Category: Statistics

PLoS One. 2022 Jan 7;17(1):e0260436. doi: 10.1371/journal.pone.0260436. eCollection 2022.

ABSTRACT

Many pathologies can occur in the periportal space and manifest as fluid accumulation, visible in Computed tomography (CT) images as a circumferential region of low attenuation around the intrahepatic portal vessels, called periportal halo (PPH). This finding is associated with different types of hepatic and extra-hepatic disease in humans and remains a non-specific sign of unknown significance in veterinary literature. The aim of this study was to investigate the prevalence of PPH in a population of patients undergoing CT examination and to assess the presence of lesions related to hepatic and extra-hepatic disease in presence of PPH. CT studies including the cranial abdomen of dogs and cats performed over a 5-year period were retrospectively reviewed. The prevalence of PPH was 15% in dogs and 1% in cats. 143 animals were included and the halo was classified as mild, moderate and severe, respectively in 51%, 34% and 15% of animals. The halo distribution was generalized in 79 cases, localized along the second generation of portal branches in 63, and along the first generation only in one. Hepatic disease was present in 58/143 and extra-hepatic disease in 110/143 of the cases. Main cause of hepatic (36%) and extra-hepatic disease (68%) was neoplasia. Associations between halo grades and neoplasia revealed to be not statistically significant (p = 0.057). In 7% of animals the CT examination was otherwise unremarkable. PPH is a non-specific finding, occurring in presence of a variety of diseases in the examined patient population.

PMID:34995282 | DOI:10.1371/journal.pone.0260436

PLoS One. 2022 Jan 7;17(1):e0260836. doi: 10.1371/journal.pone.0260836. eCollection 2022.

ABSTRACT

In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiability and computational efficiency. Especially, due to an identification problem, Poisson regression can be unstable for small samples with many zeros. Provided this, we develop a closed-form inference for an over-dispersed Poisson regression including Poisson additive mixed models. The approach is derived via mode-based log-Gaussian approximation. The resulting method is fast, practical, and free from the identification problem. Monte Carlo experiments demonstrate that the estimation error of the proposed method is a considerably smaller estimation error than the closed-form alternatives and as small as the usual Poisson regressions. For counts with many zeros, our approximation has better estimation accuracy than conventional Poisson regression. We obtained similar results in the case of Poisson additive mixed modeling considering spatial or group effects. The developed method was applied for analyzing COVID-19 data in Japan. This result suggests that influences of pedestrian density, age, and other factors on the number of cases change over periods.

PMID:34995283 | DOI:10.1371/journal.pone.0260836

Neurosurgery. 2021 Dec 2. doi: 10.1227/NEU.0000000000001738. Online ahead of print.

ABSTRACT

BACKGROUND: Hypothalamic hamartomas (HHs) are disabling congenital lesions, responsible for gelastic seizures frequently associated with catastrophic epilepsies, epileptogenic encephalopathy, and cognitive and psychiatric severe comorbidities. Stereotactic radiosurgery (SRS) is a well-established minimally invasive therapeutic approach.

OBJECTIVE: To assess whether pretherapeutic gray matter density (GMD) correlates with seizure outcome.

METHODS: We used voxel-based morphometry at whole-brain level, as depicted on pretherapeutic standard structural magnetic resonance neuroimaging. We examined 24 patients (10 male patients, 14 female patients; mean age, 12.7 yr; median, 9; range, 5.9-50) treated in Marseille University Hospital, France, between May 2001 and August 2018.

RESULTS: Most relevant anatomic area predicting postoperative Engel classes I and II vs III and IV after SRS for HHs was mesencephalic tegmentum. Higher pretherapeutic GMD in this area was associated with better outcomes for seizure cessation. The only other statistically significant clusters were right cerebellar lobule VIIIb and VIIIa. Lower pretherapeutic GMD in both clusters correlated with better Engel class outcomes. GMD decreased with age in the left mediodorsal thalamus.

CONCLUSION: Seizure cessation after SRS for HHs was associated with higher GMD in mesencephalic tegmental area, acknowledged to be involved in the neural control of explosive vocal behavior in animals. This area is connected by the mamillotegmental bundle to the lateral tuberal nucleus area of the hypothalamus, where HHs are known to rise. In the future, the detection of more gray matter in this “laugh” tegmental area based on pretherapeutic routine structural neuroimaging might help in patient selection for minimally invasive radiosurgery for HH.

PMID:34995238 | DOI:10.1227/NEU.0000000000001738

J Med Internet Res. 2021 Dec 21. doi: 10.2196/24787. Online ahead of print.

ABSTRACT

BACKGROUND: Innovative surveillance methods are needed to assess adherence to COVID-19 social distancing and stay-at-home order/self-quarantine recommendations, especially methods that can provide near real-time and/or highly geographically targeted data. Use of location-based social media image data is one possible approach that could be explored to address this problem.

OBJECTIVE: We sought to evaluate whether publicly-available near real-time social media images might be used to monitor COVID-19 health policy adherence.

METHODS: We collected a sample of 43,487 Instagram images in New York from February 7 to April 11, 2020 from the following location hashtags: #Centralpark (N = 20,937); #Brooklyn Bridge (N = 14,875); and #Timesquare (N = 7,675). After manually reviewing images for accuracy, we counted and recorded the frequency of valid daily posts at each of these hashtag locations over time, as well as rated and counted whether the individuals in the pictures at these location hashtags were social distancing (i.e., whether the individuals in the images appeared to be distanced from others versus next to or touching each other). We analyzed the number of images posted over time and the correlation between trends among hashtag locations.

RESULTS: We found a statistically significant decline in the number of posts over time across all regions, with an approximate decline of 17% across each site (p< .001). We found a positive correlation between hashtags (#Centralpark,#Brooklynbridge; r=.40), (#BrooklynBridge,#Timesquare; r=.41), (#Timesquare,#Centralpark; r=.33; p< .001 for all correlations). The logistic regression analysis showed a mild statistically significant increase in the proportion of posts over time with people appearing to be social distancing at Times Square (p<.05) and Brooklyn Bridge (p < .05), but not for Central Park.

CONCLUSIONS: Results suggest the potential of using location-based social media image data as a method for surveillance of COVID-19 health policy adherence. Future studies should further explore the implementation and ethical issues associated with this approach.

PMID:34995205 | DOI:10.2196/24787

J Med Internet Res. 2021 Dec 20. doi: 10.2196/33149. Online ahead of print.

ABSTRACT

In the Czech Republic, the strategic data-based and organisational support for individual regions and for providers of acute care on the nationwide level is coordinated by the Ministry of Health of the Czech Republic. At the beginning of the COVID-19 pandemic, the country needed to implement very quickly a system for monitoring, reporting and overall management of hospital capacities. This viewpoint paper aims to describe the purpose and basic functions of a web-based application entitled “Control Centre for Intensive Care”, which has been developed and made available for the needs of systematic online technical support for the management of intensive inpatient care across the Czech Republic during the first wave of pandemic in spring 2020. Two tools of key importance are described in the context of national methodology; namely one module for regular online updates and overall monitoring of currently free capacities of intensive care in real time, and a second module for online entering and overall record keeping of requirements on medications for COVID-19 patients. A total of 134 intensive care providers and 927 users from hospitals from all 14 regions of the Czech Republic were registered in the central Control Centre for Intensive Care database as of 31 March 2021. This web-based application enabled continuous monitoring and decision-making during the mass surge of critical care from autumn 2020 to spring 2021. The Control Centre for Intensive Care has become an indispensable part of a set of online tools that are employed on a regular basis for crisis management at the time of the COVID-19 pandemic.

PMID:34995207 | DOI:10.2196/33149

JMIR Res Protoc. 2021 Dec 18. doi: 10.2196/35558. Online ahead of print.

ABSTRACT

BACKGROUND: Workplace bullying, and violence is a well-documented issue in the midwifery profession. Negative workplace culture, conflict and bullying are the most common forms of workplace violence experienced by midwives. Workplace violence increases the risk of midwives suffering burnout, compassion fatigue, psychological trauma, poor mental health, absenteeism, loss of passion for the midwifery profession, job dissatisfaction and poor job retention. Midwifery students describe workplace violence in the form of physical, emotional and/or verbal abuse, and bullying. Therefore, there is a justification to develop conflict resolution strategies and resilience in midwifery students prior to graduation.

OBJECTIVE: To develop and facilitate a bespoke education program for South Australian (SA) midwifery students, to enable them to develop skills in conflict resolution, build resilience and identify self-care strategies.

METHODS: This study will undertake a preparatory phase summarising the body of literature on midwifery students’ knowledge, understanding and experiences of workplace bullying, and violence. Following this a three-phase sequential mixed methods research design study will be undertaken. Phase 1 – quantitative data will be collected via a semi-structured questionnaire and a validated conflict measurement tool, prior to and after attending an education workshop, and will be analysed using descriptive and inferential statistics. Results from Phase 1 will inform and guide the development of an interview schedule for Phase 2. Phase 2 – qualitative data will be gathered by facilitating one-to-one interviews and a thematic analysis will be undertaken to gain a deeper understanding of midwifery students experiences of workplace bullying, and violence. Phase 3 – data integration using triangulation will be undertaken, and meta inferences will be developed via the integration of results and findings from Phase 1 and 2.

RESULTS: The preparatory phase will commence in October 2021. Phase 1 will commence in 2022 with analysis of pre and post education results anticipated to be completed by December 2022. Phase 2 will be developed from findings of the preparatory phase and results of Phase 1. An interpretation of verbatim interview transcripts is estimated to be undertaken by April 2023. Phase 3 of the study is expected to commence in May 2023, and this will involve the analysis of collective evidence gathered from phases 1 and phase 2. The anticipated completion date for the study is December 2023.

CONCLUSIONS: The outcomes of this research will provide insights into the prevalence and impact of workplace bullying, and violence experienced by midwifery students. The findings of the research will report on levels of knowledge, skills, and confidence, and will assess the impact of a bespoke conflict resolution and resilience education workshop for midwifery students, in managing workplace bullying, and violence.

PMID:34995202 | DOI:10.2196/35558

Int J Radiat Biol. 2022 Jan 7:1-28. doi: 10.1080/09553002.2022.2024294. Online ahead of print.

ABSTRACT

Purpose: A population-based case-control study was conducted in Yangjiang and Enping areas in South China to assess whether the risk of lens opacity induced by natural high background radiation exposure is modulated by polymorphisms of ATM and TP53.Materials and methods: A total of 133 cases who were diagnosed with cortical and posterior subcapsular (PSC) opacity were recruited, and 419 healthy controls were selected through counter-matching in terms of radiation status. Genomic DNA from all the participants was genotyped with the Illumina platform for four single nucleotide polymorphisms of ATM (rs189037, rs373759, and rs4585) and TP53 (rs1042522). The cumulative lens dose received during the entire life was estimated based on annual indoor and outdoor radiation doses and gender- and age-specific occupancy factors. Non-conditional logistic regression was performed to calculate odds ratio (OR) and 95% confidence intervals (95% CI).Results: ATM rs189037 and TP53 rs1042522 were significantly related to cortical and PSC opacity. The risk of opacity was higher when individuals carried the A allele of ATM rs189037 and C allele of TP53 rs1042522, compared with GG genotype. ATM rs189037 A allele carriers (AG/AA) and TP53 rs1042522 C allele carriers (CG/CC) combined with a cumulative lens dose of 100 mGy or higher showed statistically significant opacity risks (OR =5.51, 95% CI: 1.47-20.66; OR =2.69, 95% CI: 1.10-6.60).Conclusion: The A allele of ATM rs189037 and C allele of TP53 rs1042522 increase the risk of lens opacity induced by radiation. These polymorphisms in ATM and TP53 might modify the risk of cortical and PSC opacity induced by chronic and prolonged low-dose radiation.

PMID:34995174 | DOI:10.1080/09553002.2022.2024294

IEEE Trans Neural Netw Learn Syst. 2022 Jan 7;PP. doi: 10.1109/TNNLS.2021.3137172. Online ahead of print.

ABSTRACT

Deep learning networks can be applied to the field of intelligent prediction of part surface roughness. However, the surface roughness samples of parts have the problems of high collection cost, unbalanced categories, and complicated data distribution, which inevitably limit the application of deep learning network models in the field of intelligent prediction of part surface roughness. To solve these problems, this article proposes a novel data augmentation method based on CoralGAN for prediction of part surface roughness, which introduces the domain adaptive method deep coral function to help optimize the network parameters of the generator of generative adversarial network (GAN). Specifically, the vibration signal collected during processing is converted into frequency spectrum data and input into CoralGAN. The training of the generator is guided by coral loss, that is, the distance between the covariances of the real samples and generated samples features, not just the statistical consistency of the traditional GAN. Experiments have been carried out on the three-axis vertical machining center. Research shows that the proposed method can improve the prediction accuracy of part surface roughness to 95.5%.

PMID:34995197 | DOI:10.1109/TNNLS.2021.3137172

Multivariate Behav Res. 2022 Jan 7:1-2. doi: 10.1080/00273171.2021.2009327. Online ahead of print.

NO ABSTRACT

PMID:34995143 | DOI:10.1080/00273171.2021.2009327

Am J Physiol Heart Circ Physiol. 2022 Jan 7. doi: 10.1152/ajpheart.00687.2021. Online ahead of print.

ABSTRACT

The number of research studies investigating whether similar or different cardiovascular responses or adaptations exist between males and females are increasing. Traditionally, difference-based statistical methods (e.g., t-test, ANOVA, etc.) have been implemented to compare cardiovascular function between males and females, with a P-value >0.05 used to denote similarity between sexes. However, an absence of evidence (i.e., large P-value) is not evidence of absence (i.e., no sex differences). Equivalence testing determines whether two measures or groups provide statistically equivalent outcomes, in that they differ by less than an ‘ideally prespecified’ smallest effect size of interest. Our perspective discusses the applicability and utility of integrating equivalence testing when conducting sex comparisons in cardiovascular research. An emphasis is placed on how cardiovascular researchers may conduct equivalence testing across multiple study designs (e.g., cross-sectional comparisons, repeated measures intervention, etc.). The strengths and weaknesses of this statistical tool are discussed. Equivalence analyses are relatively simple to conduct, may be used in conjunction with traditional hypothesis testing to interpret findings, and permits the determination of statistically equivalent responses between sexes. We recommend that cardiovascular researchers consider implementing equivalence testing to better our understanding of similar and different cardiovascular processes between sexes.

PMID:34995165 | DOI:10.1152/ajpheart.00687.2021