Category: Statistics

Odontology. 2023 Jan 12. doi: 10.1007/s10266-023-00784-2. Online ahead of print.

ABSTRACT

The main objective of the present study was to evaluate the effect of the morphology of titanium dioxide nanofillers on the flexural strength and shear bond strength of the dental composite. Spherical and rhombic-shaped nano titanium dioxide fillers were synthesized via solvothermal method and were characterized. Subsequently, these fillers were incorporated into a flowable composite (Filtek^™ Z350 XT Flowable Restorative) at 0.5 wt.% and 1.5 wt.% and the prepared specimens were stored in water for 24 h. The specimens were then evaluated for flexural strength using a universal testing machine. Similarly, the shear bond strength of modified composites to the tooth was evaluated and bond failures were analyzed using stereomicroscope magnification. Incorporation of nanofillers significantly enhanced the flexural strength of flowable composite (p = 0.009) with a significant increase at 0.5wt.% of spherical (p = 0.015) and rhomboidal-shaped fillers (p = 0.010). However, no statistically significant difference in flexural strength was observed among the different shapes of nanofillers. The results of our study did not show a significant effect on the shear bond strength of the composites. Thus the reinforcing ability of titanium dioxide nanofillers on dental composite was confirmed in this study, although the effect of using nanofillers with different morphology was not significant.

PMID:36633793 | DOI:10.1007/s10266-023-00784-2

Biol Trace Elem Res. 2023 Jan 12. doi: 10.1007/s12011-023-03554-x. Online ahead of print.

ABSTRACT

The association between circulating copper and the risk of liver cancer has been investigated by previous studies, while the findings were inconsistent. Thus, we aimed to evaluate the association between circulating copper and liver cancer by using meta-analysis and Mendelian randomization (MR). For meta-analysis, PubMed and Web of Science were searched to identify eligible studies published before April 4, 2022. Standardized mean difference (SMD) with 95% confidence interval (CI) in circulating copper level between liver cancer patients and controls were pooled. Furthermore, we selected genetic instruments for circulating copper from a genome-wide association study (GWAS) to conduct MR analysis. The summary statistics related to liver cancer were obtained from two large independent cohorts, UKBB and FinnGen, respectively. MR analysis was performed mainly by inverse-variance weighted (IVW) approach, followed by maximum-likelihood method as sensitivity analysis. In meta-analysis of eight studies, circulating copper was found to be higher in liver cancer patients (SMD: 1.65; 95% CI: 0.65 to 2.65) with high heterogeneity (I² = 96.40%, P = 0.001). However, inconsistent findings were observed among subgroups with high evidence. In MR analysis, genetically predicted circulating copper was not significantly associated with the risk of liver cancer by IVW in UKBB (OR: 1.38; 95% CI: 0.72 to 2.65) and FinnGen (OR: 1.10; 95% CI: 0.69 to 1.73) separately, and the pooled results produced similar results (OR: 1.18, 95% CI: 0.81 to 1.72). Moreover, non-significant finding was confirmed by using maximum-likelihood method. There is no sufficient evidence to demonstrate that high levels of circulating copper increase the risks of liver cancer.

PMID:36633787 | DOI:10.1007/s12011-023-03554-x

Prev Sci. 2023 Jan 12. doi: 10.1007/s11121-022-01485-y. Online ahead of print.

ABSTRACT

A variety of health and social problems are routinely measured in the form of categorical outcome data (such as presence/absence of a problem behavior or stages of disease progression). Therefore, proper quantitative analysis of categorical data lies at the heart of the empirical work conducted in prevention science. Categorical data analysis constitutes a broad dynamic field of methods research and data analysts in prevention science can benefit from incorporating recent advances and developments in the statistical evaluation of categorical outcomes in their methodological repertoire. The present Special Issue, Advanced Categorical Data Analysis in Prevention Science, highlights recent methods developments and illustrates their application in the context of prevention science. Contributions of the Special Issue cover a wide variety of areas ranging from statistical models for binary as well as multi-categorical data, advances in the statistical evaluation of moderation and mediation effects for categorical data, developments in model evaluation and measurement, as well as methods that integrate variable- and person-oriented categorical data analysis. The articles of this Special issue make methodological advances in these areas accessible to the audience of prevention scientists to maintain rigorous statistical practice and decision making. The current paper provides background and rationale for this Special Issue, an overview of the articles, and a brief discussion of some potential future directions for prevention research involving categorical data analysis.

PMID:36633766 | DOI:10.1007/s11121-022-01485-y

Environ Sci Pollut Res Int. 2023 Jan 12. doi: 10.1007/s11356-022-25051-9. Online ahead of print.

ABSTRACT

Phthalate metabolites have been detected from urine in most of the US population and have become a public health problem. However, the association between phthalate metabolites and hyperuricemia has been scarcely studied so far. We aimed to evaluate if phthalate metabolites were associated with hyperuricemia in US adults. A total of 8816 participants of the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 were included in our study. We used multivariable logistic regression models and restricted cubic spline (RCS) models to explore the association between urinary phthalate metabolites and hyperuricemia. Then, stratified analyses were conducted by sex and age. The prevalence of hyperuricemia in the study sample was 20.35%. Compared to the lowest quantile, the odds ratios (ORs) and 95% confidence intervals (CIs) for hyperuricemia were all statistically significant in following phthalate metabolites: 1.34 (1.13-1.58) for the second quartile in Mono-isobutyl phthalate (MiBP), 1.21 (1.01-1.46) for the highest quartile in Mono-(carboxyoctyl) phthalate (MCOP), 0.66 (0.56-0.76) for the second quartile in Mono-(2-ethyl)-hexyl phthalate (MEHP), 1.22 (1.05-1.43) for quartile 2 in Benzyl butyl phthalate (ΣBBP), and 1.43 (1.22-1.66) for the third quartile in high molecular-weight phthalate (ΣHigh MWP), respectively. Our results indicate that several urinary phthalate metabolites are positively associated with the odds of hyperuricemia.

PMID:36633744 | DOI:10.1007/s11356-022-25051-9

Environ Sci Pollut Res Int. 2023 Jan 12. doi: 10.1007/s11356-022-24824-6. Online ahead of print.

ABSTRACT

Epidemiological studies using conventional statistical methods have reported an association between individual metal exposure and hyperuricemia (HUA). There is also evidence that diet may influence HUA development, although the available data are inconsistent. We therefore used an elastic net regression (ENR) model to screen the usefulness of various environmental and dietary factors as predictors of HUA in a large sample cohort. This study included 6217 subjects drawn from the Shenzhen Aging Related Disorder Cohort. We obtained information on the subjects’ dietary habits via face-to-face interviews and used inductively coupled plasma mass spectrometry (ICP-MS) to measure the urinary concentrations of 24 metals to which elderly persons in large urban areas may be exposed. An elastic net regression (ENR) model was generated to screen the utility of the metals and dietary factors as predictors of HUA, and we demonstrated the superiority of the ENR model by comparing it to a traditional logistic regression model. The identified predictors were used to create a clinically usable nomogram for identifying patients at risk of developing HUA. The area under curve (AUC) value of the final model was 0.692 for the training set and 0.706 for the test set. Important predictors of HUA were Zn, As, V, and Fe as well as consumption of wheat, beans, and rice; the corresponding estimated odds ratios and 95% confidence intervals were 1.091 (0.932,1.251), 1.190 (1.093,1.286), 0.924 (0.793,1.055), 0.704 (0.626,0.781), 0.998 (0.996,1.001), 0.993 (0.989,0.998), and 1.001 (0.998,1.002), respectively. In contrast to previous studies, we found that both urinary metal concentrations and dietary habits are important for predicting HUA risk. Exposure to specific metals and consumption of specific foods were identified as important predictors of HUA, indicating that the incidence of this disease could be reduced by reducing exposure to these metals and promoting improved dietary habits.

PMID:36633743 | DOI:10.1007/s11356-022-24824-6

Environ Sci Pollut Res Int. 2023 Jan 12. doi: 10.1007/s11356-023-25169-4. Online ahead of print.

ABSTRACT

Industrial structure low-carbon restructuring is an essential channel to accelerate China’s economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals.

PMID:36633739 | DOI:10.1007/s11356-023-25169-4

Environ Monit Assess. 2023 Jan 12;195(2):291. doi: 10.1007/s10661-022-10844-9.

ABSTRACT

In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used to advance the estimation because it allowed for statistical analysis and comparison of climatological elements such time series, means, extremes, and trends. During these 69 years, a more erratic DTR trend was seen in the research area. This study investigates the suitability of three deep neural networks for one-step-ahead DTR time series (DTRTS) forecasting, including recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), and auto-regressive integrated moving average exogenous (ARIMAX). To evaluate the effectiveness of models in the testing set, six statistical error indicators, including root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), percent bias (PBIAS), modified index of agreement (md), and relative index of agreement (rd), were chosen. The Wilson score approach was used to do a quantitative uncertainty analysis on the prediction error to forecast the outcome DTR. The findings show that the LSTM outperforms the other models in terms of its capacity to forget, remember, and update information. It is more accurate on datasets with longer sequences and displays noticeably more volatility throughout its gradient descent. The results of a sensitivity analysis on the LSTM model, which used RMSE values as an output and took into account different look-back periods, showed that the amount of history used to fit a time series forecast model had a direct impact on the model’s performance. As a result, this model can be applied as a fresh, trustworthy deep learning method for DTRTS forecasting.

PMID:36633692 | DOI:10.1007/s10661-022-10844-9

Eur Arch Psychiatry Clin Neurosci. 2023 Jan 12. doi: 10.1007/s00406-022-01507-4. Online ahead of print.

ABSTRACT

Recent factor analytic evidence supports both two-factor (motivation and pleasure, MAP; diminished expression, EXP) and five-factor (anhedonia, asociality, avolition, blunted affect, alogia) conceptualizations of negative symptoms. However, it is unclear whether these two conceptualizations of the latent structure of negative symptoms have differential associations with external correlates. The current study evaluated external correlates of the two- and five-factor structures by examining associations with variables known to have critical relations with negative symptoms: trait affect, defeatist performance beliefs, neurocognition, and community-based psychosocial functioning. Participants included a total of 245 outpatients diagnosed with schizophrenia who were rated on the Brief Negative Symptom Scale and completed a battery of additional measures during periods of clinical stability. These additional measures included the Positive and Negative Affect Schedule, Defeatist Performance Beliefs scale, MATRICS Consensus Cognitive Battery, and Level of Function Scale. Pearson correlations indicated differential patterns of associations between the BNSS scores and the external correlates. Support for the two-factor model was indicated by a stronger association of MAP with positive affect and psychosocial functioning, compared to EXP with neurocognition. Significance tests examining a differential magnitude of associations showed that the two-dimension negative symptom structure masked unique correlational relationships among the five negative symptom domains with neurocognition and social/vocational community functioning and captured unique patterns of correlation with trait affect. Support for the five-factor model was shown by a stronger association between Blunted Affect with Attention/Vigilance, and stronger associations between Avolition, Anhedonia, and Asociality with psychosocial functioning. Results offer support for both the two-dimension and five-domain model of negative symptoms as well as a hierarchical two-dimensions-five-domains model of negative symptoms. Findings may have implications for diagnostic criteria and descriptions of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5), as well as possible treatment targets of negative symptoms.

PMID:36633673 | DOI:10.1007/s00406-022-01507-4

Graefes Arch Clin Exp Ophthalmol. 2023 Jan 12. doi: 10.1007/s00417-022-05952-8. Online ahead of print.

ABSTRACT

PURPOSE: Bevacizumab, ranibizumab, and aflibercept are commonly used to treat neovascular age-related macular degeneration (nAMD). The results of various interventional, mostly randomized head-to-head studies, indicate statistical non-inferiority of these three drugs. The results of these studies are often interpreted as the three drugs being freely interchangeable, resulting in some health systems to pressure ophthalmologists to preferentially use the less expensive bevacizumab. This study analyzes switching from aflibercept or ranibizumab to bevacizumab and back under real-world conditions in order to investigate the assumption of interchangeability of the drugs.

METHODS: Treatment data of IVT patients with diagnosed nAMD were extracted from the clinical Berlin Macular Registry database. Patients who underwent a drug switch from aflibercept or ranibizumab to bevacizumab were subject of this study. Statistical comparisons were pre-planned for best corrected visual acuity, central retinal thickness, macular volume, and length of injection interval. Additional endpoints were analyzed descriptively.

RESULTS: Mean visual acuity decreased from 0.57 ± 0.05 under aflibercept/ranibizumab to 0.68 ± 0.06 logMAR after the switch (P = 0.001; N = 63). CRT increased from 308 ± 11 µm to 336 ± 16 µm (P = 0.011; N = 63). About half of the subjects were switched back: visual acuity increased from 0.69 ± 0.08 logMAR to 0.58 ± 0.09 logMAR (N = 26). CRT decreased from 396 ± 28 to 337 ± 20 µm (N = 28).

CONCLUSION: The data provides real-world evidence that there is loss of visual acuity and an increase in retinal edema after switching to bevacizumab. Thus, the assumption of free interchangeability cannot be confirmed in this cohort.

PMID:36633668 | DOI:10.1007/s00417-022-05952-8

Eur J Pediatr. 2023 Jan 12. doi: 10.1007/s00431-022-04761-9. Online ahead of print.

ABSTRACT

Early assessment of refractory Mycoplasma pneumoniae pneumonia (RMPP) with plastic bronchitis (PB) allows timely removal of casts using fiberoptic bronchoscopic manipulation, which relieves airway obstruction and limit sequelae development. This study aimed to analyze clinical data for risk factors and develop a nomogram for early predictive evaluation of RMPP with PB. The clinical data of 1-14 year-old patients with RMPP were retrospectively analyzed. Patients were classified into a PB or non-PB group. The general characteristics, clinical symptoms, laboratory test results, imaging findings, and microscopic changes of the two groups were compared. A statistical analysis of the risk factors for developing PB was performed, and a nomogram model of risk factors was constructed. Of 120 patients with RMPP included, 68 and 52 were in the non-PB and PB groups, respectively. Using multivariate logistic regression analysis, fever before bronchoscopy, extrapulmonary complications, pleural effusion, cough duration, and lactate dehydrogenase (LDH) levels were identified as risk factors. A nomogram was constructed based on the results of the multivariate analysis. The area under the receiver operating characteristic curve value of the nomogram was 0.944 (95% confidence interval: 0.779-0.962). The Hosmer-Lemeshow test displayed good calibration of the nomogram (p = 0.376, R2 = 0.723).

CONCLUSION: The nomogram model constructed in this study based on five risk factors (persistent fever before bronchoscopy, extrapulmonary complications, pleural effusion, cough duration, and LDH levels) prior to bronchoscopy can be used for the early identification of RMPP-induced PB.

WHAT IS KNOWN: • Refractory Mycoplasma pneumoniae pneumonia (RMPP) in children has been increasingly reported and recognized, which often leads to serious complications. • Plastic bronchitis (PB) is considered to be one of the causes of RMPP, and bronchoscopic treatment should be improved as soon as possible to remove plastic sputum thrombus in bronchus.

WHAT IS NEW: • This study determined the risk factors for RMPP-induced PB. • The nomogram model constructed in this study prior to bronchoscopy can be used for the early identification of RMPP-induced PB, which facilitate the early bronchoscopic removal of casts, thereby promoting recovery and reducing cases with poor RMPP prognosis.

PMID:36633659 | DOI:10.1007/s00431-022-04761-9