Tag: statistics

Mar Pollut Bull. 2021 Jun 23;170:112625. doi: 10.1016/j.marpolbul.2021.112625. Online ahead of print.

ABSTRACT

Current knowledge of the distribution of sensitive seabirds is inadequate to safeguard seabird populations from impacts of oil spills in the Arctic. This gap is mainly driven by the fact that statistical models applied to survey data are coarse-scale and static with limited documentation of the distributional dynamics and patchiness of seabirds relevant to risk assessments related to oil spills. This paper describes a dynamic modelling framework solution for prediction of fine-scale densities and movements of seabirds in close-to-real time using fully integrated 3-D hydrodynamic models, dynamic habitat suitability models and agent-based models. The modelling framework has been developed and validated for the swimming migration of Brünnich’s Guillemot Uria lomvia in the Barents Sea. The results document that the distributional dynamics of Brünnich’s Guillemot and other seabird species to a large degree can be simulated with in-situ state variables and patterns reflecting the physical meteorology and oceanography and habitat suitability.

PMID:34174746 | DOI:10.1016/j.marpolbul.2021.112625

Comput Biol Med. 2021 Jun 15;135:104567. doi: 10.1016/j.compbiomed.2021.104567. Online ahead of print.

ABSTRACT

The Cancer Genome Atlas database offers the possibility of analyzing genome-wide expression RNA-Seq cancer data using paired counts, that is, studies where expression data are collected in pairs of normal and cancer cells, by taking samples from the same individual. Correlation of gene expression profiles is the most common analysis to study co-expression groups, which is used to find biological interpretation of -omics big data. The aim of the paper is threefold: firstly we show for the first time, the presence of a “regulation-correlation bias” in RNA-Seq paired expression data, that is an artifactual link between the expression status (up- or down-regulation) of a gene pair and the sign of the corresponding correlation coefficient. Secondly, we provide a statistical model able to theoretically explain the reasons for the presence of such a bias. Thirdly, we present a bias-removal algorithm, called SEaCorAl, able to effectively reduce bias effects and improve the biological significance of correlation analysis. Validation of the SEaCorAl algorithm is performed by showing a significant increase in the ability to detect biologically meaningful associations of positive correlations and a significant increase of the modularity of the resulting unbiased correlation network.

PMID:34174761 | DOI:10.1016/j.compbiomed.2021.104567

J Psychosom Res. 2021 Jun 17;148:110551. doi: 10.1016/j.jpsychores.2021.110551. Online ahead of print.

ABSTRACT

OBJECTIVES: The literature on childhood-onset depression and future compromised vascular function is suggestive but limited. The objective of this study was to determine if arterial stiffness, a predictor of future cardiovascular disease (CVD), measured in young adulthood, is associated with childhood-onset depression.

METHODS: Cardiometabolic risk factors and pulse wave velocity (PWV), a measure of arterial stiffness, were cross-sectionally assessed in young adults with a history of childhood-onset depression (clinical diagnosis of major depressive episode or dysthymic disorder; N = 294 probands; initially recruited via child mental health facilities across Hungary; mean age of first depressive episode = 10.4 years), their never-depressed full biological siblings (N = 269), and never-depressed controls (N = 169). The mean ages of probands, siblings, and controls at the PWV visit were 25.6, 25.0, and 21.7 years, respectively, and 8.8% of the probands were in a current depressive episode.

RESULTS: Controlling for age, sex, age*sex, education, and family clusters, PWV (m/s) did not statistically differ across the groups (probands = 7.01; siblings = 6.98; controls = 6.81). However, after adjusting for key covariates, there were several across-group differences in CVD risk factors: compared to controls, probands and siblings had higher diastolic blood pressure and lower high-density lipoprotein cholesterol, probands had higher triglycerides, and siblings had higher body mass index (all p < 0.05).

CONCLUSION: We found limited evidence of an association between a history of childhood-onset depression and young adulthood arterial stiffness. However, our findings of elevated cardiovascular risk factors in those with childhood-onset depression suggest that pediatric depression may predispose to increased CVD risk later in life and warrants further investigation.

PMID:34174712 | DOI:10.1016/j.jpsychores.2021.110551

Nurse Educ Pract. 2021 Jun 17;54:103122. doi: 10.1016/j.nepr.2021.103122. Online ahead of print.

ABSTRACT

AIMS: To describe the undergraduate nursing students’ and nursing educators’ evidence-based practice beliefs, their extent of evidence-based practice implementation and their perspectives regarding organizational culture for evidence-based practice. To identify any relationship between the mentioned variables.

BACKGROUND: The integration of evidence-based practice in nursing curricula is crucial to educate nursing students to incorporate evidence-based practice in their future clinical practice. Therefore, to promote its integration within nursing education, it is important to deeply understand how prepared academic institutions are for teaching about and supporting evidence-based practice integration.

DESIGN: Cross-sectional study.

METHODS: Nursing educators and undergraduate nursing students from nine Portuguese nursing schools were invited to participate in this study through an electronic survey comprising socio-demographic questions and the scales.

RESULTS: Sixty-eight nursing educators replied to the survey. Most were female, have PhD and have evidence-based practice training. They showed mean scores of 88.92 ± 8.18 for evidence-based practice beliefs, 40.20 ± 18.93 for evidence-based practice implementation and 80.59 ± 17.52 for evidence-based practice organizational culture and readiness. Concerning nursing educator sample, there were moderate and statistically significant relationship between: evidence-based practice beliefs and implementation; and evidence-based practice beliefs and organizational culture and readiness for school-wide integration of evidence-based practice. Between evidence-based practice implementation and organizational culture and readiness for school-wide integration of evidence-based practice, there was a small relationship. One hundred and sixty-seven undergraduate nursing students answered the survey. Mostly, they were female and were in third or fourth year of their nursing degree. Similarly, to educators, students showed mean scores of 58.69 ± 6.92 for evidence-based practice beliefs, 32.37 ± 16.97 for evidence-based practice implementation and 84.20 ± 23.48 for evidence-based practice organizational culture and readiness. Regarding undergraduate nursing student sample, there were moderate and statistically significant relationship between the different variables.

CONCLUSIONS: Both nursing educators and undergraduate nursing students had strong evidence-based practice beliefs, but low levels of evidence-based practice implementation. In nursing educators’ and undergraduate nursing students’ perspectives, there were opportunities in their schools for the development of an evidence-based practice culture. Based on results, support for development and testing of interventions, specifically tailored for promoting evidence-based practice implementation in nursing educational contexts, is recommended.

PMID:34174719 | DOI:10.1016/j.nepr.2021.103122

J Hazard Mater. 2021 Jun 17;419:126425. doi: 10.1016/j.jhazmat.2021.126425. Online ahead of print.

ABSTRACT

Effective marine oil spill management (MOSM) is crucial to minimize the catastrophic impacts of oil spills. MOSM is a complex system affected by various factors, such as characteristics of spilled oil and environmental conditions. Oil spill detection, characterization, and monitoring; risk evaluation; response selection and process optimization; and waste management are the key components of MOSM demanding timely decision-making. Applying robust computational techniques based on real-time data (e.g., satellite and aerial observations) and historical records of oil spill incidents may considerably facilitate decision-making processes. Various soft-computing and artificial intelligence-based models and mathematical techniques have been used for the implementation of MOSM’s components. This study presents a review of literature published since 2010 on the application of computational techniques in MOSM. A statistical evaluation is performed concerning the temporal distribution of papers, publishers’ engagement, research subfields, countries of studies, and selected case studies. Key findings reported in the literature are summarized for two main practices in MOSM: spill detection, characterization, and monitoring; and spill management and response optimization. Potential gaps in applying computational techniques in MOSM have been identified, and a holistic computational-based framework has been suggested for effective MOSM.

PMID:34174626 | DOI:10.1016/j.jhazmat.2021.126425

Am J Otolaryngol. 2021 Jun 18;42(6):103142. doi: 10.1016/j.amjoto.2021.103142. Online ahead of print.

ABSTRACT

PURPOSE: The aim of this systematic review is to compare the perioperative characteristics and outcomes of submental artery island flap (SAIF) to free tissue transfer (FTT) in head and neck reconstruction.

MATERIALS AND METHODS: Screening and data extraction were done with Pubmed, Embase, and Web of Science databases by two independent authors to identify randomized and observational studies that compared patient outcomes for SAIF vs. FTT for reconstruction head and neck cancer ablative surgery. Data were pooled with random-effects meta-analysis to determine pooled difference in means (DM), absolute risk differences, and 95% confidence intervals (CI). Heterogeneity was assessed with the I-squared statistic.

RESULTS: Initial query yielded 997 results, of which 7 studies met inclusion criteria. The pooled sample sizes for the SAIF and FTT cohorts were 155 and 198, respectively. SAIF reduced mean operative time by 193 min (95% CI -160 to -227), reduced hospital stay by 2.1 days (95% CI -0.9 to -3.4), and had a smaller flap area of 22.5cm² (95% CI 6.5 to 38.4). SAIF had a 5% higher incidence of partial flap necrosis than FTT (95% CI, 1 to 10), but all other perioperative complications, including recurrence rate in malignant cases, were statistically comparable.

CONCLUSIONS: The SAIF requires less operative time, hospital stay, and has comparable perioperative outcomes to FTT, but the area of flap harvest is significantly smaller. The findings of this study add to the growing body of evidence demonstrating the safety and reliability of SAIF in head and neck reconstruction.

PMID:34174670 | DOI:10.1016/j.amjoto.2021.103142

Sci Total Environ. 2021 Jun 19;793:148578. doi: 10.1016/j.scitotenv.2021.148578. Online ahead of print.

ABSTRACT

Forest dieback processes linked to drought are expected to increase due to climate warming. Remotely sensed data offer several advantages over common field monitoring methods such as the ability to observe large areas on a systematic basis and monitoring their changes, making them increasingly used to assess changes in forest health. Here we aim to use a combined approximation of fieldwork and remote sensing to explore possible links between forest dieback and land surface phenological and trend variables derived from long Landsat time series. Forest dieback was evaluated in the field over 31 plots in a Mediterranean, xeric Pinus pinaster forest. Landsat 31-year time series of three greenness (EVI, NDVI, SAVI) and two wetness spectral indices (NMDI and TCW) were derived covering the period 1990-2020. Spectral indices from time series were decomposed into trend and seasonality using a Bayesian estimator while the relationships of the phenological and trend variables among levels of damage were assessed using linear and additive mixed models. We have not found any statistical pieces of evidence of extension or shortening patterns for the length of the phenological season over the examined 31-year period. Our results indicate that the dieback process was mainly related to the trend component of the spectral indices series whereas the phenological metrics were not related to forest dieback. We also found that plots with more dying or damaged trees displayed lower spectral indices trends after a severe drought event in the middle of the 1990s, which confirms the Landsat-derived spectral indices as indicators of early-warning signals. Drops in trends occurred earlier for wetness indices rather than for greenness indices which suggests that the former could be more appropriate for dieback detection, i.e. they could be used as early warning signals of impending loss of tree vigor.

PMID:34174606 | DOI:10.1016/j.scitotenv.2021.148578

Appl Ergon. 2021 Jun 23;97:103461. doi: 10.1016/j.apergo.2021.103461. Online ahead of print.

ABSTRACT

Overhead work is known as one of the ergonomic risk factors that can lead to shoulder overload and injury. Anatomical alignment of rotator cuff muscles makes them the most vulnerable to injuries during overhead work. In this study, the effect of task rotation, as one of the administrative controls to reduce the risk of injury during overhead work, on the fatigue response of rotator cuff muscles was investigated. Twelve participants performed three submaximal exertions (5, 20, and 35% of maximum voluntary contraction (MVC)) using four task rotation sequences (increasing, decreasing, upward parabolic, and downward parabolic). Median frequency of surface electromyography (EMG), shoulder strength, and ratings of perceived exertion (RPE) were used to study the fatigue response of rotator cuff muscles. Although the average normalized muscle activity was similar in all sequences, the task rotation sequence had a significant effect on the median frequency. The effect of task rotation sequence on the strength and RPE was similar to that of the median frequency but was statistically not significant. The upward parabolic task rotation sequence resulted in the lowest fatigue among all the task sequences. Performing intense exertions apart from each other, warm-up exertions, and the presence of active recovery after the intense exertions could be the factors that produced the lowest fatigue during this sequence.

PMID:34174574 | DOI:10.1016/j.apergo.2021.103461

Sci Total Environ. 2021 Jun 21;793:148595. doi: 10.1016/j.scitotenv.2021.148595. Online ahead of print.

ABSTRACT

In the present study, hydro-meteorological variables of Chitral Basin in Hindukush region of Pakistan were studied to predict the changes in climatic components such as temperature, precipitation, humidity and river flow based on observed data from 1990 to 2019. Uncertainties in climate change projection were studied using various statistical methods, such as trend variability analysis via stationarity test and validation of regression assumptions prior to fitting of regression estimates. Also, multiple regression models were estimated for each hydro-meteorological variables for the given 30 years of observed data. Results demonstrated that temperature and, precipitation were inversely related with one another. It was observed from the regression model that temperature is decreases by 0.309 °C on the average increases in precipitation by one unit. Temperature also decreases for the increase in humidity by average 0.086 °C. Since, precipitation is negatively related with temperature, thus for increases in temperature the annual precipitation decreases by 0.278 mm annually. Humidity on the other hand, increases by 0.207% by increasing in precipitation and the temperature that causes humidity to decrease by 0.99%. Thus, it demonstrated that the flow in Chitral river increases due to precipitation by 0.306 m³/s for the change in precipitation by one unit. Findings from the present study negated the general perceptions that flow in the Chitral river has increased due to recession of glaciers with increase in the intensity of temperature.

PMID:34174604 | DOI:10.1016/j.scitotenv.2021.148595

Epidemics. 2021 Jun 19;36:100478. doi: 10.1016/j.epidem.2021.100478. Online ahead of print.

ABSTRACT

National influenza pandemic plans have evolved substantially over recent decades, as has the scientific research that underpins the advice contained within them. While the knowledge generated by many research activities has been directly incorporated into the current generation of pandemic plans, scientists and policymakers are yet to capitalise fully on the potential for near real-time analytics to formally contribute to epidemic decision-making. Theoretical studies demonstrate that it is now possible to make robust estimates of pandemic impact in the earliest stages of a pandemic using first few hundred household cohort (FFX) studies and algorithms designed specifically for analysing FFX data. Pandemic plans already recognise the importance of both situational awareness i.e., knowing pandemic impact and its key drivers, and the need for pandemic special studies and related analytic methods for estimating these drivers. An important next step is considering how information from these situational assessment activities can be integrated into the decision-making processes articulated in pandemic planning documents. Here we introduce a decision support tool that directly uses outputs from FFX algorithms to present recommendations on response options, including a quantification of uncertainty, to decision makers. We illustrate this approach using response information from within the Australian influenza pandemic plan.

PMID:34174521 | DOI:10.1016/j.epidem.2021.100478