Deep Learning Model for Pathological Grading and Prognostic Assessment of Lung Cancer Using CT Imaging: A Study on NLST and External Validation Cohorts.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning model for automated pathological grading and prognostic assessment of lung cancer using CT imaging, thereby providing surgeons with a non-invasive tool to guide surgical planning. MATERIAL AND METHODS: This study utilized 572 cases from the National Lung Screening Trial cohort, dividing them randomly into training (461 cases) and internal validation (111 cases) sets in an 8:2 ratio. Additionally, 224 cases from four cohorts obtained from the Cancer Imaging Archive, all diagnosed with non-small cell lung cancer, were included for external validation. The deep learning model, built on the MobileNetV3 architecture, was assessed in both internal and external validation sets using metrics such as accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The model's prognostic value was further analyzed using Cox proportional hazards models. RESULTS: The model achieved high accuracy, sensitivity, specificity, and AUC in the internal validation set (accuracy: 0.888, macro AUC: 0.968, macro sensitivity: 0.798, macro specificity: 0.956). External validation demonstrated comparable performance (accuracy: 0.807, macro AUC: 0.920, macro sensitivity: 0.799, macro specificity: 0.896). The model's predicted signatures correlated significantly with patient mortality and provided valuable insights for prognostic assessment (adjusted HR 2.016 [95% CI: 1.010, 4.022]). CONCLUSIONS: This study successfully developed and validated a deep learning model for the preoperative grading of lung cancer pathology. The model's accurate predictions could serve as a useful adjunct in treatment planning for lung cancer patients, enabling more effective and customized interventions to improve patient outcomes.

Association between Mixed Heavy Metal Exposure and Arterial Stiffness, with Alkaline Phosphatase Identified as a Mediator.

Elevated arterial stiffness has been associated with exposure to heavy metals such as lead (Pb) and cadmium (Cd). However, the collective impact of multiple metals and the underlying mechanisms are not fully elucidated. The purpose of this study was to assess the combined effects of exposure to nine heavy metals on arterial stiffness and explore whether serum alkaline phosphatase (ALP) acts as a mediator in this relationship. In the retrospective analysis, data from 8,700 participants were retrieved from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. Arterial stiffness was measured by estimated pulse wave velocity (ePWV). The cumulative impact of exposure to multiple metals was examined using adaptive elastic-net, environmental risk score, weighted quantile sum regression, and quantile g-computation. Additionally, mediation analysis was conducted to explore the potential mediating role of serum ALP. We found that combined exposure to multiple metals was consistently associated with elevated ePWV, with Ba, Pb, and Sb exhibiting the greatest contributions. Notably, serum ALP partially mediated the associations between individual (Pb, Sb) and mixed metal exposure with ePWV, with mediation proportions at 10.76% for Pb, 18.22% for Sb, and 11.07% for mixed metal exposure. In conclusion, this study demonstrates a clear association between exposure to heavy metals, either individually or in combination, and heightened arterial stiffness. Furthermore, the findings suggest that serum ALP activity may act as a mediator in these relationships.

Low Remnant Cholesterol and In-Hospital Bleeding Risk After Ischemic Stroke or Transient Ischemic Attack.

BACKGROUND: Bleeding risk brought by intensive lipid-lowering therapy and low low-density lipoprotein cholesterol is concerning, while evidence regarding the relationship between remnant cholesterol and bleeding is frightening. This study aimed to investigate the association between remnant cholesterol at admission and an in-hospital bleeding event after acute ischemic stroke or transient ischemic attack (TIA). METHODS AND RESULTS: A total of 3222 eligible patients admitted to Shanghai Huashan Hospital between 2015 and 2021 with complete lipid data were analyzed. Patients were classified into low (<20.0 mg/dL), moderate (20.0-29.9 mg/dL), and high (≥30 mg/dL) groups by remnant cholesterol. The mean age of patients was 63.0± 13.1 years, including 2301 (71.4%) men and 651 (20.2%) with TIA. The median (interquartile range) of remnant cholesterol was 18.6 (13.5-25.9) mg/dL. After adjustment for confounding variables, patients with low remnant cholesterol had a higher risk of bleeding events (odds ratio, 2.56 [95% CI, 1.12-6.67]) than those with moderate remnant cholesterol. The high remnant cholesterol group was not significantly associated with bleeding risk. Combined assessment of low-density lipoprotein cholesterol and remnant cholesterol further identified patients with the highest risk of bleeding events. CONCLUSIONS: Low remnant cholesterol levels were associated with bleeding events during the acute stage of ischemic stroke and TIA. The assessment of remnant cholesterol could inform the bleeding risk during hospitalization both for patients and physicians in clinical practice.

Greater variability in HDL-C was associated with an increased risk of cognitive decline in the middle- and elderly Chinese: A cohort study.

BACKGROUND: Previous studies into relationship between high-density lipoprotein cholesterol (HDL-C) and cognitive decline were constrained to a single measurement, leaving the association between HDL-C variability and risk of cognitive decline unclear. METHODS: We identified 5930 participants from the China Health and Retirement Longitudinal Study (CHARLS) who were devoid for stroke, dementia, and memory-related diseases at baseline and underwent a minimum of 2 sequential health examinations during 2011-2015. Variability in HDL-C was defined as (1) variability independent of the mean (VIM), (2) average real variability (ARV), and (3) standard deviation (SD) of HDL-C change from baseline and follow-up visits. Cognitive function was evaluated in 2018 by Mini-mental state examination (MMSE) in the Chinese version. Logistic regression was employed to explore the association between HDL-C variability and cognitive decline. Odd ratios (OR) and 95 % confidence intervals (CI) were reported. RESULTS: The study included participants from CHARLS, mean age of 57.84±8.44 years and 44 % male. After adjustment for covariates, the highest quartile of VIM was associated with an increased risk of cognitive decline [OR:1.049, 95 %CI: 1.014-1.086] compared to the lowest quartile. For each SD increment of VIM, the OR was 1.015 (95 %CI:1.003-1.027). Strong dose-response relationships were identified (P for trend: 0.005). Consistent results were obtained for other measures of HDL-C variability (ARV and SD). Similar patterns were identified in different dimensions of cognition. CONCLUSIONS: Elevated HDL-C variability was associated with increased cognitive decline risk. Strategies to reducing HDL-C variability may lower the risks of cognitive decline among the general population.

The Association between Dietary Nutrient Intake and Acceleration of Aging: Evidence from NHANES.

The acceleration of aging is a risk factor for numerous diseases, and diet has been identified as an especially effective anti-aging method. Currently, research on the relationship between dietary nutrient intake and accelerated aging remains limited, with existing studies focusing on the intake of a small number of individual dietary nutrients. Comprehensive research on the single and mixed anti-aging effects of dietary nutrients has not been conducted. This study aimed to comprehensively explore the effects of numerous dietary nutrient intakes, both singly and in combination, on the acceleration of aging. Data for this study were extracted from the 2015-2018 National Health and Nutrition Examination Surveys (NHANES). The acceleration of aging was measured by phenotypic age acceleration. Linear regression (linear), restricted cubic spline (RCS) (nonlinear), and weighted quantile sum (WQS) (mixed effect) models were used to explore the association between dietary nutrient intake and accelerated aging. A total of 4692 participants aged ≥ 20 were included in this study. In fully adjusted models, intakes of 16 nutrients were negatively associated with accelerated aging (protein, vitamin E, vitamin A, beta-carotene, vitamin B1, vitamin B2, vitamin B6, vitamin K, phosphorus, magnesium, iron, zinc, copper, potassium, dietary fiber, and alcohol). Intakes of total sugars, vitamin C, vitamin K, caffeine, and alcohol showed significant nonlinear associations with accelerated aging. Additionally, mixed dietary nutrient intakes were negatively associated with accelerated aging. Single dietary nutrients as well as mixed nutrient intake may mitigate accelerated aging. Moderately increasing the intake of specific dietary nutrients and maintaining dietary balance may be key strategies to prevent accelerated aging.

[Association between exposure to PM_(2.5) and chronic kidney disease in a population with metabolic syndrome].

OBJECTIVE: To investigate the association between long-term fine particulate matter(PM_(2.5)) exposure and the risk of chronic kidney disease(CKD) in people with abnormal metabolism syndrome(MS) components. METHODS: Based on health checkup data from a hospital in Beijing, a retrospective cohort study was used to collect annual checkup data from 2013-2019. A questionnaire was used to obtain information on demographic characteristics and lifestyle habits. We measured blood pressure, height, weight, waist circumference, concentrations of triglycerides(TG), fasting glucose, and high-density lipoprotein cholesterol(HDL-C). Longitude and latitude were also extracted from the addresses of the study subjects for pollutant exposure data estimation. Logistic regression models were used to explore the estimated effect of long-term PM_(2.5) exposure on the risk of CKD prevalence in people with abnormal MS components. Two-pollutant and multi-pollutant models were developed to test the stability of these result. Subgroup analysis was conducted based on age, the presence of MS, individual MS component abnormalities, and dual-component MS abnormalities. RESULTS: The study included 1540 study subjects with abnormal MS components at baseline, 206 with CKD during the study period. The association between long-term PM_(2.5) exposure and increased risk of CKD in people with abnormal MS fractions was statistically significant, with a 2.26-fold increase in risk of CKD for every 10 µg/m~3 increase in PM_(2.5) exposure(OR=3.26, 95% CI 2.72-3.90). The result in the dual-pollutant models and multi-pollutant models suggested that the association between long-term PM_(2.5) exposure and increased risk of CKD in people with abnormal MS fractions remained stable after controlling for contemporaneous confounding by other air pollutants. The result of subgroup analysis revealed that individuals aged 45 or older, without MS, with TG<1.7 mmol/L, HDL-C≥1.04 mmol/L, without hypertension, and with central obesity and high blood sugar had a stronger association between PM_(2.5) exposure and CKD-related health effects. CONCLUSION: Long-term exposure to PM_(2.5) may increase the risk of CKD in people with abnormal MS components. More attention should be paid to middle-aged and elderly people aged ≥45 years, people with central obesity and hyperglycemia.

Associations between sleep duration trajectories and cognitive decline: A longitudinal cohort study in China.

OBJECT: The relationship between sleep duration trajectories and cognitive decline remains uncertain. This study aims to examine the connections between various patterns of sleep duration and cognitive function. METHODS: Group-based trajectory modeling (GBTM) was employed to identify longitudinal trajectories of sleep duration over four-year follow-up period, while considering age, sex and nap duration as adjustments. Logistic regression was utilized to analyze the association between sleep trajectories and cognition, with odds ratios (OR) and 95 % confidence intervals (CI) reported. Subgroup analyses based on various demographic characteristics were conducted to explore potential differences in sleep trajectories and cognitive decline across different population subgroups. RESULTS: A total of 5061 participants were followed for four years, and three sleep duration trajectories were identified: high increasing (n = 2101, 41.6 %), stable increasing (n = 2087, 40.7 %), and low decreasing (n = 873, 17.7 %). After adjustment for basic demographic information, health status, and baseline cognition, the high increasing trajectory was found to be associated with cognitive decline in terms of global cognition (OR:1.52,95 %CI:1.18-1.96), mental intactness (OR:1.36,95 %CI:1.07-1.73) and episodic memory (OR:1.33, 95 %CI:1.05-1.67), as compared to stable increasing trajectory. These associations were particularly prominent among the non-elderly population (≤65 years) and those without depressive symptoms. CONCLUSION: This study suggests that both high increasing and low decreasing sleep duration trajectories are linked to cognitive decline, as compared to the stable increasing trajectory. Long-term attention to changes in sleep duration facilitates early prevention of cognitive decline.

Association between untreated and treated blood pressure levels and cognitive decline in community-dwelling middle-aged and older adults in China: a longitudinal study.

BACKGROUND: Optimal blood pressure (BP) levels to reduce the long-term risk of cognitive decline remains controversial. We aimed to investigate the association between BP and anti-hypertensive treatment status with cognitive decline in older adults. METHODS: This study used data from the China Health and Retirement Longitudinal Study. Cognitive function was assessed at year 2011, 2013, 2015, and 2018. Global cognitive Z-score was calculated as the average score of episodic memory and mental intactness. BP were measured at the first and second wave. Pulse pressure (PP) was calculated as systolic BP (SBP) minus diastolic BP. Cumulative BP was calculated as the area under the curve using BP measurements from 2011 to 2013. Linear mixed models were used to assess the longitudinal association between BP-related measurements and cognitive decline. RESULTS: We included 11,671 participants (47.3% men and mean age 58.6 years). Individual with BP > 140/90 mm Hg or taking anti-hypertensive medication were independently associated with accelerated cognitive decline (ß=-0.014, 95% CI: -0.020 to -0.007). Individuals with anti-hypertensive medication use, but with controlled SBP to less than 120 mm Hg did not have a significantly increased risk of cognitive decline compared with normotension (ß=-0.003, 95% CI: -0.021 to 0.014). Individuals on anti-hypertensive treatment with PP of more than 70 mm Hg had a significantly higher risk of cognitive decline (ß=-0.033, 95% CI: -0.045 to -0.020). Regardless of anti-hypertensive treatment status, both elevated baseline and cumulative SBP and PP were found to be independently associated with accelerated cognitive decline. CONCLUSIONS: Cumulatively elevated SBP, PP and uncontrolled BP were associated with subsequent cognitive decline. Effectively controlling BP with anti-hypertensive treatment may be able to preserve cognitive decline in older adults.

Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

Objectives. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by devising and externally validating a Multimodal Integrated Feature Neural Network (MIFNN). We hypothesize that the fusion of deep learning algorithms with morphological nodule features will significantly enhance diagnostic accuracy.Materials and Methods. Data were retrospectively collected from the Lung Nodule Analysis 2016 (LUNA16) dataset and four local centers in Beijing, China. The study includes patients with small pulmonary nodules (≤10 mm). We developed a neural network, termed MIFNN, that synergistically combines computed tomography (CT) images and morphological characteristics of pulmonary nodules. The network is designed to acquire clinically relevant deep learning features, thereby elevating the diagnostic accuracy of existing models. Importantly, the network's simple architecture and use of standard screening variables enable seamless integration into standard lung cancer screening protocols.Results. In summary, the study analyzed a total of 382 small pulmonary nodules (85 malignant) from the LUNA16 dataset and 101 small pulmonary nodules (33 malignant) obtained from four specialized centers in Beijing, China, for model training and external validation. Both internal and external validation metrics indicate that the MIFNN significantly surpasses extant state-of-the-art models, achieving an internal area under the curve (AUC) of 0.890 (95% CI: 0.848-0.932) and an external AUC of 0.843 (95% CI: 0.784-0.891).Conclusion. The MIFNN model significantly enhances the diagnostic accuracy of small pulmonary nodules, outperforming existing benchmarks by Zhanget alwith a 6.34% improvement for nodules less than 10 mm. Leveraging advanced integration techniques for imaging and clinical data, MIFNN increases the efficiency of lung cancer screenings and optimizes nodule management, potentially reducing false positives and unnecessary biopsies.Clinical relevance statement. The MIFNN enhances lung cancer screening efficiency and patient management for small pulmonary nodules, while seamlessly integrating into existing workflows due to its reliance on standard screening variables.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Temporal relationship between elevated serum uric acid levels and dyslipidemia: A 5-year cohort study using cross-lagged panel analysis.

BACKGROUND AND AIM: Previous studies have demonstrated an association between SUA and dyslipidemia. This study aims to explore the temporal relationship between SUA and dyslipidemia. METHODS AND RESULTS: Based on the Beijing Health Management Cohort conducted from 2013 to 2018, the data of a physical examination population was collected, including a total of 6630 study subjects. Cross-lagged panel analysis was employed to examine the temporal relationship between elevated SUA levels and dyslipidemia, indicated by either elevated TG or decreased HDL-C. The path coefficient and the 95 % CI from baseline TG to follow-up SUA were as follows: in the general population, men, women, and people with BMI ≥25 kg/m2were 0.027 (0.008-0.045), 0.024 (0.001-0.048), 0.032 (0.001-0.063) and 0.033 (0.006-0.059) (P < 0.05); however, the path coefficient from baseline SUA to follow-up TG and the 95 % CI were not statistically significant. Furthermore, the path coefficients and 95 % CIs between elevated SUA and decreased HDL-C were not statistically significant, both in the general population and in populations stratified by gender and BMI. CONCLUSIONS: We found a temporal relationship from elevated TG to elevated SUA in the general population and the populations stratified by gender and BMI (≥25 kg/m2). However, we did not observe a reverse relationship from elevated SUA to elevated TG. Additionally, we did not find a temporal relationship between decreased HDL-C and elevated SUA in both the general population and the stratified populations.

Association of chronic conditions and physical multimorbidity with new-onset incontinence in a nationwide prospective cohort study of older adults ≥ 50 years in China.

BACKGROUND: The relationship between multimorbidity (i.e. ≥ 2 chronic conditions) and incontinence (i.e. urinary and/or faecal incontinence) is underexplored. This study investigated the association between multimorbidity and incident incontinence in Chinese adults aged ≥50 years. METHODS: Data from the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study were used. The association between 12 chronic conditions, multimorbidity and new-onset incontinence was analysed using weighted logistic regression models. Mediation analysis was conducted to explore the potential mediators (self-reported health, subjective memory, depressive symptoms, disability, cognitive function, handgrip strength, mobility limitations, medications and frailty status) between multimorbidity and incontinence. FINDINGS: Among 9,986 individuals aged ≥50 years who were continent at baseline, 5.3% (n = 521) were newly incontinent 4 years later (incident cases). The risk of incident incontinence increased with physical multimorbidity (OR 2.04, 95% CI 1.62-2.57). Compared to no chronic condition, having 1, 2, 3 and ≥ 4 chronic conditions were associated with incident incontinence with OR (95% CI): 1.41 (1.01-1.97), 1.74 (1.24-2.44), 2.82 (1.93-4.12) and 3.99 (2.29-6.95), respectively. The association between multimorbidity and incontinence was mediated by self-reported health (41.2%), medications (26.6%), mobility limitations (20.9%), depressive symptoms (12.8%), disability (11.6%), subjective memory (8.7%) and frailty status (8.3%). CONCLUSION: This longitudinal study found that physical multimorbidity and specific chronic conditions may increase the risk of new-onset incontinence among Chinese adults aged ≥50 years. Self-reported health, medications and mobility limitations seemed to be important intermediate conditions between multimorbidity and incident incontinence.

PM2.5 constituents associated with childhood obesity and larger BMI growth trajectory: A 14-year longitudinal study.

BACKGROUND: The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored. METHODS: We conducted a longitudinal study among 1,450,830 Chinese children aged 6-19 years from Beijing and Zhongshan in China during 2005-2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure-response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6-19 years. RESULTS: We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036-1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139-1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory. CONCLUSIONS: Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.

The Association Between Serum Uric Acid and Cognitive Function Among Middle-Aged and Older Adults Without Hyperuricemia: The Mediating Role of Depressive Symptoms.

BACKGROUND: The association between serum uric acid (SUA) and cognitive function remains unclear, especially among individuals without hyperuricemia. We examined the cross-sectional and longitudinal bidirectional associations between SUA and cognition, as well as the mediating effect of depressive symptoms among Chinese adults. METHODS: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). SUA (continuous) and cognitive function (based on mental intactness and episodic memory) were measured at Wave 1 and Wave 3. Depressive symptoms (Center for Epidemiologic Studies Depression scale) were assessed at Wave 1. Bivariate latent change score models and mediation analysis were used to investigate these possible associations. RESULTS: A total of 6 236 participants free of hyperuricemia (aged 58.3 ±â€…8.5 years) were included. After controlling for potential confounders, the SUA level was associated with cognition at baseline (standardized r = 0.042; p = .001). Higher baseline SUA level was associated with slower subsequent cognitive decline (standardized ß = 0.026; p = .027), whereas baseline cognition was not significantly associated with subsequent change in SUA (standardized ß = 0.003; p = .817). In mediation analysis, baseline SUA was indirectly associated with subsequent cognition via baseline depressive symptoms (mediation effect 13.3%; p < .001). CONCLUSIONS: Higher baseline SUA level is associated with better baseline cognition and less subsequent cognitive decline among Chinese adults without hyperuricemia. Baseline depressive symptoms may partially mediate the association between baseline SUA and later cognition. Continued research is warranted to verify these findings and elucidate the causality and underlying mechanisms.

Association of Abnormal Lung Function and Its Subtypes With Arterial Stiffness: A Longitudinal Cohort Study.

BACKGROUND: Prior studies have reported the cross-sectional relationship between lung function and arterial stiffness, while the longitudinal association remains unclear to date. This study aimed to investigate whether abnormal lung function and its subtypes at baseline are associated with increased arterial stiffness using a cohort. METHODS AND RESULTS: This was a secondary analysis extracting 2461 participants from Beijing Health Management Cohort as baseline and annually followed for development of arterial stiffness. Abnormal lung function was defined by forced expiratory volume in 1s <80% of the predicted value, forced vital capacity of the predicted value, or forced expiratory volume in 1s/forced vital capacity ratio <70%. Increased arterial stiffness was determined by brachial-ankle pulse wave velocity ≥1400 cm/s. Cox proportional hazards model was used to calculate the hazard ratio and population attributable fraction. The mean age was 42.8±8.1 years, and 444 (18.0%) cases developed increased arterial stiffness during a median follow-up of 3.0 years. The adjusted hazard ratio (95% CI) of arterial stiffness was 1.47 (95% CI, 1.10-1.96) for abnormal lung function, with a population attributable fraction of 3.9% (95% CI, 0.8-7.1). Of subtypes, only obstructive ventilatory dysfunction was significantly associated with arterial stiffness (adjusted hazard ratio, 2.06 [95% CI, 1.27-3.36]), not restricted ventilatory dysfunction (adjusted hazard ratio, 0.95 [95% CI, 0.54-1.65]). Consistent results were observed on multiple sensitivity analyses. CONCLUSIONS: Our study indicated a longitudinal association of abnormal lung function with increased arterial stiffness using a large cohort, especially for the obstructive ventilatory dysfunction.

Parapapillary ßBM and γ Zones Played Different Roles in Axial Elongation Among Young Adolescents Using Optical Coherence Tomography.

Purpose: To evaluate the influencing factors of parapapillary ßBM and γ zones incidence in young adolescents and to explore their associations with axial length progression. Methods: In this prospective cohort study, 976 seventh-grade students from nine secondary schools in Beijing, China, were enrolled and followed up 1 year later. Parapapillary ßBM zone was defined as retinal pigment epithelium loss while Bruch's membrane was present. Parapapillary γ zone was defined as the absence of retinal pigment epithelium and Bruch's membrane. Logistic regression model was used to analyze the influencing factors of ßBM and γ zone incidence. A linear mixed model was used to analyze the associations between parapapillary zones and axial elongation. Results: Of the 976 participants, 139 (14.2%) had only ßBM zone, 398 (40.8%) had only γ zone, and 171 (17.5%) had both. At follow-up, the incidence of ßBM zone was 11.5% (76/659), and the incidence of γ zone was 9.7% (39/404). Optic disc tilt, thinner subfoveal choroid, and longer axial length at baseline showed a higher risk of γ zone incidence. The absence of γ zone at baseline showed a faster axial length progression. When the baseline axial length was 25 mm or longer, the ßBM zone was also related to the axial elongation. Conclusions: The γ zone was associated with axial length progression, and the ßBM zone was also associated with the axial length progression when the axial length exceeded 25 mm, which was consistent with the notion that excessive axial length growth not only is the extension of the eyeball but also has its own pathologic changes.

Machine Learning Model of ResNet50-Ensemble Voting for Malignant-Benign Small Pulmonary Nodule Classification on Computed Tomography Images.

BACKGROUND: The early detection of benign and malignant lung tumors enabled patients to diagnose lesions and implement appropriate health measures earlier, dramatically improving lung cancer patients' quality of living. Machine learning methods performed admirably when recognizing small benign and malignant lung nodules. However, exploration and investigation are required to fully leverage the potential of machine learning in distinguishing between benign and malignant small lung nodules. OBJECTIVE: The aim of this study was to develop and evaluate the ResNet50-Ensemble Voting model for detecting the benign and malignant nature of small pulmonary nodules (<20 mm) based on CT images. METHODS: In this study, 834 CT imaging data from 396 patients with small pulmonary nodules were gathered and randomly assigned to the training and validation sets in an 8:2 ratio. ResNet50 and VGG16 algorithms were utilized to extract CT image features, followed by XGBoost, SVM, and Ensemble Voting techniques for classification, for a total of ten different classes of machine learning combinatorial classifiers. Indicators such as accuracy, sensitivity, and specificity were used to assess the models. The collected features are also shown to investigate the contrasts between them. RESULTS: The algorithm we presented, ResNet50-Ensemble Voting, performed best in the test set, with an accuracy of 0.943 (0.938, 0.948) and sensitivity and specificity of 0.964 and 0.911, respectively. VGG16-Ensemble Voting had an accuracy of 0.887 (0.880, 0.894), with a sensitivity and specificity of 0.952 and 0.784, respectively. CONCLUSION: Machine learning models that were implemented and integrated ResNet50-Ensemble Voting performed exceptionally well in identifying benign and malignant small pulmonary nodules (<20 mm) from various sites, which might help doctors in accurately diagnosing the nature of early-stage lung nodules in clinical practice.

Intraindividual difference in estimated GFR by creatinine and cystatin C, cognitive trajectories and motoric cognitive risk syndrome.

BACKGROUND: Intraindividual differences between estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) and creatinine (eGFRcr) can convey important clinical information regarding the health status. However, the clinical implications of these differences (eGFRdiff) for risk of cognitive decline and motoric cognitive risk syndrome (MCR) remains unclear. We aimed to investigate the longitudinal associations of eGFRdiff with cognitive trajectories and incident MCR. METHODS: Based on the China Health and Retirement Longitudinal Study, we identified two study sub-cohorts: one for cognitive trajectory follow-up (6423 participants; years:2011-2018) and another for incident MCR follow-up (2477 participants; years:2011-2015). The eGFRdiff was defined as eGFRcys minus eGFRcr. Adjusted ordinal and binary logistics regression models were separately used to assess the associations of eGFRdiff with cognitive trajectories and incident MCR. We also performed discordance analyses for eGFRdiff vs eGFRcys, eGFRcr or eGFR based on both creatinine and cystatin C (eGFRcys-cr). RESULTS: In the first sub-cohort, four distinct 7-year cognitive trajectories were identified. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was associated with a lower risk of poorer cognitive trajectories (OR: 0.909, 95% CI: 0.877-0.942). In the second sub-cohort, 121 participants developed incident MCR after a 4-year follow-up. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was linked with a 25.3% (95%CI: 16.6%-33.2%) decreased risk for MCR. The above associations persisted in individuals with normal kidney function. Additionally, the risk for cognitive decline and incident MCR was more strongly associated with eGFRcys than eGFRcr and eGFRcys-cr. For the discordance analyses, 'discordantly high eGFRdiff/low eGFR' group, but not 'discordantly low eGFRdiff/high eGFR', exhibited a significantly lower risk of poorer cognitive trajectories and MCR compared to the concordant group. CONCLUSIONS: A large negative difference between eGFRcys and eGFRcr (eGFRcys lower than eGFRcr) was associated with higher risk of cognitive decline and incident MCR. The eGFRdiff could capture additional valuable risk information beyond eGFRcys, eGFRcr, and eGFRcys-cr.

Separate and Joint Associations of Remnant Cholesterol Accumulation and Variability With Carotid Atherosclerosis: A Prospective Cohort Study.

Background We aimed to examine separate and joint associations of remnant cholesterol (RC) accumulation and variability with the risk of carotid atherosclerosis (CAS) in the general population. Methods and Results A total of 6213 participants who underwent 3 sequential health examinations during 2010 to 2015 were enrolled and were followed up until December 31, 2021. Cumulative RC (cumRC) and RC variability among the 3 visits were the exposure of interest in our study. Adjusted Cox models were performed to calculate the hazard ratio (HR) and 95% CI. C-statistics, integrated discrimination improvement, and the net reclassification index were used to estimate the incremental predictive ability. During a median follow-up of 4.00 years, 2613 participants developed CAS. Higher cumRC (HR, 1.33 [95% CI, 1.17-1.52]) and greater RC variability (HR, 1.22 [95% CI, 1.08-1.39]) were significantly associated with elevated risk of CAS, independent of traditional cardiovascular risk factors and low-density lipoprotein cholesterol. Participants were divided into 4 groups according to the median of cumRC and RC variability to assess their joint associations. Compared with "low cumRC and low variability," "high cumRC and high variability" had the highest risk of CAS, followed by "high cumRC and low variability" and "low cumRC and high variability." Finally, joint assessment of RC accumulation and variability had the significantly highest incremental effect on the predictive value of CAS versus single-time-point measures of RC. Conclusions Excessive cumRC levels and greater RC variability were each independently associated with higher incidence of CAS, and their coexistence could further yield significantly higher risks.

Association Between Long-Term Exposure to Fine Particulate Matter Constituents and Progression of Cerebral Blood Flow Velocity in Beijing: Modifying Effect of Greenness.

Few studies have explored the effects of fine particulate matter (PM2.5) and its constituents on the progression of cerebral blood flow velocity (BFV) and the potential modifying role of greenness. In this study, we investigated the association of PM2.5 and its constituents, including sulfate (SO4 2-), nitrate (NO3 -), ammonium (NH4 +), organic matter (OM), and black carbon (BC), with the progression of BFV in the middle cerebral artery. Participants from the Beijing Health Management Cohort who underwent at least two transcranial Doppler sonography examinations during 2015-2020 were recruited. BFV change and BFV change rate were used to define the progression of cerebral BFV. Linear mixed effects models were employed to analyze the data, and the weighted quantile sum regression assessed the contribution of PM2.5 constituents. Additionally, greenness was examined as a modifier. Among the examined constituents, OM exhibited the strongest association with BFV progression. An interquartile range increase in PM2.5 and OM exposure concentrations was associated with a decrease of -16.519 cm/s (95% CI: -17.837, -15.201) and -15.403 cm/s (95% CI: -16.681, -14.126) in BFV change, and -10.369 cm/s/year (95% CI: -11.387, -9.352) and -9.615 cm/s/year (95% CI: -10.599, -8.632) in BFV change rate, respectively. Furthermore, stronger associations between PM2.5 and BFV progression were observed in individuals working in areas with lower greenness, those aged under 45 years, and females. In conclusion, reducing PM2.5 levels in the air, particularly the OM constituent, and enhancing greenness could potentially contribute to the protection of cerebrovascular health.