Tag: statistics

J Clin Endocrinol Metab. 2021 Aug 10:dgab591. doi: 10.1210/clinem/dgab591. Online ahead of print.

ABSTRACT

PURPOSE: Although homocysteine accumulation is a reported risk factor for several age-related disorders, little is known on its relationship with osteoarthritis (OA). We therefore investigated for associations of homocysteine and C677T polymorphism in methylenetetrahydrofolate reductase (MTHFR), which is involved in homocysteine clearance, with the development and progression of spinal OA, through a combined cross-sectional and longitudinal cohort study.

METHODS: A total of 1306 Japanese postmenopausal outpatients participating in the Nagano Cohort Study were followed for a 9.7-year mean period. Cross-sectional multiple logistic regression for spinal OA prevalence at registration by serum homocysteine level was performed with adjustment for confounders. In addition to Kaplan-Meier analysis, multivariate Cox regression was employed to examine the independent risk of MTHFR C677T variant for spinal OA progression.

RESULTS: Multivariate regression analysis revealed a significant association between homocysteine and spinal OA prevalence (odds ratio 1.38; 95% confidence interval [CI] 1.14-1.68). Kaplan-Meier curves showed a gene dosage effect of the T allele in MTHFR C677T polymorphism on the accelerated progression of spinal OA severity (P = 0.003). A statistically significant independent risk of the T allele for spinal OA advancement was validated by Cox regression analysis. Respective adjusted hazard ratios for the CT/TT and TT genotypes were 1.68 (95% CI 1.16-2.42) and 1.67 (95% CI 1.23-2.28).

CONCLUSIONS: Circulating homocysteine and C677T variant in MTHFR are associated with the prevalence rate and ensuing progression, respectively, of spinal OA. These factors may represent potential interventional targets to prevent OA development and improve clinical outcomes.

PMID:34375425 | DOI:10.1210/clinem/dgab591

Am J Prev Cardiol. 2021 Mar 29;5:100154. doi: 10.1016/j.ajpc.2021.100154. eCollection 2021 Mar.

ABSTRACT

[This corrects the article DOI: 10.1016/j.ajpc.2020.100035.].

PMID:34375372 | PMC:PMC8315598 | DOI:10.1016/j.ajpc.2021.100154

Am J Clin Nutr. 2021 Aug 10:nqab261. doi: 10.1093/ajcn/nqab261. Online ahead of print.

ABSTRACT

BACKGROUND: Both diet and familial factors have a major role in the development of cardiovascular disease (CVD). However, it remains unclear whether familial predisposition to CVD modifies the association between dietary factors and CVD.

OBJECTIVES: The aim was to assess whether the association between diet and CVD varies with familial predisposition to CVD.

METHODS: In this prospective cohort of the UK Biobank, 462,155 CVD-free participants were included in 2006-2010 and followed for CVD incidence until 2020. Food intake was measured using a short food-frequency questionnaire. Familial predisposition was measured by self-reported family history of CVD and by polygenic risk score (PRS) for CVD based on summary statistics of independent genome-wide association studies.

RESULTS: During a median follow-up of 11.2 y, 46,164 incident CVD cases were identified. A moderately higher risk of CVD was associated with more frequent processed-meat consumption, with an adjusted HR of 1.07 (95% CI: 1.03, 1.11; highest vs. lowest level). Conversely, intakes of fish, cheese, vegetables, and fruit were each associated with reduced CVD risk [HR (95% CI): 0.92 (0.89, 0.96), 0.90 (0.86, 0.94), 0.98 (0.95, 1.00), and 0.93 (0.89, 0.96), respectively]. Stratification analyses by family history of CVD and by PRS for CVD revealed an inverse association between CVD and intakes of fish and cheese, for both subgroups with and without a familial predisposition to CVD. Notably, while the association between processed-meat intake and CVD was restricted to individuals with a familial predisposition to CVD [e.g., HR: 1.11 (1.05, 1.16) and 1.03 (0.97, 1.10) for with and without a family history, respectively, P-interaction < 0.001], the risk reduction of CVD associated with vegetable and fruit intake was only noted among participants without a CVD familial predisposition [e.g., HR for fruit consumption: 1.00 (0.97, 1.03) and 0.91 (0.87, 0.95), respectively, P < 0.001].

CONCLUSIONS: Familial factors modify the association between diet and CVD, underscoring the need for personalized dietary guidelines for CVD prevention.

PMID:34375391 | DOI:10.1093/ajcn/nqab261

PLoS One. 2021 Aug 10;16(8):e0255446. doi: 10.1371/journal.pone.0255446. eCollection 2021.

ABSTRACT

BACKGROUND: Obesity is the cause of cardiovascular diseases and other diseases, leading to increased medical costs, and causing a great burden to individuals, families and society. The prevalence of obesity is increasing and has become a global health problem. There is growing evidence that gut microbiota plays an important role in obesity. In this article, we revealed the differences in the gut microbiota between 21 people with obesity and 21 control subjects, and predicted the functional potential changes by 16S rRNA sequencing of the fecal bacteria of the subjects.

METHODS: The raw sequencing data of 21 healthy Beijing volunteers was downloaded from Microbial Genome Database System. Microbial 16S rRNA genes of 21 adults with obesity were sequenced on an Illumina MiSeq instrument and analyzed by using bioinformatics and statistical methods.

RESULTS: The diversity of gut microbiota in people with obesity decreased significantly. There were significant differences in gut microbiota between the Obesity and Control group at different levels. At the phylum level, Firmicutes, Bacteroidetes, Actinobacteria and Fusobacteria are significantly different between the Obesity and Control group. In people with obesity, the ratio of Firmicutes/Bacteroidetes decreased significantly. At the genus level, there were significant differences among the 16 major genera, of which four genera Prevotella, Megamonas, Fusobacterium and Blautia increased significantly in people with obesity, while the remaining 12 genera, Faecalibacterium, Lachnospiracea_incertae_sedis, Gemmiger and Clostridium XlVa, etc. decreased significantly. At the species level, nine species including Bacteroides uniformis and Prevotella copri had significant differences. Compared with the control group, subjects with obesity were abnormalities in 57 pathways, mainly in Carbohydrate metabolism and Lipid metabolism.

CONCLUSIONS: Overall, our study revealed differences in the gut microbiota between people with obesity and control subjects, providing novel target for the treatment of individuals with obesity.

PMID:34375351 | DOI:10.1371/journal.pone.0255446

PLoS One. 2021 Aug 10;16(8):e0255852. doi: 10.1371/journal.pone.0255852. eCollection 2021.

ABSTRACT

INTRODUCTION: The number of elderly patients undergoing major surgery is rapidly increasing. They are particularly at risk of developing postoperative neurocognitive disorders (NCD). Earlier studies suggested that processed electroencephalographic (EEG) monitors may reduce the incidence of postoperative NCD. However, none of these studies controlled for intraoperative nociception levels or personalized blood pressure targets. Their results remain unclear if the reduction in the incidence of postoperative NCD relates to avoidance of any electroencephalographic pattern suggesting excessive anesthesia depth.

OBJECTIVE: The objective of this trial is to investigate-in patients ≥ 70 years old undergoing major non-cardiac surgery-the effect of EEG-guided anesthesia on postoperative NCD while controlling for intraoperative nociception, personalized blood pressure targets, and using detailed information provided by the EEG monitor (including burst suppression ratio, density spectral array, and raw EEG waveform).

MATERIAL AND METHODS: This prospective, randomized, controlled trial will be conducted in a single Canadian university hospital. Patients ≥ 70 years old undergoing elective major non-cardiac surgery will be included in the trial. The administration of sevoflurane will be adjusted to maintain a BIS index value between 40 and 60, to keep a Suppression Ratio (SR) at 0%, to keep a direct EEG display without any suppression time and a spectrogram with most of the EEG wave frequency within the alpha, theta, and delta frequencies in the EEG-guided group. In the control group, sevoflurane will be administered to achieve an age-adjusted minimum alveolar concentration of [0.8-1.2]. In both groups, a nociception monitor will guide intraoperative opioid administration, individual blood pressure targets will be used, and cerebral oximetry used to tailor intraoperative hemodynamic management. The primary endpoint will be the incidence of NCD at postoperative day 1, as evaluated by the Montreal Cognitive Assessment (MoCA). Secondary endpoints will include the incidence of postoperative NCD at different time points and the evaluation of cognitive trajectories up to 90 days after surgery among EEG-guided and control groups.

STUDY REGISTRATION: NCT04825847 on ClinicalTrials.gov.

PMID:34375362 | DOI:10.1371/journal.pone.0255852

J Clin Invest. 2021 Aug 10:152702. doi: 10.1172/JCI152702. Online ahead of print.

ABSTRACT

The efficacy of COVID-19 mRNA vaccines is high, but breakthrough infections still occur. We compared the SARS-CoV-2 genomes of 76 breakthrough cases after full vaccination with BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), or JNJ-78436735 (Janssen) to unvaccinated controls (February-April 2021) in metropolitan New York, including their phylogenetic relationship, distribution of variants, and full spike mutation profiles. Their median age was 48 years; seven required hospitalization and one died. Most breakthrough infections (57/76) occurred with B.1.1.7 (Alpha) or B.1.526 (Iota). Among the 7 hospitalized cases, 4 were infected with B.1.1.7, including 1 death. Both unmatched and matched statistical analyses considering age, sex, vaccine type, and study month as covariates supported the null hypothesis of equal variant distributions between vaccinated and unvaccinated in chi-squared and McNemar tests (p>0.1) highlighting a high vaccine efficacy against B.1.1.7 and B.1.526. There was no clear association among breakthroughs between type of vaccine received and variant. In the vaccinated group, spike mutations in the N-terminal domain and receptor-binding domain that have been associated with immune evasion were overrepresented. The evolving dynamic of SARS-CoV-2 variants requires broad genomic analyses of breakthrough infections to provide real-life information on immune escape mediated by circulating variants and their spike mutations.

PMID:34375308 | DOI:10.1172/JCI152702

PLoS One. 2021 Aug 10;16(8):e0245642. doi: 10.1371/journal.pone.0245642. eCollection 2021.

ABSTRACT

The study aimed to model and quantify the health burden induced by four non-communicable diseases (NCDs) in Egypt, the first to be conducted in the context of a less developing county. The study used the State-Space model and adopted two Bayesian methods: Particle Filter and Particle Independent Metropolis-Hastings to model and estimate the NCDs’ health burden trajectories. We drew on time-series data of the International Health Metric Evaluation, the Central Agency for Public Mobilization and Statistics (CAPMAS) Annual Bulletin of Health Services Statistics, the World Bank, and WHO data. Both Bayesian methods showed that the burden trajectories are on the rise. Most of the findings agreed with our assumptions and are in line with the literature. Previous year burden strongly predicts the burden of the current year. High prevalence of the risk factors, disease prevalence, and the disease’s severity level all increase illness burden. Years of life lost due to death has high loadings in most of the diseases. Contrary to the study assumption, results found a negative relationship between disease burden and health services utilization which can be attributed to the lack of full health insurance coverage and the pattern of health care seeking behavior in Egypt. Our study highlights that Particle Independent Metropolis-Hastings is sufficient in estimating the parameters of the study model, in the case of time-constant parameters. The study recommends using state Space models with Bayesian estimation approaches with time-series data in public health and epidemiology research.

PMID:34375334 | DOI:10.1371/journal.pone.0245642

PLoS One. 2021 Aug 10;16(8):e0254959. doi: 10.1371/journal.pone.0254959. eCollection 2021.

ABSTRACT

The Depressive and Anxious Avoidance in Prolonged Grief Questionnaire (DAAPGQ) was developed to measure depressive and anxious avoidance behaviors, which, according to cognitive-behavioral models, are supposed to play an important role in the development and maintenance of prolonged grief. The present study aimed to develop a German version of the DAAPGQ and evaluate its psychometric properties and validity within a representative sample of the German general population (N = 2531). The German-language DAAPGQ was developed using a forward-backward translation procedure. Then, a subsample of individuals who reported having lost a significant other (N = 1371) of a representative sample was assessed with the German DAAPGQ, along with information on sociodemographic characteristics, prolonged grief symptom severity (PG-13), general anxiety (GAD-2) and depression (PHQ-2). The factor structure of the DAAPGQ was evaluated using confirmatory factor analyses, reliability by calculating internal consistency on subscale level and convergent validity by correlations between DAAPQG subscale sores with PG-13, GAD-2 and PHQ-2 sum scores. As expected, a two-factor model with correlated latent variables showed good fit to the data, replicating findings from the original version. Internal consistency was high for both subscales (Cronbach’s α .86 and .95, respectively). Convergent validity was established by theoretically expected and statistically significant positive correlations of DAAPGQ subscales with symptom severity of prolonged grief, depression, and anxiety and negative correlations with time since loss. Furthermore, the addition of depressive and anxious avoidance significantly improved the prediction of prolonged grief symptom severity over sociodemographic and loss-related information. In sum, our results suggest that the German-language DAAPGQ is a reliable and valid measure of depressive and anxious avoidance and a useful tool to improve our knowledge on the role of avoidance in prolonged grief. We also provide descriptive data to improve the applicability of the DAAPGQ for individual diagnostics.

PMID:34375341 | DOI:10.1371/journal.pone.0254959

IEEE Trans Pattern Anal Mach Intell. 2021 Aug 10;PP. doi: 10.1109/TPAMI.2021.3103114. Online ahead of print.

ABSTRACT

Enhancing the visibility in extreme low-light environments is a challenging task. Under nearly lightless condition, existing image denoising methods could easily break down due to significantly low SNR. In this paper, we systematically study the noise statistics in the imaging pipeline of CMOS photosensors, and formulate a comprehensive noise model that can accurately characterize the real noise structures. Our novel model considers the noise sources caused by digital camera electronics which are largely overlooked by existing methods yet have significant influence on raw measurement in the dark. It provides a way to decouple the intricate noise structure into different statistical distributions with physical interpretations. Moreover, our noise model can be used to synthesize realistic training data for learning-based low-light denoising algorithms. In this regard, although promising results have been shown recently with deep convolutional neural networks, the success heavily depends on abundant noisy-clean image pairs for training, which are tremendously difficult to obtain in practice. Extensive experiments on multiple low-light denoising datasets — including a newly collected one in this work covering various devices — show that a deep neural network trained with our proposed noise formation model can reach surprisingly-high accuracy. The results are on par with or sometimes even outperform training with paired real data.

PMID:34375279 | DOI:10.1109/TPAMI.2021.3103114

IEEE Trans Neural Netw Learn Syst. 2021 Aug 10;PP. doi: 10.1109/TNNLS.2021.3102323. Online ahead of print.

ABSTRACT

This article introduces a neural approximation-based method for solving continuous optimization problems with probabilistic constraints. After reformulating the probabilistic constraints as the quantile function, a sample-based neural network model is used to approximate the quantile function. The statistical guarantees of the neural approximation are discussed by showing the convergence and feasibility analysis. Then, by introducing the neural approximation, a simulated annealing-based algorithm is revised to solve the probabilistic constrained programs. An interval predictor model (IPM) of wind power is investigated to validate the proposed method.

PMID:34375291 | DOI:10.1109/TNNLS.2021.3102323