR, or their combined effect on reperfusion in patients with endovascularly-treated acute ischaemic stroke. This study therefore aimed to analyse the impact of RDW and NLR on poor functional outcomes and failed reperfusion following endovascular treatment in patients with acute anterior circulation ischaemic stroke. MethodsA total of 275 patients with acute anterior circulation ischaemic stroke treated endovascularly between 2015 and 2018 were enrolled in this study. The relationships between RDW, NLR, and poor outcomes were analysed using univariate and multivariate logistic regression models and receiver operating characteristic (ROC) curve analysis. The Youden Index was applied to determine the cut-off value. ResultsMultivariate logistic regression analysis identified RDW (p = 0.015) and NLR (p = 0.015) as independent predictors of mortality at the 3rd month. ROC curve analysis of RDW revealed a cutoff value of 14.25 (p = 0.009) for poor clinical outcomes (modified Rankin scale [mRS] 3–6). Similarly, a cutoff value of 14.25 was found for mortality prediction (p = 0.003). The cutoff value for poor clinical outcome (mRS 3–6) in the NLR was determined as 5.93 (p = 0.003), whereas the cutoff value for mortality was set at 5.17 (p = 0.028). RDW also predicted failed reperfusion, with a cutoff value of 17.75 (p = 0.048). ConclusionsHigh RDW and NLR upon admission were identified as independent indicators of mortality in endovascularly treated acute anterior circulation ischemic stroke patients. Furthermore, the RDW could potentially predict failed reperfusion.

AI for Multistructure Incidental Findings and Mortality Prediction at Chest CT in Lung Cancer Screening.

Background Incidental extrapulmonary findings are commonly detected on chest CT scans and can be clinically important. Purpose To integrate artificial intelligence (AI)-based segmentation for multiple structures, coronary artery calcium (CAC), and epicardial adipose tissue with automated feature extraction methods and machine learning to detect extrapulmonary abnormalities and predict all-cause mortality (ACM) in a large multicenter cohort. Materials and Methods In this post hoc analysis, baseline chest CT scans in patients enrolled in the National Lung Screening Trial (NLST) from August 2002 to September 2007 were included from 33 participating sites. Per scan, 32 structures were segmented with a multistructure model. For each structure, 15 clinically interpretable radiomic features were quantified. Four general codes describing abnormalities reported by NLST radiologists were applied to identify extrapulmonary significant incidental findings on the CT scans. Death at 2-year and 10-year follow-up and the presence of extrapulmonary significant incidental findings were predicted with ensemble AI models, and individualized structure risk scores were evaluated. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the performance of the models for prediction of ACM and extrapulmonary significant incidental findings. The Pearson χ2 test and Kruskal-Wallis rank sum test were used for statistical analyses. Results A total of 24 401 participants (median age, 61 years [IQR, 57-65 years]; 14 468 male) were included. In 3880 of 24 401 participants (16%), 4283 extrapulmonary significant incidental findings were reported. During the 10-year follow-up, 3389 of 24 401 participants (14%) died. CAC had the highest feature importance for predicting the three study end points. The 10-year ACM model demonstrated the best AUC performance (0.72; per-year mortality of 2.6% above and 0.8% below the risk threshold), followed by 2-year ACM (0.71; per-year mortality of 1.13% above and 0.3% below the risk threshold) and prediction of extrapulmonary significant incidental findings (0.70; probability of occurrence of 25.4% above and 9.6% below the threshold). Conclusion A fully automated AI model indicated extrapulmonary structures at risk on chest CT scans and predicted ACM with explanations. ClinicalTrials.gov Identifier: NCT00047385 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Yanagawa and Hata in this issue.

New Immunological Indexes for the Effect of Systemic Inflammation on Oocyte and Embryo Development in Women With Unexplained Infertility: Systemic Immune Response Index and Pan-Immune-Inflammation Value.

Predicting the impact of systemic inflammation on oocyte and embryonic development in unexplained infertile women using the new immunological indexes. This retrospective cohort study was conducted using the records of the In Vitro Fertilization Department of Ankara Gülhane Training and Research Hospital. After reviewing the records of patients who had undergone in vitro fertilization (IVF) for unexplained infertility (UI) and excluding all known factors that could cause systemic immune inflammation, the systemic immune response index (SIRI), and pan-immune score were calculated from the pre-treatment hemogram parameters between the embryo arrest (EA) group and the embryo transfer group. It was investigated whether there was a statistical difference between the two groups and whether an SIRI value affecting embryo quality was found. A receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cut-off values for inflammatory markers to predict EA. The 108 EA group (embryos that were arrested during their development and could not be transferred) and the 140 embryo transfer group showed statistically significant differences in the parameters of systemic inflammatory index (SII), SIRI, pan-immune inflammation value (PIV), and neutrophil/lymphocyte ratio (NLR) (p < 0.05). These inflammatory parameters, which were examined before ovulation induction, also correlated positively with the required total dose of gonadotropin and negatively with the ovarian sensitivity index (OSI). SII, SIRI, PIV, and NLR have specific cut-off values with ROC analysis and determine the effect of the inflammatory status of the environment in which the oocyte develops on EA (p < 0.005). In women with UI, high levels of systemic immune inflammation have a negative impact on oocyte and embryo development, and treatments to suppress inflammation may improve IVF success.

Pseudo-continuous and territorial arterial spin labeling MRI for assessment of cerebral perfusion in moyamoya disease after revascularization: A comparative study with digital subtraction angiography

PurposeTo evaluate if pseudo-continuous arterial spin labeling (pcASL) and territorial ASL (tASL) can assess cerebral perfusion post-revascularization in Moyamoya disease and compare with digital subtraction angiography (DSA) outcomes. Materials and methodsPatients diagnosed with Moyamoya disease who underwent pcASL using two post-labeling delays (short ASL, 1,525 ms; delayed ASL, 2,525 ms), tASL, and DSA 3 months after surgery at a single institution were retrospectively evaluated. Manual delineation on pcASL cerebral blood flow (CBF) maps covered middle cerebral artery (MCA) territory on both sides, and cerebellum. Normalized CBF (nCBF) was calculated. Revascularization in the MCA territory was evaluated with external carotid angiography and tASL, graded on a three-point scale. Intermodality agreement was analyzed with weighted κ statistics. Correlation between pcASL-derived nCBF and tASL-measured revascularization, and revascularization grade from direct angiography, was determined. Diagnostic performance of pcASL and tASL was evaluated using DSA as a reference via receiver operating characteristic (ROC) curve analysis. ResultsA total of 32 hemispheres from 31 patients were assessed. On the operated side, sASL and dASL had nCBF values of 1.00 ± 0.30 and 1.31 ± 0.31, respectively. Revascularization area grading showed substantial intermodality agreement (weighted κ = 0.68; 95 % CI: 0.49, 0.87). DSA revascularization moderately correlated with sASL and dASL nCBF values (r = 0.56 and 0.47) and strongly correlated with tASL revascularization area (r = 0.73). ROC analysis revealed that sASL and dASL nCBF values reflected revascularization (area under the curve (AUC) = 0.86 and 0.77) and tASL revascularization area (AUC = 0.91). Combined pcASL and tASL had an AUC of 0.93, comparable to tASL alone, improving diagnostic performance. The diagnostic accuracy of nCBF for sASL was 87.5 %, superior to 75 % for dASL. The diagnostic accuracy of tASL external carotid artery revascularization area was 87.5 %, with sensitivity and specificity of 88 % and 85.7 %, respectively. ConclusionThe combination of pcASL and tASL outperformed pcASL alone in assessing cerebral perfusion post-Moyamoya disease revascularization.

766. LASTING SYMPTOMS AFTER OESOPHAGEAL RESECTIONAL SURGERY (LASORS): MULTICENTRE VALIDATION COHORT STUDY

Abstract Background As outcomes following curative-intent oesophageal cancer treatment improve, more patients are living with the long-term morbidity of cancer therapies, the symptoms of which are poorly recognised and understood. Existing symptomatology and quality-of-life tools are cumbersome and moreover are not designed specifically for evaluation of post-treatment survivorship. The LASER study and subsequent consultation process identified six key symptoms thought to predict poor health-related quality-of-life (HRQoL) as measured by validated European Organisation for Research and Treatment of Cancer (EORTC) tools. The current study aimed to validate this six-symptom LAsting Symptoms after Oesophageal Resection (LASOR) clinical tool, and assess its clinical utility. Methods In this multi-centre cohort study, patients who underwent oesophagectomy between January 2015 and June 2019 across the United Kingdom, and were disease-free at least one-year post-treatment, were asked to complete LASOR, EORTC-QLQ-C30 and QLQ-OG25 questionnaires. LASOR symptoms (low mood, reduced energy, thoracotomy pain, heartburn, diarrhoea, and bloating after eating) were evaluated using composite scores based on frequency and quality of life impact, and correlated with EORTC HRQoL scores. The ability of the LASOR tool to predict patients with poor HRQoL was validated using receiver operating characteristic (ROC) curve analysis. Patient acceptability of the tool was assessed using a separate questionnaire. Results 263 participants were included. 192 (73%) were males. Surgical technique included open (61%), hybrid (18%), and minimally-invasive (21%). 203 patients (77%) received neoadjuvant chemotherapy or chemoradiotherapy. 148 patients (56%) experienced a post-operative complication. Four LASOR symptoms were associated with significantly lower HRQoL: reduced energy (OR=2.13; 95% CI 1.20-2.87), low mood (OR=1.86; 95% CI 1.45–3.12), diarrhoea (OR=1.48; 95% CI 1.06–2.06), and bloating (OR=1.35; 95%CI 1.03-1.77). In combination, the LASOR symptoms produced an area under the ROC curve of 0.85 (sensitivity = 0.82, specificity = 0.73). Conclusion The six-symptom LASOR tool generated a reliable model for identification of patients with a poor HRQoL, with an overall diagnostic accuracy of over 80%. This is the first clinical symptom tool to be validated in the post-curative-treatment setting for patients with oesophageal cancer. The LASOR tool is straightforward to administer and highly acceptable to patients, and can be used to identify those at risk of high morbidity and poor quality of life in surveillance programmes. In turn, evidence-based survivorship services can be integrated into patient follow-up to alleviate the burden of cancer treatment on oesophagectomy patients.