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.

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.

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.

BACKGROUND: Historically, clinicians have relied on medical risk factors and clinical symptoms for preterm birth risk assessment. In nulliparous women, clinicians may rely solely on reported symptoms to assess for the risk of preterm birth. The routine use of ultrasound during pregnancy offers the opportunity to incorporate quantitative ultrasound scanning of the cervix to potentially improve assessment of preterm birth risk.
OBJECTIVE: This study aimed to investigate the efficiency of quantitative ultrasound measurements at relatively early stages of pregnancy to enhance identification of women who might be at risk for spontaneous preterm birth.
METHODS: A prospective cohort study of pregnant women was conducted with volunteer participants receiving care from the University of Illinois Hospital in Chicago, Illinois. Participants received a standard clinical screening followed by 2 research screenings conducted at 20±2 and 24±2 weeks. Quantitative ultrasound scans were performed during research screenings by registered diagnostic medical sonographers using a standard cervical length approach. Quantitative ultrasound features were computed from calibrated raw radiofrequency backscattered signals. Full-term birth outcomes and spontaneous preterm birth outcomes were included in the analysis. Medically indicated preterm births were excluded from the analysis. Using data from each visit, logistic regression with Akaike information criterion feature selection was conducted to derive predictive models for each time frame based on historical clinical and quantitative ultrasound features. Model evaluations included a likelihood ratio test of quantitative ultrasound features, cross-validated receiver operating characteristic curve analysis, sensitivity, and specificity.
RESULTS: On the basis of historical clinical features alone, the best predictive model had an estimated receiver operating characteristic area under the curve of 0.56±0.03. By the time frame of Visit 1, a predictive model using both historical clinical and quantitative ultrasound features provided a modest improvement in the area under the curve (0.63±0.03) relative to that of the predictive model using only historical clinical features. By the time frame of Visit 2, the predictive model using historical clinical and quantitative ultrasound features provided significant improvement (likelihood ratio test, P<.01), with an area under the curve of 0.69±0.03.
CONCLUSIONS: Accurate identification of women at risk for spontaneous preterm birth solely through historical clinical features has been proven to be difficult. In this study, a history of preterm birth was the most significant historical clinical predictor of preterm birth risk, but the historical clinical predictive model performance was not statistically significantly better than the no-skill level. According to our study results, including quantitative ultrasound yields a statistically significant improvement in risk prediction as the pregnancy progresses.

Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10-3 mm2/s; SD = 0.31 × 10-3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10-3 mm2/s; SD = 0.28 × 10-3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10-3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.

To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors.
The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis.
A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability.
Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.

UNASSIGNED: To describe the demographics and phenotypes of malignancies-associated dermatomyositis (MADM) in east China and pinpoint potential factors indicative of malignancies in patients with dermatomyositis and establish a predictive model.
UNASSIGNED: We retrospectively analyzed clinical data from 134 patients with adult-onset dermatomyositis hospitalized between January 2019 and May 2022 in one comprehensive hospital. Clinical data including disease course, initial symptoms and signs, and demographic information were retrieved from the Electronic Medical Records System. Other parameters including myositis-specific autoantibodies profiles, ferritin, sedimentation, etc. were all referable. Multivariable multinomial logistic regression was employed to simulate a model to predict cancer risks. Receiver operating characteristic curve was adopted to evaluate the potency of the model.
UNASSIGNED: 134 patients with adult-onset dermatomyositis were aptly enrolled in this study based on inclusive and exclusive criteria: 12 (8.96%) with malignancies, 57 (42.53%) with aberrant tumor biomarkers but no malignancies, 65 (48.51%) with neither malignancies nor abnormal tumor biomarkers. Senior diagnostic age, higher LDH, higher ferritin, positive anti-TIF1γ and anti-Mi2 rather than anti-NXP2 autoantibodies were positive indicators of malignancies. Additionally, neither initial complaints nor signs were found to be correlated to a tendency towards malignancies. Digestive system, nasopharyngeal, and lung malignancies were mostly documented in east China. One multivariable multinomial logistic regression model was established to predict the phenotypes of dermatomyositis on the basis of potential malignancies and the overall sensitivity and specificity was satisfactory.
UNASSIGNED: Positivity of anti-TIF1γ and anti-Mi2 autoantibodies are highly indicative of malignancies while the role of anti-NXP2 autoantibody in MADM in the Chinese population remains unclear. The phenotypes of malignancies can be predicted through the model and the predictive power is sufficient. More attention should be paid to malignancies screening in patients with aberrant tumor biomarkers but no malignancies, particularly digestive system, nasopharyngeal, and lung malignancies in patients with dermatomyositis but without malignancies.

In the Danish population, about one-in-ten adults have prediabetes, undiagnosed, poorly or potentially sub-regulated diabetes, for short DMRC. It is important to offer these citizens relevant healthcare intervention. We therefore built a model for prediction of prevalent DMRC. Data were derived from the Lolland-Falster Health Study undertaken in a rural-provincial area of Denmark with disadvantaged health. We included variables from public registers (age, sex, age, citizenship, marital status, socioeconomic status, residency status); from self-administered questionnaires (smoking status, alcohol use, education, self-rated health, dietary habits, physical activity); and from clinical examinations (body mass index (BMI), pulse rate, blood pressure, waist-to-hip ratio). Data were divided into training/testing datasets for development and testing of the prediction model. The study included 15,801 adults; of whom 1,575 with DMRC. Statistically significant variables in the final model included age, self-rated health, smoking status, BMI, waist-to-hip ratio, and pulse rate. In the testing dataset this model had an area under the curve (AUC) = 0.77 and a sensitivity of 50% corresponding to a specificity of 84%. In a health disadvantaged Danish population, presence of prediabetes, undiagnosed, or poorly or potentially sub-regulated diabetes could be predicted from age, self-rated health, smoking status, BMI, waist-to-hip ratio, and pulse rate. Age is known from the Danish personal identification number, self-rated health and smoking status can be obtained from simple questions, and BMI, waist-to-hip ratio, and pulse rate can be measured by any person in health care and potentially by the person him/her-self. Our model might therefore be useful as a screening tool.

Currently, the study outcomes of anthropometric markers to predict the risk of hypertension are still inconsistent due to the effect of racial disparities. This study aims to investigate the most effective predictors for screening and prediction of hypertension (HTN) in the Chinese middle-aged and more elderly adult population and to predict hypertension using obesity and lipid-related markers in Chinese middle-aged and older people.
The data for the cohort study came from the China Health and Retirement Longitudinal Study (CHARLS), including 4423 middle-aged and elderly people aged 45 years or above. We examined 13 obesity- and lipid-related indices, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). To compare the capacity of each measure to forecast the probability of developing HTN, the receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for HTN in the elderly and determining their cut-off value, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related anthropometric indicators with HTN was performed using binary logistic regression analysis.
During the four years, the incident rates of HTN in middle-aged and elderly men and women in China were 22.08% and 17.82%, respectively. All the above 13 indicators show a modest predictive power (AUC > 0.5), which is significant for predicting HTN in adults (middle-aged and elderly people) in China (P < 0.05). In addition, when WHtR = 0.501 (with an AUC of 0.593, and sensitivity and specificity of 63.60% and 52.60% respectively) or TYg-WHtR = 4.335 (with an AUC of 0.601, and sensitivity and specificity of 58.20% and 59.30% respectively), the effect of predicting the incidence risk of men is the best. And when WHtR = 0.548 (with an AUC of 0.609, and sensitivity and specificity of 59.50% and 56.50% respectively) or TYg-WHtR = 4.781(with an AUC of 0.617, and sensitivity and specificity of 58.10% and 60.80% respectively), the effect of predicting the incidence risk of women is the best.
The 13 obesity- and lipid-related indices in this study have modest significance for predicting HTN in Chinese middle-aged and elderly patients. WHtR and Tyg-WHtR are the most cost-effective indicators with moderate predictive value of the development of HTN.