On sample size estimation of the arithmetic mean of a lognormal distribution with and without type i

This article presents several formulas to approximate the required sample size to estimate the arithmetic mean of a lognormal distribution with desired accuracy and confidence under and without the presence of type I censoring to the left. We present tables of exact sample sizes which are based on Land's exact confidence interval of the lognormal mean. Monte Cario estimates of coverage probabilities show the appropriateness of these exact proposed sample sizes at 95% confidence level

Factors associated with HIV and syphilis screenings among pregnant women at first antenatal visit in Lusaka, Zambia

Objectives: To identify characteristics associated with obtaining HIV and syphilis screenings of pregnant women attending a first antenatal visit in Lusaka, Zambia. Results: Among 18,231 participants from April 2015 to January 2016, 95% obtained HIV screening, 29% obtained syphilis screening, and 4% did not obtain antenatal HIV or syphilis screenings. Divorced/separated women were associated with a moderate decrease in prevalence of obtaining HIV (adjusted prevalence ratio (aPR) 0.88, 95% confidence interval (95% CI) 0.82, 0.95) and syphilis (aPR 0.51, 95% CI 0.27, 0.96) screenings compared to married women. Women with previous pregnancies were associated with a slight decrease in prevalence of obtaining HIV screening (aPR 0.97, 95% CI 0.95, 0.99) compared to women without previous pregnancy. Older women ≥ 35 years were associated with a slight decrease in prevalence of obtaining HIV screening (aPR 0.96, 95% CI 0.92, 0.99) compared to younger women. The statistically significant differences were not of clinical relevance as defined by a proportional difference of 10 percent. Findings of this study show that a vast majority of pregnant women are obtaining HIV screenings but not syphilis screenings during first antenatal visit. Provision of antenatal HIV and syphilis screening at first visit is only weakly related to patient level factors.Fil: Davis, Rindcy. University of Tulane; Estados UnidosFil: Xiong, Xu. University of Tulane; Estados UnidosFil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Lefante, John. University of Tulane; Estados UnidosFil: Cafferata, Maria Luisa. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Mwenechanya, Musaku. University Teaching Hospital Lusaka; ZambiaFil: Mwanakalanga, Friday Habulembe. University Teaching Hospital Lusaka; ZambiaFil: Chomba, Elwyn. University Teaching Hospital Lusaka; ZambiaFil: Buekens, Pierre. University of Tulane; Estados Unido

Do personality traits affect productivity?:Evidence from the lab

While survey data supports a strong relationship between personality and labor market outcomes, the exact mechanisms behind this association remain unexplored. In this paper, we take advantage of a controlled laboratory set-up to explore whether this relationship operates through productivity. Using a real-e ort task, we analyse the impact of the Big Five personality traits on performance. We nd that more neurotic subjects perform worse, and that more conscientious individuals perform better. These ndings are in line with previous survey studies and suggest that at least part of the e ect of personality on labor market outcomes operates through individual productivity. In addition, we nd evidence that gender and university major a ect the impact of the Big Five personality traits on performance

Expanding Research Capacity in Sub-Saharan Africa Through Informatics, Bioinformatics, and Data Science Training Programs in Mali

Bioinformatics and data science research have boundless potential across Africa due to its high levels of genetic diversity and disproportionate burden of infectious diseases, including malaria, tuberculosis, HIV and AIDS, Ebola virus disease, and Lassa fever. This work lays out an incremental approach for reaching underserved countries in bioinformatics and data science research through a progression of capacity building, training, and research efforts. Two global health informatics training programs sponsored by the Fogarty International Center (FIC) were carried out at the University of Sciences, Techniques and Technologies of Bamako, Mali (USTTB) between 1999 and 2011. Together with capacity building efforts through the West Africa International Centers of Excellence in Malaria Research (ICEMR), this progress laid the groundwork for a bioinformatics and data science training program launched at USTTB as part of the Human Heredity and Health in Africa (H3Africa) initiative. Prior to the global health informatics training, its trainees published first or second authorship and third or higher authorship manuscripts at rates of 0.40 and 0.10 per year, respectively. Following the training, these rates increased to 0.70 and 1.23 per year, respectively, which was a statistically significant increase (p < 0.001). The bioinformatics and data science training program at USTTB commenced in 2017 focusing on student, faculty, and curriculum tiers of enhancement. The program’s sustainable measures included institutional support for core elements, university tuition and fees, resource sharing and coordination with local research projects and companion training programs, increased student and faculty publication rates, and increased research proposal submissions. Challenges reliance of high-speed bandwidth availability on short-term funding, lack of a discounted software portal for basic software applications, protracted application processes for United States visas, lack of industry job positions, and low publication rates in the areas of bioinformatics and data science. Long-term, incremental processes are necessary for engaging historically underserved countries in bioinformatics and data science research. The multi-tiered enhancement approach laid out here provides a platform for generating bioinformatics and data science technicians, teachers, researchers, and program managers. Increased literature on bioinformatics and data science training approaches and progress is needed to provide a framework for establishing benchmarks on the topics

Metabolic Syndrome and Acute Respiratory Distress Syndrome in Hospitalized Patients With COVID-19

Importance: Obesity, diabetes, and hypertension are common comorbidities in patients with severe COVID-19, yet little is known about the risk of acute respiratory distress syndrome (ARDS) or death in patients with COVID-19 and metabolic syndrome. Objective: To determine whether metabolic syndrome is associated with an increased risk of ARDS and death from COVID-19. Design, setting, and participants: This multicenter cohort study used data from the Society of Critical Care Medicine Discovery Viral Respiratory Illness Universal Study collected from 181 hospitals across 26 countries from February 15, 2020, to February 18, 2021. Outcomes were compared between patients with metabolic syndrome (defined as ≥3 of the following criteria: obesity, prediabetes or diabetes, hypertension, and dyslipidemia) and a control population without metabolic syndrome. Participants included adult patients hospitalized for COVID-19 during the study period who had a completed discharge status. Data were analyzed from February 22 to October 5, 2021. Exposures: Exposures were SARS-CoV-2 infection, metabolic syndrome, obesity, prediabetes or diabetes, hypertension, and/or dyslipidemia. Main outcomes and measures: The primary outcome was in-hospital mortality. Secondary outcomes included ARDS, intensive care unit (ICU) admission, need for invasive mechanical ventilation, and length of stay (LOS). Results: Among 46 441 patients hospitalized with COVID-19, 29 040 patients (mean [SD] age, 61.2 [17.8] years; 13 059 [45.0%] women and 15713 [54.1%] men; 6797 Black patients [23.4%], 5325 Hispanic patients [18.3%], and 16 507 White patients [57.8%]) met inclusion criteria. A total of 5069 patients (17.5%) with metabolic syndrome were compared with 23 971 control patients (82.5%) without metabolic syndrome. In adjusted analyses, metabolic syndrome was associated with increased risk of ICU admission (adjusted odds ratio [aOR], 1.32 [95% CI, 1.14-1.53]), invasive mechanical ventilation (aOR, 1.45 [95% CI, 1.28-1.65]), ARDS (aOR, 1.36 [95% CI, 1.12-1.66]), and mortality (aOR, 1.19 [95% CI, 1.08-1.31]) and prolonged hospital LOS (median [IQR], 8.0 [4.2-15.8] days vs 6.8 [3.4-13.0] days; P \u3c .001) and ICU LOS (median [IQR], 7.0 [2.8-15.0] days vs 6.4 [2.7-13.0] days; P \u3c .001). Each additional metabolic syndrome criterion was associated with increased risk of ARDS in an additive fashion (1 criterion: 1147 patients with ARDS [10.4%]; P = .83; 2 criteria: 1191 patients with ARDS [15.3%]; P \u3c .001; 3 criteria: 817 patients with ARDS [19.3%]; P \u3c .001; 4 criteria: 203 patients with ARDS [24.3%]; P \u3c .001). Conclusions and relevance: These findings suggest that metabolic syndrome was associated with increased risks of ARDS and death in patients hospitalized with COVID-19. The association with ARDS was cumulative for each metabolic syndrome criteria present

Some Convergence Problems On Heavy Tail Estimation Using Upper Order Statistics For Generalized Pareto and Lognormal Distributions

In some applications, the population characteristics of main interest can be found in the tails of the distribution function. The study of risk of extreme events will lead to the use of probability distributions and the scenarios that correspond to the tail of these distributions. Considering two approaches: parametric and nonparametric, the research emphasizes the assessment of distribution tails, assuming that underlying distributions are heavy tailed. Two heavy tailed distributions are considered: Generalized Pareto and Lognormal. The Maximum likelihood estimation method, using the complete sample, and using only the upper order statistics provide estimators of the parameters. Measures of Bias and Mean Squared Error of the estimators of the parameters, and the Conditional Mean Exceedence Functions of the distributions, are generated. The methodology for estimating population parameters, has potential applications in financial markets, quality control, assurance portfolios, monitoring of residual discharges, medical applications, design of environmental policies, or calibration and adjustment of processes and equipment. The main idea is to present, and analyze the methods used for the estimation, and some convergence problems when these two distribution functions are used in generating scenarios

Clinical pharmacist team-based care in a safety net medical home: facilitators and barriers to chronic care management

Collaborative care models incorporating pharmacists have been shown to improve quality of care for patients with hypertension and/or diabetes. Little is known about how to integrate such services outside of clinical trials. The authors implemented a 22-month observational study to evaluate pharmacy collaborative care for hypertension and diabetes in a safety net medical home that incorporated population risk stratification, clinical decision support, and medication dose adjustment protocols. Patients in the pharmacy group saw their primary care provider (PCP) more often and had higher baseline systolic blood pressure (SBP) and diastolic blood pressure (DBP) and A1c levels compared to patients who only received care from their PCPs. There were no significant differences in the proportion of patients achieving treatment goals (SB

Biochemical and molecular characteristics among infants with abnormal newborn screen for very-long-chain acyl-CoA dehydrogenase deficiency: A single center experience

Objective: To define the biochemical and molecular characteristics and diagnostic outcomes of a large US cohort of VLCAD deficiency positive cases as detected by newborn screening (NBS) with MS:MS. This relatively common disorder of fatty acid oxidation is screened for in every state in America and often results in extensive testing of multiple samples to arrive at a diagnostic conclusion. Materials and methods: We compared NBS dried blood spot (DBS) acylcarnitine profile (ACP) C14, C14:1, C14:2, C14:1/C12:1 ratio and plasma C14, C14:1, C14:2, C14:1/C12:1, C14:1/C16 and C14:1/C2 ratios among true positive and false positive cases. Results of VLCAD enzyme analysis, molecular testing and fibroblast fatty acid oxidation probe assay were analyzed. Results: The presence of compound heterozygous or homozygous pathogenic variants, along with elevations of C14, C14:1 and C14:1/C12:1 ratio, identified 19 VLCAD deficiency cases. All were asymptomatic at most recent follow-up visits. The C14:1/C12:1 ratio in NBS-DBS ACP and plasma acylcarnitine profiles at follow-up (follow-up plasma ACP), is the most useful marker to differentiate between true and false positive cases. Among all cases with molecular analysis data available, approximately 56.7% had a single pathogenic mutation. Lymphocyte enzyme analysis (n = 61) was uninformative in 23% of cases studied. Conclusion: VLCAD deficiency NBS by MS:MS is highly effective at identifying asymptomatic affected infants. Our cohort showed that elevation of C14:1/C12:1, in both NBS DBS and plasma ACP, was informative in discriminating affected from unaffected individuals and contributes to improve the accuracy of confirmatory testing of infants with presumptive positive for VLCAD deficiency

Respiratory Health Effects Associated with Restoration Work in Post-Hurricane Katrina New Orleans

Background. This study examines prevalence of respiratory conditions in New Orleans-area restoration workers after Hurricane Katrina. Methods. Between 2007 and 2010, spirometry and respiratory health and occupational questionnaire were administered to 791 New Orleans-area adults who mostly worked in the building construction and maintenance trades or custodial services. The associations between restoration work hours and lung function and prevalence of respiratory symptoms were examined by multiple linear regression, , or multiple logistic regression. Results. 74% of participants performed post-Katrina restoration work (median time: 620 hours). Symptoms reported include episodes of transient fever/cough (29%), sinus symptoms (48%), pneumonia (3.7%), and new onset asthma (4.5%). Prevalence rate ratios for post-Katrina sinus symptoms (PRR = 1.3; CI: 1.1, 1.7) and fever and cough (PRR = 1.7; CI: 1.3, 2.4) were significantly elevated overall for those who did restoration work and prevalence increased with restoration work hours. Prevalence rate ratios with restoration work were also elevated for new onset asthma (PRR = 2.2; CI: 0.8, 6.2) and pneumonia (PRR = 1.3; CI: 0.5, 3.2) but were not statistically significant. Overall, lung function was slightly depressed but was not significantly different between those with and without restoration work exposure. Conclusions. Post-Katrina restoration work is associated with moderate adverse effects on respiratory health, including sinusitis and toxic pneumonitis