Establishment and validation of a predictive nomogram for polyuria during general anesthesia in thoracic surgery.

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.

Relationship between amide ratio assessed by Fourier-transform infrared spectroscopy: A biomarker candidate for polycythemia vera disease.

The study utilized Fourier transform infrared (FTIR) spectroscopy coupled with chemometrics to investigate protein composition and structural changes in the blood serum of patients with polycythemia vera (PV). Principal component analysis (PCA) revealed distinct biochemical properties, highlighting elevated absorbance of phospholipids, amides, and lipids in PV patients compared to healthy controls. Ratios of amide I/amide II and amide I/amide III indicated alterations in protein structures. Support vector machine analysis and receiver operating characteristic curves identified amide I as a crucial predictor of PV, achieving 100% accuracy, sensitivity, and specificity, while amide III showed a lower predictive value (70%). PCA analysis demonstrated effective differentiation between PV patients and controls, with key wavenumbers including amide II, amide I, and CH lipid vibrations. These findings underscore the potential of FTIR spectroscopy for diagnosing and monitoring PV.

The potential presence of infection may be indicated through non-invasive prediction of procalcitonin and C-reactive protein levels within the initial three days after cervical cerclage: a retrospective case-control study.

PURPOSE: To identify which non-invasive infection indicators could better predict post-cervical cerclage (CC) infections, and on which days after CC infection indicators should be closely monitored. METHODS: The retrospective, single-center study included 619 single-pregnancy patients from January 2021 to December 2022. Patients were categorized into infected and uninfected groups based on physicians' judgments of post-CC infections. Registered information included patient characteristics, cervical insufficiency history, gestational age at CC, surgical method (McDonald/Shirodkar), purpose of CC, mid-pregnancy miscarriage/preterm birth, infection history or risk factors, and infection indices on days 1, 3, 5, and 7 after CC. Propensity score matching (PSM) was applied to reduce patient characteristic bias. Statistical analysis of C-reactive protein (CRP), white blood cell (WBC), neutrophil count (NEU), percentage of neutrophil count (NEU_P), interleukin-6 (IL-6), and procalcitonin (PCT) in the infected group compared with the uninfected group was performed using chi-square tests and t-tests. Receiver operating characteristic (ROC) curves were used to further assess the diagnostic value of CRP, PCT, and CRP-PCT in combination. RESULTS: Among the 619 included patients, 206 patients were matched using PSM and subsequently assessed. PCT values on day 1 and day 3 after CC exhibited significant differences between the two groups in two statistical ways (P < 0.01, P < 0.05). The CRP levels on day 1 were significantly higher in the infected group compared to the uninfected group in two statistical ways (P < 0.05). On day 3, the mean CRP value was significantly elevated in the infected group compared to the uninfected group (P < 0.05). Analyses of IL-6, WBC, NEU, and NEU_P did not yield clinically significant results. The area under the ROC curves for CRP, PCT, and CRP-PCT on day 1 and day 3 were all below 0.7. In the preventive CC group, the AUC values of CRP and CRP-PCT obtained on d1 were found to be higher than 0.7, indicating moderate diagnostic accuracy. CONCLUSION: For women after CC surgery, especially of preventive aim, increased serum CRP and PCT levels from post-CC day 1 to day 3 may signal a potential postoperative infection, warranting close monitoring.

Bioinformatics and systems biology approach to identify the pathogenetic link of neurological pain and major depressive disorder.

Neurological pain (NP) is always accompanied by symptoms of depression, which seriously affects physical and mental health. In this study, we identified the common hub genes (Co-hub genes) and related immune cells of NP and major depressive disorder (MDD) to determine whether they have common pathological and molecular mechanisms. NP and MDD expression data was downloaded from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (Co-DEGs) for NP and MDD were extracted and the hub genes and hub nodes were mined. Co-DEGs, hub genes, and hub nodes were analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Finally, the hub nodes, and genes were analyzed to obtain Co-hub genes. We plotted Receiver operating characteristic (ROC) curves to evaluate the diagnostic impact of the Co-hub genes on MDD and NP. We also identified the immune-infiltrating cell component by ssGSEA and analyzed the relationship. For the GO and KEGG enrichment analyses, 93 Co-DEGs were associated with biological processes (BP), such as fibrinolysis, cell composition (CC), such as tertiary granules, and pathways, such as complement, and coagulation cascades. A differential gene expression analysis revealed significant differences between the Co-hub genes ANGPT2, MMP9, PLAU, and TIMP2. There was some accuracy in the diagnosis of NP based on the expression of ANGPT2 and MMP9. Analysis of differences in the immune cell components indicated an abundance of activated dendritic cells, effector memory CD8+ T cells, memory B cells, and regulatory T cells in both groups, which were statistically significant. In summary, we identified 6 Co-hub genes and 4 immune cell types related to NP and MDD. Further studies are needed to determine the role of these genes and immune cells as potential diagnostic markers or therapeutic targets in NP and MDD.

Identifying the risk factors for pancreatic fistula after laparoscopic pancreaticoduodenectomy in patients with pancreatic cancer.

BACKGROUND: Laparoscopic pancreaticoduodenectomy (LPD) is a surgical procedure for treating pancreatic cancer; however, the risk of complications remains high owing to the wide range of organs involved during the surgery and the difficulty of anastomosis. Pancreatic fistula (PF) is a major complication that not only increases the risk of postoperative infection and abdominal hemorrhage but may also cause multi-organ failure, which is a serious threat to the patient's life. This study hypothesized the risk factors for PF after LPD. AIM: To identify the risk factors for PF after laparoscopic pancreatoduodenectomy in patients with pancreatic cancer. METHODS: We retrospectively analyzed the data of 201 patients admitted to the Fudan University Shanghai Cancer Center between August 2022 and August 2023 who underwent LPD for pancreatic cancer. On the basis of the PF's incidence (grades B and C), patients were categorized into the PF (n = 15) and non-PF groups (n = 186). Differences in general data, preoperative laboratory indicators, and surgery-related factors between the two groups were compared and analyzed using multifactorial logistic regression and receiver-operating characteristic (ROC) curve analyses. RESULTS: The proportions of males, combined hypertension, soft pancreatic texture, and pancreatic duct diameter ≤ 3 mm; surgery time; body mass index (BMI); and amylase (Am) level in the drainage fluid on the first postoperative day (Am > 1069 U/L) were greater in the PF group than in the non-PF group (P < 0.05), whereas the preoperative monocyte count in the PF group was lower than that in the non-PF group (all P < 0.05). The logistic regression analysis revealed that BMI > 24.91 kg/m² [odds ratio (OR) =13.978, 95% confidence interval (CI): 1.886-103.581], hypertension (OR = 8.484, 95%CI: 1.22-58.994), soft pancreatic texture (OR = 42.015, 95%CI: 5.698-309.782), and operation time > 414 min (OR = 15.41, 95%CI: 1.63-145.674) were risk factors for the development of PF after LPD for pancreatic cancer (all P < 0.05). The areas under the ROC curve for BMI, hypertension, soft pancreatic texture, and time prediction of PF surgery were 0.655, 0.661, 0.873, and 0.758, respectively. CONCLUSION: BMI (> 24.91 kg/m²), hypertension, soft pancreatic texture, and operation time (> 414 min) are considered to be the risk factors for postoperative PF.

Cost-benefit considerations of the biased diagnostician.

OBJECTIVES: In the cognitive process of establishing a diagnosis, the performance of a diagnostician can be characterized in terms of sensitivity and specificity. The aims of the present study are to analyze in quantitative terms how cognitive bias affects the performance of a diagnostician, and how a diagnostician's biased decision making is further influenced by personal cost-benefit considerations. METHODS: The test matrices of two sequential diagnostic tests are manipulated according to the rules of linear algebra, using multiplication of the second with the first test matrix to calculate their joint test characteristics. The decision tree and receiver operating characteristic (ROC) of a biased and unbiased diagnostician are used to calculate which combination of test characteristics maximizes the expected utility value. RESULTS: Biased diagnosticians cannot establish a diagnosis beyond their own limited or distorted level of understanding. An unbiased and a biased diagnostician alike adjust their choice of test characteristics according to their different cost-benefit estimation of the various test outcomes. From the perspective of an unbiased diagnostician, the choices made by a biased diagnostician appear to invert reality. However, the same appearance of inverted reality is perceived by the biased diagnostician, judging the choices made by the unbiased diagnostician. CONCLUSIONS: As a general principle, human testers cannot test beyond their own level of understanding. They only see what they know. As they base their judgment on preconceived notions about the utilities associated with different test outcomes, human testers also tend to only know what they want to know.

Discriminative validity and interpretability of the mood and feelings questionnaire.

BACKGROUND: Using the Mood and Feelings Questionnaire (MFQ) to differentiate between depression severity levels remains unexplored. We explored the discriminative validity of the MFQ to identify an optimal cut-off MFQ score to distinguish between subthreshold-to-mild and moderate-to-severe depression severity levels. METHODS: An observational cross-sectional design was used in a sample (N = 67) of help-seeking youth (ages 13 to 18, inclusive) experiencing depressive symptoms. The MFQ was administered verbatim to youth by a research analyst over the phone. Youth were then grouped into subthreshold-to-mild or moderate-to-severe depression severity categories based on scores received on the Kiddie Schedule for Affective Disorders and Schizophrenia-Depression Rating Scale. Receiver Operating Characteristic curve analyses were conducted, with area under the curve (AUC) and Youden Index (J) as primary indices. We hypothesized that the lower limit of the 95 % confidence interval for the area under the curve would be ≥0.70. RESULTS: The primary analysis yielded an AUC of 0.85 (95 % CI: 0.763-0.947) and an optimal cut-off of ≥43 (J = 0.60, positive predictive value = 91.4 %, negative predictive value = 62.5 %, sensitivity = 72.7 %, specificity = 87.0 %). LIMITATIONS: Our study collected a small sample, and as such cannot identify how subgroup classification (e.g., based on race or gender) may moderate outcomes. Further, unknown measurement error of the predictor and reference variable measures can bias the estimates. CONCLUSIONS: Our preliminary findings highlight the potential for the MFQ to support clinical decision-making relevant to adolescents experiencing varying severities of depressive symptoms in secondary care settings.

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Objective: 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. Methods: 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. Results: 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. Conclusion: 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.

A Summed Score From Cardiopulmonary Exercise Test Parameters Predicts 1-Year Mortality in Newly Diagnosed Interstitial Lung Disease.

BACKGROUND: Cardiopulmonary exercise testing (CPET) is a unique diagnostic tool that assesses the functional capacity of the heart, lungs, and peripheral oxidative system in an integrated manner. However, the clinical utility of CPET for evaluating interstitial lung disease (ILD) remains uncertain. The objective of this study was to determine the predictive value of CPET for mortality in subjects with ILD. METHODS: We prospectively enrolled subjects with ILD who underwent CPET at a tertiary medical center in Taiwan and followed up their survival status for 12 months. Mortality prediction was based on comparing CPET parameters between subjects who survived and those who died. We further analyzed CPET parameters that showed significant differences using receiver operating characteristic curves to identify their optimal cutoff values. RESULTS: A total of 106 newly diagnosed subjects with ILD underwent CPET, and the 1-y mortality rate was 7.5%. Six CPET variables were found to be significant predictors of mortality: peak oxygen consumption, oxygen pulse, end-tidal partial pressure of carbon dioxide, heart rate recovery 1 min after CPET, minute ventilation to carbon dioxide output slope, and functional aerobic impairment. We calculated a summed score by adding the number of CPET variables that exceeded their cutoff values. Subjects with a summed score of 6 had a 1-y survival rate of only 25%, whereas subjects with scores of 0-5 had a survival rate of 98%. CONCLUSIONS: In conclusion, the summed score represents a useful tool for screening patients with ILD who can undergo a CPET to determine their prognosis.

Short- and long-term performance of risk calculation tools for mortality in patients with acute coronary syndrome.

Background: The mortality rate of acute coronary syndrome (ACS) remains high. Therefore, patients with ACS should undergo early risk stratification, for which various risk calculation tools are available. However, it remains uncertain whether the predictive performance varies over time between risk calculation tools for different target periods. This study aimed to compare the predictive performance of risk calculation tools in estimating short- and long-term mortality risks in patients with ACS, while considering different observation periods using time-dependent receiver operating characteristic (ROC) analysis. Methods: This study included 404 consecutive patients with ACS who underwent coronary angiography at our hospital from March 2017 to January 2021. The ACTION and GRACE scores for short-term risk stratification purposes and CRUSADE scores for long-term risk stratification purposes were calculated for all participants. The participants were followed up for 36 months to assess mortality. Using time-dependent ROC analysis, we evaluated the area under the curve (AUC) of the ACTION, CRUSADE, and GRACE scores at 1, 6, 12, 24, and 36 months. Results: Sixty-six patients died during the observation periods. The AUCs at 1, 6, 12, 24, and 36 months of the ACTION score were 0.942, 0.925, 0.889, 0.856, and 0.832; those of the CRUSADE score were 0.881, 0.883, 0.862, 0.876, and 0.862; and those of the GRACE score 0.949, 0.928, 0.888, 0.875, and 0.860, respectively. Conclusions: The ACTION and GRACE scores were excellent risk stratification tools for mortality in the short term. The prognostic performance of each risk score was almost similar in the long term, but the CRUSADE score might be a superior risk stratification tool in the longer term than 3 years.

Diagnostic Accuracy of Transient Elastography in Hepatosteatosis in Youth With Obesity.

Context: Steatotic liver disease is common but overlooked in childhood obesity; diagnostic methods are invasive or expensive. Objective: We sought to determine the diagnostic accuracy of vibration-controlled transient elastography (VCTE) compared with magnetic resonance imaging (MRI) in adolescents with obesity and high risk for hepatosteatosis. Methods: Baseline data in 3 clinical trials enrolling adolescents with obesity were included (NCT03919929, NCT03717935, NCT04342390). Liver fat was assessed using MRI fat fraction and VCTE-based controlled attenuation parameter (CAP). Hepatosteatosis was defined as MRI fat fraction ≥5.0%. The area under the receiver-operating characteristic curves (AUROCs) for CAP against MRI was calculated, and optimal CAP using the Youden index for hepatosteatosis diagnosis was determined. Results: Data from 82 adolescents (age 15.6 ± 1.4 years, body mass index 36.5 ± 5.9 kg/m2, 81% female) were included. Fifty youth had hepatosteatosis by MRI (fat fraction 9.3% ; 95% CI 6.7, 14.0), and 32 participants did not have hepatosteatosis (fat fraction 3.1%; 95% CI 2.2, 3.9; P < .001). The hepatosteatosis group had higher mean CAP compared with no hepatosteatosis (293 dB/m; 95% CI 267, 325 vs 267 dB/m; 95% CI 248, 282; P = .0120). A CAP of 281 dB/m had the highest sensitivity (60%) and specificity (74%) with AUROC of 0.649 (95% CI 0.51-0.79; P = .04) in the entire cohort. In a subset of participants with polycystic ovary syndrome (PCOS), a CAP of 306 dB/m had the highest sensitivity (78%) and specificity (52%) and AUROC of 0.678 (95% CI 0.45-0.90; P = .108). Conclusion: CAP of 281 dB/m has modest diagnostic performance for hepatosteatosis compared with MRI in youth with significant obesity. A higher CAP in youth with PCOS suggests that comorbidities might affect optimal CAP in hepatosteatosis diagnosis.

Association of traditional and novel obesity indicators with stroke risk: Findings from the Rural Chinese cohort study.

BACKGROUND AND AIMS: Few researchers have compared the effectiveness of traditional and novel obesity indicators in predicting stroke incidence. We aimed to evaluate the associations between six obesity indices and stroke risk, and to further identify the optimal indicator. METHODS AND RESULTS: A total of 14,539 individuals from the Rural Chinese Cohort Study were included in the analyses. We used the Cox proportional hazards regression models to evaluate the association between six obesity indices (including body mass index [BMI], waist circumference [WC], conicity index [C-index], lipid accumulation product [LAP], visceral adiposity index [VAI], and Chinese visceral adiposity index [CVAI]) and stroke risk. Receiver operating characteristic curves were employed to compare their predictive ability on stroke risk. During a median follow-up period of 11.13 years, a total of 1257 cases of stroke occurred. In the multiple-adjusted Cox regression model, WC, BMI, C-index, and CVAI were positively associated with ischemic stroke (P < 0.01) rather than hemorrhagic stroke risk. Dose-response analyses showed a linear correlation of WC, BMI, C-index, and LAP (Poverall <0.05, and Pnonlinear >0.05), but a non-linear correlation of CVAI (Poverall <0.05, and Pnonlinear <0.05) with the risk of ischemic stroke. CVAI demonstrates the highest areas under the curves (AUC: 0.661, 95% CI: 0.653-0.668), indicating a superior predictive ability for ischemic stroke occurrence compared to other five indices (P < 0.001). CONCLUSION: WC, BMI, C-index, LAP, and CVAI were all positively related to the risk of ischemic stroke, among which CVAI exhibited stronger predictive ability for ischemic stroke.

Evaluating prognostic biomarkers for survival outcomes subject to informative censoring.

Prognostic biomarkers for survival outcomes are widely used in clinical research and practice. Such biomarkers are often evaluated using a C-index as well as quantities based on time-dependent receiver operating characteristic curves. Existing methods for their evaluation generally assume that censoring is uninformative in the sense that the censoring time is independent of the failure time with or without conditioning on the biomarker under evaluation. With focus on the C-index and the area under a particular receiver operating characteristic curve, we describe and compare three estimation methods that account for informative censoring based on observed baseline covariates. Two of them are straightforward extensions of existing plug-in and inverse probability weighting methods for uninformative censoring. By appealing to semiparametric theory, we also develop a doubly robust, locally efficient method that is more robust than the plug-in and inverse probability weighting methods and typically more efficient than the inverse probability weighting method. The methods are evaluated and compared in a simulation study, and applied to real data from studies of breast cancer and heart failure.

Examining early adherence measures as predictors of subsequent adherence in an intensive longitudinal study of individuals in mutual help groups: One day at a time.

BACKGROUND: Individuals with a substance use disorder complete ecological momentary assessments (EMA) at lower rates than community samples. Previous research in tobacco users indicates that early log-in counts to smoking cessation websites predicted subsequent smoking cessation website usage. We extended this line of research to examine individuals who are seeking to change their drinking behaviors through mutual support groups. We examined whether adherence in the first 7 days (1487 observations) of an intensive longitudinal study design could predict subsequent EMA protocol adherence (50% and 80% adherence separately) at 30 (5700 observations) and 60 days (10,750 observations). METHODS: Participants (n = 132) attending mutual-help groups for alcohol use completed two assessments per day for 6 months. We trained four classification models (logistic regression, recursive partitioning, support vector machines, and neural networks) using a training dataset (80% of the data) with each of the first 7 days' cumulative EMA assessment completion. We then tested these models to predict the remaining 20% of the data and evaluated model classification accuracy. We also used univariate receiver operating characteristic curves to examine the minimal combination of days and completion percentage to best predict subsequent adherence. RESULTS: Different modeling techniques can be used with early assessment completion as predictors to accurately classify individuals that will meet minimal and optimal adherence rates later in the study. Models ranged in their performance from poor to outstanding classification, with no single model clearly outperforming other models. CONCLUSIONS: Traditional and machine learning approaches can be used concurrently to examine several methods of predicting EMA adherence based on early assessment completion. Future studies could investigate the use of several algorithms in real time to help improve participant adherence rates by monitoring early adherence and using early assessment completion as features in predictive modeling.

Analysis of factors associated with positive surgical margins and the five-year survival rate after prostate cancer resection and predictive modeling.

Background: This study analyzed the risk factors associated with positive surgical margins (PSM) and five-year survival after prostate cancer resection to construct a positive margin prediction model. Methods: We retrospectively analyzed the clinical data of 148 patients treated with prostatectomy. The patients were divided into PSM group and Negative surgical margins (NSM) group. Several parameters were compared between the groups. All patients were followed up for 60 months. The risk factors for PSM and five-year survival were evaluated by univariate analysis, followed by multifactorial dichotomous logistic regression analysis. Finally, ROC curves were plotted for the risk factors to establish a predictive model for PSM after prostate cancer resection. Results: (1) Serum PSA, percentage of positive puncture stitches, clinical stage, surgical approach, Gleason score on puncture biopsy, and perineural invasion were significantly associated with the risk of PSM (P < 0.05). Serum PSA, perineural invasion, Gleason score on puncture biopsy, and percentage of positive puncture stitches were independent risk factors for PSM. (2) Total prostate-specific antigen (tPSA) by puncture, nutritional status, lymph node metastasis, bone metastasis, and seminal vesicle invasion may be risk factors for five-year survival. Lymph node metastasis and nutritional status were the main risk factors for the five-year survival of patients with prostate cancer. (3) After plotting the ROC curve, the area under the curve (AUC) [AUC: 0.776, 95%, confidence interval (CI): 0.725 to 0.854] was found to be a valid predictor of PSM; the AUC [AUC: 0.664, 95%, confidence interval (CI): 0.576 to 0.753] was also a valid predictor of five-year survival (P < 0.05). (4) The scoring system had a standard error of 0.02 and a cut-off value of 6. It predicted PSM after prostate cancer resection with moderate efficacy. Conclusions: Serum PSA, perineural invasion, puncture biopsy Gleason score, and percentage of positive puncture stitches were independent risk factors for positive surgical margins (PSM). Also, lymph node metastasis and nutritional status were the main risk factors for the five-year survival of patients with prostate cancer. Overall, the prediction efficacy of this scoring system concerning the risk of PSM after prostate cancer resection was moderate.

Investigation of the structural changes in the hippocampus and prefrontal cortex using FTIR spectroscopy in sleep deprived mice.

Sleep is a basic, physiological requirement for living things to survive and is a process that covers one third of our lives. Melatonin is a hormone that plays an important role in the regulation of sleep. Sleep deprivation affect brain structures and functions. Sleep deprivation causes a decrease in brain activity, with particularly negative effects on the hippocampus and prefrontal cortex. Despite the essential role of protein and lipids vibrations, polysaccharides, fatty acid side chains functional groups, and ratios between amides in brain structures and functions, the brain chemical profile exposed to gentle handling sleep deprivation model versus Melatonin exposure remains unexplored. Therefore, the present study, aims to investigate a molecular profile of these regions using FTIR spectroscopy measurement's analysis based on lipidomic approach with chemometrics and multivariate analysis to evaluate changes in lipid composition in the hippocampus, prefrontal regions of the brain. In this study, C57BL/6J mice were randomly assigned to either the control or sleep deprivation group, resulting in four experimental groups: Control (C) (n = 6), Control + Melatonin (C + M) (n = 6), Sleep Deprivation (S) (n = 6), and Sleep Deprivation + Melatonin (S + M) (n = 6). Interventions were administered each morning via intraperitoneal injections of melatonin (10 mg/kg) or vehicle solution (%1 ethanol + saline), while the S and S + M groups underwent 6 h of daily sleep deprivation from using the Gentle Handling method. All mice were individually housed in cages with ad libitum access to food and water within a 12-hour light-dark cycle. Results presented that the brain regions affected by insomnia. The structure of phospholipids, changed. Yet, not only changes in lipids but also in amides were noticed in hippocampus and prefrontal cortex tissues. Additionally, FTIR results showed that melatonin affected the lipids as well as the amides fraction in cortex and hippocampus collected from both control and sleep deprivation groups.

Diagnostic cut-off value of haemoglobin A1c for diabetes mellitus in Harare, Zimbabwe.

Very little is known about the diagnostic performance of the American Diabetes Association glycated haemoglobin (HbA1c) cut-off of 6.5% in resource-limited settings. This study, conducted between February 2023 and May 2023, aimed to determine the optimal HbA1c cut-off for the diagnosis of diabetes mellitus by measuring HbA1c and fasting plasma glucose levels in 120 adults attending care at a tertiary hospital in Harare, Zimbabwe. The optimal HbA1c cut-off was 6.1% and glucose levels were strongly correlated with HbA1c values. The prevalence of diabetes mellitus was higher (28.3%) at our derived HbA1c cut-off than with the American Diabetes Association criterion (21.6%). What this study adds: This study highlights the need for population-specific cut-off HbA1c values in the diagnosis of diabetes mellitus.

Dose-response association between Chinese visceral adiposity index and cardiovascular disease: a national prospective cohort study.

Background: Chinese visceral adiposity index (CVAI) is a reliable visceral obesity index, but the association between CVAI and risk of cardiovascular disease (CVD) remains unclear. We explored the associations of CVAI with incident CVD, heart disease, and stroke and compared the predictive power of CVAI with other obesity indices based on a national cohort study. Methods: The present study included 7,439 participants aged ≥45 years from China Health and Retirement Longitudinal Study (CHARLS). Cox regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Restricted cubic splines analyses were adopted to model the dose-response associations. Receiver operator characteristic (ROC) analyses were used to compare the predictive ability of different obesity indices (CVAI, visceral adiposity index [VAI], a body shape index [ABSI], conicity index [CI], waist circumference [WC], and body mass index [BMI]). Results: During 7 years' follow-up, 1,326 incident CVD, 1,032 incident heart disease, and 399 stroke cases were identified. The HRs (95% CI) of CVD, heart disease, and stroke were 1.50 (1.25-1.79), 1.29 (1.05-1.57), and 2.45 (1.74-3.45) for quartile 4 versus quartile 1 in CVAI. Linear associations of CVAI with CVD, heart disease, and stroke were observed (P nonlinear >0.05) and per-standard deviation (SD) increase was associated with 17% (HR 1.17, 1.10-1.24), 12% (1.12, 1.04-1.20), and 31% (1.31, 1.18-1.46) increased risk, respectively. Per-SD increase in CVAI conferred higher risk in participants aged<60 years than those aged ≥60 years (P interaction<0.05). ROC analyses showed that CVAI had higher predictive value than other obesity indices (P<0.05). Conclusions: CVAI was linearly associated with risk of CVD, heart disease, and stroke and had best performance for predicting incident CVD. Our findings indicate CVAI as a reliable and applicable obesity index to identify higher risk of CVD.

Diagnostic accuracy and clinical utility of the PHQ-2 and GAD-2: a comparison with long-format measures for depression and anxiety.

Background: Anxiety and depression are highly prevalent and often comorbid mental disorders that are encompassed within the broad category of emotional disorders. The frequent comorbidity of anxiety and depression can pose challenges for accurate diagnosis and treatment which, in turn, highlights the need for reliable measurements that are simultaneously responsive to change and prevent non-response bias. Brief measures of anxiety and depression can potentially increase response rates due to their brevity and ease of administration. This study evaluates the psychometric characteristics, discriminative accuracy, and sensitivity to change of the Generalized Anxiety Disorder 2-item scale (GAD-2) and the Patient Health Questionnaire 2-item scale (PHQ-2) within a clinical population. Method: The sample comprised treatment-seeking participants (n = 3,411), screened (n = 2,477) to receive an internet-based psychotherapeutic intervention (cognitive-behavioral, psychodynamic, or waitlist). Results: Brief measures can effectively detect individuals who may be eligible for a diagnosis of depression and anxiety, not only prior to but also during and following the completion of psychological treatment. The discriminative ability of the GAD-2 was significantly greater during active treatment and at post-assessment compared with pre-treatment screening, although no such differences were found for the PHQ-2. Finally, endorsing the most severe response option on the GAD-2 and PHQ-2 was associated with a high probability of presenting with clinically relevant anxiety and depressive symptoms. Conclusion: Brief measures of anxiety and depression are viable instruments to screen for and monitor anxiety and depressive symptoms. Clinical trial registration: ClinicalTrials.gov, identifier NCT05016843.

Associations between serum ferritin baselines and trajectories and the incidence of metabolic dysfunction-associated steatotic liver disease: a prospective cohort study.

BACKGROUND AND AIMS: Evidence from prospective cohort studies on the relationship between metabolic dysfunction-associated steatotic liver disease (MASLD) and longitudinal changes in serum ferritin (SF) still limited. This study aimed to investigate the associations of SF baselines and trajectories with new-onset MASLD and to present a MASLD discriminant model. METHODS: A total of 1895 participants who attended health examinations at least three times in a hospital in Dalian City between 2015 and 2022 were included. The main outcome was the incidence of MASLD. The associations between SF baselines and trajectories with the risk of MASLD were analyzed by Cox proportional hazards regression, restricted cubic spline (RCS) analysis and time-dependent receiver operating characteristic (ROC) curve analysis. In addition, a MASLD discrimination model was established using logistic regression analyses. RESULTS: Among the 1895 participants, 492 developed MASLD during follow-up. Kaplan-Meier analysis indicated that participants in the low-stable trajectory group had a longer MASLD-free time compared with participants in other groups. Compared with those in the low-stable trajectory group, the adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for the risk of new-onset MASLD in the medium-high, high-stable and high-high trajectory groups were 1.54(1.18-2.00), 1.77(1.35-2.32) and 1.55(1.07-2.26), respectively (Ptrend < 0.001). The results were robust in subgroup and sensitivity analyses. Multivariate Cox proportional regression showed that SF was an independent risk factor of MASLD (HR = 1.002, 95%CI: 1.000-1.003, P = 0.003). The restricted cubic spline demonstrated a nonlinear relationship between SF and the risk of MASLD. The 8-variable model had high discriminative performance, good accuracy and clinical effectiveness. The ROC curve results showed that AUC was greater than that of the FLI, HSI and ZJU models (all P < 0.01). CONCLUSIONS: Not only a higher baseline SF but also SF changing trajectory are significantly associated with risk of new-onset MASLD. SF could be a predictor of the occurrence of MASLD.