Receiver Operating Curve Curve Research Articles

Pathological PCI as a prognostic marker of survival after neoadjuvant chemotherapy in patients undergoing interval cytoreduction with or without HIPEC in FIGO stage IIIC high grade serous ovarian cancer.

To determine the best possible value of pathological PCI (pPCI) as a prognostic marker for survival in high-grade serous epithelial ovarian cancer patients in patients treated with neoadjuvant chemotherapy and interval cytoreductive surgery. All patients with FIGO stage IIIC high-grade serous ovarian carcinoma were included. Receiver operating curves (ROC) were used to determine the best possible score for pPCI in predicting survival. Survival curves were calculated using the Kaplan-Meier test, and factors affecting survival were compared using the log-rank test. From January 2018 to January 2024, 171 patients who underwent interval cytoreductive surgery were included. Complete cytoreduction was achieved in 88% of the patients. ROC curves determined a (pPCI) cut-off value of 8 as the best possible score for predicting survival with a sensitivity of 82% and specificity of 67% (Youden's Index = 0.60). pPCI with a cut-off value of 8 showed improved OS (p = 0.002) and DFS, (p = 0.001) in both univariate and multivariate analyses. Following interval cytoreductive surgery, despite optimal complete cytoreductive surgery, a pathological PCI of 8 is a poor prognostic indicator of survival and may serve as a surrogate clinical marker for guiding clinicians in adjuvant treatment, especially in resource-driven settings in the real world.

The predictive value of the triglyceride glucose index combined with cystatin C for the prognosis of patients with acute coronary syndrome.

Recent studies have shown that the triglyceride glucose index (TyG) and cystatin C (CysC) are closely related to cardiovascular disease, but there is limited research on the prognosis of patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI). The aim of this study was to explore the predictive value of the combination of the TyG index and CysC in predicting major adverse cardiovascular events (MACEs) in ACS patients who underwent PCI. This retrospective study included 319 ACS patients who underwent PCI. The clinical endpoint was the occurrence of MACEs, including all-cause mortality, heart failure, non-fatal myocardial infarction, target vessel revascularization, and angina requiring hospitalization. Patients were classified into MACEs (65 cases) and non-MACEs (254 cases) groups. Univariate factor and multivariate analysis were used to identify predictors of MACEs. The receiver operating curve (ROC) of the prediction model of MACEs was determined. Additionally, the net reclassification improvement and integrated discrimination improvement indexes were calculated to further assess the additional predictive value of the risk factors for MACEs. Subgroup and interaction analysis between the TyG index combined with CysC and MACEs were conducted in various subgroups. Patients were stratified according to the optimal cutoff point value of the TyG index and the CysC determined by ROC curve analysis. The Kaplan-Meier analysis method was used to construct a survival curve 1 year after PCI. During a median follow-up period of 14 months, 65 (20.38%) patients had experienced at least one primary endpoint event. Multivariate logistic regression analysis indicated that the TyG index and CysC were independently associated with an increased risk of MACEs after PCI (OR, 2.513, 95% CI 1.451-4.351, P= 0.001; and OR, 4.741, 95% CI 1.344-16.731, P=0.016, respectively). The addition of the TyG index and CysC to the baseline risk model had the strongest incremental effect for predicting MACEs in terms of the C-statistic from 0.789 (95% CI 0.723-0.855, P<0.001) to 0.799 (95% CI 0.733-0.865, P<0.001). Furthermore, Kaplan-Meier analysis demonstrated that a TyG index greater than 9.325 and a CysC value greater than 1.065 mg/ml were significantly associated with an increased risk of MACEs (log-rank, all P < 0.01). The TyG index predicts MACEs after PCI in patients with ASC independent of known cardiovascular risk factors. Adjustment of the CysC by the TyG index further improves the predictive ability for MACEs in patients with ACS undergoing PCI. Thus, both of them are expected to become new prognostic indicators for MACEs in patients with ACS after PCI.

Evaluating the association of radiographic parameters of proximal humerus fractures managed conservatively with functional outcomes.

Treatment of proximal humerus fractures remains controversial. Understanding the factors that can affect the long-term functional outcomes can aid with management choices. This primary aim of this paper is to evaluate the association of radiographic parameters with functional outcomes. Radiographic parameters [Caput-collum-diaphyseal (CCD) angles, Y-scapular angles, and humeral head height (HHH)] were studied. The patients were split into varus and valgus groups based on the CCD angles and retroverted and anteverted groups based on Y-scapular angles. Functional outcome was measured by Oxford Shoulder Score (OSS), Constant Shoulder Score (CSS), and quick Disabilities of Arm, Shoulder and Hand score at 1 year follow-up. Intra- and interrater reliability were measured with the intraclass correlation coefficients (ICCs). Receiver operator curve (ROC) analysis and logistic regression analysis defined the optimal value for abnormalities on radiographic evaluation as an outcome predictor. 111 patients were recruited (mean age 69, 78% female). Median final radiographic assessment was at 7 months. Mean initial/final CCD was 119o /111o (varus, n = 36) and 153o/140o (valgus, n = 75). Mean initial/final Y-scapula angle was 27o/27o (retroversion, n = 101) and 70o/40o (anteversion, n = 9). There was a significant relationship between OSS and final Y-scapular angle in the retroverted group (adj coeff 0.034, p = 0.009) with optimum predictive retroversion angulation of 25o predicting poor functional outcome (OSS < 40), area under the ROC curve of 0.614. Higher initial valgus and retroversion significantly predicted more change in the final angle (adj coeff - 0.349, p = 0.002, adj coeff - 0.527, p < 0.001respectively). Both intra-rater and inter-rater reliability for the radiographic parameters were excellent (ICC > 0.9). Radiographic parameters whilst having excellent reliability, have a limited ability to predict short-term functional recovery. The extent of retroversion is the most important predictor for functional recovery with 25o a cut-off guide. Fractures with a higher initial valgus and retroversion tend to displace more.

Evaluation of the levels of salivary paxillin in oral potentially malignant disorders and malignant lesions

BackgroundThe scientific community has been particularly interested in oral squamous cell carcinoma (OSCC) because of the cancer’s extremely high incidence and fatality rates worldwide. It has been proposed that paxillin is involved in certain malignancies as an oncogene. Additionally, several investigations have assessed paxillin expression and investigated its function in developing distinct human carcinomas, including squamous cell carcinoma. Furthermore, it was discovered that there is a strong link between paxillin levels and cancer progression and spread.ObjectiveThis investigation was carried out to analyze and compare the salivary paxillin levels between oral potentially malignant disorders (OPMDs), OSCC and the healthy controls to assess its potential role as a biomarker of oral cancer aiming for early diagnosis and better prognosis of OSCC.MethodsForty-five patients, ranging in age from thirty to seventy-five, were divided into three groups: fifteen patients with OPMDs, fifteen patients with OSCC, and fifteen controls. Paxillin was identified in saliva samples by using an ELISA kit.ResultsPatients with OSCC and OPMDs have considerably greater salivary Paxillin levels than the healthy control group. The receiver operating curve (ROC) analysis was used in our study to distinguish patients with OPMDs from those with OSCC. The ROC curve constructed with the OPMDs group as the positives had lower sensitivity and area under the curve (AUC) values [100% and 1] than the ROC curve with the malignant group as the positives [93.3% and 0.997], respectively. Furthermore, ROC analysis performed between OPMDs group and the malignant group showed a specificity of 73.3% and a cut-off value ≥ 7.9 .ConclusionPaxillin can be considered a reliable biomarker for identifying and comparing OPMDs and OSCC cancerous changes.ClinicalTrials.gov IdentifierNCT06154551- 4/12/2023.

Thromboelastogram and coagulation function index: relevance for female breast cancer.

Screening and postoperative intervention of breast tumors are critical for the effective diagnosis and treatment of disease development, and reliable diagnostic/screening methods become a key link. Thromboelastogram (TEG), routine platelet (PLT) count, and the coagulation function indicators in patients with different breast diseases were determined and analyzed to explore their predictive value in secondary bleeding disorders. A total of 131 patients with breast diseases, admitted to Jiangsu University Affiliated Hospital from January 2019 to December 2022, were selected as the research subjects. The detection items were analyzed using the receiver operating curve (ROC) after grouping for secondary bleeding disorders of patients with breast cancer. The reaction (R) and the coagulation (K) times were lower in the malignant breast disease group, while the coagulation angle (α), maximum amplitude (MA), coagulation index (CI), fibrinogen (FIB), and D-dimer (D-D) were higher than those in the benign breast disease group. The t-tests proved that the MA and FIB values were statistically significant (p < 0.05) in the benign and malignant breast disease groups. The R and K in patients with breast diseases were positively correlated with the activated partial thromboplastin time (aPTT) and D-D, but were negatively correlated with PLT. The α angle was negatively correlated with aPTT and D-D, but was positively correlated with PLT. The MA for PLT function was positively correlated with FIB and PLT. CI was negatively correlated with aPTT, thrombin time (TT), and D-D, but was positively correlated with PLT. ROC curve analysis showed that the CI and α angle had a significant predictive value, whereas the correlation of the other indicators was relatively low. Coagulation tests showed significant differences in patients with breast cancer, differing from those with benign breast diseases. TEG combined with conventional coagulation indicators is potentially valuable for the prediction of secondary bleeding disorders in patients with breast cancer.

Albumin-to-Globulin Ratio Combined with Neutrophil-to-Lymphocyte Ratio as a Prognostic Predictor in Multiple Myeloma with Renal Impairment.

The albumin-to-globulin ratio (AGR) and neutrophil-to-lymphocyte ratio (NLR) have been recently regarded as promising prognostic factors in various malignancies. The present study investigated the prognostic value of combining the AGR and NLR (ANS) for risk assessments in multiple myeloma (MM) with renal impairment (RI). From 2011 to 2018, 79 patients with MM and RI were enrolled in this study. Receiver operating curves (ROCs) were constructed to determine optimal AGR and NLR thresholds for predicting overall survival (OS) and progression-free survival (PFS) during follow up. The prognostic values of AGR, NLR, and ANS were evaluated with Cox regression and Kaplan-Meier methods. We also created a predictive nomogram for prognostic evaluations of OS and PFS, and the predictive accuracy was assessed with a concordance index (c-index). The ROC curves analyses showed that the optimal cut-off levels were 2.27 for NLR and 1.57 for AGR. A high NLR and a high ANS were significantly associated with worse OS and PFS. However, a high NLR combined with a low AGR was associated with worse OS. Multivariate analyses demonstrated that both the NLR and ANS were independent predictors for both OS and PFS and that a low AGR was an independent predictor of a reduced OS. The nomogram accurately predicted OS (c-index: 0.785) and PFS (c-index: 0.786) in patients with MM and RI. ANS may serve as a potential prognostic biomarker in patients with MM and RI. The proposed nomograms may facilitate prognostic predictions for patients with MM and RI.

Development and validation of a multi-parameter nomogram for venous thromboembolism in gastric cancer patients: a retrospective analysis.

Gastric cancer (GC), one of the highest venous thromboembolism (VTE) incidence rates in cancer, contributes to considerable morbidity, mortality, and, prominently, extra cost. However, up to now, there is not a high-quality VTE model to steadily predict the risk for VTE in China. Consequently, setting up a prediction model to predict the VTE risk is imperative. Data from 3,092 patients from December 15, 2017, to December 31, 2022, were retrospectively analyzed. Multiple logistic regression analysis was performed to assess risk factors for GC, and a nomogram was constructed based on screened risk factors. A receiver operating curve (ROC) and calibration plot was created to evaluate the accuracy of the nomogram. The risk factors of suffering from VTE were older age (OR = 1.02, 95% CI [1.00-1.04]), Karnofsky Performance Status (KPS) ≥ 70 (OR = 0.45, 95% CI [0.25-0.83]), Blood transfusion (OR = 2.37, 95% CI [1.47-3.84]), advanced clinical stage (OR = 3.98, 95% CI [1.59-9.99]), central venous catheterization (CVC) (OR = 4.27, 95% CI [2.03-8.99]), operation (OR = 2.72, 95% CI [1.55-4.77]), fibrinogen degradation product (FDP) >5 µg/mL (OR = 1.92, 95% CI [1.13-3.25]), and D-dimer > 0.5 mg/L (OR = 2.50, 95% CI [1.19-5.28]). The area under the ROC curve (AUC) was 0.82 in the training set and 0.85 in the validation set. Our prediction model can accurately predict the risk of the appearance of VTE in gastric cancer patients and can be used as a robust and efficient tool for evaluating the possibility of VTE.

Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach

BackgroundVarious surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD.MethodsWe followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model’s predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram.ResultsThe TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34–4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63–0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off.ConclusionDue to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.

Associations between renal function, hippocampal volume, and cognitive impairment in 544 outpatients.

Cognitive impairment and brain atrophy are common in chronic kidney disease patients. It remains unclear whether differences in renal function, even within normal levels, influence hippocampal volume (HCV) and cognition. We aimed to investigate the association between estimated glomerular filtration rate (eGFR), HCV and cognition in outpatients. This single-center retrospective study enrolled 544 nonrenal outpatients from our hospital. All participants underwent renal function assessment and 3.0 T magnetic resonance imaging (MRI) in the same year. HCV was also measured, and cognitive assessments were obtained. The correlations between eGFR, HCV, and cognitive function were analyzed. Logistic regression analysis was performed to identify the risk factors for hippocampal atrophy and cognitive impairment. Receiver-operator curves (ROCs) were performed to find the cut-off value of HCV that predicts cognitive impairment. The mean age of all participants was 66.5 ± 10.9 years. The mean eGFR of all participants was 88.5 ± 15.1 mL/min/1.73 m2. eGFR was positively correlated with HCV and with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Univariate and multivariate logistic regression analysis showed Age ≥ 65 years, eGFR < 75 mL/min/1.73 m2, Glucose ≥6.1 mmol/L and combined cerebral microvascular diseases were independent risk factors for hippocampal atrophy and Age ≥ 65 years, left hippocampal volume (LHCV) <2,654 mm3 were independent risk factors for cognitive impairment in outpatients. Although initial unadjusted logistic regression analysis indicated that a lower eGFR (eGFR < 75 mL/min/1.73 m2) was associated with poorer cognitive function, this association was lost after adjusting for confounding variables. ROC curve analysis demonstrated that LHCV <2,654 mm3 had the highest AUROC [(0.842, 95% CI: 0.808-0.871)], indicating that LHCV had a credible prognostic value with a high sensitivity and specificity for predicting cognitive impairment compared with age in outpatients. Higher eGFR was associated with higher HCV and better cognitive function. eGFR < 75 mL/min/1.73 m2 was an independent risk factor for hippocampal atrophy after adjusting for age. It is suggested that even eGFR < 75 mL/min/1.73 m2, lower eGFR may still be associated with hippocampal atrophy, which is further associated with cognitive impairment. LHCV was a favorable prognostic marker for predicting cognitive impairment rather than age.

Relationship of immature granulocytes with disease activity in rheumatoid arthritis.

To determine whether the IG count (#) and IG percentage (%) are associated with disease activity in rheumatoid arthritis (RA). This retrospective study included 65 RA patients and 65 healthy controls. Clinical and demographic characteristics of controls and RA patients (at active period and when the patients achieved remission) were obtained from medical records. Disease activity was defined by disease activity score 28 (DAS28). Furthermore, the clinical disease activity index (CDAI), and simple disease activity index (SDAI) were calculated. For the differential diagnosis of RA patients from healthy controls, the cut-off value was estimated by making receiver-operator curves (ROC). In active RA patients, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), IG#, and IG% levels were significantly higher compared to the healthy controls (p < .001, for all). When the patients achieved remission, DAS28, CDAI, SDAI, ESR, CRP, IG#, and IG% values were significantly decreased (p < .001, for all). IG# and IG% were significantly positively correlated with DAS28, CDAI, SDAI, ESR, and CRP (p = .024, p = .008, p = .003, p < .001, p < .001, respectively). According to ROC curve analysis, IG% and IG# were the biomarkers to have a significant diagnostic value for RA with the area under the curve of 0.853 and 0.865 (p < .001, for all). The present study demonstrated that two novel inflammatory markers, IG# and IG%, can be useful for monitoring RA patients' disease activity. Furthermore, IG# and IG% can also be used as fast, inexpensive, and easily available complementary diagnostic markers to diagnose RA patients.

A Radiological-Radiomics model for differentiation between minimally invasive adenocarcinoma and invasive adenocarcinoma less than or equal to 3 cm: A two-center retrospective study

ObjectiveTo develop a Radiological-Radiomics (R-R) combined model for differentiation between minimal invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA) of lung adenocarcinoma (LUAD) and evaluate its predictive performance. MethodsThe clinical, pathological, and imaging data of a total of 509 patients (522 lesions) with LUAD diagnosed by surgical pathology from 2 medical centres were retrospectively collected, with 392 patients (402 lesions) from center 1 trained and validated using a five-fold cross-validation method, and 117 patients (120 lesions) from center 2 serving as an independent external test set. The least absolute shrinkage and selection operator (LASSO) method was utilized to filter features. Logistic regression was used to construct three models for predicting IA, namely, Radiological model, Radiomics model, and R-R model. Also, receiver operating curve curves (ROCs) were plotted, generating corresponding area under the curve (AUC), sensitivity, specificity, and accuracy. ResultsThe R-R model for IA prediction achieved an AUC of 0.918 (95 % CI: 0.889–0.947), a sensitivity of 80.3 %, a specificity of 88.2 %, and an accuracy of 82.1 % in the training set. In the validation set, this model exhibited an AUC of 0.906 (95 % CI: 0.842–0.970), a sensitivity of 79.9 %, a specificity of 88.1 %, and an accuracy of 81.8 %. In the external test set, the AUC was 0.894 (95 % CI: 0.824–0.964), a sensitivity of 84.8 %, a specificity of 78.6 %, and an accuracy of 83.3 %. ConclusionThe R-R model showed excellent diagnostic performance in differentiating MIA and IA, which can provide a certain reference for clinical diagnosis and surgical treatment plans.

#2589 Predictive value of serum lactate in ICU dialysis-dependent AKI patients

Abstract Background and Aims Hyperlactatemia is frequently observed in critically ill patients. It is often associated with unfavorable outcomes and serves as a strong predictor of mortality. Renal replacement therapy aims to mitigate lactate accumulation in this particular subgroup of patients, but the effectiveness of this therapy in reducing morbidity and mortality in acute kidney injury (AKI) associated lactic acidosis remains inconclusive. The aim of this retrospective study was to evaluate the predictive role of serum lactate in dialysis-dependent AKI patients stratified on three different underlying etiologies (septic shock, concomitant liver failure and metformin-associated lactic acidosis). Method A retrospective, single-center cohort analysis was conducted to examine patients with AKI who underwent hemodialysis in our ICU between 2022 and 2023 and had a serum lactate &amp;gt; 4 mmol/L. Patients were stratified according to underlying etiology: isolated septic shock with AKI, shock with concomitant AKI and fulminant liver failure (serum ammonia &amp;gt; 100 µmol/L), and AKI with metformin-associated lactic acidosis (MALA). We compared patients according to age and 3-day, 30-day, and 90-day mortality. Finally, we performed receiver-operating-curve (ROC) analysis to potential predictive power of serum lactate for 30-day mortality. Results The median age of our cohort of 63 patients was 67 (range 52 - 74) years, with a median lactate level of 12.9 (7.6 – 18.0) mmol/L. The 3-day, 30-day and 90-day mortality rate was 57%, 78%, and 83%, respectively. We observed that patients with concomitant liver failure were significantly younger (p = 0.004). Interestingly, while all groups have comparable 90-day mortality, patients with septic shock exhibit extremely high 3-day mortality (74%), compared to 35% and 25% for acute liver failure and metformin-associated shock. ROC curve analysis showed that serum lactate was highly predictive of 30-day mortality in group of AKI with concomitant fulminant liver dysfunction. On the contrary, in metformin-associated hyperlactatemia the level of serum lactate showed no such prediction. Conclusion Our retrospective analysis underscores the crucial importance of differentiating between various groups of patients (septic shock, concomitant liver failure and metformin-associated lactic acidosis) in patients with hyperlactatemia. In metformin-induced kidney failure, the level of lactate does not predict mortality, while in the cases of AKI with concurrent acute liver dysfunction our results are highly suggestive that dialysis may not be effective for severe lactacidosis. The findings contribute valuable insights for designing future prospective studies in this complex patient population.

Development and Validation of Hospital Mental Health Screen to Detect Psychiatric Morbidity in Medically Ill Patients in India

Background: Psychiatric morbidities often go unnoticed in medically ill patients. It is essential to screen patients with medical morbidity so that they can be referred to psychiatrists for early interventions in general hospitals in India. There is a potential lacuna in terms of the availability of a scale that can aptly identify psychiatric symptoms in medically ill patients beyond depression or anxiety, especially in low-resource settings like India. Aim: The aim was to detect psychiatric morbidity in medically ill patients in India. Methodology: Items were generated using deductive and inductive approaches. Item-Content Validity Index (I-CVI) and Scale-Content Validity Index/Universal Agreement (S-CVI/UA) were computed by involving eight subject matter specialists. The tool was circulated to 397 medically ill patients for computing The exploratory factor analysis (EFA). Domain-wise reliability using Cronbach’s alpha was calculated for six factors. The concurrent criterion validity of the Hospital Mental Health Screen (HMHS) tool was calculated by the receiver operating curve (ROC) against the gold standard of any psychiatric morbidity diagnosed by two psychiatrists in 397 medically ill patients. We used IBM SPSS version 23. Results: Initially, 34 items were generated. At the I-CVI threshold of 79%, seven items were discarded. The S-CVI/UA of the scale was 85.1%. The Kaiser–Meier–Olkin Measure of Sampling Adequacy (KMO MSA) was found to be 0.916. At a factor loading threshold of 0.4 and an eigenvalue above 1, a six-factor structure was extracted using principal component analysis and varimax rotation. Domain-wise reliability was computed, which was between 0.657 and 0.840. The final tool consisted of 27 Likert items (0 = never to 4 = always). Using the ROC curve at the 19.5 threshold, 91.4% of the positive outcomes were correctly classified and 9.5% of the adverse outcomes were expected to be incorrectly identified by the HMHS screening tool. Conclusion: HMHS is a valid and reliable tool with good screening properties, designed especially for the Indian setting. This scale can assist in identifying psychiatric morbidity in medically ill patients in low-resource settings. There is further scope for performing confirmatory factor analysis (CFA) to reinforce the factor structure of HMHS.

Prognostic value of preoperative combined neutrophil, monocyte, and lymphocyte scores in patients with renal cell carcinoma undergoing laparoscopic nephrectomy: A retrospective study.

In a multi-institutional clinical study, we assessed the prognostic significance of a novel indicator preoperative peripheral blood immune (PBIS) scores that combined ratios of preoperative lymphocyte, monocyte, and neutrophil of renal cell carcinoma (RCC) patients undergoing laparoscopic nephrectomy. Between January 2014 and December 2019, 438 patients with RCC were retrospectively analyzed in three centers. We used X-tile software to obtain the optimum cut-off values for neutrophils, monocytes, and lymphocytes to classify the patients. To assess the relationship between PBIS score and overall survival (OS), and cancer-specific survival (CSS) in patients with RCC by Kaplan-Meier survival curves and Cox regression analyses. In addition, predictive OS and CSS nomograms were constructed. The discriminative ability of nomogram and predictive performance accuracy were verified with consistency index (C-index), calibration curves, receiver operating curve (ROC) curves, decision curve analysis (DCA) curves, and time-dependent ROC curves. The optimum cutoff values for monocytes, lymphocytes, and neutrophils were 0.46, 1.01, and 4.50, respectively. We divided patients into four subgroups according to PBIS scores, which were significantly associated with M-stage (p = 0.008), T-stage (p < 0.001), N-stage (p = 0.006), and AJCC stage (p < 0.001). Multivariate Cox regression analysis revealed that RCC patients with lower PBIS scores showed a worse postoperative prognosis and served as an independent predictor of OS (p = 0.002) and CSS (p < 0.001). Ultimately, the nomograms based on PBIS scores demonstrated excellent predictive performance for OS (C-index: 0.770) and CSS (C-index: 0.828) through the analysis of calibration curves, ROC curves, DCA curves, and time-dependent ROC curves. PBIS score served as novel and effective predictor to accurately predict OS and CSS in patients with RCC receiving laparoscopic nephrectomy.

Utility of Blood Biomarkers to Predict Marrow Iron Stores in Children.

Iron deficiency is common in children with kidney failure, but current guidelines are based on biomarkers of iron stores that may be influenced by inflammation. This is the first study that examined which serum iron indices were associated with stainable marrow iron stores (the gold standard) in this population with kidney failure who underwent bone biopsies. This cross-sectional study enrolled 71 clinically stable children and young adults receiving dialysis who underwent bone biopsy for chronic kidney disease-mineral bone disorder between 2007 through 2011. Bone biopsies were stained with Perls' Prussian blue and independently interpreted by a pathologist blinded to participants' iron parameters and clinical status. Marrow staining was scored absent vs. present to facilitate receiver operator curve (ROC) analysis. In ROC analysis, the ability of serum ferritin to detect stainable marrow iron stores was compared with that of transferrin saturation (TSAT), serum hepcidin, and clinical guideline-based iron deficiency cut-offs for serum iron, TSAT, and their combinations. Mean age was 17.2 ± 4.4 years (range 2-28), and 30% of patients were female. Median dialysis vintage was 1.2 (IQR 0.7, 2.0) years, and 56% were supported by peritoneal dialysis. Mean hemoglobin was 12.4 ± 1.7 g/dl, and 35% were receiving iron supplementation at the time of biopsy. Based on the gold standard of depleted marrow iron stores, 46.5% of patients were iron-deficient. As an indicator of marrow iron staining, serum ferritin provided a higher area under the ROC curve than serum hepcidin, TSAT, or clinical guidelines-based evaluation of TSAT + ferritin. In this cohort of children and young adults with kidney failure, serum ferritin provided the best indication of stainable marrow iron stores, followed by transferrin saturation.

Identification and Verification of Potential Ferroptosis-Related Biomarkers in Cervical Cancer

This study screened important genes contributing to morbidity from differential ferroptosis-related genes (FRGs) in cervical cancer and to establish a risk assessment model with ferroptosis-related LncRNAs. Total RNA sequencing data were extracted from The cancer genome atlas (TCGA), Gene Expression Omnibus (GEO) and Genotype-Tissue Expression (GTEx). By differential analysis, we identified ferroptosis-related hub genes close to prevalence of cervical cancer. According to receiver operator curves (ROC) curves, hub genes have good diagnostic performance. The diagnostic potential of hub genes for occurrence of the disease was further assessed and verified. Further, a risk-assessing model based on ferroptosis-related LncRNAs was established. Finally, the differential expressions of hub genes were verified through qRT-PCR. Five hub genes were identified, and we found through GO, KEGG and immune infiltration, that the hub genes are connection with cervical cancer. The Area Under Curve (AUC) values were all greater than 0.8 in ROC curve, and the hub genes presented differences between disease and control groups in validation set GSE29570. We created a risk assessment model with 16 ferroptosis-related LncRNAs. There was a difference in survival between high-risk and low-risk groups. The AUC result for risk assessment model reached 0.792, and there were significant expression differences of Hub genes in Huvec and Hela cells. The study screened 5 hub genes and constructed the risk-assessment model based on 16 LncRNAs associated with ferroptosis genes.

Geospatial technique for the delineation of groundwater potential zones using multi-criteria-based AHP and MIF methods

ABSTRACT In the recent past, the growing climate change and transformation of the green cover into urban areas have posed a threat to natural water supply, which will have a direct impact on water demand for emerging cities such as Nava Raipur. As a result, the increasing demand coupled with the reduced availability of surface water prompts scientific investigation into groundwater availability and its sustainable management as an alternative. The study attempted to determine groundwater potential zones using the analytic hierarchy process (AHP) and multi-influencing factor (MIF) techniques. Twelve contextually significant regulating environmental factors were selected, and their significance and influences on decision-making approaches models have been attempted to determine through the sensitivity analysis. The final GWPZ map obtained, from a combination of thematic layers, was verified using the receiver operating curve (ROC) and the area under curve (AUC) with discharge (yield) records taken from 21 bore wells. According to the ROC curve's AUC estimation, MIF can explain 82.9% of the actual groundwater situation in the region, and for AHP, an AUC value of 0.751 is relatively low. This indicates that the MIF model is the most appropriate to accurately define potential groundwater zones for emerging cities like Nava Raipur.

Screening for central precocious puberty by single basal Luteinizing Hormone levels

PurposeTo identify cut-off for basal LH levels and for pelvic ultrasound uterine and ovarian parameters indicating an Hypotalamic–Pituitary–Gonadal (HPG) axis activation as diagnostic of Central Precocious Puberty (CPP).Methods248 girls referred for suspected precocious/early puberty who had undergone a GnRH stimulation test were enrolled and divided into three groups: Premature Idiopathic Thelarche (PIT), CPP, and Early Puberty (EA). For every patient basal serum Luteinising Hormone (LH) and Follicle Stimulating Hormone (FSH), basal LH/FSH ratio and pelvic ultrasonographic parameters were also collected. Through the use of Receiver Operating Curves (ROCs) the sensitivity (Se) and specificity (Sp) of basal LH, FSH, LH/FSH ratio and ultrasonographic parameters were evaluated at each level and Area Under the Curve (AUC) was measured.ResultsBasal LH model ≥0.14 mIU/mL reached the highest predictability (90.6% and 78.2%, Se and Sp, respectively). Basal LH/FSH ratio ≥0.1 showed a sensitivity of 85.90% and a specificity of 78.14%, while basal FSH cut-off (≥2.36 mIU/mL) had the lowest predictability, with a less favourable sensitivity (71%) and specificity (70.5%). Cut-off point for uterine length as 35 mm, (83.5% and 42.9% of Se and Sp, respectively) was calculated. For ovarian volumes, ROC curves showed very low sensitivity and specificity.ConclusionA single basal LH measurement under the cut-off limit may be adequate to exclude an HPG axis activation as CPP.

Shock index and its variants as predictors of mortality in severe traumatic brain injury.

The increase in severe traumatic brain injury (sTBI) incidence is a worldwide phenomenon, resulting in a heavy disease burden in the public health systems, specifically in emerging countries. The shock index (SI) is a physiological parameter that indicates cardiovascular status and has been used as a tool to assess the presence and severity of shock, which is increased in sTBI. Considering the high mortality of sTBI, scrutinizing the predictive potential of SI and its variants is vital. To describe the predictive potential of SI and its variants in sTBI. This study included 71 patients (61 men and 10 women) divided into two groups: Survival (S; n = 49) and Non-survival (NS; n = 22). The responses of blood pressure and heart rate (HR) were collected at admission and 48 h after admission. The SI, reverse SI (rSI), rSI multiplied by the Glasgow Coma Score (rSIG), and Age multiplied SI (AgeSI) were calculated. Group comparisons included Shapiro-Wilk tests, and independent samples t-tests. For predictive analysis, logistic regression, receiver operator curves (ROC) curves, and area under the curve (AUC) measurements were performed. No significant differences between groups were identified for SI, rSI, or rSIG. The AgeSI was significantly higher in NS patients at 48 h following admission (S: 26.32 ± 14.2, and NS: 37.27 ± 17.8; P = 0.016). Both the logistic regression and the AUC following ROC curve analysis showed that only AgeSI at 48 h was capable of predicting sTBI outcomes. Although an altered balance between HR and blood pressure can provide insights into the adequacy of oxygen delivery to tissues and the overall cardiac function, only the AgeSI was a viable outcome-predictive tool in sTBI, warranting future research in different cohorts.

Volumetric segmentation analysis of the levator ani muscle using magnetic resonance imaging in pelvic floor function assessment

In this case-control study, we aimed to evaluate how muscle volume affects pelvic floor function by analyzing the levator ani muscle (LAM) using volumetric segmentation in addition to standard magnetic resonance (MR) defecography assessments. We enrolled 85 patients with varying degrees of pelvic floor dysfunction (PFD) and 85 age- and gender-matched controls in this retrospective study. All patients had MR defecography images, while all controls had pelvic MR images obtained for other reasons. Group comparisons were performed using independent samples t-tests and Mann-Whitney U tests. The receiver operating curve (ROC) was constructed to establish a cut-off value for a normal LAM volume. Interrater reliability was assessed by calculating the intraclass correlation coefficient. A P value of less than 0.05 was considered statistically significant. Volumetric measurements revealed that the control group had higher LAM volumes, and the ROC curve analysis indicated a cut-off value of 38934.3 mm3 with a sensitivity of 0.812 and specificity of 0.8 for PFD assessment using LAM volumetric measurement. Gender did not significantly affect LAM volume in the control group. Alongside the useful structural and functional information acquired from MR defecography images, volumetric analysis, and three-dimensional reconstructions of LAM may help to improve the accuracy of the diagnosis.