scholarly journals The health impact of (sexual) torture amongst Afghan, Iranian and Kurdish refugees: A literature review

2018 ◽  
Vol 28 (3) ◽  
pp. 77-91
Author(s):  
Roghieh Dehghan
Keyword(s):  
Sexual Violence ◽  
Health Impact ◽  
Small Sample ◽  
Torture Survivors ◽  
Adverse Health Outcomes ◽  
Sexual Torture ◽  
Health Related ◽  
Small Sample Sizes ◽  
Online Catalogue ◽  
The Impact

Background: Amongst Muslim majority countries, torture is reported most in Afghanistan and Iran. In addition, despite the significant impact of sexual violence on individuals and public health, the issue has been poorly researched amongst victims of torture. Objectives: The original intention of this paper was to review the health impact of sexual torture amongst Iranian and Afghan refugees in high-income countries; however, a comprehensive search of relevant databases did not produce any results. The aim of this review was then altered to examine those health-related studies that explored the impact of torture in this population. Special attention was given to the discussion of gender and sexual violence in those studies. Methodology: Web of Science, PILOTS, Medline, PsycINFO, Scopus, Popline and the online catalogue at DIGNITY were searched for health studies that examined the health impact or predictors of adverse health outcomes in Afghan, Iranian and Kurdish refugee survivors of torture. Outcome: Seven papers were identified and examined in this review. The results were limited by the diverse methodologies, by the use of psychiatric tools that had not been validated in this population, and by small sample sizes. Since there is a high prevalence of sexual torture in Iranian and Kurdish refugees, the issue merits greater attention in this population. Studies are most limited amongst the Afghan population. Moreover, there is a great need for further culture-andgender- specific health research in torture survivors from Muslim backgrounds.

scholarly journals Viscoelastometric Testing to Assess Hemostasis of COVID-19: A Systematic Review

2021 ◽  
Vol 10 (8) ◽  
pp. 1740
Author(s):  
Marion Bareille ◽  
Michaël Hardy ◽  
Jonathan Douxfils ◽  
Stéphanie Roullet ◽  
Dominique Lasne ◽  
...  
Keyword(s):  
Systematic Review ◽  
Mechanical Strength ◽  
Small Sample ◽  
The Common ◽  
Small Sample Sizes ◽  
Definition Of ◽  
Reported Data ◽  
Prophylactic Anticoagulation ◽  
The Impact ◽  
Heparin Neutralization

Infection by SARS-CoV-2 is associated with a high risk of thrombosis. The laboratory documentation of hypercoagulability and impaired fibrinolysis remains a challenge. Our aim was to assess the potential usefulness of viscoelastometric testing (VET) to predict thrombotic events in COVID-19 patients according to the literature. We also (i) analyzed the impact of anticoagulation and the methods used to neutralize heparin, (ii) analyzed whether maximal clot mechanical strength brings more information than Clauss fibrinogen, and (iii) critically scrutinized the diagnosis of hypofibrinolysis. We performed a systematic search in PubMed and Scopus databases until December 31st, 2020. VET methods and parameters, and patients’ features and outcomes were extracted. VET was performed for 1063 patients (893 intensive care unit (ICU) and 170 non-ICU, 44 studies). There was extensive heterogeneity concerning study design, VET device used (ROTEM, TEG, Quantra and ClotPro) and reagents (with non-systematic use of heparin neutralization), timing of assay, and definition of hypercoagulable state. Notably, only 4 out of 25 studies using ROTEM reported data with heparinase (HEPTEM). The common findings were increased clot mechanical strength mainly due to excessive fibrinogen component and impaired to absent fibrinolysis, more conspicuous in the presence of an added plasminogen activator. Only 4 studies out of the 16 that addressed the point found an association of VETs with thrombotic events. So-called functional fibrinogen assessed by VETs showed a variable correlation with Clauss fibrinogen. Abnormal VET pattern, often evidenced despite standard prophylactic anticoagulation, tended to normalize after increased dosing. VET studies reported heterogeneity, and small sample sizes do not support an association between the poorly defined prothrombotic phenotype of COVID-19 and thrombotic events.

scholarly journals Cannabis and breastfeeding

2020 ◽  
Vol 25 (Supplement_1) ◽  
pp. S26-S28 ◽  
Author(s):  
Lisa Graves
Keyword(s):  
Health Care Providers ◽  
Small Sample ◽  
Adverse Outcomes ◽  
Care Providers ◽  
High Quality ◽  
High Quality Evidence ◽  
Small Sample Sizes ◽  
The Impact ◽  
Quality Evidence

Abstract Cannabis is one of the most commonly used substances in Canada with 15% of Canadians reporting use in 2019. There is emerging evidence that cannabis is linked to an impact on the developing brain in utero and adverse outcomes in infants, children, and adolescents. The impact of cannabis during breastfeeding has been limited by studies with small sample sizes, follow-up limited to 1 year and the challenge of separating prenatal exposure from that during breastfeeding. In the absence of high-quality evidence, health care providers need to continue to engage women in conversation about the potential concerns related to breastfeeding and cannabis use.

Real-world data evaluating immunotherapy markers and checkpoint inhibitor response among GI cancers in a large community-based oncology network.

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 113-113
Author(s):  
Carissa Jones ◽  
Rebecca Lachs ◽  
Emma Sturgill ◽  
Amanda Misch ◽  
Caressa Lietman ◽  
...  
Keyword(s):  
Checkpoint Inhibitor ◽  
Small Sample ◽  
Tumor Type ◽  
Real World Data ◽  
Loss To Follow Up ◽  
Kaplan Meier ◽  
Gi Cancers ◽  
Small Sample Sizes ◽  
Line Of Therapy ◽  
The Impact

113 Background: Checkpoint inhibitor (CPI) therapies have shown prolonged survival in patients (pts) with microsatellite instability (MSI). Tumor mutation burden (TMB) has also been associated with benefit from CPIs, with pembrolizumab recently approved for solid tumors with a TMB of ≥10 muts/mb. However, the validity of a tissue-agnostic approach has been debated given the high degree of TMB variation across tumor types. We sought to evaluate the impact of TMB and MSI on CPI response in pts with advanced gastrointestinal (GI) cancers who received NGS profiling. Methods: Patients within the Sarah Cannon network with GI cancer and comprehensive next generation sequencing (NGS) data were identified through Genospace, Sarah Cannon’s clinico-genomic analytics platform. Microsatellite (MS) status [high (MSI-H) vs. stable (MSS)] was defined by NGS. TMB-high (TMB-H) was defined as ≥10 muts/mb. Kaplan-Meier estimates were used to examine time to treatment failure (TTF), defined as the time from therapy start to start of next therapy, death, or loss to follow-up. Results: We identified 5,788 pts with GI cancers who received NGS, of which 48% (N=3,603) had colorectal cancer (CRC). MS status was evaluated on 4,219 (66%) NGS reports, TMB on 2,922 (46%) reports, and both on 2,863 (45%) reports. MSI-H and TMB-H co-occurred on 127 reports (4%), MSS/TMB-H occurred on 312 reports (11%), and MSS/TMB-Low (TMB-L) occurred on 2,424 reports (85%). No reports were MSI-H/TMB-L. Overall, 580 pts (14%) received CPI therapy (N=52 MSI-H/TMB-H, N=41 MSS/TMB-H, N=215 MSS/TMB-L). Independent of line of therapy or tumor type, TTF was significantly shorter for CPI vs. non-CPI therapies [median TTF (mTTF)=151 vs. 238 days, respectively, p=3.4x10-9]. As expected, MSI-H was also associated with longer CPI TTF compared to MSS (mTTF=727 vs. 124 days, p=3.1x10-11). Due to small sample sizes, further analyses were focused on pts with CRC (Table). TMB-H was independently associated with longer CPI TTF compared to TMB-L (Table, p=9.2x10-10). Similarly, the co-occurrence of MSI-H/TMB-H was also associated with longer CPI TTF (Table). However, there was no difference in CPI TTF for MSS/TMB-H and MSS/TMB-L (Table, p=0.45). All pts who received non-CPI therapies, regardless of MS/TMB group, had longer TTF than MSS/TMB-H and MSS/TMB-L pts who received CPI (Table). mTTF [days (N)] for pts with CRC by biomarker. Conclusions: Despite recent tissue-agnostic approvals, TMB does not appear to be a good biomarker of CPI response in pts with CRC. Rather, time to CPI failure is associated with the co-occurrence of TMB-H with MSI-H. Continued research is needed to identify better biomarkers of response to immunotherapy in GI cancers. [Table: see text]

scholarly journals The impact of the 30 most cited articles on hip arthroscopy: what is the subject matter?

2020 ◽  
Vol 7 (1) ◽  
pp. 14-21
Author(s):  
Alexander von Glinski ◽  
Emre Yilmaz ◽  
Ryan Goodmanson ◽  
Clifford Pierre ◽  
Sven Frieler ◽  
...  
Keyword(s):  
Surgical Treatment ◽  
Hip Arthroscopy ◽  
Randomized Clinical Trials ◽  
Technical Note ◽  
Small Sample ◽  
Level Of Evidence ◽  
Thomson Reuters ◽  
Treatment Indications ◽  
Small Sample Sizes ◽  
The Impact

Abstract The purpose of this study was to identify the 30 most cited articles on hip arthroscopy and discuss their influence on recent surgical treatment. Due to advancements in hip arthroscopy, there is a widening spectrum of diagnostic and treatment indications. The purpose of this study was to identify the 30 most cited articles on hip arthroscopy and discuss their influence on contemporary surgical treatment. The Thomson Reuters Web of Science was used to identify the 30 most cited studies on hip arthroscopy between 1900 and 2018. These 30 articles generated 6152 citations with an average of 205.07 citations per item. Number of citations ranged from 146 to 461. Twenty-five out of the 30 papers were clinical cohort studies with a level of evidence between III and IV, encompassing 4348 patients. Four studies were reviewed (one including a technical note) and one a case report. We were able to identify the 30 most cited articles in the field of hip arthroscopy. Most articles were reported in high-impact journals, but reported small sample sizes in a retrospective setting. Prospective multi-arm cohort trials or randomized clinical trials represent opportunities for future studies.

The scale of it all: postcanine tooth size, the taxon-level effect, and the universality of Gould's scaling law

Paleobiology ◽  
2010 ◽  
Vol 36 (2) ◽  
pp. 188-203 ◽  
Author(s):  
Lynn E. Copes ◽  
Gary T. Schwartz
Keyword(s):  
Body Mass ◽  
Scaling Law ◽  
Small Sample ◽  
Tooth Size ◽  
Mathematical Methods ◽  
Scaling Relationship ◽  
Small Sample Sizes ◽  
Relationship Of ◽  
The Impact ◽  
Level Effect

In a seminal paper in 1975, Gould proposed that postcanine occlusal area (PCOA) should scale metabolically (0.75) with body mass across mammals. By regressing PCOA against skull length in a small sample of large-bodied herbivorous mammals, Gould provided some marginal support for this hypothesis, which he then extrapolated as a universal scaling law for Mammalia. Since then, many studies have sought to confirm this scaling relationship within a single order and have found equivocal support for Gould's assertion. In part, this may be related to the use of proxies for both PCOA and body mass, small sample sizes, or the influence of a “taxon-level effect,” rendering Gould's scaling “universal” problematic.Our goal was to test the universality of Gould's prediction and the impact of the taxon-level effect on regressions of tooth size on body mass in a large extant mammalian sample (683 species spanning 14 orders). We tested for the presence of two types of taxon-level effect that may influence the acceptance or rejection of hypothesized scaling coefficients. The hypotheses of both metabolic and isometric scaling can be rejected in Mammalia, but not in all sub-groups therein. The level of data aggregation also influences the interpretation of the scaling relationship. Because the scaling relationship of tooth size to body mass is highly dependent on both the taxonomic level of analysis and the mathematical methods used to organize the data, paleontologists attempting to retrodict body mass from fossilized dental remains must be aware of the effect that sample composition may have on their results.

Does Removable Partial Denture Quality Affect Individuals’ Oral Health?

2008 ◽  
Vol 87 (8) ◽  
pp. 736-739 ◽  
Author(s):  
M. Inukai ◽  
K. Baba ◽  
M.T. John ◽  
Y. Igarashi
Keyword(s):  
Oral Health ◽  
Linear Regression Analysis ◽  
Japanese Version ◽  
Health Impact ◽  
Removable Partial Denture ◽  
Related Quality ◽  
Important Health ◽  
Health Related ◽  
Clinically Significant ◽  
The Impact

The impact of oral disorders and interventions on individuals’ perceived oral health and oral-health-related quality of life (OHRQoL) is being increasingly recognized as an important health component. This study examined the association between denture quality and OHRQoL in individuals wearing removable partial dentures (RPDs). The study participants were 245 consecutive patients (mean age: 63.3 ± 8.7 yrs) at a university-based prosthodontic clinic who wore RPDs for more than one month. RPD quality and OHRQoL were determined by means of a 100-mm visual analog scale (VAS) and the 49-item Oral Health Impact Profile-Japanese version (OHIP-J49), respectively. Linear regression analysis between RPD quality and OHRQoL revealed that a 10-mm VAS increase in RPD quality rating was related to −2.8 OHIP-J49 units (95% confidence interval: −4.5 to −1.1, p = 0.001), which represents an improvement in OHRQoL. The results suggest that RPD quality influences individuals’ OHRQoL to a clinically significant extent.

scholarly journals The Positive Effects of a Combined Program of Creative Dance and BrainDance on Health-Related Ouality of Life as Perceived by Primary School Students

2018 ◽  
Vol 79 (1) ◽  
pp. 42-52 ◽  
Author(s):  
Olga Theocharidou ◽  
Georgios Lykesas ◽  
Ioannis Giossos ◽  
Dimitrios Chatzopoulos ◽  
Maria Koutsouba
Keyword(s):  
Physical Education ◽  
Primary School ◽  
Educational Intervention ◽  
Small Sample ◽  
Primary School Students ◽  
School Students ◽  
Creative Dance ◽  
Positive Effects ◽  
Health Related ◽  
The Impact

Abstract The combination of Creative Dance and BrainDance within the context of physical education could be a promising innovation. This combined program can be implemented in primary school to help students achieve a better and more holistic assessment of their Health-Related Quality of Life (HRQoL), covering aspects of physical, emotional, social, and mental functioning and well-being. The aim of this study was to investigate the impact that a combined Creative Dance and BrainDance program based on the Laban Theory of Movement Analysis has on HRQoL perceptions of primary school students when this program is implemented within the context of the physical education curriculum in primary school. For this purpose, an eight-week educational intervention was designed combining Creative Dance and BrainDance into one single program. The survey sample consisted of 32 fifth- and sixth-grade primary school students. The Kidscreen-52 questionnaire was used to collect data. Data analysis was performed with the use of descriptive statistical indices and mixed analysis of variance (ANOVA). Although the results showed no differences between the beginning and end of the educational intervention, a fact that might be due to the small sample and the time of the implementation of the program (limited to 8 weeks), its implementation produced very good results with regard to improvisation, body control, balance, and coordination, as well as kinaesthetic awareness and musical rhythmic skills. Creative Dance and BrainDance promote imagination, creativity, improvisation, and self-esteem in general, particularly in primary school students..

scholarly journals The Preventable Risk Integrated ModEl and Its Use to Estimate the Health Impact of Public Health Policy Scenarios

Scientifica ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-21 ◽  
Author(s):  
Peter Scarborough ◽  
Richard A. Harrington ◽  
Anja Mizdrak ◽  
Lijuan Marissa Zhou ◽  
Aiden Doherty
Keyword(s):  
Public Health ◽  
Web Application ◽  
Population Level ◽  
Health Impact ◽  
Integrated Model ◽  
Noncommunicable Disease ◽  
Small Samples ◽  
Low Carbon ◽  
Health Related ◽  
The Impact

Noncommunicable disease (NCD) scenario models are an essential part of the public health toolkit, allowing for an estimate of the health impact of population-level interventions that are not amenable to assessment by standard epidemiological study designs (e.g., health-related food taxes and physical infrastructure projects) and extrapolating results from small samples to the whole population. The PRIME (Preventable Risk Integrated ModEl) is an openly available NCD scenario model that estimates the effect of population-level changes in diet, physical activity, and alcohol and tobacco consumption on NCD mortality. The structure and methods employed in the PRIME are described here in detail, including the development of open source code that will support a PRIME web application to be launched in 2015. This paper reviews scenario results from eleven papers that have used the PRIME, including estimates of the impact of achieving government recommendations for healthy diets, health-related food taxes and subsidies, and low-carbon diets. Future challenges for NCD scenario modelling, including the need for more comparisons between models and the improvement of future prediction of NCD rates, are also discussed.

Procedures for the Analysis of Differential Item Functioning (DIF) for Small Sample Sizes

2005 ◽  
Vol 28 (3) ◽  
pp. 283-294 ◽  
Author(s):  
Jin-Shei Lai ◽  
Jeanne Teresi ◽  
Richard Gershon
Keyword(s):  
Differential Item Functioning ◽  
Small Sample ◽  
Small Samples ◽  
Sample Sizes ◽  
Education And Health ◽  
Item Functioning ◽  
Related Quality ◽  
Health Related ◽  
Small Sample Sizes

An item with differential item functioning (DIF) displays different statistical properties, conditional on a matching variable. The presence of DIF in measures can invalidate the conclusions of medical outcome studies. Numerous approaches have been developed to examine DIF in many areas, including education and health-related quality of life. There is little consensus in the research community regarding selection of one best method, and most methods require large sample sizes. This article describes some approaches to examine DIF with small samples (e.g., less than 200).

scholarly journals Integrating multi-omics data with deep learning for predicting cancer prognosis

2019 ◽  
Author(s):  
Hua Chai ◽  
Xiang Zhou ◽  
Zifeng Cui ◽  
Jiahua Rao ◽  
Zheng Hu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Small Sample ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Omics Data ◽  
Hazards Model ◽  
Small Sample Sizes ◽  
The Impact

AbstractMotivationAccurately predicting cancer prognosis is necessary to choose precise strategies of treatment for patients. One of effective approaches in the prediction is the integration of multi-omics data, which reduces the impact of noise within single omics data. However, integrating multi-omics data brings large number of redundant variables and relative small sample sizes. In this study, we employed Autoencoder networks to extract important features that were then input to the proportional hazards model to predict the cancer prognosis.ResultsThe method was applied to 12 common cancers from the Cancer Genome Atlas. The results show that the multi-omics averagely improves 4.1% C-index for prognosis prediction over single mRNA data, and our method outperforms previous approaches by at least 7.4%. A comparison of the contribution of single omics data show that mRNA contributes the most, followed by the DNA methylation, miRNA, and the copy number variation. In the case study for differential gene expression analysis, we identified 161 differentially expressed genes in the cervical cancer, among which 77 genes (65.8%) have been proven to be associated with cancer. In addition, we performed the cross-cancer test where the model trained on one cancer was used to predict the prognosis of another cancer, and found 23 pairs of cancers have a C-index larger than 0.5, with the largest value of 0.68. Thus, this study has provided a deep learning framework to effectively integrate multiple omics data to predict cancer prognosis.

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