Tag: statistics

Diabetes Res Clin Pract. 2023 Dec 23:111080. doi: 10.1016/j.diabres.2023.111080. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed at assessing the changes of left atrial (LA) volume and strain function in metabolic syndrome (MS) patients using four-dimensional automatic left atrial quantification (4D-LAQ) and exploring independent correlative factors for LA function.

METHODS: A total of 110 MS patients and 70 normal controls were selected and assigned into the MS group and the control group, respectively. Echocardiogram parameters were routinely examined and the thickness of epicardial adipose tissue (EAT) were measured with a parasternal long axis of left ventricle(LV). The LA volume and strain parameters were determined using 4D-LAQ. The independent correlation factors for LA strain parameters in MS patients were investigated through linear regression analysis.

RESULTS: Compared with the control group, LA volume parameters were increased in the MS group, LA strain parameters and LA emptying fraction (LAEF) were decreased (all P < 0.05). EAT thickness is associated with LA reservoir longitudinal strain (LASr), conduit longitudinal strain (LAScd), reservoir circumferential strain (LASr-c), and conduit circumferential strain (LAScd-c) (all P < 0.05). LA contraction longitudinal (LASct) and circumferential strain (LASct-c) were not statistically significant. Regression analysis results show that systolic blood pressure (SBP) and triglyceride (TG) are independent correlative factors. Intra-observer and inter-observer repeatability test showed that the LA parameters examined by 4D-LAQ had good agreement.

CONCLUSIONS: 4D-LAQ is capable of effectively assessing the LA function in MS patients and providing a useful reference for clinical diagnosis. SBP and TG serve as the independent correlative factors for LA function.

PMID:38145827 | DOI:10.1016/j.diabres.2023.111080

Adv Nutr. 2023 Dec 23:100165. doi: 10.1016/j.advnut.2023.100165. Online ahead of print.

ABSTRACT

Although a posteriori dietary patterns (DPs) naturally reflect actual dietary behavior in a population, their specificity limits generalizability. Among other issues, the absence of a standardized approach to analysis have further hindered discovery of genuinely reproducible DPs across studies from the same/similar populations. A systematic review on a posteriori DPs from principal component analysis or exploratory factor analysis (EFA) across study populations from Italy provides the basis to explore assessment and drivers of DP reproducibility in a case study of epidemiological interest. First to our knowledge, we carried out a qualitative (i.e., similarity plots built on text descriptions) and quantitative (i.e., congruence coefficients, CCs) assessment of DP reproducibility. The 52 selected papers were published in 2001-2022 and represented dietary habits in 1965-2022 from 70% of the Italian regions; children/adolescents, pregnancy/breastfeeding women, and elderly were considered in 15 papers. The included studies mainly derived EFA-based DPs on food groups from food-frequency questionnaires and were of “good quality” according to standard scales. Based on text descriptions, the 186 identified DPs were collapsed into 113 (69 food-based and 44 nutrient-based) apparently different DPs (39.3% reduction), later summarized along with the 3 Mixed-Salad/Vegetable-based Patterns, Pasta-and-Meat-oriented/Starchy Patterns, and Dairy Products and Sweets/Animal-based Patterns groups, by matching similar food-based and nutrient-based groups of collapsed DPs. Based on CCs (215 CCs, 68 DPs, 18 papers using the same input lists), all pairs of DPs showing the same/similar names were at least “fairly similar” and ∼81% were “equivalent”. The 30 “equivalent” DPs ended up into 6 genuinely different DPs (80% reduction) that targeted fruit and (raw) vegetables, pasta and meat combined, and cheese and deli meats. Such reduction reflects the same study design, list of input variables, and DP identification method followed across papers from the same groups. This review was registered at PROSPERO as CRD42022341037. STATEMENT OF SIGNIFICANCE (2 SENTENCES, TRUE NOVELTY): This is the first systematic review collecting evidence on Italian dietary patterns derived from principal component or exploratory factor analysis. The systematic review provides the basis for a qualitative and quantitative assessment of reproducibility of Italian dietary patterns, as based on text descriptions and congruence coefficients, respectively. We found that Italian dietary patterns based on fruit and (raw) vegetables, pasta and meat combined, and cheese and deli meats are reproducible across studies, although more rigorous statistical approaches may allow a better identification of reproducible dietary patterns and related causes. The established evidence base may inform dietary pattern identification in the Italian population and more generally future research on dietary pattern reproducibility across studies within the same country.

PMID:38145798 | DOI:10.1016/j.advnut.2023.100165

Int J Pharm. 2023 Dec 23:123746. doi: 10.1016/j.ijpharm.2023.123746. Online ahead of print.

ABSTRACT

The intricate structure of the eye poses difficulties in drug targeting, which can be surmounted with the help of nanoformulation strategies. With this view, brinzolamide nanosponges (BNS) were prepared using the emulsion solvent evaporation technique and optimized via Box-Behnken statistical design. The optimized BNS were further incorporated into a poloxamer 407 in situ gel (BNS-ISG) and evaluated. The optimized BNS showed spherical morphology, entrapment efficiency of 83.12±1.2% with particle size of 114±2.32 nm and PDI of 0.11±0.01. The optimized BNS-ISG exhibited a pseudoplastic behavior and depicted a gelling temperature and gelation time of 35±0.5°C and 10±2 s respectively. In-vitro release and ex- vivo permeation studies of BNS-ISG demonstrated a sustained release pattern as compared to Brinzox®. Additionally, the HET-CAM and in vitro cytotoxicity studies (using SIRC cell line) ensured that the formulation was non-irritant and nontoxic for ophthalmic delivery. The in vivo pharmacodynamic study using rabbit model depicted that BNS-ISG treatment significantly lowers the intra ocular pressure for prolonged period of time when compared with Brinzox®. In conclusion, the BNS-ISG is an efficient and scalable drug delivery system with significant potential as the targeted therapy of posterior segment eye diseases.

PMID:38145779 | DOI:10.1016/j.ijpharm.2023.123746

Photodiagnosis Photodyn Ther. 2023 Dec 23:103943. doi: 10.1016/j.pdpdt.2023.103943. Online ahead of print.

ABSTRACT

AIMS: Bleached enamel reversal using antioxidants sodium ascorbate (SA), Green tea extract (GTE), Grape seed extract (GSE), Curcumin photosensitizer (CP) and Er: YAG laser on the adhesive strength and marginal leakage of composite material bonded to the bleached enamel surface.

MATERIALS AND METHODS: Enamel surface of hundred and twenty sound human first premolar teeth was cleansed using pumice and bleached with 35% hydrogen peroxide. The samples were randomly divided into 5 groups based on the antioxidants used. n=20 Group 1 (Control): No antioxidant agent, Group 2: 10% SA solution, Group 3: 6.5% GSE, Group 4: 5% GTE, Group 5: Er: YAG laser and Group 6: CP. Following reversal, the composite was built and cured for 40 seconds. All the specimens were stored in distilled water at room temperature for 1 day. Microleakage, SBS, and failure mode were analyzed. Kolmogorov-Smirnov test, one-way analysis of variance, and Tukey’s multiple post hoc test were used to analyze the data statistically.

RESULTS: Group 2 (SA) (20.11 ±5.79 nm) exhibited minimum value of microleakage and highest SBS (10.22 ± 1.62 MPa). Whereas, Group 1 (No antioxidant agent) displayed maximum scores of marginal leakage (28.11±8.89 nm) and lowest SBS (7.02 ± 1.22 MPa).

CONCLUSION: CP, GTE and GSE can be used as a potential alternative to the commonly used SA solution to reverse the negative impact of bleaching on the enamel surface. The use of reversal agents CP, GTE and GSE improves bond values with a decrease in microleakage scores However, future studies are still warranted to conclude the outcomes of the existing study.

PMID:38145770 | DOI:10.1016/j.pdpdt.2023.103943

Bioresour Technol. 2023 Dec 23:130252. doi: 10.1016/j.biortech.2023.130252. Online ahead of print.

ABSTRACT

The escalating demand for long-chain polyunsaturated fatty acids (PUFAs) due to their vital health effects has deepened the exploration of sustainable sources. Thraustochytrium sp. stands out as a promising platform for omega-3 and 6 PUFA production. This research strategically optimizes key parameters: temperature, salinity, pH, and G:Y:P ratio and the optimized conditions for maximum biomass, total lipid, and DHA enhancement were 28 °C, 50 %, 6, and 10:1:2 respectively. Process optimization enhanced 32.30 and 31.92 % biomass (9.88 g/L) and lipid (6.57 g/L) yield. Notably, DHA concentration experienced a substantial rise of 69.91 % (1.63 g/L), accompanied by notable increases in EPA and DPA by 82.69 % and 31.47 %, respectively. MANOVA analysis underscored the statistical significance of the optimization process (p < 0.01), with all environmental factors significantly influencing biomass and lipid data (p < 0.05), particularly impacting DHA production. Thraustochytrium sp. can be a potential source of commercial DHA production with the fine-tuning of these key process parameters.

PMID:38145766 | DOI:10.1016/j.biortech.2023.130252

Environ Res. 2023 Dec 23:117995. doi: 10.1016/j.envres.2023.117995. Online ahead of print.

ABSTRACT

BACKGROUND: The increasing problem of bacterial resistance, particularly with quinolone-resistant Escherichia coli (QnR eco) poses a serious global health issue.

METHODS: We collected data on QnR eco resistance rates and detection frequencies from 2014 to 2021 via the China Antimicrobial Resistance Surveillance System, complemented by meteorological and socioeconomic data from the China Statistical Yearbook and the China Meteorological Data Service Centre (CMDC). Comprehensive nonparametric testing and multivariate regression models were used in the analysis.

RESULT: Our analysis revealed significant regional differences in QnR eco resistance and detection rates across China. Along the Hu Huanyong Line, resistance rates varied markedly: 49.35 in the northwest, 54.40 on the line, and 52.30 in the southeast (P = 0.001). Detection rates also showed significant geographical variation, with notable differences between regions (P < 0.001). Climate types influenced these rates, with significant variability observed across different climates (P < 0.001). Our predictive model for resistance rates, integrating climate and healthcare factors, explained 64.1% of the variance (adjusted R-squared = 0.641). For detection rates, the model accounted for 19.2% of the variance, highlighting the impact of environmental and healthcare influences.

CONCLUSION: The study found higher resistance rates in warmer, monsoon climates and areas with more public health facilities, but lower rates in cooler, mountainous, or continental climates with more rainfall. This highlights the strong impact of climate on antibiotic resistance. Meanwhile, the predictive model effectively forecasts these resistance rates using China’s diverse climate data. This is crucial for public health strategies and helps policymakers and healthcare practitioners tailor their approaches to antibiotic resistance based on local environmental conditions. These insights emphasize the importance of considering regional climates in managing antibiotic resistance.

PMID:38145731 | DOI:10.1016/j.envres.2023.117995

Acta Psychol (Amst). 2023 Dec 23;242:104122. doi: 10.1016/j.actpsy.2023.104122. Online ahead of print.

ABSTRACT

BACKGROUND: Culturally appropriate mental health care is essential in remote Australia. However, while associated with the development of an effective therapeutic alliance, current literature insufficiently reports the retention and psychotherapy outcomes of Indigenous adults. We aimed to describe the characteristics and retention of clients attending the Far North Mental Health and Wellbeing Service (FNS).

METHODS: We conducted a retrospective cross-sectional study on clients who received one or more psychotherapy consultations between 1st July 2019 and 31st December 2020. Population, entrance, and treatment characteristics were described, with retention compared between the major cultural groups. Entrance characteristics comprised referral pathway and reason for presentation and were investigated as alternative predictors of client retention.

FINDINGS: There were 186 non-Indigenous (68.3 % female) and 174 Indigenous (62.6 % female) clients, with a median number of 3.0 consultations (IQR 2.0-5.3). Indigenous status did not significantly predict retention. Referral pathway significantly predicted the number of consultations (Wald X²(6) = 17.67, p = .0071) and immediate discontinuation (Wald X²(6) = 12.94, p = .044), with self-referred clients having the highest retention. Initial presentation reason significantly predicted the number of consultations (Wald X²(5) = 13.83, p = .017), with clients with potential health hazards related to socioeconomic and psychosocial circumstances having the lowest retention. Significantly more Indigenous clients presented for this reason (20.1 % vs 4.3 %).

INTERPRETATION: Comparable retention of Indigenous clients suggests cultural appropriateness of the psychotherapy being delivered by the FNS. Services might use the described therapeutic approach as a guide for culturally appropriate care.

PMID:38145592 | DOI:10.1016/j.actpsy.2023.104122

Accid Anal Prev. 2023 Dec 24;196:107433. doi: 10.1016/j.aap.2023.107433. Online ahead of print.

ABSTRACT

Driving behavior is considered as the primary crash influencing factor, whereas studies claimed that over 90% crashes were attributed by behavior features. Therefore, unveil pre-crash driving behavior features is of great importance for crash prevention. Previous studies have established the correlations between features such as vehicle speed, speed variability, and the probability of crash occurrences, but these analyses have concluded inconsistent results. This is due to the varying operating characteristics among roadway facilities, where given the same driving behavior statistical features, the corresponding traffic states are not identical. In this study, a behavioral entropy index was proposed to address the abovementioned issue. First, through comparing the individual driving behavior with the group distribution, behavioral entropy index was calculated to quantify the abnormality of driving behavior. Then, crash classification models were established by comparing the behavioral entropy prior to crash events and normal driving conditions. The empirical analyses have been conducted based on 1,634,770 naturalistic driving trajectories and 1027 crash events. And models have been carried out for urban roadway sections, urban intersections, and highway sections separately. The results showed that utilizing the behavior entropy instead of the statistical features could enhance the crash classification accuracy by 11.3%. And common pre-crash features of increased behavioral entropy were identified. Moreover, the speed coefficient of variation (QCV) entropy was concluded as the most influencing factor, which can be used for real-time driving risk monitoring and enables individual-level hazard mitigation.

PMID:38145588 | DOI:10.1016/j.aap.2023.107433

IEEE Trans Med Imaging. 2023 Dec 25;PP. doi: 10.1109/TMI.2023.3347258. Online ahead of print.

ABSTRACT

Low-dose computed tomography (LDCT) helps to reduce radiation risks in CT scanning while maintaining image quality, which involves a consistent pursuit of lower incident rays and higher reconstruction performance. Although deep learning approaches have achieved encouraging success in LDCT reconstruction, most of them treat the task as a general inverse problem in either the image domain or the dual (sinogram and image) domains. Such frameworks have not considered the original noise generation of the projection data and suffer from limited performance improvement for the LDCT task. In this paper, we propose a novel reconstruction model based on noise-generating and imaging mechanism in full-domain, which fully considers the statistical properties of intrinsic noises in LDCT and prior information in sinogram and image domains. To solve the model, we propose an optimization algorithm based on the proximal gradient technique. Specifically, we derive the approximate solutions of the integer programming problem on the projection data theoretically. Instead of hand-crafting the sinogram and image regularizers, we propose to unroll the optimization algorithm to be a deep network. The network implicitly learns the proximal operators of sinogram and image regularizers with two deep neural networks, providing a more interpretable and effective reconstruction procedure. Numerical results demonstrate our proposed method improvements of > 2.9 dB in peak signal to noise ratio, > 1.4% promotion in structural similarity metric, and > 9 HU decrements in root mean square error over current state-of-the-art LDCT methods.

PMID:38145543 | DOI:10.1109/TMI.2023.3347258

IEEE Trans Vis Comput Graph. 2023 Dec 25;PP. doi: 10.1109/TVCG.2023.3346641. Online ahead of print.

ABSTRACT

Currently, growing data sources and long-running algorithms impede user attention and interaction with visual analytics applications. Progressive visualization (PV) and visual analytics (PVA) alleviate this problem by allowing immediate feedback and interaction with large datasets and complex computations, avoiding waiting for complete results by using partial results improving with time. Yet, creating a progressive visualization requires more effort than a regular visualization but also opens up new possibilities, such as steering the computations towards more relevant parts of the data, thus saving computational resources. However, there is currently no comprehensive overview of the design space for progressive visualization systems. We surveyed the related work of PV and derived a new taxonomy for progressive visualizations by systematically categorizing all PV publications that included visualizations with progressive features. Progressive visualizations can be categorized by well-known visualization taxonomies, but we also found that progressive visualizations can be distinguished by the way they manage their data processing, data domain, and visual update. Furthermore, we identified key properties such as uncertainty, steering, visual stability, and real-time processing that are significantly different with progressive applications. We also collected evaluation methodologies reported by the publications and conclude with statistical findings, research gaps, and open challenges. A continuously updated visual browser of the survey data is available at visualsurvey.net/pva.

PMID:38145517 | DOI:10.1109/TVCG.2023.3346641