Examining the Factors Influencing Applicants’ Placement on One General Surgery Program’s Rank Order List

Purpose Surgery residency applications include variables that determine an individual’s rank on a program’s match list. We performed this study to determine which residency application variables are the most impactful in creating our program’s rank order list. Methods We completed a retrospective examination of all interviewed applicants for the 2019 match. We recorded United States Medical Licensing Examinations (USMLE) step I and II scores, class quartile rank from the Medical Student Performance Evaluation (MSPE), Alpha Omega Alpha (AOA) membership, geographic region, surgery clerkship grade, and grades on other clerkships. The MSPE and letters of recommendation were reviewed by two of the authors and assigned a score of 1 to 3, where 1 was weak and 3 was strong. The same two authors reviewed the assessments from each applicant’s interview and assigned a score from 1-5, where 1 was poor and 5 was excellent. Univariate analysis was performed, and the significant variables were used to construct an adjusted multivariate model with significance measured at P < .05. Results Univariate analysis for all 92 interviewed applicants demonstrated that USMLE step 2 scores ( P = .002), class quartile rank ( P = .004), AOA status ( P = .014), geographic location ( P < .001), letters of recommendation ( P < .001), and interview rating ( P < .001) were significant in predicting an applicant’s position on the rank list. On multivariate analysis only USMLE step 2 ( P = .018) and interview ( P < .001) remained significant. Conclusion USMLE step 2 and an excellent interview were the most important factors in constructing our rank order list. Applicants with a demonstrated strong clinical fund of knowledge that develop a rapport with our faculty and residents receive the highest level of consideration for our program.

Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance

Early outbreak detection is a key aspect in the containment of infectious diseases, as it enables the identification and isolation of infected individuals before the disease can spread to a larger population. Instead of detecting unexpected increases of infections by monitoring confirmed cases, syndromic surveillance aims at the detection of cases with early symptoms, which allows a more timely disclosure of outbreaks. However, the definition of these disease patterns is often challenging, as early symptoms are usually shared among many diseases and a particular disease can have several clinical pictures in the early phase of an infection. As a first step toward the goal to support epidemiologists in the process of defining reliable disease patterns, we present a novel, data-driven approach to discover such patterns in historic data. The key idea is to take into account the correlation between indicators in a health-related data source and the reported number of infections in the respective geographic region. In an preliminary experimental study, we use data from several emergency departments to discover disease patterns for three infectious diseases. Our results show the potential of the proposed approach to find patterns that correlate with the reported infections and to identify indicators that are related to the respective diseases. It also motivates the need for additional measures to overcome practical limitations, such as the requirement to deal with noisy and unbalanced data, and demonstrates the importance of incorporating feedback of domain experts into the learning procedure.

Increasing Incidence of Juvenile Idiopathic Arthritis: A Trend Over 31 Years in Southern Sweden

Background The reported incidence of juvenile idiopathic arthritis (JIA) varies from studies around the world, depending on patient collection techniques, geographic region, and time. Our aim was to study the mean annual incidence of juvenile arthritis in a population-based setting using two regional cohorts of children diagnosed with juvenile chronic arthritis (JCA) and JIA over a period of 31 years.Findings The study population was 651 children diagnosed 1980-2010. The mean annual incidence over the period was 9.9 per 100,000 children, with a range from 4.2 per 100,000 in 1980 to 17.1 per 100,000 children in 2010. When comparing incidence rate between the decade of diagnosis using rate ratios, there is a significant difference with diagnosis 1980-1989 as comparator.Conclusions We show a statistically significant increase in the incidence of JIA over three decades in a population-based cohort of children with juvenile arthritis.

Distribution of Human Immunodeficiency Virus and Human T-Leukemia Virus Co-infection in Bahia, Brazil

Human Immunodeficiency Virus (HIV) and Human T-Leukemia Virus (HTLV) are retroviruses that share similar routes of transmission. In Brazil, the prevalence of HIV and HTLV varies according to geographic region. The state of Bahia, located in the Northeast region, is considered endemic for both retroviruses. The present study aimed to characterize the frequency of HIV/HTLV coinfection and evaluate the geographic distribution of coinfection throughout the state. This cross-sectional study was conducted at the state's Central Laboratory of Public Health (LACEN-BA) and included all samples from 2004 to 2013 submitted to serological testing for anti-HIV and anti-HTLV-1/2, screened by chemiluminescence/ELISA and confirmed by Western blot. Infection rates are expressed as the number of infected individuals per 100,000 inhabitants from each municipality. A total of 129,158 samples originating from 358/417 (85.8%) municipalities in Bahia were evaluated. HTLV was detected in 2.4% of the HIV-positive samples (n = 42) compared to 0.5% of those with negative HIV serology (n = 677) (OR: 4.65; CI: 3.39–6.37). HIV/HTLV coinfection was more frequent in women (69.0%); the median age of coinfected individuals was 47.2 years [interquartile range (IQR): 41.6–55.4 years]. In the 14/417 (3.4%) municipalities where at least one case of HIV/HTLV coinfection was detected, the overall HTLV coinfection rate in HIV-positive samples was 0.25 (range: 0.17–13.84) per 100,000 inhabitants. Most cases of HIV/HTLV-1 coinfection (21/37, 57%) were concentrated in the municipality of Salvador. Isolated instances (one or two cases) of HIV/HTLV-1 coinfection were distributed across municipalities known to be endemic for HTLV infection.

The Influence of Regional Differences on the Reliability of the AO Spine Sacral Injury Classification System

Study Design Global cross-sectional survey. Objective To explore the influence of geographic region on the AO Spine Sacral Classification System. Methods A total of 158 AO Spine and AO Trauma members from 6 AO world regions (Africa, Asia, Europe, Latin and South America, Middle East, and North America) participated in a live webinar to assess the reliability, reproducibility, and accuracy of classifying sacral fractures using the AO Spine Sacral Classification System. This evaluation was performed with 26 cases presented in randomized order on 2 occasions 3 weeks apart. Results A total of 8320 case assessments were performed. All regions demonstrated excellent intraobserver reproducibility for fracture morphology. Respondents from Europe (k = .80) and North America (k = .86) achieved excellent reproducibility for fracture subtype while respondents from all other regions displayed substantial reproducibility. All regions demonstrated at minimum substantial interobserver reliability for fracture morphology and subtype. Each region demonstrated >90% accuracy in classifying fracture morphology and >80% accuracy in fracture subtype compared to the gold standard. Type C morphology (p2 = .0000) and A3 (p1 = .0280), B2 (p1 = .0015), C0 (p1 = .0085), and C2 (p1 =.0016, p2 =.0000) subtypes showed significant regional disparity in classification accuracy (p1 = Assessment 1, p2 = Assessment 2). Respondents from Asia (except in A3) and the combined group of North, Latin, and South America had accuracy percentages below the combined mean, whereas respondents from Europe consistently scored above the mean. Conclusions In a global validation study of the AO Spine Sacral Classification System, substantial reliability of both fracture morphology and subtype classification was found across all geographic regions.

Pandemic-related declines in hospitalization for non-COVID-19-related illness in the United States from January through July 2020

Background The COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has substantially impacted healthcare utilization worldwide. The objective of this retrospective analysis of a large hospital discharge database was to compare all-cause and cause-specific hospitalizations during the first six months of the pandemic in the United States with the same months in the previous four years. Methods Data were collected from all hospitals in the Premier Healthcare Database (PHD) and PHD Special Release reporting hospitalizations from January through July for each year from 2016 through 2020. Hospitalization trends were analyzed stratified by age group, major diagnostic categories (MDCs), and geographic region. Results The analysis included 286 hospitals from all 9 US Census divisions. The number of all-cause hospitalizations per month was relatively stable from 2016 through 2019 and then fell by 21% (57,281 fewer hospitalizations) between March and April 2020, particularly in hospitalizations for non-respiratory illnesses. From April onward there was a rise in the number of monthly hospitalizations per month. Hospitalizations per month, nationally and in each Census division, decreased for 20 of 25 MDCs between March and April 2020. There was also a decrease in hospitalizations per month for all age groups between March and April 2020 with the greatest decreases in hospitalizations observed for patients 50–64 and ≥65 years of age. Conclusions Rates of hospitalization declined substantially during the first months of the COVID-19 pandemic, suggesting delayed routine, elective, and emergency care in the United States. These lapses in care for illnesses not related to COVID-19 may lead to increases in morbidity and mortality for other conditions. Thus, in the current stage of the pandemic, clinicians and public-health officials should work, not only to prevent SARS-CoV-2 transmission, but also to ensure that care for non-COVID-19 conditions is not delayed.

Surface Water Quality Assessment, Prediction & Modelling of River Daya in Odisha

A decision tree -based approach is projected to predict surface water quality and is a good tool to assess quality and guarantee property safe use of water for drinking. The most objective of this study is to assess the surface water quality of the Daya watercourse to work out the quality of drinking functions. Samples were collected from designated locations throughout totally different seasons (winter, summer, rainy) over a amount of five years (2016, 2017, 2018, 2019, and 2020). Total dissolved solids, pH, alkalinity, chloride, nitrate, total hardness, calcium, magnesium, iron, fluoride, were all tested as well as total coliform, fecal coliform, and E. coli. The main goal is to use decision tree regression to construct a model to assess and predict water quality changes in the Daya geographic region of Odisha, India, and compare it to statistical methods.

Association of improved air quality with lower dementia risk in older women

Late-life ambient air pollution is a risk factor for brain aging, but it remains unknown if improved air quality (AQ) lowers dementia risk. We studied a geographically diverse cohort of older women dementia free at baseline in 2008 to 2012 (n = 2,239, aged 74 to 92). Incident dementia was centrally adjudicated annually. Yearly mean concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated using regionalized national universal kriging models and averaged over the 3-y period before baseline (recent exposure) and 10 y earlier (remote exposure). Reduction from remote to recent exposures was used as the indicator of improved AQ. Cox proportional hazard ratios (HRs) for dementia risk associated with AQ measures were estimated, adjusting for sociodemographic, lifestyle, and clinical characteristics. We identified 398 dementia cases during follow up (median = 6.1 y). PM2.5 and NO2 reduced significantly over the 10 y before baseline. Larger AQ improvement was associated with reduced dementia risks (HRPM2.5 0.80 per 1.78 μg/m3, 95% CI 0.71–0.91; HRNO2 0.80 per 3.91 parts per billion, 95% CI 0.71–0.90), equivalent to the lower risk observed in women 2.4 y younger at baseline. Higher PM2.5 at baseline was associated with higher dementia risk (HRPM2.5 1.16 per 2.90 μg/m3, 95% CI 0.98–1.38), but the lower dementia risk associated with improved AQ remained after further adjusting for recent exposure. The observed associations did not substantially differ by age, education, geographic region, Apolipoprotein E e4 genotypes, or cardiovascular risk factors. Long-term AQ improvement in late life was associated with lower dementia risk in older women.

Gender Differences in Using Arabizi Among Jordanian Undergraduate Students: A Socio-Linguistic Study

This study aimed to explore the statistical differences between each gender in using Arabizi according to their age, place of living. The sample of the study consisted (283) students selected randomly from both Yarmouk and Jadara universities. A quantitative method approach was employed by the researchers in order to answer the questions of the study. A fourteen-item questionnaire was adapted, developed and validated based on the past literature and data collection in order to achieve the purpose of the study. The results showed that there are statistically significant differences at (α = 0.05) due to the gender variable in favor of females, and regarding the age variable the preference is in favor 19-24 age group, and no preference found related to the place of living. The study recommends examining other students who study different majors in these two universities or in other universities located in/ out the geographic region.

First morphometry, reproduction, and genetic data for Blennius ocellaris (Linnaeus, 1758) from the Black Sea

Two specimens of the butterfly blenny, Blennius ocellaris, were caught off the coast of Ordu (Black Sea, Turkey) in April 2021 by trammel net. The aim of this paper is to further document occurrence and distribution of the butterfly blenny for the Black Sea and for Turkish marine ichthyofauna and to provide first morphometric, reproduction, and genetic data on this species to the Black Sea fauna species. Some morphometric and meristic characters were measured and presented as the percentage of total length (TL%). All morphometric measurements except eye diameter, pre-anal length, and maximum body depth were higher in the male individual. It was observed that the head makes up almost 1/4 of the body. It was determined that the ripe eggs were in their final stage of development (Stage IV). Gonad’s weight of a female individual was 2.85 g and the number of eggs was determined as 2993. The mean egg diameter was measured as 1070.7 ±15.63 μm (from 1050.2 to 1123.1 μm). The mitochondrial DNA gene regions of 16S rRNA and COI of the specimens were sequenced and analyzed. The generated partial sequences of COI and 16S rRNA were 621 bp and 551 bp, respectively. The maximum likelihood tree generated with the COI gene sequences retrieved from the GenBank database demonstrated geographic region-based distinction and sequences of the Black Sea specimens nested with the reference specimen sequences from the Western Mediterranean Sea and the Sea of Marmara.