Demographic Age Research Articles

Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort.

We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N=299), mild cognitive impairment (MCI; N=192), or dementia (DEM; N=65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). Plasma biomarkers differed across diagnostic groups (DEM>MCI>CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. Plasma biomarkers differ across diagnostic groups (DEM>MCI>CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.

A joinpoint analysis examining trends in firearm injuries at six us trauma centers from 2016 to 2022

BackgroundThere is an epidemic of firearm injuries in the United States since the mid-2000s. Thus, we sought to examine whether hospitalization from firearm injuries have increased over time, and to examine temporal changes in patient demographics, firearm injury intent, and injury severity.MethodsThis was a multicenter, retrospective, observational cohort study of patients hospitalized with a traumatic injury to six US level I trauma centers between 1/1/2016 and 6/30/2022. ICD-10-CM cause codes were used to identify and describe firearm injuries. Temporal trends were compared for demographics (age, sex, race, insured status), intent (assault, unintentional, self-harm, legal intervention, and undetermined), and severity (death, ICU admission, severe injury (injury severity score ≥ 16), receipt of blood transfusion, mechanical ventilation, and hospital and ICU LOS (days). Temporal trends were examined over 13 six-month intervals (H1, January–June; H2, July–December) using joinpoint regression and reported as semi-annual percent change (SPC); significance was p < 0.05.ResultsFirearm injuries accounted for 2.6% (1908 of 72,474) of trauma hospitalizations. The rate of firearm injuries initially declined from 2016-H1 to 2018-H2 (SPC = − 4.0%, p = 0.002), followed by increased rates from 2018-H2 to 2020-H1 (SPC = 9.0%, p = 0.005), before stabilizing from 2020-H1 to 2022-H1 (0.5%, p = 0.73). NH black patients had the greatest hospitalization rate from firearm injuries (14.0%) and were the only group to demonstrate a temporal increase (SPC = 6.3%, p < 0.001). The proportion of uninsured patients increased (SPC = 2.3%, p = 0.02) but there were no temporal changes by age or sex. ICU admission rates declined (SPC = − 2.2%, p < 0.001), but ICU LOS increased (SPC = 2.8%, p = 0.04). There were no significant changes over time in rates of death (SPC = 0.3%), severe injury (SPC = 1.6%), blood transfusion (SPC = 0.6%), and mechanical ventilation (SPC = 0.6%). When examined by intent, self-harm injuries declined over time (SPC = − 4.1%, p < 0.001), assaults declined through 2019-H2 (SPC = − 5.6%, p = 0.01) before increasing through 2022-H1 (SPC = 6.5%, p = 0.01), while undetermined injuries increased through 2019-H1 (SPC = 24.1%, p = 0.01) then stabilized (SPC = − 4.5%, p = 0.39); there were no temporal changes in unintentional injuries or legal intervention.ConclusionsHospitalizations from firearm injuries are increasing following a period of declines, driven by increases among NH Black patients. Trauma systems need to consider these changing trends to best address the needs of the injured population.

Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods

ABSTRACT Objectives To evaluate an artificial intelligence (AI) model in predicting soft tissue and alveolar bone changes following orthodontic treatment and compare the predictive performance of the AI model with conventional prediction models. Materials and Methods A total of 1774 lateral cephalograms of 887 adult patients who had undergone orthodontic treatment were collected. Patients who had orthognathic surgery were excluded. On each cephalogram, 78 landmarks were detected using PIPNet-based AI. Prediction models consisted of 132 predictor variables and 88 outcome variables. Predictor variables were demographics (age, sex), clinical (treatment time, premolar extraction), and Cartesian coordinates of the 64 anatomic landmarks. Outcome variables were Cartesian coordinates of the 22 soft tissue and 22 hard tissue landmarks after orthodontic treatment. The AI prediction model was based on the TabNet deep neural network. Two conventional statistical methods, multivariate multiple linear regression (MMLR) and partial least squares regression (PLSR), were each implemented for comparison. Prediction accuracy among the methods was compared. Results Overall, MMLR demonstrated the most accurate results, while AI was least accurate. AI showed superior predictions in only 5 of the 44 anatomic landmarks, all of which were soft tissue landmarks inferior to menton to the terminal point of the neck. Conclusions When predicting changes following orthodontic treatment, AI was not as effective as conventional statistical methods. However, AI had an outstanding advantage in predicting soft tissue landmarks with substantial variability. Overall, results may indicate the need for a hybrid prediction model that combines conventional and AI methods.

Post-COVIDmental health of librarians in Vietnam

This study aims to measure the mental well-being levels of librarians in Vietnamin the new normal context after the COVID-19 pandemic. The findings are expected to advocate for future policy interventions regarding mental health carefor staffin Vietnam’s librariesand information centerssince the pandemic has made coping with crises recognised globally as an integral part of life. On this ground, a survey was designed and administered online for librarians across Vietnam to self-rate their 5 dimensions of psychological generalwell-being using the WHO-5 [1]together with the Revised Life Orientation Test (LOT-R) [2],and Strahan-Gerbasi’s 1972 short version of the Marlow‐Crowne Social Desirability Scale [3].The survey shows despite the low mid-COVID mental health, there was a statisticallysignificant increase in mental health scores in the new normal. There are abouttwo-thirds of the surveyed librarians areinfected with COVID-19. For either the mid-or post-COVIDmental health, there was a statistically significant difference in scores between the infected and uninfected ones. Threeindependent-samplet-tests on genders, marital and parenthood statuses only found statistically significant differences in mid-and post-COVIDmental health scores between different marital and parenthood statuses, with the unmarried and the ones with no children scoring higher on both mid-and post-COVIDmental health over their counterparts. Eight one-way between-groups ANOVA tests conducted on a wide range of demographics (geographical area, library type, library size, age, seniority, position, specialization, and qualification) only showed statistically significant differences in mid- 2and post-COVIDmental health scores between different age groups, seniority levels, and types of position.

Demodex folliculorum (Trombidiformes: Demodecidae) infestation in medical students with facial dermatoses and healthy groups.

Demodex folliculorum (Simon, 1842) has been associated with various dermatological conditions. This study aimed to assess the prevalence of Demodex infestation in medical students with facial dermatoses compared with healthy medical students serving as controls. A total of 250 participants were enrolled, including 150 individuals with facial dermatoses and 100 healthy controls. Sampling was performed based on the standardized skin surface biopsy method. Demographic characteristics, specifically gender and age, were not statistically different between the patient and control groups. Among the facial dermatosis patients, 25 out of 150 (16.6%) were found to have Demodex infestation, while only three out of the 100 healthy controls (3%) exhibited infestations. The only identified species was D. folliculorum. The rates of Demodex infestation were significantly higher in the patients compared to the control groups. These findings indicate a higher prevalence of Demodex infestation among medical students with facial dermatosis, particularly in those diagnosed with folliculitis, acne vulgaris, and inflammatory papule, when compared to healthy controls. A better understanding of the relationship between D. folliculorum infestation and these dermatological conditions may lead to improved diagnostic and treatment strategies in the future.

The future of work in an ageing world: Priorities for advancing age equality at work

In an ageing world, age equality is critical for securing the future of work. Yet workplaces have not been designed with demographic ageing in mind, and age discrimination remains prevalent. This article offers a provocation to encourage the use of an age lens when considering the future of work and workplace change. It puts forward suggestions for future research and scholarship, to reframe equality law, and to build a research agenda that helps advance workplace equality for people of all ages.

Application of Patient-Reported Outcome Measurements in Adult Tumor Clinical Trials in China: Cross-Sectional Study.

International health policies and researchers have emphasized the value of evaluating patient-reported outcomes (PROs) in clinical studies. However, the characteristics of PROs in adult tumor clinical trials in China remain insufficiently elucidated. This study aims to assess the application and characteristics of PRO instruments as primary or secondary outcomes in adult randomized clinical trials related to tumors in China. This cross-sectional study identified tumor-focused randomized clinical trials conducted in China between January 1, 2010, and June 30, 2022. The ClinicalTrials.gov database and the Chinese Clinical Trial Registry were selected as the databases. Trials were classified into four groups based on the use of PRO instruments: (1) trials listing PRO instruments as primary outcomes, (2) trials listing PRO instruments as secondary outcomes, (3) trials listing PRO instruments as coprimary outcomes, and (4) trials without any mention of PRO instruments. Pertinent data, including study phase, settings, geographic regions, centers, participant demographics (age and sex), funding sources, intervention types, target diseases, and the names of PRO instruments, were extracted from these trials. The target diseases involved in the trials were grouped according to the American Joint Committee on Cancer Staging Manual, 8th Edition. Among the 6445 trials examined, 2390 (37.08%) incorporated PRO instruments as part of their outcomes. Within this subset, 26.82% (641/2390) listed PRO instruments as primary outcomes, 52.72% (1260/2390) as secondary outcomes, and 20.46% (489/2390) as coprimary outcomes. Among the 2,155,306 participants included in these trials, PRO instruments were used to collect data from 613,648 (28.47%) patients as primary or secondary outcomes and from 74,287 (3.45%) patients as coprimary outcomes. The most common conditions explicitly using specified PRO instruments included thorax tumors (217/1280, 16.95%), breast tumors (176/1280, 13.75%), and lower gastrointestinal tract tumors (173/1280, 13.52%). Frequently used PRO instruments included the European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire-30, the visual analog scale, the numeric rating scale, the Traditional Chinese Medicine Symptom Scale, and the Pittsburgh Sleep Quality Index. Over recent years, the incorporation of PROs has demonstrated an upward trajectory in adult randomized clinical trials on tumors in China. Nonetheless, the infrequent measurement of the patient's voice remains noteworthy. Disease-specific PRO instruments should be more effectively incorporated into various tumor disease categories in clinical trials, and there is room for improvement in the inclusion of PRO instruments as clinical trial end points.

Measuring User Experience Inclusivity in Human-AI Interaction via Five User Problem-Solving Styles

Motivations: Recent research has emerged on generally how to improve AI products’ Human-AI Interaction (HAI) User Experience (UX), but relatively little is known about HAI-UX inclusivity. For example, what kinds of users are supported, and who are left out? What product changes would make it more inclusive? Objectives: To help fill this gap, we present an approach to measuring what kinds of diverse users an AI product leaves out and how to act upon that knowledge. To bring actionability to the results, the approach focuses on users’ problem-solving diversity. Thus, our specific objectives were: (1) to show how the measure can reveal which participants with diverse problem-solving styles were left behind in a set of AI products; and (2) to relate participants’ problem-solving diversity to their demographic diversity, specifically gender and age. Methods: We performed 18 experiments, discarding two that failed manipulation checks. Each experiment was a 2x2 factorial experiment with online participants, comparing two AI products: one deliberately violating one of 18 HAI guideline and the other applying the same guideline. For our first objective, we used our measure to analyze how much each AI product gained/lost HAI-UX inclusivity compared to its counterpart, where inclusivity meant supportiveness to participants with particular problem-solving styles. For our second objective, we analyzed how participants’ problem-solving styles aligned with their gender identities and ages. Results &amp; Implications: Participants’ diverse problem-solving styles revealed six types of inclusivity results: (1) the AI products that followed an HAI guideline were almost always more inclusive across diversity of problem-solving styles than the products that did not follow that guideline—but “who” got most of the inclusivity varied widely by guideline and by problem-solving style; (2) when an AI product had risk implications, four variables’ values varied in tandem: participants’ feelings of control, their (lack of) suspicion, their trust in the product, and their certainty while using the product; (3) the more control an AI product offered users, the more inclusive it was; (4) whether an AI product was learning from “my” data or other people’s affected how inclusive that product was; (5) participants’ problem-solving styles skewed differently by gender and age group; and (6) almost all of the results suggested actions that HAI practitioners could take to improve their products’ inclusivity further. Together, these results suggest that a key to improving the demographic inclusivity of an AI product (e.g., across a wide range of genders, ages, etc.) can often be obtained by improving the product’s support of diverse problem-solving styles.

Bridging perceived organizational support with learning motivation and work engagement: the mediating role of focus on opportunity.

Perceived Organizational Support (POS) represents the extent to which employees believe their organization values their contributions and well-being. While higher POS is associated with increased work engagement and learning motivation, the intricacies of this relationship, especially the mediation by Occupational Future Time Perspective (OFTP), are not well understood. We conducted an online survey of 2,046 working individuals aged 20-69 to assess the relationships between POS and two outcome variables, Learning Goal Orientation (LGO), and work engagement with multiple regression analyses for all ages and in the younger age group (under 45). Then, the mediating effects of Focus on Opportunity (FOO) - a primary component of OFTP- on these relationships were examined. Of 2046 participants, 887 were younger than 45 years old. Younger participants, predominantly more educated and inclined towards professional jobs, exhibited higher LGO but lower work engagement compared to their older counterparts. POS showed positive correlations with LGO, and FOO significantly mediated the relationship, especially in the young group. Furthermore, a positive relationship between POS and work engagement was noted, with FOO as a partial mediator. POS correlates positively with both LGO and work engagement across various age demographics, with FOO critically mediating this relationship. To enhance employee engagement and learning motivation, organizations should emphasize bolstering both POS and FOO.

The Prevalence of Anemia Among Vietnamese Children: A Systematic Review and Meta-Analysis.

While anemia constitutes a prevalent health issue among children in Vietnam, comprehensive aggregate data remain scarce. Consequently, the objective of this meta-analysis is to establish the pooled prevalence of anemia in the pediatric population of Vietnam. A comprehensive systematic search of existing prevalence studies was conducted up until June 2022, encompassing databases such as PubMed, Scopus, and the Cochrane Library, as well as reference list analysis. Pooled prevalence estimates, along with 95% confidence intervals (CIs), were calculated using a random-effects model. Publication bias was assessed using the Egger regression test and funnel plot inspection. Subgroup analyses were performed to identify potential variations in anemia prevalence across study groups. The pooled prevalence estimate for anemia among children under 10-year-olds amounted to 35.5% (95% CI = [23.9, 49.1]). Notably, gender-specific analyses unveiled distinct prevalence rates, with 37.8% among males and 33.4% among females. Furthermore, variations in anemia prevalence among Vietnamese children were evident across different demographic strata, encompassing gender, age groups, and rural or poor rural residency. The calculated pooled prevalence of anemia among children in Vietnam revealed a significant burden. Addressing this issue necessitates targeted interventions within specific regions and the implementation of government policies aligned with global targets for the eradication of childhood anemia.

Orbital learning: a novel, actively orchestrated decentralised learning for healthcare

A novel collaborative and continual learning across a network of decentralised healthcare units, avoiding identifiable data-sharing capacity, is proposed. Currently available methodologies, such as federated learning and swarm learning, have demonstrated decentralised learning. However, the majority of them face shortcomings that affect their performance and accuracy. These shortcomings include a non-uniform rate of data accumulation, non-uniform patient demographics, biased human labelling, and erroneous or malicious training data. A novel method to reduce such shortcomings is proposed in the present work through selective grouping and displacing of actors in a network of many entities for intra-group sharing of learning with inter-group accessibility. The proposed system, known as Orbital Learning, incorporates various features from split learning and ensemble learning for a robust and secure performance of supervised models. A digital embodiment of the information quality and flow within a decentralised network, this platform also acts as a digital twin of healthcare network. An example of ECG classification for arrhythmia with 6 clients is used to analyse its performance and is compared against federated learning. In this example, four separate experiments are conducted with varied configurations, such as varied age demographics and clients with data tampering. The results obtained show an average area under receiver operating characteristic curve (AUROC) of 0.819 (95% CI 0.784–0.853) for orbital learning whereas 0.714 (95% CI 0.692–0.736) for federated learning. This result shows an increase in overall performance and establishes that the proposed system can address the majority of the issues faced by existing decentralised learning methodologies. Further, a scalability demo conducted establishes the versatility and scalability of this platform in handling state-of-the-art large language models.

Public Perceptions of Opioid Use for Chronic Non-Cancer Pain

Background: Chronic non-cancer pain affects 20% of Americans. This is significantly impacted by the ongoing opioid crisis and reduced opioid dispensing. Public perceptions additionally shape pain management strategies. Purpose: This study explores public attitudes toward prescription opioids for chronic non-cancer pain. We aim to understand how public attitudes are influenced by the evolving opioid crisis and shifting opioid use patterns. Methods: In Michigan, 823 adults participated in a Qualtrics survey on attitudes toward nonmedical and medical prescription opioid use. Multivariable logistic regression was performed to identify factors associated with beliefs that doctors prescribe opioids for too long (Model 1) and chronic pain patients should transition to alternative treatments (Model 2). Results: About half (49.4%) of respondents believed doctors keep patients on prescription opioids for too long, while two-thirds (65.7%) agreed chronic pain patients should be tapered off medications. Knowing someone who misused opioids and perceptions of substance use (e.g. perceived risk of prescription opioid misuse, stigma toward chronic pain patients, perceived prevalence of prescription opioid misuse, and awareness of fentanyl) were associated with greater odds of believing doctors keep patients on opioids too long. Demographics (age and education), substance use histories and perceptions (e.g. perceived risk and stigma) were associated with greater odds of believing patients should be tapered off their medication. Conclusions: These findings inform strategies to correct public misperceptions, emphasizing the importance of personal experience, perceived risks, and stigmatization of chronic pain patients. This insight can guide effective pain management for those with chronic non-cancer pain.

Development of a contextualized index of multiple deprivation for age-friendly cities: Evidence from Hong Kong

Deprivation refers to the state of having unmet basic needs, defined by societal standards. We argue that the mono emphasis on material deprivation is insufficient, as the characteristics of physical and social environments play a crucial role in either accelerating deprivation or providing additional resources/support to compensate for lack of income or basic household demands. We extend the focal point of the multiple deprivation framework to Hong Kong, an ultra-dense metropolis experiencing rapid demographic aging. We construct a Hong Kong index of multiple deprivation with seven domains. Highly deprived neighborhoods are likely to be located in areas with ultra-high residential density, where living conditions are substandard (e.g., subdivided units). Urban areas that used to have a large proportion of resettlement and industrial lands are likely to become deprived owing to the uneven distribution of urban amenities and the fragmentation of residential areas by industrial land.

Abstract PO2-29-04: An AI-based safeguard process to reduce aggressive missed cancers in dense breasts at screening mammography

Abstract Background: Dense breast tissue makes cancerous lesions difficult to identify on mammograms, resulting in many cancers missed at screening in patients with dense breasts. These missed cancers are then only diagnosed once they have grown to the point they can be more easily distinguished from the surrounding dense tissue. Dense breast tissue is more common in younger women, for whom early detection and diagnosis could lead to fewer years of life lost. This challenge motivated the FDA’s decision this year to require breast density to be included in patient reports, but notification does not solve the problem that these cancers are still often missed. Missing aggressive, fast growing cancers is particularly worrisome given they are more likely to progress to a stage where they are difficult to treat by the time they are detected in the future. Methods: A prospective study was conducted at one group practice of 6 radiologists over the course of 12 months to test a safeguard process to detect missed cancers so they could be treated more readily. AI software (Saige, DeepHealth, Inc.) was used to flag the most suspicious screening mammography exams that had not been recalled for work-up by an initial interpreting radiologist. An expert breast imager performed a safeguard review of each exam flagged. If the expert decided a recall was warranted, she would consult with the initial interpreting radiologist to decide if the patient should be recalled for further (diagnostic) imaging. Data was collected for each breast cancer diagnosed during this period. Patient data included breast density, age, and race. Cancer follow up data included pathology classification, hormone status, grade, staging, and Ki67 score. Aggressive cancers were identified as those with high grade (Grade 3), high Ki67 ( &amp;gt;=20%) or clinical stage of IIA or greater. A comparison was performed between cancers detected by the original interpreting radiologist and those detected through the safeguard process. Results: During the study period, 40,532 mammograms were obtained and 2,296 were flagged for safeguard review. The safeguard review led to 130 additional patient recalls and 41 additional cancer diagnoses. In women with dense breast tissue, 103 cancers were detected by routine interpretation and an additional 18 cancers (17.5%) detected through the safeguard process. In women without dense breast tissue, 116 cancers were detected by routine interpretation and 23 additional cancers were detected through the safeguard process. The cancers detected through the safeguard process included a larger percent of aggressive cancers (34.1% vs 30.6%, p=0.66) and more than double the percent of triple-negative cancers (9.8% vs 4.1%, p=0.13), though these differences were not statistically significant. The cancers detected through the safeguard process were from patients with similar demographics (age and race) to those whose cancers were detected by the interpreting radiologist. Conclusion: The AI-driven safeguard process results in a significant increase in breast cancers that would have been missed in patients with dense breast tissue. Many of the additional cancers were aggressive with almost 10% being triple-negative cancers. Without the safeguard process those aggressive cancers would not likely have been diagnosed until the next screening cycle in 1-2 years when treatment would likely have been less effective and outcomes poorer. Citation Format: Bryan Haslam, Jiye Kim, A. Gregory Soresen. An AI-based safeguard process to reduce aggressive missed cancers in dense breasts at screening mammography [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-29-04.

Does Game-Based Learning Promote Academic Engagement Amongst Millennial OMFS Residents?

BackgroundHouse staff participating in surgical residency programs are often comprised of adult learners from the millennial generation (Gen Y). With the increasing gap in both age and learning styles between these residents and their educators, their educators are struggling to keep them academically engaged. PurposeThe purpose of this study was to measure the association between implementing a digital online Jeopardy!® (Sony Pictures Studios, Culver City, CA) style game (digital game) (Factile© Solace Creative, LLC, Melbourne Beach, FL) into oral maxillofacial surgery (OMS) resident didactic training and Oral and Maxillofacial Surgery In-service Training Examination (OMSITE) scores. Study Design, Setting, SampleThis study was a retrospective cohort study conducted at The New York Presbyterian Hospital/Weill Cornell Medicine (NYP/WCM). OMS residents who took the OMSITE exam were included in the study. Exclusion criteria included OMS residents who did not take the OMSITE in a given year. Independent VariableThe independent variable was the timing of the implementation of the digital game, divided into before and after implementation. Main Outcome VariablesThe primary outcome variable was OMSITE scores. CovariatesCovariates included demographics (age, gender, race), year of training, and number of examination attempts. AnalysesDescriptive and bivariate statistics included Fisher's exact test and Wilcoxon rank sum test. Linear mixed modeling was performed to take into account multiple observations per participants. ResultsThe sample composed of 14 resident subjects with a median age of 27.5 [27.0, 28.7]. Females represented 29% of the cohort. Seventy-one percent of the participants were PGY-1. The median (interquartile range [IQR]) OMSITE score pre-implementation: 61 (48,71) and post-implementation: 79 (68,87). On average, the OMSITE scores, improved significantly following the implementation of this study modality (p < 0.001). ConclusionsDigital games may be an effective learning tool to prepare residents for OMSITE by promoting academic engagement.

Effect of cortisol and glycosylated-hemoglobin levels on mortality in intensive care unit.

To research the effects of blood cortisol and hemoglobinA1c (HBA1C) levels on mortality in patients admitted to the intensive care unit (ICU) and whether these factors could be used as reliable indicators for mortality risk assessment in these patients. After receiving approval from the ethics committee, 79 patients admitted to ICU were included in the study. From patient files, we collected data on demographics (age, gender), presence of diabetes mellitus, and levels of cortisol, HbA1C, glucose, and lactate measured during hospitalization, along with acute physiology and chronic health evaluation (APACHE) II scores calculated within the first 24 hours. In our study, we planned to investigate the relationship between patients' cortisol and HbA1C levels and mortality. A total of 79 patients were included in the study. The mortality rate of the patients included in the study was 65.8%. In the model established with all variables, only cortisol level (p=0.017) and APACHE II score (p=0.005) were defined to affect mortality. Cortisol levels at the time of admission to the ICU were found to affect mortality and can be considered a predictive factor, while HBA1C levels showed no such effect. Our findings indicate that neither cortisol nor HBA1C levels had an impact on the duration of mechanical ventilation or length of stay in the ICU.

The Spatio-Temporal Distribution of Suicide-related Emergency Calls in a European City: Age and Gender Patterns, and Neighborhood Influences.

Objective: The aim of this study was to conduct a comprehensive spatio-temporal analysis of suicide-related emergency calls in the city of Valencia (Spain) over a six-year period. To this end we first examined age and gender patterns and, second, the influence of neighborhood characteristics on general and gender-specific spatio-temporal patterns of suicide-related emergency calls. Method: Geocoded data on suicide-related emergency calls between 2017 and 2022 (N = 10,030) were collected from the 112 emergency service in Valencia. Data were aggregated at the census block group level, used as a proxy for neighborhoods, and trimesters were considered as the temporal unit. Two set of analyses were performed: (1) demographic (age and gender) and temporal descriptive analyses and (2) general and gender-specific Bayesian spatio-temporal autoregressive models. Results: Descriptive analyses revealed a higher incidence of suicide-related emergency calls among females and an increase in calls among the 18-23 age group from 2020 onwards. The general spatio-temporal model showed higher levels of suicide-related emergency calls in neighborhoods characterized by lower education levels and population density, and higher residential mobility, aging population, and immigrant concentration. Relevant gender differences were also observed. A seasonal effect was noted, with a peak in calls during spring for females and summer for males. Conclusions: These findings highlight the need for comprehensive mental health targeted interventions and preventive strategies that account for gender-specific disparities, age-related vulnerabilities, and the specific characteristics of neighborhoods.

Personal identification using frontal sinus coding methods: The effect of mixed image modality comparisons.

Several code-based methods have been created for comparing the frontal sinus in skeletal identification scenarios. However, little is known regarding matched-pair accuracy rates of these methods or how varying image modalities may affect these rates. The goals of this study were to validate the exclusion rates and to establish matched-pair accuracy rates of two well-cited coding methods, Cameriere etal. [23] and Tatlisumak etal. [24]. Additionally, individual variables were assessed for consistency in scoring between image modalities. Using a sample of U.S. African American, Native American, and European American females and males (n = 225), we examined individual variable scoring and string codes between two different image modalities (radiographs and CT-based 3D models). Arcades showed poor scoring consistency between modalities (p < 0.001). Although exclusion rates were similar to those reported in the original studies (93%-96%), matched-pair accuracy rates were low (13%-18%). None of the demographics (collection, sex, age, ancestry, and orientation) had an effect on the odds of a match. Interobserver and intraobserver analyses showed moderate to near-perfect agreement for all variables except supraorbital cells, which had minimal to no agreement. Currently, we do not recommend the application of these frontal sinus coding methods independent of other supporting identification methods given low variable consistency and accuracy rates. Visual identification should still be used to include or exclude an identification when using the frontal sinus.

Disparities in Metabolic Syndrome and Neurocognitive Function Among Older Hispanics/Latinos with Human Immunodeficiency Virus.

Neurocognitive impairment and metabolic syndrome (MetS) are prevalent in persons with HIV (PWH). We examined disparities in HIV-associated neurocognitive function between Hispanic and non-Hispanic White older PWH, and the role of MetS in explaining these disparities. Participants included 116 community-dwelling PWH aged 50-75 years enrolled in a cohort study in southern California [58 Hispanic (53% Spanish speaking) and 58 age-comparable non-Hispanic White; overall group: age: M = 57.9, standard deviation (SD) = 5.7; education (years): M = 13, SD = 3.4; 83% male, 58% AIDS, 94% on antiretroviral therapy]. Global neurocognition was derived from T-scores adjusted for demographics (age, education, sex, ethnicity, language) on a battery of 10 cognitive tests. MetS was ascertained via standard criteria that considered central obesity, and fasting elevated triglycerides, low high-density lipoprotein cholesterol and elevated glucose, or medical treatment for these conditions. Covariates examined included sociodemographic, psychiatric, substance use and HIV disease characteristics. Compared with non-Hispanic Whites, Hispanics showed worse global neurocognitive function (Cohen's d = 0.56, p < 0.05) and had higher rates of MetS (38% vs. 56%, p < 0.05). A stepwise regression model including ethnicity and significant covariates showed Hispanic ethnicity was the sole significant predictor of worse global neurocognition (B = -3.82, SE = 1.27, p < 0.01). A model also including MetS showed that both Hispanic ethnicity (B = -3.39, SE = 1.31, p = 0.01) and MetS (B = -2.73, SE = 1.31, p = 0.04) were independently associated with worse neurocognition. In conclusion, findings indicate that increased MetS is associated with worse neurocognitive function in both Hispanic and non-Hispanic White older PWH, but does not explain neurocognitive disparities. MetS remains an important target for intervention efforts to ameliorate neurocognitive dysfunction among diverse older PWH.

The ‘demographic winter’ in Italy: Crisis factors, problematic issues and policy actions

Demographic issues are becoming key to the debate on the future of Europe, and of Italy in particular, which has the lowest birth rate in Europe but is among the top-ranked countries for demographic ageing. The general improvement of living conditions and the ageing of large cohorts cannot be supported by the economic activity of the younger generations, which calls into question the security of certain aspects of the social pact, such as the provision of pensions and health care. While encouraging an awareness among Italians of the trends and problems they will have to deal with, all national actors must cooperate to ensure the recovery of the birth rate, and to harness the economic benefits of incoming migrants and the experiences of older people. It is equally necessary to meet the needs of young people and enhance their social role. Only through such cooperation will it be possible to create a favourable climate for actions that will allow us to control and direct these demographic phenomena and not to suffer from them.