Category: Statistics

Cutis. 2023 Nov;112(5):229-231. doi: 10.12788/cutis.0891.

ABSTRACT

Dermatology has long been recognized as a highly competitive field within medicine, with extremely limited spots available for aspiring dermatologists to secure residencies across the United States. We sought to evaluate the trends and factors influencing the match process in dermatology residencies, particularly given the changes brought on by the COVID-19 pandemic. Using data from publicly available match lists and regional categorizations, we studied the rates of internal and regional matches for dermatology applicants in the postpandemic era (2022-2023) compared with prepandemic statistics. Overall, the research sheds light on the evolving dynamics of dermatology residency matching in response to pandemic-induced changes and applicant preferences.

PMID:38091443 | DOI:10.12788/cutis.0891

PLoS One. 2023 Dec 13;18(12):e0289195. doi: 10.1371/journal.pone.0289195. eCollection 2023.

ABSTRACT

Segmentation of breast ultrasound images is a crucial and challenging task in computer-aided diagnosis systems. Accurately segmenting masses in benign and malignant cases and identifying regions with no mass is a primary objective in breast ultrasound image segmentation. Deep learning (DL) has emerged as a powerful tool in medical image segmentation, revolutionizing how medical professionals analyze and interpret complex imaging data. The UNet architecture is a highly regarded and widely used DL model in medical image segmentation. Its distinctive architectural design and exceptional performance have made it popular among researchers. With the increase in data and model complexity, optimization and fine-tuning models play a vital and more challenging role than before. This paper presents a comparative study evaluating the effect of image preprocessing and different optimization techniques and the importance of fine-tuning different UNet segmentation models for breast ultrasound images. Optimization and fine-tuning techniques have been applied to enhance the performance of UNet, Sharp UNet, and Attention UNet. Building upon this progress, we designed a novel approach by combining Sharp UNet and Attention UNet, known as Sharp Attention UNet. Our analysis yielded the following quantitative evaluation metrics for the Sharp Attention UNet: the Dice coefficient, specificity, sensitivity, and F1 score values obtained were 0.93, 0.99, 0.94, and 0.94, respectively. In addition, McNemar’s statistical test was applied to assess significant differences between the approaches. Across a number of measures, our proposed model outperformed all other models, resulting in improved breast lesion segmentation.

PMID:38091358 | DOI:10.1371/journal.pone.0289195

J Physician Assist Educ. 2023 Dec 13. doi: 10.1097/JPA.0000000000000567. Online ahead of print.

ABSTRACT

PURPOSE: The primary aim of this study was the examination of relationships between students’ preadmission achievement, intraphysician assistant (PA) program achievement, and Physician Assistant National Certifying Examination (PANCE) performance using path analysis regression. Second, this study explored the extent to which the theoretical model differed based on several key demographic variables: sex and undergraduate major.

METHODS: This retrospective, single-institution study examined data from 2015 to 2022 (n = 322). Analysis included descriptive statistics, bivariate correlations, and path analysis using structural equation modeling to examine direct, indirect, and total effects of all predictors on the primary outcome variable, PANCE.

RESULTS: PACKRAT-I demonstrated the largest total effect size on PANCE total score (β = .45). Total effect size on PANCE was small yet significant for prerequisite grade point average (GPA), Graduate Record Exam verbal and quantitative subscores, a comprehensive didactic cardiology examination, didactic and clinical year GPAs, and End of Rotation examination mean score (β < .25). The relationship between mean preceptor evaluation score and PANCE was nonsignificant. Subgroup analyses showed differences between female and male in the relationship between several didactic variables and preceptor evaluations. No differences were detected between groups based on undergraduate major.

CONCLUSION: This PANCE analysis revealed relationships among pre-PA and intra-PA performance metrics that may subsequently support data-informed strategies for programs to identify at-risk students, aid student success, and support the assessment of curriculum. Future studies should replicate the approach using a larger, multi-institution sample that examines additional preprogram and intraprogram achievement variables.

PMID:38091357 | DOI:10.1097/JPA.0000000000000567

West Afr J Med. 2023 Nov 30;40(11):1164-1172.

ABSTRACT

BACKGROUND: Metabolic syndrome is a constellation of abnormalities which includes central obesity, dyslipidaemia, elevated blood pressure and hyperglycemia. Hypertension, (which is a very common component of metabolic syndrome), and diabetes mellitus, are independently associated. Also, studies examining metabolic syndrome inAbuja, a city with affluence-driven lifestyle, are not available. This study aimed to investigate the prevalence of metabolic syndrome among hypertensive patients in Abuja, Nigeria, as well as to examine the associations between metabolic syndrome and certain factors in that cohort of hypertensive patients.

METHODS: This was a retrospective study that used data from hypertensive patients who attended clinic over a period of five years. Eight hundred and fifty-eight, (858-combined), case files of pre-treated, (previously known hypertensive patients) and newly diagnosed hypertensive participants were used for the study. The student t-tests were used to compare continuous variables, while Chi-square (χ2) tests were used for relationship between qualitative variables. The likelihood ratio test was employed to further confirm the statistical significance of certain independent variables relating with metabolic syndrome. A P-value of < 0.05 was considered statistically significant.

RESULTS: The mean ages were 48.70±12.18, 49.19±11.06 and 48.2±13.3 years for combined group, the pre-treated and the newly-diagnosed groups respectively. The pre-treated, group consists of those previously known hypertensive patients, while the new group consists of those who were newly diagnosed hypertensive patients and were treatment naïve. The prevalence of metabolic syndrome in this study was 45.5% in the combined group, 47.23% in the pre-treated group and 37.3% in the newly diagnosed group. The commonest component of metabolic syndrome was reduced high density lipoprotein cholesterol, HDL-C.

CONCLUSION: Metabolic syndrome is prevalent among hypertensive patients in Abuja, Nigeria. Some correlates of metabolic syndrome include; elevated BMI, truncal obesity, elevated total cholesterol, the use of thiazide diuretics and beta blockers as antihypertensives.

PMID:38091343

PLOS Glob Public Health. 2023 Dec 13;3(12):e0002679. doi: 10.1371/journal.pgph.0002679. eCollection 2023.

ABSTRACT

Brazil was one of the countries most affected during the first year of the COVID-19 pandemic, in a pre-vaccine era, and mathematical and statistical models were used in decision-making and public policies to mitigate and suppress SARS-CoV-2 dispersion. In this article, we intend to overview the modeling for COVID-19 in Brazil, focusing on the first 18 months of the pandemic. We conducted a scoping review and searched for studies on infectious disease modeling methods in peer-reviewed journals and gray literature, published between January 01, 2020, and June 2, 2021, reporting real-world or scenario-based COVID-19 modeling for Brazil. We included 81 studies, most corresponding to published articles produced in Brazilian institutions. The models were dynamic and deterministic in the majority. The predominant model type was compartmental, but other models were also found. The main modeling objectives were to analyze epidemiological scenarios (testing interventions’ effectiveness) and to project short and long-term predictions, while few articles performed economic impact analysis. Estimations of the R0 and transmission rates or projections regarding the course of the epidemic figured as major, especially at the beginning of the crisis. However, several other outputs were forecasted, such as the isolation/quarantine effect on transmission, hospital facilities required, secondary cases caused by infected children, and the economic effects of the pandemic. This study reveals numerous articles with shared objectives and similar methods and data sources. We observed a deficiency in addressing social inequities in the Brazilian context within the utilized models, which may also be expected in several low- and middle-income countries with significant social disparities. We conclude that the models were of great relevance in the pandemic scenario of COVID-19. Nevertheless, efforts could be better planned and executed with improved institutional organization, dialogue among research groups, increased interaction between modelers and epidemiologists, and establishment of a sustainable cooperation network.

PMID:38091336 | DOI:10.1371/journal.pgph.0002679

PLoS One. 2023 Dec 13;18(12):e0284851. doi: 10.1371/journal.pone.0284851. eCollection 2023.

ABSTRACT

Scales, sets of discrete pitches that form the basis of melodies, are thought to be one of the most universal hallmarks of music. But we know relatively little about cross-cultural diversity of scales or how they evolved. To remedy this, we assemble a cross-cultural database (Database of Musical Scales: DaMuSc) of scale data, collected over the past century by various ethnomusicologists. Statistical analyses of the data highlight that certain intervals (e.g., the octave, fifth, second) are used frequently across cultures. Despite some diversity among scales, it is the similarities across societies which are most striking: step intervals are restricted to 100-400 cents; most scales are found close to equidistant 5- and 7-note scales. We discuss potential mechanisms of variation and selection in the evolution of scales, and how the assembled data may be used to examine the root causes of convergent evolution.

PMID:38091315 | DOI:10.1371/journal.pone.0284851

PLoS One. 2023 Dec 13;18(12):e0287961. doi: 10.1371/journal.pone.0287961. eCollection 2023.

ABSTRACT

BACKGROUND: One of the three main targets of the World Health Organization (WHO) End TB Strategy (2015-2035) is that no tuberculosis (TB) patients or their households face catastrophic costs (defined as exceeding 20% of the annual household income) because of the disease. Our study seeks to determine, as a baseline, the magnitude and main drivers of the costs associated with TB disease for patients and their households and to monitor the proportion of households experiencing catastrophic costs in Brazil.

METHODS: A national cross-sectional cluster-based survey was conducted in Brazil in 2019-2021 following WHO methodology. TB patients of all ages and types of TB were eligible for the survey. Adult TB patients and guardians of minors (<18 years old) were interviewed once about costs, time loss, coping measures, income, household expenses, and asset ownership. Total costs, including indirect costs measured as reported household income change, were expressed as a percentage of annual household income. We used descriptive statistics to analyze the cost drivers and multivariate logistic regression to determine factors associated with catastrophic costs.

RESULTS: We interviewed 603 patients, including 538 (89%) with drug-sensitive (DS) and 65 (11%) with drug-resistant (DR) TB. Of 603 affected households, 48.1% (95%CI: 43-53.2) experienced costs above 20% of their annual household income during their TB episode. The proportion was 44.4% and 78.5% among patients with DS- and DR-TB, respectively. On average, patients incurred costs of US$1573 (95%CI: 1361.8-1785.0) per TB episode, including pre-diagnosis and post-diagnosis expenses. Key cost drivers were post-diagnosis nutritional supplements (US$317.6, 95%CI: 232.7-402.6) followed by medical costs (US$85.5, 95%CI: 54.3-116.5) and costs of travel for clinic visits during treatment (US$79.2, 95%CI: 61.9-96.5). In multivariate analysis, predictors of catastrophic costs included positive HIV status (aOR = 3.0, 95%CI:1.1-8.6) and self-employment (aOR = 2.7, 95%CI:1.1-6.5); high education was a protective factor (aOR = 0.1, 95%CI:0.0-0.9).

CONCLUSIONS: Although the services offered to patients with TB are free of charge in the Brazilian public health sector, the availability of free diagnosis and treatment services does not alleviate patients’ financial burden related to accessing TB care. The study allowed us to identify the costs incurred by patients and suggest actions to mitigate their suffering. In addition, this study established a baseline for monitoring catastrophic costs and fostering a national policy to reduce the costs to patients for TB care in Brazil.

PMID:38091306 | DOI:10.1371/journal.pone.0287961

PLoS One. 2023 Dec 13;18(12):e0295752. doi: 10.1371/journal.pone.0295752. eCollection 2023.

ABSTRACT

Common prosperity stands as a pivotal concept and objective within China’s socialism with distinctive characteristics, serving as a fundamental assurance and basis for ensuring its people’s happiness and comprehensive development. This research employs a Coupled Coordination Degree Model to construct a common prosperity Index using data from China between 2010 and 2020. The study investigates the influence of innovation and entrepreneurship on common prosperity while examining the regulating roles played by the government and market during this process. The outcomes demonstrate that innovation substantially facilitates the realization of common prosperity. The relationship between entrepreneurship and common prosperity follows a positive “U”-shaped curve, where entrepreneurship significantly contributes to common prosperity upon reaching a particular scale. Further investigations reveal heterogeneity in the impact of innovation and entrepreneurship on common prosperity. Specifically, innovation significantly contributes to common prosperity in the northern regions, whereas entrepreneurship has a noteworthy impact on common prosperity in the southern regions. Moreover, it is worth noting that both innovation and entrepreneurship have a significant influence on common prosperity in areas characterized by low economic development levels and a scarcity of fixed capital. The fiscal effects of the government attenuate the promoting effect of innovation on common prosperity but enhance the adverse influence of entrepreneurship. On the contrary, market mechanisms mitigate the negative impact of entrepreneurship on common prosperity. Consequently, achieving common prosperity requires strengthened regional innovation cooperation, encouraging advanced regions to lead underdeveloped regions, and leveraging the regulatory roles of both the government and the market, thus progressing gradually towards common prosperity.

PMID:38091305 | DOI:10.1371/journal.pone.0295752

Proc Natl Acad Sci U S A. 2023 Dec 19;120(51):e2309760120. doi: 10.1073/pnas.2309760120. Epub 2023 Dec 13.

ABSTRACT

Genetic assimilation is the process by which a phenotype that is initially induced by an environmental stimulus becomes stably inherited in the absence of the stimulus after a few generations of selection. While the concept has attracted much debate after being introduced by C. H. Waddington 70 y ago, there have been few experiments to quantitatively characterize the phenomenon. Here, we revisit and organize the results of Waddington’s original experiments and follow-up studies that attempted to replicate his results. We then present a theoretical model to illustrate the process of genetic assimilation and highlight several aspects that we think require further quantitative studies, including the gradual increase of penetrance, the statistics of delay in assimilation, and the frequency of unviability during selection. Our model captures Waddington’s picture of developmental paths in a canalized landscape using a stochastic dynamical system with alternative trajectories that can be controlled by either external signals or internal variables. It also reconciles two descriptions of the phenomenon-Waddington’s, expressed in terms of an individual organism’s developmental paths, and that of Bateman in terms of the population distribution crossing a hypothetical threshold. Our results provide theoretical insight into the concepts of canalization, phenotypic plasticity, and genetic assimilation.

PMID:38091287 | DOI:10.1073/pnas.2309760120

PLoS One. 2023 Dec 13;18(12):e0294557. doi: 10.1371/journal.pone.0294557. eCollection 2023.

ABSTRACT

BACKGROUND: General practitioners (GPs) often assess patients with acute infections. It is challenging for GPs to recognize patients needing immediate hospital referral for sepsis while avoiding unnecessary referrals. This study aimed to predict adverse sepsis-related outcomes from telephone triage information of patients presenting to out-of-hours GP cooperatives.

METHODS: A retrospective cohort study using linked routine care databases from out-of-hours GP cooperatives, general practices, hospitals and mortality registration. We included adult patients with complaints possibly related to an acute infection, who were assessed (clinic consultation or home visit) by a GP from a GP cooperative between 2017-2019. We used telephone triage information to derive a risk prediction model for sepsis-related adverse outcome (infection-related ICU admission within seven days or infection-related death within 30 days) using logistic regression, random forest, and neural network machine learning techniques. Data from 2017 and 2018 were used for derivation and from 2019 for validation.

RESULTS: We included 155,486 patients (median age of 51 years; 59% females) in the analyses. The strongest predictors for sepsis-related adverse outcome were age, type of contact (home visit or clinic consultation), patients considered ABCD unstable during triage, and the entry complaints”general malaise”, “shortness of breath” and “fever”. The multivariable logistic regression model resulted in a C-statistic of 0.89 (95% CI 0.88-0.90) with good calibration. Machine learning models performed similarly to the logistic regression model. A “sepsis alert” based on a predicted probability >1% resulted in a sensitivity of 82% and a positive predictive value of 4.5%. However, most events occurred in patients receiving home visits, and model performance was substantially worse in this subgroup (C-statistic 0.70).

CONCLUSION: Several patient characteristics identified during telephone triage of patients presenting to out-of-hours GP cooperatives were associated with sepsis-related adverse outcomes. Still, on a patient level, predictions were not sufficiently accurate for clinical purposes.

PMID:38091283 | DOI:10.1371/journal.pone.0294557