Category: Statistics

Cancer Control. 2024 Jan-Dec;31:10732748241292786. doi: 10.1177/10732748241292786.

ABSTRACT

OBJECTIVE: To investigate the impact of urinary iodine concentration (UIC) and post-stimulatory thyroglobulin (ps-Tg) levels on the therapeutic efficacy of differentiated thyroid cancer (DTC) patients after initial radioiodine therapy, and to analyze the validity of these indicators as prognostic factors.

METHODS: A total of 213 DTC patients received initial radioiodine therapy from June 2022 to September 2023. Demographic data and UIC were collected before and after therapy. Thyrotropin, thyroglobulin (Tg), and thyroglobulin antibody levels were assessed. Iodine uptake rate was measured, and therapeutic efficacy was evaluated 6 months post-therapy. Statistical tests were used for data comparison, and logistic regression analysis for response factors.

RESULTS: Post-therapy UIC and pre-post UIC difference were significantly correlated with Tg levels but not with reaching excellent response (ER) indicated by suppression of Tg levels below 0.2 ug/L. Ps-Tg levels related to therapeutic efficacy, while UIC did not correlate with outcomes. ROC curve analysis found optimal ps-Tg cut-off points for the low-intermediate and high-risk groups classified by primary tumor size, invasion, metastasis, and pathological type.

CONCLUSION: Post-treatment UIC and pre-post UIC difference correlate with ps-Tg levels. Ps-Tg levels are an associated factor for DTC, but UIC changes, despite correlation with ps-Tg, are not significantly related to outcomes and cannot be used as a prognostic factor.

PMID:39405376 | DOI:10.1177/10732748241292786

Proc Natl Acad Sci U S A. 2024 Oct 22;121(43):e2412872121. doi: 10.1073/pnas.2412872121. Epub 2024 Oct 15.

ABSTRACT

Obesity is a major public health crisis in the United States (US) affecting 42% of the population, exacerbating a spectrum of other diseases and contributing significantly to morbidity and mortality overall. Recent advances in pharmaceutical interventions, particularly glucagon-like peptide-1 (GLP-1) receptor agonists (e.g., semaglutide, liraglutide) and dual gastric inhibitory polypeptide and GLP-1 receptor agonists (e.g., tirzepatide), have shown remarkable efficacy in weight-loss. However, limited access to these medications due to high costs and insurance coverage issues restricts their utility in mitigating the obesity epidemic. We quantify the annual mortality burden directly attributable to limited access to these medications in the US. By integrating hazard ratios of mortality across body mass index categories with current obesity prevalence data, combined with healthcare access, willingness to take the medication, and observed adherence to and efficacy of the medications, we estimate the impact of making these medications accessible to all those eligible. Specifically, we project that with expanded access, over 42,000 deaths could be averted annually, including more than 11,000 deaths among people with type 2 diabetes. These findings underscore the urgent need to address barriers to access and highlight the transformative public health impact that could be achieved by expanding access to these novel treatments.

PMID:39405358 | DOI:10.1073/pnas.2412872121

PLoS One. 2024 Oct 15;19(10):e0308654. doi: 10.1371/journal.pone.0308654. eCollection 2024.

ABSTRACT

With the improvement of education level and the expansion of higher education, more students can have the opportunities to obtain better education, and the pressure of employment competition is also increasing. How to improve students’ employment competitiveness, comprehensive quality and the ability to explore paths for career planning and employment strategies has become a common concern in today’s society. Under the background of today’s informatization, the paths of career planning and employment strategies are becoming more and more informatized. The support of Internet is essential for obtaining more employment information. As a representative product of the information age, deep learning provides people with a better path. This paper conducts an in-depth study of the career planning and employment strategy paths based on deep learning in the information age. Research has shown that in the current information age, deep learning through career planning and employment strategy paths can help students solve the main problems they face in career planning education and better meet the needs of today’s society. Career awareness increased by 35% and self-improvement by 15%. This indicated that in the information age, career planning and employment strategies based on deep learning are a way to conform to the trend of the times, which can better help college students improve their understanding, promote employment, and promote self-development.This study combines quantitative and qualitative methods, collects data through questionnaires, and uses deep learning model for analysis. Control group and experimental group were set up to evaluate the effect of career planning education. Descriptive statistics and correlation analysis were used to ensure the accuracy and reliability of the results.

PMID:39405324 | DOI:10.1371/journal.pone.0308654

PLoS One. 2024 Oct 15;19(10):e0311850. doi: 10.1371/journal.pone.0311850. eCollection 2024.

ABSTRACT

In ophthalmology and otolaryngology, data collected from paired body parts are typically reformatted into categorical bilateral data structures for subsequent research. This article applies Donner’s equal correlation coefficient model and obtains nine simultaneous confidence intervals (SCI) of proportion ratios under three asymptotic statistical methods and three ways of multiplicity adjustment. The empirical coverage probability and mean interval width are evaluated through Monte Carlo simulations. A real example is used to demonstrate the proposed methods.

PMID:39405312 | DOI:10.1371/journal.pone.0311850

PLoS One. 2024 Oct 15;19(10):e0309177. doi: 10.1371/journal.pone.0309177. eCollection 2024.

ABSTRACT

BACKGROUND: Women developing preeclampsia (PE) or fetal growth restriction (FGR) during pregnancy are at higher risk for cardiovascular diseases (CVD) later in life. We aimed to analyse cardiovascular health of women 10-20 years after affected pregnancies in comparison to women after uneventful pregnancies. In addition, we assessed a potential long-term effect of the NO-donor pentaerythrityl tetranitrate (PETN).

METHODS: Women 10-20 years after severe PE, including women receiving PETN during pregnancy and matched controls were recruited and assessed for baseline clinical data and cardiovascular function by transthoracic echocardiography, VICORDER and USCOM. SPSS was used for statistical analysis.

RESULTS: 53 participants after PE/FGR (13 with former PETN intake) and 51 controls were recruited for follow-up at an average of 14 years after index pregnancies. Compared to controls, women after PE/FGR had a significantly higher incidence of arterial hypertension (13.7% vs. 41.5%, p<0.001), and were more likely to be hypertensive (41.2% vs. 67.30%, p = 0.008). There were no differences in cardiovascular function observed. Affected women with PETN intake during pregnancy showed lower mean values for right atrial area and ventricle in comparison to controls and also to affected women without former medication.

CONCLUSIONS: In conclusion, our study results confirm that the risk of CVD is increased in women after PE/FGR compared to women after uneventful pregnancies. Contrary to our expectations, no major cardiovascular changes were observed in our cohort 10-20 years post pregnancy. The observed differences found in right heart dimensions were within reference ranges, and should be interpreted with caution.

PMID:39405308 | DOI:10.1371/journal.pone.0309177

PLoS One. 2024 Oct 15;19(10):e0311542. doi: 10.1371/journal.pone.0311542. eCollection 2024.

ABSTRACT

The aim of this research is to investigate the role of servicescape on re-patronage and recommended intention through pleasure feeling and satisfaction in healthcare settings that put substantial contribution in the process of healthcare service delivery. Data were collected through cross-sectional convenience sampling via a self-administered survey questionnaire from 431 clinical outpatients who revisit the same hospital of metropolitan areas of Punjab, Pakistan. Structural Equation Modeling (SEM) was carried out for path analysis through AMOS (24.0 V), while statistical measures were analyzed using SPSS (25.0 V). The present study results revealed that patients’ intention optimistically triggered through partial mediation and affirm the direct and indirect association with servicescape. It also revealed that patient-recommended and re-patronage intentions to visit the clinic were statistically substantial and positively influenced by intervening constructs of pleasure feeling and satisfaction. Additionally, it is found that servicescape and pleasure feeling contributed to 30% change in satisfaction. Moreover, pleasure feeling, and satisfaction contributed to 50% change in re-patronage and 31% change in recommendation intention of the patients. The current study findings contribute significantly to servicescape literature from a theatrical perspective and reevaluate the patterns and operations in healthcare. It also helps managers and administrators of private hospitals to make strategies to increase patient satisfaction.

PMID:39405306 | DOI:10.1371/journal.pone.0311542

J Med Internet Res. 2024 Oct 15;26:e49704. doi: 10.2196/49704.

ABSTRACT

BACKGROUND: Studies have shown that patients have difficulty understanding medical jargon in electronic health record (EHR) notes, particularly patients with low health literacy. In creating the NoteAid dictionary of medical jargon for patients, a panel of medical experts selected terms they perceived as needing definitions for patients.

OBJECTIVE: This study aims to determine whether experts and laypeople agree on what constitutes medical jargon.

METHODS: Using an observational study design, we compared the ability of medical experts and laypeople to identify medical jargon in EHR notes. The laypeople were recruited from Amazon Mechanical Turk. Participants were shown 20 sentences from EHR notes, which contained 325 potential jargon terms as identified by the medical experts. We collected demographic information about the laypeople’s age, sex, race or ethnicity, education, native language, and health literacy. Health literacy was measured with the Single Item Literacy Screener. Our evaluation metrics were the proportion of terms rated as jargon, sensitivity, specificity, Fleiss κ for agreement among medical experts and among laypeople, and the Kendall rank correlation statistic between the medical experts and laypeople. We performed subgroup analyses by layperson characteristics. We fit a beta regression model with a logit link to examine the association between layperson characteristics and whether a term was classified as jargon.

RESULTS: The average proportion of terms identified as jargon by the medical experts was 59% (1150/1950, 95% CI 56.1%-61.8%), and the average proportion of terms identified as jargon by the laypeople overall was 25.6% (22,480/87,750, 95% CI 25%-26.2%). There was good agreement among medical experts (Fleiss κ=0.781, 95% CI 0.753-0.809) and fair agreement among laypeople (Fleiss κ=0.590, 95% CI 0.589-0.591). The beta regression model had a pseudo-R² of 0.071, indicating that demographic characteristics explained very little of the variability in the proportion of terms identified as jargon by laypeople. Using laypeople’s identification of jargon as the gold standard, the medical experts had high sensitivity (91.7%, 95% CI 90.1%-93.3%) and specificity (88.2%, 95% CI 86%-90.5%) in identifying jargon terms.

CONCLUSIONS: To ensure coverage of possible jargon terms, the medical experts were loose in selecting terms for inclusion. Fair agreement among laypersons shows that this is needed, as there is a variety of opinions among laypersons about what is considered jargon. We showed that medical experts could accurately identify jargon terms for annotation that would be useful for laypeople.

PMID:39405109 | DOI:10.2196/49704

ACS Appl Mater Interfaces. 2024 Oct 15. doi: 10.1021/acsami.4c15275. Online ahead of print.

ABSTRACT

We applied Bayesian optimization (BO), a machine learning (ML) technique, to optimize the growth conditions of monolayer WS₂ using photoluminescence (PL) intensity as the objective function. Through iterative experiments guided by BO, an improvement of 86.6% in PL intensity is achieved within 13 optimization rounds. Statistical analysis revealed the relationships between growth conditions and PL intensity, highlighting the importance of critical conditions, including the tungsten source concentration and Ar flow rate. Furthermore, the effectiveness of BO is demonstrated by comparison with random search, showing its ability to converge to optimal conditions with fewer iterations. This research highlights the potential of ML-driven approaches in accelerating material synthesis and optimization processes, paving the way for advances in two-dimensional (2D) material-based technologies.

PMID:39405090 | DOI:10.1021/acsami.4c15275

Ear Nose Throat J. 2024 Oct 15:1455613241290498. doi: 10.1177/01455613241290498. Online ahead of print.

ABSTRACT

Background: Nasal bone fractures are pretty common. The most common causes include interpersonal violence, traffic accidents, sports injuries, and falls. This study aimed to assess patients presenting with nasal bone fractures not only for nasal trauma but also for personality disorders, impulsivity, and attention-deficit/hyperactivity disorder (ADHD) using psychiatric questionnaires. Methods: The study included 41 patients, and the control group consisted of 43 volunteers without nasal bone fracture; neither the patients nor the volunteers had previously been diagnosed with or treated for psychiatric disorders. The psychiatric questionnaires administered were the Eysenck Personality Questionnaire Revised-Short Form (EPQR-S), the Barratt Impulsivity Scale-Short Form (BIS-11-SF), and Turgay’s Adult ADD/ADHD DSM-IV-based Scale. Results: The most common cause of nasal bone fractures in our study was violence (41.5%), followed by traffic accidents (29.3%), falls (17%), and sports injuries (12.2%). In the EPQR-S assessment, the nasal bone fracture (NBF) group had significantly-higher total scores than the control group (CG) (P < .001). In the subscales of the questionnaire, extroversion, psychoticism, and lie subscale scores were higher in the NBF group than in the CG. In the BIS-11-SF assessment, the NBF group had higher total scores than the CG (P < .001). Assessment using Turgay’s adult ADD/ADHD DSM IV-based diagnostic screening and rating scale revealed no statistically-significant difference between the NBF group and the CG in terms of attention deficit and hyperactivity. Conclusion: We found that psychoticism patterns and impulsivity were more prevalent in the patient group, whereas ADD/ADHD was not. The results of our study suggest that performing a psychiatric assessment may be the right decision in patients presenting with NBFs caused by violence, whether they are the aggressor or the victim.

PMID:39405071 | DOI:10.1177/01455613241290498

JAMA Netw Open. 2024 Oct 1;7(10):e2438526. doi: 10.1001/jamanetworkopen.2024.38526.

NO ABSTRACT

PMID:39405066 | DOI:10.1001/jamanetworkopen.2024.38526