A case-control study of occupational risk factors for pancreatic cancer in poultry plant workers: a random forest approach.

BACKGROUND: Poultry plant workers are exposed to chemical carcinogens and oncogenic viruses in their work environment. Our objective was to identify jobs and workplaces related to poultries that could increase the pancreatic cancer risk. METHODS: We conducted a case-control study within a defined cohort of poultry workers. We used a random forest algorithm to identify features that could increase pancreatic cancer in the poultry plant workers. RESULTS: The mean age of participants was 59.49 years. The majority of the study participants were females (51.30%) and Whites (71.0%). The following workplaces and job tasks had an association with increased pancreatic cancer mortality: working in chicken and turkey plants, working in plants where food products were processed and canned, working in a place where poultry and animals where present, working as a hunter for game animals, working as a veterinarian in places had animals and different poultry birds, working in pet houses and working in places where birds were handled and killed. The accuracy and the area under the curve of the model were 72.3 and 71.50%. CONCLUSION: Chicken and turkey plant workers could be at risk for pancreatic cancer mortality. We need to confirm the results in future studies.

The Relationship between Insulin Resistance and Spatial QRS-T Angle in American Adults.

BACKGROUND: Insulin resistance can impair the electrical conductivity of the heart. Spatial QRS-T axis reflects ventricular depolarization and repolarization. The relationship between insulin resistance and spatial QRS-T angle has not been examined in the general population. OBJECTIVE: We examined the relationship between insulin resistance and spatial QRS-T angle in an American population-based sample. METHODS: We used data collected from the National Health and Nutrition Examination Survey III (NHANES III), and a directed acyclic graph to select confounders. We fitted logistic regression models and adjusted for the effect of the confounders. We stratified all analyses by gender. RESULTS: The odds ratios (OR) of the abnormal QRS-T angle and their 95% confidence intervals (CI) for females and males were 1.08 (1.03-1.16) and 1.03 (0.96-1.11), respectively. A 5-unit increase in insulin resistance in females increased the odds of an abnormal QRS-T angle by 47% (OR = 1.47, 95% CI, 1.10-2.10); in males, a 5-unit increase in insulin resistance increased the OR by 17% (OR = 1.17, 95% CI, 0.82-1.70). CONCLUSIONS: Spatial QRS-T angle may be associated with insulin resistance, especially in women. The individuals with a higher insulin resistance value had higher odds for major adverse cardiovascular events. Nevertheless, the results of this study should be verified in prospective studies.

Analysis of Professional Competencies for the Clinical Research Data Management Profession.

OBJECTIVE: This job analysis was conducted to compare, assess and refine the competencies of the clinical research data management profession. MATERIALS AND METHODS: Two questionnaires were administered in 2015 and 2018 to collect information from data managers on professional competencies, types of data managed, types of studies supported, and necessary foundational knowledge. RESULTS: In 2018 survey, 67 professional competencies were identified. Job tasks differed between early- to mid-career and mid- to late-career practitioners. A large variation in the types of studies conducted and variation in the data managed by the participants was observed. DISCUSSION: Clinical research data managers managed different types of data with variety of research settings, which indicated a need for training in methods and concepts that could be applied across therapeutic areas and types of data. CONCLUSION: The competency survey reported here serves as the foundation for the upcoming revision of the Certified Clinical Data Manager (CCDMTM) exam.

Metabolic syndrome and P-wave duration in the American population.

PURPOSE: Metabolic syndrome has a high prevalence in the United States. P-wave duration is a valuable indicator for atrial electrical conduction. Abnormalities in atrial electrical conduction can predispose to atrial fibrillation. Our objective was to estimate the effect of metabolic syndrome on P-wave duration in a nationally representative sample. METHODS: We included 6499 adults who participated in the National Health and Nutrition Examination Survey III (1988-1994). We estimated the effect of metabolic syndrome and its components on P-wave duration after adjusting for confounders such as demographic and lifestyle variables. We stratified the analyses by gender. RESULTS: Irrespective of gender, participants with metabolic syndrome had a longer P-wave duration than that of those without it. In addition, we observed a positive linear dose-response relation between metabolic syndrome components and P-wave duration. CONCLUSIONS: Patients with metabolic syndrome had a longer P-wave duration. They might have been at a higher risk for atrial fibrillation and mortality; they need to be periodically checked by their health care providers. However, the results of this study should be confirmed in prospective studies.

The relation of blood lead and QRS-T angle in American adults.

The QRS-T angle is a key ECG predictor for ventricular arrhythmia. Lead has a strong relation with cardiovascular diseases; however, no study has been conducted to investigate the association between lead exposure and QRS-T angle. Thus, we explored this association in a population-based representative sample: NHANES III. We used the standard 12-lead ECGs to calculate Spatial QRS-T angles. Blood lead concentration was measured using graphite furnace atomic absorption spectrophotometry method. We conducted multivariate weighted logistic regression to adjust for impaired fasting glucose, hypertension, poverty index, age, race, and smoking status. We found that when the log of blood lead increased by one unit, the odds of an abnormal QRS-T angle increased by 34% among men and 4% among women. We suggest the use of QRS-T angle deviation among those who are exposed to lead to detect individuals at risk for adverse cardiovascular outcomes such as arrhythmias.

Association Between Urinary Cadmium and QRS|T Angle Among Adults in the United States.

OBJECTIVE: Cadmium's effect on QRS|T angle has not been studied. An abnormal QRS|T angle deviation may increase the risk for ventricular dysrhythmias. METHODS: We calculated the orientation of spatial QRS|T angle using QRS and T amplitudes of leads V2, V5, V6, and AVF from the National Health and Nutritional Examination Survey III. Cadmium concentration was measured in urine. We fit weighted unadjusted and adjusted logistic regressions to calculate odds ratios and their corresponding 95% confidence intervals. RESULTS: A unit increase in the logarithm of urinary cadmium increased the odds of QRS|T angle deviation by 30% [1.30 (1.01 to 1.61)]. CONCLUSIONS: Cadmium exposure was associated with an abnormal QRS|T angle in women but not in men. Women exposed to cadmium should be periodically evaluated to detect QRS|T angle deviation, which can predispose them to ventricular dysrhythmias.

The Association between SNPs and a Quantitative Trait: Power Calculation.

A power calculation for a study with a quantitative outcome requires information on the outcome distribution under the alternative hypothesis. Researchers face challenges when they concisely specify alternative distributions in genetic studies because power depends on genotype frequencies and the average effect of each genotype. In GWAS, investigators evaluate hundreds of thousands of associations; therefore it is unrealistic to specify gene frequencies and gene effects for each test and some simplification is needed. Software packages are available to calculate power, but many of them have limited flexibility and / or may have a steep learning curve. In this review, we describe to researchers and graduate students the essentials of a power calculation for testing for an association between a quantitative trait and genotypes. In addition, we provide them with the codes of the different available software packages-free and commercial-to calculate this power. The calculations can be carried out using virtually any computer language that computes the cumulative distribution function of a non-central F-distribution.