scholarly journals Decision letter: Assessing the danger of self-sustained HIV epidemics in heterosexuals by population based phylogenetic cluster analysis

2017 ◽  
Keyword(s):  
Cluster Analysis ◽  
Population Based ◽  
Phylogenetic Cluster ◽  
Phylogenetic Cluster Analysis

#65: Characterization of Resistance Patterns Among Isolates of E. coli and Klebsiella sp. from Wastewater, and Clinical Samples in a Tertiary Care Children’s Hospital in Lima, Peru

2021 ◽  
Vol 10 (Supplement_1) ◽  
pp. S7-S7
Author(s):  
Carlos F Santillán ◽  
Pablo Tsukayama ◽  
Maritza Calderón ◽  
Camila Castillo ◽  
Janet Huancachoque
Keyword(s):  
Escherichia Coli ◽  
Cluster Analysis ◽  
Tertiary Care ◽  
Healthcare Personnel ◽  
Clinical Samples ◽  
Hospital Wastewater ◽  
Beta Lactamases ◽  
Phylogenetic Cluster ◽  
Phylogenetic Cluster Analysis ◽  
Esbl Producers

Abstract Background Environmental monitoring of enterobacteria in hospital wastewater could be a useful tool to understand the composition of the microbiota in patients, their visits, and healthcare personnel, but it also may be useful for monitoring antimicrobial resistance among healthcare-associated infections in hospitalized patients. The aim of this study was to characterize and describe the phenotypic and genotypic antimicrobial resistance of Escherichia coli and Klebsiella sp. strains from wastewater and from clinical isolates in a tertiary care children’s hospital in Lima, Perú. Methods We systematically collected 70 isolates of Escherichia coli and Klebsiella sp. from wastewater and 24 isolates of the same enterobacteria from blood and urine cultures at Instituto Nacional de Salud del Niño San Borja (INSN-SB) in Lima from December 2018 to May 2019. Susceptibility profiles were evaluated following CLSI criteria. We used the Jarlier method for the detection of extended-spectrum beta-lactamases (ESBL). For detection of AmpC beta-lactamases, we used discs of cefoxitin, ceftazidime, and ceftriaxone combined with cloxacillin and cefotaxime. For the detection of carbapenemase production, we used EDTA and phenylboronic acid inhibitors between meropenem and imipenem disks. We performed genomic sequencing for the detection of resistance genes and to perform a phylogenetic cluster analysis. Results We collected a total of 94 isolates (70 from wastewater and 24 from clinical samples). Among the total isolates, 19 (20.2%) were ESBL producers. The frequency of ESBL producers in wastewater was 7.1% (5/24), whereas the frequency of ESBL producers in clinical samples was 58.3% (14/70). The most frequent resistance genes were tet (variant 34 and A) and blaTEM-1. The frequency of tet(34) and tet(A) were 10% and 7%, respectively, in isolates from wastewater, whereas the frequency of these genes were 0% and 6%, respectively, in clinical isolates. The gene blaCTX-M-15 was present in isolates from wastewater (1%) and clinical samples (2%). Phylogenetic cluster analysis found no similarities between isolates from wastewater and to those from clinical samples, suggesting that the population of these enterobacteria were different in wastewater compared with clinical samples. Conclusions Enterobacteria from hospital wastewater may not reflect the profile of infections caused by these microorganisms. However, they may reflect the microbiological microbiota among patients, their visits, and hospital healthcare personnel. Further studies that compare the phenotypic and genotypic characteristics among isolates from wastewater and the enteric microbiota from these individuals would be necessary to assess this hypothesis.

scholarly journals Interactions between life expectancy and the incidence and mortality rates of cancer in China: a population-based cluster analysis

2018 ◽  
Vol 38 (1) ◽  
pp. 44 ◽  
Author(s):  
Xiuying Gu ◽  
Rongshou Zheng ◽  
Changfa Xia ◽  
Hongmei Zeng ◽  
Siwei Zhang ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Life Expectancy ◽  
Mortality Rates ◽  
Population Based ◽  
Incidence And Mortality

scholarly journals A Pilot Exploratory Study to Form Subgroups Using Cluster Analysis of Family Needs Survey Scores for Providing Tailored Support to Parents Caring for a Population-Based Sample of 5-Year-Old Children with Developmental Concerns

2022 ◽  
Vol 19 (2) ◽  
pp. 744
Author(s):  
Motohide Miyahara
Keyword(s):  
Cluster Analysis ◽  
Pilot Study ◽  
Support Groups ◽  
Hierarchical Clustering ◽  
Missing Values ◽  
Population Based ◽  
Small Scale ◽  
Second Phase ◽  
Family Needs ◽  
Need For Information

In a population-based developmental screening program, healthcare providers face a practical problem with respect to the formation of groups to efficiently address the needs of the parents whose children are screened positive. This small-scale pilot study explored the usefulness of cluster analysis to form type-specific support groups based on the Family Needs Survey (FNS) scores. All parents (N = 68), who accompanied their 5-year-old children to appointments for formal assessment and diagnostic interviews in the second phase of screening, completed the FNS as part of a developmental questionnaire package. The FNS scores of a full dataset (N = 55) without missing values were subjected to hierarchical and K-means cluster analyses. As the final solution, hierarchical clustering with a three-cluster solution was selected over K-means clustering because the hierarchical clustering solution produced three clusters that were similar in size and meaningful in each profile pattern: Cluster 1—high need for information and professional support (N = 20); cluster 2—moderate need for information support (N = 16); cluster 3—high need for information and moderate need for other support (N = 19). The range of cluster sizes was appropriate for managing and providing tailored services and support for each group. Thus, this pilot study demonstrated the utility of cluster analysis to classify parents into support groups, according to their needs.

scholarly journals Personal values in adolescence and their associations with metabolic biomarkers in adulthood: a population-based study in Japan

2020 ◽  
Author(s):  
Natsu Sasaki ◽  
Kazuhiro Watanabe ◽  
Norito Kawakami
Keyword(s):  
Cluster Analysis ◽  
Waist Circumference ◽  
Personal Values ◽  
Linear Regression Analysis ◽  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Multiple Linear Regression Analysis ◽  
Population Based ◽  
Z Score ◽  
Self Reporting Questionnaire

Abstract Background: Personal values, which are formed in early life, can have an impact on the health outcome later in life. Objective: The aim of this study is to investigate the relationship between personal values in adolescence and bio-indicators related to metabolic syndrome (MetS) in adulthood.Participant and Methods: The longitudinal data was used from the Japanese Study on Stratification, Health, Income, and Neighborhood (J-SHINE) in 2012 and 2017. Personal values in adolescence were retrospectively obtained in 2017 from a self-reporting questionnaire, composed of value priorities and commitment to the values. Venous samples were collected in 2012 for low and high-density lipoprotein (LDL, HDL) cholesterol and hemoglobin A1c (HbA1c). Body mass index (BMI), waist circumference and systolic and diastolic blood pressure (SBP, DBP) were also measured. The associations of each variable were examined by partial correlation analysis. In addition, multiple linear regression analysis was conducted to examine overall associations between personal values and the sum of standardized scores (Z-score) of the biomarkers as a proxy of MetS. Furthermore, cluster analysis was conducted to identify groups of the participants who have some specific values and to examine their associations with the Z-score. Results: The total population (n=668) included 261 men and 407 women. Among men, the personal value priority of “Having influence on society” was associated with high HDL cholesterol (partial r=0.13, p=0.032) and “Cherishing familiar people” with low waist circumference (r=-0.129, p=0.049), low SBP, and high DBP (r=-0.135, p=0.039; r=0.134, p=0.041). In women, “Not bothering others” was associated with high SBP and low DBP (r=0.125, p=0.015; r=-0.123, p=0.017). "Economically succeeding" were associated with worse outcome (β=0.162, p=0.042). In the cluster analysis, both in men and women, the cluster which had highest openness to change value; “Having and keeping a belief”, “Exploring what you were interested in” and “Actively challenging” with the highest commitment showed worst proxy outcomes although there were no significant differences.Conclusions: Although some significant associations were found between personal values in adolescence and MetS-related markers in adulthood, overall associations were not strong. Culturally prevailing values were likely to be associated with a good outcome of metabolic health.

scholarly journals Geographic atrophy phenotype identification by cluster analysis

2017 ◽  
Vol 102 (3) ◽  
pp. 388-392 ◽  
Author(s):  
Jordi Monés ◽  
Marc Biarnés
Keyword(s):  
Growth Rate ◽  
Cluster Analysis ◽  
Slow Growth ◽  
Fundus Autofluorescence ◽  
Population Based ◽  
Geographic Atrophy ◽  
Age Related Macular Degeneration ◽  
Qualitative Description ◽  
Age Related ◽  
Soft Drusen

Background/aimsTo identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis.MethodsThis was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared.ResultsData were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm2/year, respectively, p=0.0005).ConclusionCluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern.

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