BACKGROUND: To develop and evaluate a predictive nomogram for polyuria during general anesthesia in thoracic surgery.
METHODS: A retrospective study was designed and performed. The whole dataset was used to develop the predictive nomogram and used a stepwise algorithm to screen variables. The stepwise algorithm was based on Akaike\'s information criterion (AIC). Multivariable logistic regression analysis was used to develop the nomogram. The receiver operating characteristic (ROC) curve was used to evaluate the model\'s discrimination ability. The Hosmer-Lemeshow (HL) test was performed to check if the model was well calibrated. Decision curve analysis (DCA) was performed to measure the nomogram\'s clinical usefulness and net benefits. P < 0.05 was considered to indicate statistical significance.
RESULTS: The sample included 529 subjects who had undergone thoracic surgery. Fentanyl use, gender, the difference between mean arterial pressure at admission and before the operation, operation type, total amount of fluids and blood products transfused, blood loss, vasopressor, and cisatracurium use were identified as predictors and incorporated into the nomogram. The nomogram showed good discrimination ability on the receiver operating characteristic curve (0.6937) and is well calibrated using the Hosmer-Lemeshow test. Decision curve analysis demonstrated that the nomogram was clinically useful.
CONCLUSIONS: Individualized and precise prediction of intraoperative polyuria allows for better anesthesia management and early prevention optimization.

UNASSIGNED: This study aims to investigate the agreement between the Huaxi Emotional Index (HEI) and the Nurses\' Global Assessment of Suicide Risk (NGASR) in assessing high suicide risk and to explore the predictive value of HEI in identifying high suicide risk among patients with depression.
UNASSIGNED: Convenience sampling was used and 386 inpatients with depression were included in this cross-sectional study. All patients were admitted to the Mental Health Center, West China Hospital between June and December 2023. The inclusion criteria were as follows, a diagnosis of depression according to the International Classification of Diseases, Tenth Revision (ICD-10), age over 18, and completion of both NGASR and HEI assessments. According to the exclusion criteria, depression patients who had other comorbid mental disorders or those who had severe cognitive impairments and were unable to communicate effectively were excluded. The study was approved by the Biomedical Ethics Review Committee of West China Hospital (Approval No. 647, 2021). Demographic data such as age, sex, ethnicity, marital status, and educational attainment were collected using a self-designed questionnaire. Both the HEI and NGASR were applied to evaluate the patients. We conducted statistical analyses with SPSS 27, employing Spearman\'s rank correlation for correlation analysis, Kappa tests for consistency between the two instruments, and receiver operating characteristic (ROC) curves for evaluating the predictive performance of HEI scores for high suicide risk, with the optimal HEI cutoff value determined on the basis of the Youden Index.
UNASSIGNED: The study included 386 depression inpatients with an average age of 32 years and an average length-of-stay of 14 days. Of these participants, 252 were female (65.3%) and 134 were male (34.7%). Regarding ethnicity, most of the participants were Han Chinese (89.4%), Tibetans accounted for 7.3%, and other minorities, 3.3%. Regarding marital status, 51.3% of the participants were married, 41.2% single, 6.5% divorced, and 1.0% widowed. Regarding educational attainment, 26.2% had an undergraduate or graduate education, 20.7% had junior college education, 24.8% had high school or secondary technical school education, and 28.2% had middle school education or less. The NGASR identified 57.3% of the participants as being at high suicide risk, while the HEI identified 53.6% as having severe emotional distress. There was a moderate agreement between the HEI and the NGASR scores, with a Kappa value of 0.518 ( P<0.001), indicating statistically significant differences. At an HEI score of 17, the Youden Index peaked at 0.52, predicting high suicide risk with a specificity of 76.36%, a sensitivity of 76.02%, and an area under the ROC curve of 0.829 (95% CI: 0.787-0.871), demonstrating statistically significant differences.
UNASSIGNED: HEI and NGASR demonstrate moderate agreement in assessing high suicide risk among depression patients. The HEI questionnaire effectively predicts high suicide risk in patients with depression, with 17 being the optimal cutoff value for assessing high suicide risk.

OBJECTIVE: This study aimed to assess the diagnostic potential of the Antibody concentration ratio in identifying treatment-refractory myasthenia gravis (MG).
METHODS: A retrospective analysis was conducted on 116 MG patients who underwent antibody detection at least twice between June 1, 2015, and June 1, 2023. Demographic and clinical characteristics were collated to ascertain their association with refractory MG. The Antibody Concentration Ratio was applied to determine treatment response, using the International Consensus Guidance criteria as the reference standard. The area under nonparametric receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated to assess the diagnostic efficacy of the Antibody concentration ratio following consecutive immunotherapy relative to initial antibody concentrations for refractory MG.
RESULTS: 19 out of 116 patients were unequivocally diagnosed with refractory MG. A significant correlation was found between the Antibody Concentration Ratio and refractory MG status in treatment-refractory and treatment-responsive patients. Subsequently, the AUC demonstrated the robust diagnostic capability of the Antibody concentration ratio for refractory MG, with an AUC of 0.8709 (95% CI: 0.7995-0.9422, p < 0.0001). The optimal cut-off value stood at 0.8903, exhibiting a sensitivity of 94.74% (95% CI: 75.36%-99.73%), a specificity of 68.04% (95% CI: 58.23%-76.48%), and accuracy of 72.41% (95% CI: 64.28%-80.54%).
CONCLUSIONS: Elevated Antibody Concentration Ratio is intrinsically linked with refractory MG and exhibits potential as an diagnostic biomarker for the condition.

Depression is a serious psychiatric illness that causes great inconvenience to the lives of elderly individuals. However, the diagnosis of depression is somewhat subjective. Nontargeted gas chromatography (GC)/liquid chromatography (LC)-mass spectrometry (MS) was used to study the plasma metabolic profile and identify objective markers for depression and metabolic pathway variation. We recruited 379 Chinese community-dwelling individuals aged ≥ 65. Plasma samples were collected and detected by GC/LC‒MS. Orthogonal partial least squares discriminant analysis and a heatmap were utilized to distinguish the metabolites. Receiver operating characteristic curves were constructed to evaluate the diagnostic value of these differential metabolites. Additionally, metabolic pathway enrichment was performed to reveal metabolic pathway variation. According to our standard, 49 people were included in the depression cohort (DC), and 49 people age- and sex-matched individuals were included in the non-depression cohort (NDC). 64 metabolites identified via GC‒MS and 73 metabolites identified via LC‒MS had significant contributions to the differentiation between the DC and NDC, with VIP values > 1 and p values < 0.05. Three substances were detected by both methods: hypoxanthine, phytosphingosine, and xanthine. Furthermore, 1-(sn-glycero-3-phospho)-1D-myo-inositol had the largest area under the curve (AUC) value (AUC = 0.842). The purine metabolic pathway is the most important change in metabolic pathways. These findings show that there were differences in plasma metabolites between the depression cohort and the non-depression cohort. These identified differential metabolites may be markers of depression and can be used to study the changes in depression metabolic pathways.

OBJECTIVE: To explore the relationship between the percentage of energy intake from macronutrients and obesity in Chinese adult residents, and analyze the cut-off values of macronutrients for predicting obesity.
METHODS: Data was collected in China Health and Nutrition Survey(CHNS)in 1991-2018. Adults who participated in at least two waves of the surveys and were not obese at baseline were selected as the study subjects. Obesity was defined as body mass index(BMI)≥28.0 kg/m~2. Generalized estimating equation was used to analyze the relationship between the percentage of energy intake from macronutrients and BMI and obesity, and receiver operating characteristic curve(ROC) was used to analyze the cut-off values of percentage of energy intake from macronutrients to predict obesity.
RESULTS: The percentage of energy intake from protein and fat of adult residents in 15 provinces(autonomous regions and municipalities) in China showed an increasing trend(P<0.01), and the percentage of energy intake from carbohydrate showed a decreasing trend(P<0.01) between 1991 and 2018. After adjusting for covariates, the group of percentage of energy intake from fat in 20%～30%(β=0.05, 95%CI 0.01-0.08)and ≥30%(β=0.15, 95%CI 0.11-0.18)were positively correlated with BMI compared with the group of percentage of energy intake from fat <20%, and the risk of obesity in 20%-30% and ≥ 30% was increased by 17%(OR=1.17, 95%CI 1.04-1.31)and 6%(OR=1.06, 95%CI 1.24-1.56), respectively. Compared with the group of the percentage of energy intake from carbohydrate < 50%, the group of 50% to 65%(β=-0.08, 95% CI-0.11--0.05) and ≥ 65%(β=-0.17, 95%CI-0.20--0.13) was negatively correlated with BMI, and the percentage of energy intake from carbohydrate ≥ 65% reduced the risk of obesity(OR=0.71, 95%CI 0.63-0.80).
CONCLUSIONS: Carbohydrate intake was inversely correlated with the risk of obesity, and fat intake was positively correlated with the risk of obesity. Moderate intake of carbohydrates and reduced fat intake can prevent obesity.

UNASSIGNED: To examine the correlation of neutrophil CD64 (nCD64) index with neurosyphilis (NS) across different stages of syphilis.
UNASSIGNED: A total of 1243 syphilis patients at different stages (344 of primary, 385 of secondary, and 514 of tertiary) included in this study were divided into NS and non-NS (NNS). Correlations of nCD64 index with currently used syphilis biomarkers were explored using Spearman correlation test. Relationships between nCD64 index and NS at different stages were investigated by stratified analysis and restricted cubic spline model. The diagnostic performance of nCD64 index for NS was assessed by receiver operating characteristic (ROC) curve.
UNASSIGNED: Significant statistical correlations of nCD64 index with cerebrospinal fluid (CSF) NS indicators were found in secondary and tertiary syphilis. Increased nCD64 index was associated with increased risk of NS in secondary and tertiary syphilis. ROC analysis values further confirmed the diagnostic potential of nCD64 index for NS. Marked decrease of nCD64 index was observed in NS patients after effective antisyphilitic treatments.
UNASSIGNED: The nCD64 index may help to the diagnosis of NS in secondary and tertiary syphilis.

In many modern machine learning applications, changes in covariate distributions and difficulty in acquiring outcome information have posed challenges to robust model training and evaluation. Numerous transfer learning methods have been developed to robustly adapt the model itself to some unlabeled target populations using existing labeled data in a source population. However, there is a paucity of literature on transferring performance metrics, especially receiver operating characteristic (ROC) parameters, of a trained model. In this paper, we aim to evaluate the performance of a trained binary classifier on unlabeled target population based on ROC analysis. We proposed Semisupervised Transfer lEarning of Accuracy Measures (STEAM), an efficient three-step estimation procedure that employs (1) double-index modeling to construct calibrated density ratio weights and (2) robust imputation to leverage the large amount of unlabeled data to improve estimation efficiency. We establish the consistency and asymptotic normality of the proposed estimator under the correct specification of either the density ratio model or the outcome model. We also correct for potential overfitting bias in the estimators in finite samples with cross-validation. We compare our proposed estimators to existing methods and show reductions in bias and gains in efficiency through simulations. We illustrate the practical utility of the proposed method on evaluating prediction performance of a phenotyping model for rheumatoid arthritis (RA) on a temporally evolving EHR cohort.

The connection between the triglyceride-glucose index (TyG index) and gestational diabetes mellitus (GDM) is currently debated. Our study aimed to investigate the connection between the TyG index and GDM within the Korean population.
Using publically accessible data in Korea, we performed a secondary study on a sample of 589 pregnant women who were carrying a single fetus. The analysis employed a binary logistic regression model, some sensitivity analyses, and subgroup analysis to investigate the association between the TyG index and the occurrence of GDM. To assess the TyG index\'s potential to predict GDM, a receiver operating characteristic (ROC) study was also carried out.
The mean age of the pregnant women was 32.065 ± 3.798 years old, while the mean TyG index was 8.352 ± 0.400. The prevalence rate of GDM was found to be 6.112%. Upon adjusting for potential confounding variables, a positive association was detected between the TyG index and incident GDM (OR = 12.923, 95%CI: 3.581-46.632, p = 0.00009). The validity of this connection was further confirmed by subgroup analysis and sensitivity analyses. With an area under the ROC curve of 0.807 (95%CI: 0.734-0.879), the TyG index showed strong predictive power for GDM. The TyG index\'s ideal cutoff value for detecting GDM was found to be 8.632, with a sensitivity of 78.7% and a specificity of 72.2%.
The findings of our study provide evidence that an increased TyG index is significantly associated with the occurrence of GDM. Utilizing the TyG index during the 10-14 week gestational period may be a valuable tool in identifying pregnant individuals at a heightened risk for developing GDM. Early detection enables timely and efficacious interventions, thereby enhancing the prognosis of affected individuals.

Type 2 diabetes mellitus (T2DM) remains a major and widespread public health concern throughout the world. The prevalence of T2DM in the elderly has risen to the top of the list of public health concerns. In this study, obesity- and lipid-related indices were used to predict T2DM in middle-aged and elderly Chinese adults.
The data came from the China Health and Retirement Longitudinal Study (CHARLS), including 7902 middle-aged and elderly participants aged 45 years or above. The study assessed the association of obesity- and lipid-related indices and T2DM by measuring 13 indicators, including body mass index (BMI), waist circumference(WC), waist-height ratio (WHtR), conicity index(CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The association of 13 obesity- and lipid-related indices with T2DM was investigated by binary logistic regression. Additionally, the predictive anthropometric index was evaluated, and the ideal cut-off value was established using the receiver operating characteristic (ROC) curve analysis and area under the curve (AUC).
The study included 7902 participants, of whom 3638(46.04) and 4264(53.96) were male and female. The prevalence of T2DM in mid-aged and old adults in China was 9.02% in males and 9.15% in females. All the above 13 indicators show a modest predictive power (AUC>0.5), which was significant for predicting T2DM in adults (middle-aged and elderly people) in China (P<0.05). The results revealed that TyG-WHtR [AUC =0.600, 95%CI: 0.566-0.634] in males and in females [AUC =0.664, 95%CI: 0.636-0.691] was the best predictor of T2DM (P<0.05).
Most obesity- and lipid-related indices have important value in predicting T2DM. Our results can provide measures for the early identification of T2DM in mid-aged and elderly Chinese to reduce the prevalence of T2DM and improve health.

OBJECTIVE: This study evaluates the ROX index\'s accuracy in predicting the success or failure of high-flow nasal cannula (HFNC) therapy in children under 2 years with acute respiratory failure (ARF) from lower respiratory tract infections.
METHODS: From January 2018 to 2021 we conducted this multicenter retrospective cohort study, which included patients aged 2-24 months. We aimed to assess HFNC therapy outcomes as either success or failure. The analysis covered patient demographics, diagnoses, vital signs, and ROX index values at intervals from 0 to 48 h after initiating HFNC. We used bivariate analysis, repeated measures ANOVA, multivariate logistic regression, and the area under the receiver operating characteristic (AUC-ROC) curve for statistical analysis.
RESULTS: The study involved 529 patients from six centers, with 198 females (37%) and a median age of 9 months (IQR: 3-15 months). HFNC therapy failed in 38% of cases. We observed significant variability in failure rates across different centers and physicians (p < .001). The ROX index was significantly associated with HFNC outcomes at all time points, showing an increasing trend in success cases over time (p < .001), but not in HFNC failure cases. Its predictive ability is limited, with AUC-ROC values ranging from 0.56 at the start to 0.67 at 48 h.
CONCLUSIONS: While the ROX index is associated with HFNC outcomes in children under 2 years, its predictive ability is modest, impacted by significant variability among patients, physicians, and centers. These findings emphasize the need for more reliable predictive tools for HFNC therapy in this patient population.