Category: Statistics

Proc Natl Acad Sci U S A. 2022 May 24;119(21):e2117308119. doi: 10.1073/pnas.2117308119. Epub 2022 May 19.

NO ABSTRACT

PMID:35588449 | DOI:10.1073/pnas.2117308119

PLoS One. 2022 May 19;17(5):e0268686. doi: 10.1371/journal.pone.0268686. eCollection 2022.

ABSTRACT

BACKGROUND AND AIMS: The number of hypertensive population rises year by year recently, and their age becomes more youthful. For a long time, hypertension has long been regarded as a multi-factorial disease. In addition to smoking, genetics, diet and other factors, helicobacter pylori (H. pylori) had been regarded as a potential risk factor for hypertension in recent years. However, most studies had certain limitations and their results were inconsistent. Thus, it is necessary for us to assess the impact of H. pylori on hypertension through meta-analysis.

METHODS: We searched all published relevant literature through multiple databases by July 23, 2021. Pooled results were calculated under the random effect model. Heterogeneity was evaluated by the Q statistic and the I2 statistic. The risk of bias was evaluated via ROBINS-I tool. Publication bias was evaluated by the Egger test and Begg funnel plot.

RESULTS: 6 eligible studies involving 11317 hypertensive patients and 12765 controls were selected from 20767 retrieval records. Our research confirmed that H. pylori significantly increased the probability of suffering from hypertension in the random effect model (OR:1.34, 95% CI:1.10-1.63, P = 0.002, I2 = 74%). The same results were also found in both Asian population and developing country (OR:1.28, 95%CI:1.05-1.55, P = 0.003, I2 = 78.5%).

CONCLUSIONS: Our results confirmed that H. pylori was a vital risk factor for hypertension. H. pylori-infected people were 13.4% higher risk for hypertension than uninfected individuals. In addition, it will be a new method to prevent and treat hypertension by eradicating H. pylori.

TRIAL REGISTRATION: The registration number for systematic review in PROSPERO CRD42021279677.

PMID:35588432 | DOI:10.1371/journal.pone.0268686

IEEE J Biomed Health Inform. 2022 May 19;PP. doi: 10.1109/JBHI.2022.3175862. Online ahead of print.

ABSTRACT

As different scientific disciplines begin to converge on machine learning for causal inference, we demonstrate the application of machine learning algorithms in the context of longitudinal causal estimation using electronic health records. Our aim is to formulate a marginal structural model for estimating diabetes care provisions in which we envisioned hypothetical (i.e. counterfactual) dynamic treatment regimes using a combination of drug therapies to manage diabetes: metformin, sulfonylurea and SGLT-2i. The binary outcome of diabetes care provisions was defined using a composite measure of chronic disease prevention and screening elements [27] including (i) primary care visit, (ii) blood pressure, (iii) weight, (iv) hemoglobin A1c, (v) lipid, (vi) ACR, (vii) eGFR and (viii) statin medication. We used several statistical learning algorithms to describe causal relationships between the prescription of three common classes of diabetes medications and quality of diabetes care using the electronic health records contained in National Diabetes Repository. In particular, we generated an ensemble of statistical learning algorithms using the SuperLearner framework based on the following base learners: (i) least absolute shrinkage and selection operator, (ii) ridge regression, (iii) elastic net, (iv) random forest, (v) gradient boosting machines, and (vi) neural network. Each statistical learning algorithm was fitted using the pseudo-population generated from the marginalization of the time-dependent confounding process. Covariate balance was assessed using the longitudinal (i.e. cumulative-time product) stabilized weights with calibrated restrictions. Our results indicated that the treatment drop-in cohorts (with respect to metformin, sulfonylurea and SGLT-2i) may have improved diabetes care provisions in relation to treatment naive (i.e. no treatment) cohort. As a clinical utility, we hope that this article will facilitate discussions around the prevention of adverse chronic outcomes associated with type II diabetes through the improvement of diabetes care provisions in primary care.

PMID:35588417 | DOI:10.1109/JBHI.2022.3175862

PLoS One. 2022 May 19;17(5):e0268511. doi: 10.1371/journal.pone.0268511. eCollection 2022.

ABSTRACT

First developed in 1982, the double Poisson model, where goals scored by each team are assumed to be Poisson distributed with a mean depending on attacking and defensive strengths, remains a popular choice for predicting football scores, despite the multitude of newer methods that have been developed. This paper examines the pre-tournament predictions made using this model for the Euro 2020 football tournament. These predictions won the Royal Statistical Society’s prediction competition, demonstrating that even this simple model can produce high-quality results. Moreover, the paper also presents a range of novel analytic results which exactly quantify the conditions for the existence and uniqueness of the solution to the equations for the model parameters. After deriving these results, it provides a novel examination of a potential problem with the model-the over-weighting of the results of weaker teams-and illustrates the effectiveness of ignoring results against the weakest opposition. It also compares the predictions with the actual results of Euro 2020, showing that they were extremely accurate in predicting the number of goals scored. Finally, it considers the choice of start date for the dataset, and illustrates that the choice made by the authors (which was to start the dataset just after the previous major international tournament) was close to optimal, at least in this case. The findings of this study give a better understanding of the mathematical behaviour of the double Poisson model and provide evidence for its effectiveness as a match prediction tool.

PMID:35588428 | DOI:10.1371/journal.pone.0268511

IEEE Trans Vis Comput Graph. 2022 May 19;PP. doi: 10.1109/TVCG.2022.3175532. Online ahead of print.

ABSTRACT

A fundamental problem in visual data exploration concerns whether observed patterns are true or merely random noise. This problem is especially pertinent in visual analytics, where the user is presented with a barrage of patterns, without any guarantees of their statistical validity. Recently this problem has been formulated in terms of statistical testing and the multiple comparisons problem. In this paper, we identify two levels of multiple comparisons problems in visualization: the within-view and the between-view problem. We develop a statistical testing procedure for interactive data exploration that controls the family-wise error rate on both levels. The procedure enables the user to determine the compatibility of their assumptions about the data with visually observed patterns. We present use-cases where we visualize and evaluate patterns in real-world data.

PMID:35588414 | DOI:10.1109/TVCG.2022.3175532

Andrology. 2022 May 19. doi: 10.1111/andr.13196. Online ahead of print.

ABSTRACT

BACKGROUND: Addiction is a global problem that has many negative consequences on human health as well as the quality of life.

OBJECTIVES: This review aimed to assess the effect of addiction on human male fertility.

METHODS: A systematic review was conducted on various electronic sites.

RESULTS: The initial literature search identified a total of 5239 articles in all searched databases. After removing duplicates and application of inclusion/exclusion criteria,177 were potential articles, 112 were omitted because no direct relevance was encountered. Finally, 65 studies were retained for review. They were classified according to the type of addiction into; opioids and cannabinoids (18 articles), alcohol (7 articles), cocaine (2 articles), Androgenic Anabolic steroids AAS (15 articles), tobacco (10 articles) and caffeine (13 articles). Most of these recruited articles demonstrated a negative impact of the addressed substance on male fertility with variable levels of evidence.

CONCLUSIONS: It was concluded that addiction harms human male fertility that should be put into consideration. More future studies are needed after a proper methodological and statistical approach, including logistic regression analysis, to predict the effect of a specific substance on human male fertility. This article is protected by copyright. All rights reserved.

PMID:35588397 | DOI:10.1111/andr.13196

Cornea. 2022 May 13. doi: 10.1097/ICO.0000000000003058. Online ahead of print.

ABSTRACT

PURPOSE: The objective of this study was to compare the effectiveness and safety of short versus standard riboflavin induction times in cross-linking (CXL) for keratoconus.

METHODS: A retrospective comparative study was conducted with data from the Save Sight Keratoconus Registry. Inclusion criteria were epithelium-off technique, standard UVA CXL protocol (3 mW/cm2 for 30 minutes), riboflavin induction for 15 minutes (short) or 30 minutes (standard), and 1 year of follow-up data after CXL. Outcome measures included changes in best-corrected visual acuity (BCVA), keratometry in the steepest meridian (K2), maximum keratometry (Kmax), thinnest pachymetry (TCT), and adverse events. Analysis was conducted using mixed-effects regression models adjusted for age, sex, visual acuity, keratometry, pachymetry, practice, and eye laterality.

RESULTS: Two hundred eighty eyes (237 patients; mean, 27.3 ± 10.5 years old; 30% female) were included. The riboflavin induction time was short in 102 eyes (82 patients) and standard in 178 eyes (155 patients). The baseline characteristics (sex, mean age, BCVA, keratometry, and pachymetry [TCT]) were similar between the groups. At the 1-year follow-up visit, no statistically significant differences were observed in flattening in K2 and improvement in BCVA. Greater Kmax flattening [-1.5 diopters (D) vs. -0.5D, P = 0.031] and a greater proportion of >2% increase in TCT (23.5 vs. 11.3, P = 0.034) and haze (29 vs. 15, P = 0.005) were observed with short riboflavin induction.

CONCLUSIONS: Short and standard riboflavin induction times achieved similar degrees of flattening in K2 and improvement in vision. Greater improvements in Kmax and TCT were seen with short riboflavin times; however, this group had higher rates of haze.

PMID:35588392 | DOI:10.1097/ICO.0000000000003058

J Comput Biol. 2022 May 19. doi: 10.1089/cmb.2021.0600. Online ahead of print.

ABSTRACT

Nitrogen uptake in legumes is facilitated by bacteria such as Rhizobium leguminosarum. For this bacterium, gene expression data are available, but functional gene annotation is less well developed than for other model organisms. More annotations could lead to a better understanding of the pathways for growth, plant colonization, and nitrogen fixation in R. leguminosarum. In this study, we present a pipeline that combines novel scores from gene coexpression network analysis in a principled way to identify the genes that are associated with certain growth conditions or highly coexpressed with a predefined set of genes of interest. This association may lead to putative functional annotation or to a prioritized list of genes for further study.

PMID:35588362 | DOI:10.1089/cmb.2021.0600

Jpn J Radiol. 2022 May 19. doi: 10.1007/s11604-022-01290-1. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of the study was to evaluate whether ultra-low-dose computed tomography (ULD-CT) could replace conventional-dose CT (CD-CT) for diagnosis of acute wrist, ankle, knee, and shoulder fractures in emergency departments (ED).

METHODS: We developed CD-CT and ULD-CT scanning schemes for the various joints of the four limbs and scanned emergency patients prospectively. When performing CD-CT, a conventional bone reconstruction algorithm was used, while ULD-CT used both soft tissue and bone algorithms. A five-point scale was used to evaluate whether ULD-CT image quality affected surgical planning. The image quality and diagnostic performance of different types of scanned and reconstructed images for diagnosing fractures were evaluated and compared. Effective radiation dose of each group was calculated.

RESULTS: Our study included 56 normal cases and 185 fracture cases. The combination of bone and soft tissue algorithms on ULD-CT can improve diagnostic performance, such that on ULD-CT, the sensitivity improved from 96.7% to 98.9%, specificity from 98.2% to 100%, positive predictive value from 99.4% to 100%, negative predictive value from 90.2% to 96.6% and diagnostic accuracy ranged from 97.5% to 99.1%. There were no statistically significant differences between ULD-CT and CD-CT on diagnostic performance (p values, 0.40-1.00). The radiation doses for ULD-CT protocols were only 3.0-7.7% of those for CD-CT protocols (all p < 0.01).

CONCLUSIONS: In the emergency department, the 320-row detector ULD-CT could replace CD-CT in the diagnosis of limb joint fractures. The combination of bone algorithm with soft tissue algorithm reconstruction can further improve the image quality and diagnostic performance.

PMID:35588348 | DOI:10.1007/s11604-022-01290-1

Pharmaceut Med. 2022 May 19. doi: 10.1007/s40290-022-00427-x. Online ahead of print.

ABSTRACT

BACKGROUND: In 2007, the priority review voucher (PRV) was implemented in the US to incentivize research and development (R&D) for tropical diseases. The PRV is issued by the US FDA and grants a quicker review to manufacturers upon successful development of a product for a disease eligible for the program.

OBJECTIVE: The objective of this analysis was to assess whether the PRV has incentivized R&D (measured as clinical trial activity) for the intended tropical diseases.

METHOD: We used a difference-in-difference-in-differences (DDD) strategy by exploiting variation in its implementation across diseases and registries around the world. Clinical trials were retrieved from the World Health Organization International Clinical Trials Registry Platform for the years 2005-2019.

RESULTS: We found a positive, but not statistically significant, effect of the PRV on stimulating R&D activity. Delayed effects of the policy could not be found.

CONCLUSION: Our findings, which were robust across a series of robustness tests, suggest that the PRV program is not associated with a trigger in innovation for neglected diseases and therefore should not be considered as a stand-alone solution. It should be supplemented with other government measures to incentivize R&D activity. To increase the value of the program, we recommend that the PRV only be awarded to novel products and not to products that have already been licensed outside the US. Doing so would restrict the number of vouchers awarded and slow down their ongoing market depreciation. Finally, we propose that product sponsors be required to submit an access plan for PRV-awarded products.

PMID:35588350 | DOI:10.1007/s40290-022-00427-x