Category: Statistics

J Obstet Gynaecol Res. 2021 Sep 27. doi: 10.1111/jog.15040. Online ahead of print.

ABSTRACT

AIM: The aim of this study was to compare the surgical outcomes between patients who were staged laparoscopically for early-stage endometrioid-type endometrial cancer (EC) between those who underwent prophylactic ligation of uterine arteries (UAs) prior to pelvic lymphadenectomy and the patients who were operated with standard procedure.

METHODS: This retrospective study was conducted in women diagnosed with early-stage and low/intermediate-risk endometrioid-type EC. The control group included patients who underwent standard laparoscopic pelvic lymphadenectomy and the study group concerned patients who underwent prophylactic ligation of UA prior to pelvic lymphadenectomy. The prophylactic ligation of UA procedure was performed at a point just proximal to its origin.

RESULTS: The mean lymph node count dissected in the study group was higher in terms of statistical significance (17.5 ± 2.2 vs. 19.8 ± 3.6, p = 0.003 and p ˂ 0.05). The rate of the patients who had a positive pelvic lymph node detected did not differ between groups (7.4% vs. 16.7%, p = 0.258 and p ˂ 0.05). The operation time (OT) of the patients in the study group did not differ between groups (p = 0.546 and p ˂ 0.05). Hemoglobin drop (-0.5 ± 0.7) and hematocrite drop (-0.8 ± 0.9) values in the study group were found to be lower in the study group (p = 0.000, p = 0.000, and p ˂ 0.05).

CONCLUSIONS: Performing prophylactic ligation of UA at its origin prevents unwanted bleeding and facilitates the laparoscopic pelvic lymphadenectomy procedure.

PMID:34571568 | DOI:10.1111/jog.15040

J Am Med Inform Assoc. 2021 Sep 27:ocab203. doi: 10.1093/jamia/ocab203. Online ahead of print.

ABSTRACT

OBJECTIVE: Deep significance clustering (DICE) is a self-supervised learning framework. DICE identifies clinically similar and risk-stratified subgroups that neither unsupervised clustering algorithms nor supervised risk prediction algorithms alone are guaranteed to generate.

MATERIALS AND METHODS: Enabled by an optimization process that enforces statistical significance between the outcome and subgroup membership, DICE jointly trains 3 components, representation learning, clustering, and outcome prediction while providing interpretability to the deep representations. DICE also allows unseen patients to be predicted into trained subgroups for population-level risk stratification. We evaluated DICE using electronic health record datasets derived from 2 urban hospitals. Outcomes and patient cohorts used include discharge disposition to home among heart failure (HF) patients and acute kidney injury among COVID-19 (Cov-AKI) patients, respectively.

RESULTS: Compared to baseline approaches including principal component analysis, DICE demonstrated superior performance in the cluster purity metrics: Silhouette score (0.48 for HF, 0.51 for Cov-AKI), Calinski-Harabasz index (212 for HF, 254 for Cov-AKI), and Davies-Bouldin index (0.86 for HF, 0.66 for Cov-AKI), and prediction metric: area under the Receiver operating characteristic (ROC) curve (0.83 for HF, 0.78 for Cov-AKI). Clinical evaluation of DICE-generated subgroups revealed more meaningful distributions of member characteristics across subgroups, and higher risk ratios between subgroups. Furthermore, DICE-generated subgroup membership alone was moderately predictive of outcomes.

DISCUSSION: DICE addresses a gap in current machine learning approaches where predicted risk may not lead directly to actionable clinical steps.

CONCLUSION: DICE demonstrated the potential to apply in heterogeneous populations, where having the same quantitative risk does not equate with having a similar clinical profile.

PMID:34571540 | DOI:10.1093/jamia/ocab203

Handchir Mikrochir Plast Chir. 2021 Sep 27. doi: 10.1055/a-1380-3922. Online ahead of print.

ABSTRACT

BACKGROUND: Microsurgery is a specific surgical expertise that involves operating on very small structures, and requires the assistance of a magnifying device: a microscope or loupes. Several factors have been identified that could affect the quality of microsurgical performance in training or surgical procedures.

OBJECTIVE: The objective of this study was to assess the impact of the selected factors – caffeine, alcohol and physical exercise – on a microsurgical task prior its performance.

METHODS: Ten students from the 5th and 6th years of medical studies who had completed the advanced microsurgical course performed a “6-stitches test” on a latex glove spanned over a cup prior to and after consumption of caffeine, alcohol and performing physical exercises. The times taken to complete the task at baseline and post-exposure were recorded.

RESULTS: The results of the study show a statistically significant positive effect of caffeine and a statistically significant negative effect of physical exercise on microsurgical performance when performed shortly before the task. Small dose of alcohol taken before the task showed had little effect on performance.

PMID:34571547 | DOI:10.1055/a-1380-3922

Brief Bioinform. 2021 Sep 24:bbab389. doi: 10.1093/bib/bbab389. Online ahead of print.

ABSTRACT

Pleiotropy has important implication on genetic connection among complex phenotypes and facilitates our understanding of disease etiology. Genome-wide association studies provide an unprecedented opportunity to detect pleiotropic associations; however, efficient pleiotropy test methods are still lacking. We here consider pleiotropy identification from a methodological perspective of high-dimensional composite null hypothesis and propose a powerful gene-based method called MAIUP. MAIUP is constructed based on the traditional intersection-union test with two sets of independent P-values as input and follows a novel idea that was originally proposed under the high-dimensional mediation analysis framework. The key improvement of MAIUP is that it takes the composite null nature of pleiotropy test into account by fitting a three-component mixture null distribution, which can ultimately generate well-calibrated P-values for effective control of family-wise error rate and false discover rate. Another attractive advantage of MAIUP is its ability to effectively address the issue of overlapping subjects commonly encountered in association studies. Simulation studies demonstrate that compared with other methods, only MAIUP can maintain correct type I error control and has higher power across a wide range of scenarios. We apply MAIUP to detect shared associated genes among 14 psychiatric disorders with summary statistics and discover many new pleiotropic genes that are otherwise not identified if failing to account for the issue of composite null hypothesis testing. Functional and enrichment analyses offer additional evidence supporting the validity of these identified pleiotropic genes associated with psychiatric disorders. Overall, MAIUP represents an efficient method for pleiotropy identification.

PMID:34571531 | DOI:10.1093/bib/bbab389

Brief Bioinform. 2021 Sep 25:bbab402. doi: 10.1093/bib/bbab402. Online ahead of print.

ABSTRACT

The identification of differentially expressed genes between different cell groups is a crucial step in analyzing single-cell RNA-sequencing (scRNA-seq) data. Even though various differential expression analysis methods for scRNA-seq data have been proposed based on different model assumptions and strategies recently, the differentially expressed genes identified by them are quite different from each other, and the performances of them depend on the underlying data structures. In this paper, we propose a new ensemble learning-based differential expression analysis method, scDEA, to produce a more stable and accurate result. scDEA integrates the P-values obtained from 12 individual differential expression analysis methods for each gene using a P-value combination method. Comprehensive experiments show that scDEA outperforms the state-of-the-art individual methods with different experimental settings and evaluation metrics. We expect that scDEA will serve a wide range of users, including biologists, bioinformaticians and data scientists, who need to detect differentially expressed genes in scRNA-seq data.

PMID:34571530 | DOI:10.1093/bib/bbab402

Epilepsy Res. 2021 Sep 22;177:106774. doi: 10.1016/j.eplepsyres.2021.106774. Online ahead of print.

ABSTRACT

Previous findings have suggested that a preictal state might precede the epileptic seizure onset, which is the basis for seizure prediction attempts. Preictal states can be apprehended as outliers that differ from an interictal baseline and display clinical changes. We collected daily clinical scores from patients with epilepsy who underwent continuous video-EEG and assessed the ability of several outlier detection methods to identify preictal states. Results from 24 patients suggested that outlying clinical features were suggestive of preictal states and can be identified by statistical methods: AUC = 0.71, 95 % CI = [0.63 – 0.79]; PPV = 0.77, 95 % CI = [0.70 – 0.84]; FPR = 0.31, 95 % CI = [0.21 – 0.44]); and F1 score = 0.74, 95 % CI = [0.64 – 0.81]. Such algorithms could be straightforwardly implemented in a mobile device (e.g., tablet or smartphone), which would allow a longer data collection that could improve prediction performances. Additional clinical – and even multimodal – parameters could identify more subtle physiological modifications.

PMID:34571459 | DOI:10.1016/j.eplepsyres.2021.106774

Neuropsychobiology. 2021 Sep 27:1-8. doi: 10.1159/000518996. Online ahead of print.

ABSTRACT

INTRODUCTION: Emotion regulation (ER), the ability to actively modulate one’s own emotion reactions, likely depends on the individual’s current emotional state. Here, we investigated whether negative emotions induced by an interpersonal autobiographic script affect the neuronal processes underlying ER.

METHODS: Twenty healthy participants were recruited and underwent functional magnetic resonance imaging (fMRI) during performance of distancing, a specific ER strategy, while viewing emotionally arousing pictures. Participants were instructed to either naturally experience (“permit” condition) or to actively downregulate (“regulate” condition) their emotional responses to the presented stimuli. Before each of the 4 runs in total, a neutral or negative autobiographical audio script was presented. The negative script comprised an emotionally negative event from childhood or adolescence that represented either emotional abuse or emotional neglect. The second event comprised an everyday neutral situation. We aimed at identifying the neural correlates of ER and their modulation by script-driven imagery.

RESULTS: fMRI analyses testing for greater responses in the “regulate” than the “permit” condition replicated previously reported neural correlates of ER in the right dorsolateral prefrontal cortex and the right inferior parietal lobule. A significant ER effect was also observed in the left orbitofrontal cortex. In the amygdala, we found greater responses in the “permit” compared to the “regulate” condition. We did not observe a significant modulation of the ER effects in any of these regions by the negative emotional state induced by autobiographical scripts. Bayesian statistics confirmed the absence of such modulations by providing marginal evidence for null effects.

DISCUSSION: While we replicated previously reported neural correlates of ER, we found no evidence for an effect of mood induction with individualized autobiographical scripts on the neural processes underlying ER in healthy participants.

PMID:34571510 | DOI:10.1159/000518996

Public Health. 2021 Sep 24;199:87-95. doi: 10.1016/j.puhe.2021.07.011. Online ahead of print.

ABSTRACT

OBJECTIVES: Safe blood transfusion plays an important role in the prevention of transfusion-transmissible infections, and hepatitis C virus (HCV) infection is one of the major problems associated with this procedure. This meta-analysis aimed to determine the prevalence of HCV infection in Chinese blood donors.

STUDY DESIGN: The study design of this study is a meta-analysis.

METHODS: Eligible studies were retrieved from PubMed, Embase, China National Knowledge Infrastructure, China Science and Technology Journal Database and Wanfang literature databases from 2010 to 2020. The effect measure was presented as HCV prevalence with a 95% confidence interval (CI). Q test was used to assess the heterogeneity, and the I² statistics was determined to decide whether a random effects model or a fixed effects model should be used as the pooling method. Subgroup analyses were also conducted.

RESULTS: A total of 62 eligible studies, including 9,007,220 HCV blood donors, were analysed. Of the total blood donors, 35,017 were infected with HCV. The pooled HCV prevalence was 0.415% (95% CI: 0.371-0.458). The subgroup analysis revealed that the prevalence of positivity to anti-HCV antibodies was significantly different in each year (P < 0.05). However, no significant difference was observed in HCV prevalence in terms of sex. Moreover, the prevalence of positivity to anti-HCV was remarkably higher in first-time blood donors than in repeat blood donors (P < 0.05), and the rate of HCV infection among university students was significantly lower than that among soldiers (P < 0.05).

CONCLUSIONS: The rate of HCV infection showed a downward trend from 2010 to 2014, increased in 2015-2016, and finally decreased in 2017-2018. Thus, the prevalence of HCV infection has decreased in Chinese blood donors after comprehensive prevention and treatment.

PMID:34571442 | DOI:10.1016/j.puhe.2021.07.011

Nurse Educ Today. 2021 Sep 10;107:105140. doi: 10.1016/j.nedt.2021.105140. Online ahead of print.

ABSTRACT

BACKGROUND: In 2018, the Korean version of the Clinical Learning Environment, Supervision, and Nurse Teacher scale was evaluated for validity and reliability.

OBJECTIVES: This study aimed to test the instrument’s measurement invariance and to compare the latent means of groups.

DESIGN: This was a cross-sectional study.

SETTINGS: Nursing departments in four metropolitan cities and five regions of Korea. The study sample comprised 507 nursing students.

PARTICIPANTS: Bachelor’s-level nursing students in their third and fourth years who have experienced clinical practicum.

METHODS: Data were collected from November 11 to December 24, 2018 using the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale. Confirmatory factor analysis and multi-group confirmatory factor analysis were conducted. Measurement invariance of the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale was tested in the following order: configural invariance, factor-loading invariance, intercept invariance, factor variance/covariance invariance, and residual invariance, by student year, hospital grade (tertiary or general hospital) and assignment of a nurse instructor (or not).

RESULTS: The measurement invariance of the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale by student year and hospital grade were confirmed by configural invariance, factor-loading invariance, intercept invariance, factor variance/covariance invariance, and residual invariance. The measurement invariance of the scale by assignment of a nurse instructor (or not) was also confirmed for configural invariance, factor-loading invariance, partial intercept invariance, partial factor variance/covariance invariance, and partial residual invariance. Comparing latent mean values, there was a statistically significant difference in the mean of the sub-dimensions of the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale by student year, hospital grade, and nurse assignment (or not).

CONCLUSIONS: The Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale is an appropriate instrument for measuring the clinical learning environment regardless of student year, hospital grade, or nurse assignment.

PMID:34571445 | DOI:10.1016/j.nedt.2021.105140

Mar Pollut Bull. 2021 Sep 24;173(Pt A):112989. doi: 10.1016/j.marpolbul.2021.112989. Online ahead of print.

ABSTRACT

The principal objective of this study is to assess the saltwater intrusion and hydrogeochemical processes that affect groundwater geochemistry in the coastal aquifers of southwestern India. Groundwater samples were collected seasonally and the physico-chemical parameters determined on-site. Major ions were determined in the laboratory. Hydrochemical diagrams, ionic ratios, and multivariate statistical analysis were adopted for understanding the groundwater chemistry. Gibbs plot identified that rock-water interaction and evaporation were the mechanisms regulating hydrogeochemistry. Ionic ratios have shown that coastal wells were contaminated with saltwater intrusion during the pre-monsoon season. Hierarchical cluster analysis classified the samples based on their quality; sample clusters with high NO₃^– were in densely populated areas, whereas sample clusters with moderate salt content in the coastal areas. Another cluster showed high concentrations of salts, typically the zones of saltwater intrusion. The study concludes that influence of seasons, geogenic and anthropogenic factors contribute to the heterogeneous chemistry of groundwater.

PMID:34571386 | DOI:10.1016/j.marpolbul.2021.112989