scholarly journals Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

2015 ◽  
Vol 143 (16) ◽  
pp. 3538-3545 ◽  
Author(s):  
M. TREMBLAY ◽  
J. S. DAHM ◽  
C. N. WAMAE ◽  
W. A. DE GLANVILLE ◽  
E. M. FÈVRE ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Linear Models ◽  
Principal Component ◽  
Large Datasets ◽  
Single Step ◽  
Large Dataset ◽  
Western Kenya ◽  
The People ◽  
Increased Risk ◽  
Using Data

SUMMARYLarge datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization.

scholarly journals Emerging issues in genomic selection

2021 ◽  
Author(s):  
I Misztal ◽  
I Aguilar ◽  
D Lourenco ◽  
L Ma ◽  
J Steibel ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Sparse Matrices ◽  
Large Datasets ◽  
Single Step ◽  
Genomic Information ◽  
Long Term Effects ◽  
Additive Variance ◽  
Recent Developments ◽  
Emerging Issues ◽  
Using Data

Abstract Genomic selection is now practiced successfully across many species. However, many questions remain such as long-term effects, estimations of genomic parameters, robustness of GWAS with small and large datasets, and stability of genomic predictions. This study summarizes presentations from at the 2020 ASAS symposium. The focus of many studies until now is on linkage disequilibrium (LD) between two loci. Ignoring higher level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWAS studies using small genomic datasets frequently find many marker-trait associations whereas studies using much bigger datasets find only a few. Most current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit computation of p-values from GBLUP, where models can be arbitrarily complex but restricted to genotyped animals only, and to single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as one SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. While many issues in genomic selection have been solved, many new issues that require additional research continue to surface.

scholarly journals Laws Mandating Coprescription of Naloxone and Their Impact on Naloxone Prescription in Five US States, 2014–2018

2020 ◽  
Vol 110 (6) ◽  
pp. 881-887 ◽  
Author(s):  
Traci C. Green ◽  
Corey Davis ◽  
Ziming Xuan ◽  
Alexander Y. Walley ◽  
Jeffrey Bratberg
Keyword(s):  
Rhode Island ◽  
Linear Models ◽  
Us States ◽  
Standing Order ◽  
Life Saving ◽  
Increased Risk ◽  
Before And After ◽  
Using Data ◽  
Pharmacy Chain

Objectives. To examine early impacts of laws that require naloxone to be prescribed to patients at increased overdose risk. Methods. Using data from 2014 to 2018 from a large pharmacy chain, CVS Pharmacy, we examined the effects of naloxone-prescribing mandates 90 days before and after they took effect in Arizona, Florida, Rhode Island, Vermont, and Virginia. We compared the number of naloxone doses initiated directly by prescribers and by pharmacy standing order, prescriber specialty, pharmacies dispensing, and payor type by applying linear models and the χ2 test. Results. Naloxone-prescribing mandates increased pharmacy naloxone provision 255% from 90 days before to after implementation. This approach appeared to engage more prescribers (1028 before to 4285 after), complement ongoing naloxone provision under pharmacy standing orders, expand geographic reach (from 40% to 80% of pharmacies dispensing), and broaden the naloxone payor mix in 4 (P < .05) of 5 states. Conclusions. Mandating the prescribing of naloxone quickly expands access to this life-saving medication for more people in more places. Other states should consider mandating the coprescription of naloxone to individuals at increased risk of overdose.

MODEL UNTUK MENILAI KESIAPAN PEMDA “DKI JAKARTA” DALAM PENGEMBANGAN WILAYAH BERBASIS DUNIA USAHA

2012 ◽  
Vol 11 (1) ◽  
Author(s):  
Puguh Suharso
Keyword(s):  
Data Gathering ◽  
Business Environment ◽  
Standard Of Living ◽  
Achievement Level ◽  
Global Competitiveness ◽  
The People ◽  
Frame Work ◽  
Using Data ◽  
Level Of Effort ◽  
Research Analysis

Globalisation era is surely passed on and to lead the people of the world into social interactive one another and also economical competitiveness. How far is DKI Jakarta Government preparing to be up against the global competitiveness in the frame-work to manifest improving the standard of living like advanced of society. There are some of indicators to be used as well as criterion to measure an achievement level of effort to be advanced of society, i.e infrastructure which needed by entrepreneur like : permission, taxation, laboract, traffic road, customs and harbor, publics infrastructure servicing, landuse, security condition, business financial access, and business environment condition. It was the research analysis be done by using data gathering from entrepreneur opinion at the operational area. The aim of research analysis is to measure how level of each indicator value has DKI Jakarta Government prepared to be up against the global competitiveness ? The research conclusion says that : DKI Jakarta Government has well enough prepared to be up against the global competitiveness. The weakness indicator is just taxation because its category included in bad (goodless) while the other indicators are well enough. The measuring parameters due to weakness taxationare time necessity for servicing to arrange tax, amount and various of region retribution, amount and various of region tax, and clarity of tax arrangement prucedure.

scholarly journals Country of Origin Effects on the Average Annual Values of NHL Player Contracts

2019 ◽  
Vol 7 (2) ◽  
pp. 24
Author(s):  
Aju J. Fenn ◽  
Lucas Gerdes ◽  
Samuel Rothstein
Keyword(s):  
Quantile Regression ◽  
Fixed Effects ◽  
Country Of Origin ◽  
Large Datasets ◽  
National Hockey League ◽  
Dummy Variables ◽  
Country Of Origin Effects ◽  
Performance Statistics ◽  
Career Performance ◽  
Using Data

Using data from 2005 to 2016, this paper examines if players in the National Hockey League (NHL) are being paid a positive differential for their services due to the competition from the Kontinental Hockey League (KHL) and the Swedish Hockey League (SHL). In order to control for performance, we use two different large datasets, (N = 4046) and (N = 1717). In keeping with the existing literature, we use lagged performance statistics and dummy variables to control for the type of NHL contract. The first dataset contains lagged career performance statistics, while the performance statistics are based on the statistics generated during the years under the player’s previous contract. Fixed effects least squares (FELS) and quantile regression results suggest that player production statistics, contract status, and country of origin are significant determinants of NHL player salaries.

Sibling Alcohol Use Disorder Is Associated With Increased Risk for Suicide Attempt

2021 ◽  
pp. 216770262110250
Author(s):  
Mallory E. Stephenson ◽  
Sara Larsson Lönn ◽  
Jessica E. Salvatore ◽  
Jan Sundquist ◽  
Kenneth S. Kendler ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Suicide Attempt ◽  
Alcohol Use Disorder ◽  
Cox Regression ◽  
Population Based ◽  
Swedish Population ◽  
Sibling Pairs ◽  
Increased Risk ◽  
Using Data ◽  
Shared Genetic

The association between having a sibling diagnosed with alcohol use disorder (AUD) and risk for suicide attempt may be attributable to shared genetic liability between AUD and suicidal behavior, effects of environmental exposure to a sibling’s AUD, or both. To distinguish between these alternatives, we conducted a series of Cox regression models using data derived from Swedish population-based registers with national coverage. Among full sibling pairs (656,807 males and 607,096 females), we found that, even after we accounted for the proband’s AUD status, the proband’s risk for suicide attempt was significantly elevated when the proband’s sibling was affected by AUD. Furthermore, the proband’s risk for suicide attempt was consistently higher when the sibling’s AUD registration had occurred more recently. Our findings provide evidence for exposure to sibling AUD as an environmental risk factor for suicide attempt and suggest that clinical outreach may be warranted following a sibling’s diagnosis with AUD.

scholarly journals Comparing Patient Characteristics, Clinical Outcomes, and Biomarkers of Severe Asthma Patients in Taiwan

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 764
Author(s):  
Shih-Lung Cheng ◽  
Kuo-Chin Chiu ◽  
Hsin-Kuo Ko ◽  
Diahn-Warng Perng ◽  
Hao-Chien Wang ◽  
...  
Keyword(s):  
Severe Asthma ◽  
Clinical Characteristics ◽  
Linear Models ◽  
Patient Characteristics ◽  
Emergency Department Visits ◽  
Receiver Operating Characteristic Curves ◽  
Increased Risk ◽  
Significant Difference ◽  
Asthma Patients ◽  
Patients At Risk

Purpose: To understand the association between biomarkers and exacerbations of severe asthma in adult patients in Taiwan. Materials and Methods: Demographic, clinical characteristics and biomarkers were retrospectively collected from the medical charts of severe asthma patients in six hospitals in Taiwan. Exacerbations were defined as those requiring asthma-specific emergency department visits/hospitalizations, or systemic steroids. Enrolled patients were divided into: (1) those with no exacerbations (non-exacerbators) and (2) those with one or more exacerbations (exacerbators). Receiver operating characteristic curves were used to determine the optimal cut-off value for biomarkers. Generalized linear models evaluated the association between exacerbation and biomarkers. Results: 132 patients were enrolled in the study with 80 non-exacerbators and 52 exacerbators. There was no significant difference in demographic and clinical characteristics between the two groups. Exacerbators had significantly higher eosinophils (EOS) counts (367.8 ± 357.18 vs. 210.05 ± 175.24, p = 0.0043) compared to non-exacerbators. The optimal cut-off values were 292 for EOS counts and 19 for the Fractional exhaled Nitric Oxide (FeNO) measure. Patients with an EOS count ≥ 300 (RR = 1.88; 95% CI, 1.26–2.81; p = 0.002) or FeNO measure ≥ 20 (RR = 2.10; 95% CI, 1.05–4.18; p = 0.0356) had a significantly higher risk of exacerbation. Moreover, patients with both an EOS count ≥ 300 and FeNO measure ≥ 20 had a significantly higher risk of exacerbation than those with lower EOS count or lower FeNO measure (RR = 2.16; 95% CI, 1.47–3.18; p = < 0.0001). Conclusions: Higher EOS counts and FeNO measures were associated with increased risk of exacerbation. These biomarkers may help physicians identify patients at risk of exacerbations and personalize treatment for asthma patients.

Prognostic role of Krebs von den Lungen-6 (KL-6) measurement in idiopathic pulmonary fibrosis: a systematic review and meta-analysis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Elena Aloisio ◽  
Federica Braga ◽  
Chiara Puricelli ◽  
Mauro Panteghini
Keyword(s):  
Systematic Review ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Binary Data ◽  
Meta Analysis ◽  
Mortality Prediction ◽  
Asian Populations ◽  
Increased Risk ◽  
Using Data ◽  
Patient Prognosis

Abstract Objectives Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial disease with limited therapeutic options. The measurement of Krebs von den Lungen-6 (KL-6) glycoprotein has been proposed for evaluating the risk of IPF progression and predicting patient prognosis, but the robustness of available evidence is unclear. Methods We searched Medline and Embase databases for peer-reviewed literature from inception to April 2020. Original articles investigating KL-6 as prognostic marker for IPF were retrieved. Considered outcomes were the risk of developing acute exacerbation (AE) and patient survival. Meta-analysis of selected studies was conducted, and quantitative data were uniformed as odds ratio (OR) or hazard ratio (HR) estimates, with corresponding 95% confidence intervals (CI). Results Twenty-six studies were included in the systematic review and 14 were finally meta-analysed. For AE development, the pooled OR (seven studies) for KL-6 was 2.72 (CI 1.22–6.06; p=0.015). However, a high degree of heterogeneity (I2=85.6%) was found among selected studies. Using data from three studies reporting binary data, a pooled sensitivity of 72% (CI 60–82%) and a specificity of 60% (CI 52–68%) were found for KL-6 measurement in detecting insurgence of AE in IPF patients. Pooled HR (seven studies) for mortality prediction was 1.009 (CI 0.983–1.036; p=0.505). Conclusions Although our meta-analysis suggested that IPF patients with increased KL-6 concentrations had a significant increased risk of developing AE, the detection power of the evaluated biomarker is limited. Furthermore, no relationship between biomarker concentrations and mortality was found. Caution is also needed when extending obtained results to non-Asian populations.

scholarly journals A Conceptual Framework Integrating “Building Back Better” and Post-Earthquake Needs for Recovery and Reconstruction

2021 ◽  
Vol 13 (10) ◽  
pp. 5608
Author(s):  
Manjiang Shi ◽  
Qi Cao ◽  
Baisong Ran ◽  
Lanyan Wei
Keyword(s):  
Disaster Recovery ◽  
Social Process ◽  
Principal Component ◽  
Assessment Method ◽  
International Consensus ◽  
Long Term Stability ◽  
The People ◽  
Policy Guidance ◽  
The Impact ◽  
Post Disaster

Global disasters due to earthquakes have become more frequent and intense. Consequently, post-disaster recovery and reconstruction has become the new normal in the social process. Through post-disaster reconstruction, risks can be effectively reduced, resilience can be improved, and long-term stability can be achieved. However, there is a gap between the impact of post-earthquake reconstruction and the needs of the people in the disaster area. Based on the international consensus of “building back better” (BBB) and a post-disaster needs assessment method, this paper proposes a new (N-BBB) conceptual model to empirically analyze recovery after the Changning Ms 6.0 earthquake in Sichuan Province, China. The reliability of the model was verified through factor analysis. The main observations were as follows. People’s needs focus on short-term life and production recovery during post-earthquake recovery and reconstruction. Because of disparities in families, occupations, and communities, differences are observed in the reconstruction time sequence and communities. Through principal component analysis, we found that the N-BBB model constructed in this study could provide strong policy guidance in post-disaster recovery and reconstruction after the Changning Ms 6.0 earthquake, effectively coordinate the “top-down” and “bottom-up” models, and meet the diversified needs of such recovery and reconstruction.

scholarly journals Genotyping cognate Plasmodium falciparum in humans and mosquitoes to estimate onward transmission of asymptomatic infections

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kelsey M. Sumner ◽  
Elizabeth Freedman ◽  
Lucy Abel ◽  
Andrew Obala ◽  
Brian W. Pence ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Odds Ratio ◽  
Asymptomatic Malaria ◽  
Major Contributor ◽  
Western Kenya ◽  
High Transmission ◽  
Transmission Reduction ◽  
Asymptomatic Infections ◽  
Infection Types ◽  
Natural Settings

AbstractMalaria control may be enhanced by targeting reservoirs of Plasmodium falciparum transmission. One putative reservoir is asymptomatic malaria infections and the scale of their contribution to transmission in natural settings is not known. We assess the contribution of asymptomatic malaria to onward transmission using a 14-month longitudinal cohort of 239 participants in a high transmission site in Western Kenya. We identify P. falciparum in asymptomatically- and symptomatically-infected participants and naturally-fed mosquitoes from their households, genotype all parasites using deep sequencing of the parasite genes pfama1 and pfcsp, and use haplotypes to infer participant-to-mosquito transmission through a probabilistic model. In 1,242 infections (1,039 in people and 203 in mosquitoes), we observe 229 (pfcsp) and 348 (pfama1) unique parasite haplotypes. Using these to link human and mosquito infections, compared with symptomatic infections, asymptomatic infections more than double the odds of transmission to a mosquito among people with both infection types (Odds Ratio: 2.56; 95% Confidence Interval (CI): 1.36–4.81) and among all participants (OR 2.66; 95% CI: 2.05–3.47). Overall, 94.6% (95% CI: 93.1–95.8%) of mosquito infections likely resulted from asymptomatic infections. In high transmission areas, asymptomatic infections are the major contributor to mosquito infections and may be targeted as a component of transmission reduction.

scholarly journals Dietary patterns related to total mortality and cancer mortality in the United States

2021 ◽  
Author(s):  
Marcela R. Entwistle ◽  
Donald Schweizer ◽  
Ricardo Cisneros
Keyword(s):  
United States ◽  
Dietary Patterns ◽  
Cancer Mortality ◽  
Cox Regression ◽  
Total Mortality ◽  
Principal Component ◽  
The United States ◽  
Red Meat ◽  
Increased Risk ◽  
All Cause Mortality

Abstract Purpose This study investigated the association between dietary patterns, total mortality, and cancer mortality in the United States. Methods We identified the four major dietary patterns at baseline from 13,466 participants of the NHANES III cohort using principal component analysis (PCA). Dietary patterns were categorized into ‘prudent’ (fruits and vegetables), ‘western’ (red meat, sweets, pastries, oils), ‘traditional’ (red meat, legumes, potatoes, bread), and ‘fish and alcohol’. We estimated hazard ratios for total mortality, and cancer mortality using Cox regression models. Results A total of 4,963 deaths were documented after a mean follow-up of 19.59 years. Higher adherence to the ‘prudent’ pattern was associated with the lowest risk of total mortality (5th vs. 1st quintile HR 0.90, 95% CI 0.82–0.98), with evidence that all-cause mortality decreased as consumption of the pattern increased. No evidence was found that the ‘prudent’ pattern reduced cancer mortality. The ‘western’ and the ‘traditional’ patterns were associated with up to 22% and 16% increased risk for total mortality (5th vs. 1st quintile HR 1.22, 95% CI 1.11–1.34; and 5th vs. 1st quintile HR 1.16, 95% CI 1.06–1.27, respectively), and up to 33% and 15% increased risk for cancer mortality (5th vs. 1st quintile HR 1.33, 95% CI 1.10–1.62; and 5th vs. 1st quintile HR 1.15, 95% CI 1.06–1.24, respectively). The associations between adherence to the ‘fish and alcohol’ pattern and total mortality, and cancer mortality were not statistically significant. Conclusion Higher adherence to the ‘prudent’ diet decreased the risk of all-cause mortality but did not affect cancer mortality. Greater adherence to the ‘western’ and ‘traditional’ diet increased the risk of total mortality and mortality due to cancer.

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