Category: Statistics

Comput Biol Med. 2024 Dec 1;184:109484. doi: 10.1016/j.compbiomed.2024.109484. Online ahead of print.

ABSTRACT

BACKGROUND: Sleep spindles may be implicated in sensing and regulation of peripheral glucose. Whether spindle density in patients with type 2 diabetes mellitus (T2DM) differs from that of healthy subjects is unknown.

METHODS: Our retrospective analysis of polysomnography (PSG) studies identified 952 patients with T2DM and 952 sex-, age- and BMI-matched control subjects. We extracted spindles from PSG electroencephalograms and used rank-based statistical methods to test for differences between subjects with and without diabetes. We also explored potential modifiers of spindle density differences. We replicated our analysis on independent data from the Sleep Heart Health Study.

RESULTS: We found that patients with T2DM exhibited about half the spindle density during sleep as matched controls (P < 0.0001). The replication dataset showed similar trends. The patient-minus-control paired difference in spindle density for pairs where the patient had major complications were larger than corresponding paired differences in pairs where the patient lacked major complications, despite both patient groups having significantly lower spindle density compared to their respective control subjects. Patients with a prescription for a glucagon-like peptide 1 receptor agonist had significantly higher spindle density than those without one (P ≤ 0.03). Spindle density in patients with T2DM monotonically decreased as their highest recorded HbA1C level increased (P ≤ 0.003).

CONCLUSIONS: T2DM patients had significantly lower spindle density than control subjects; the size of that difference was correlated with markers of disease severity (complications and glycemic control). These findings expand our understanding of the relationships between sleep and glucose regulation.

PMID:39622099 | DOI:10.1016/j.compbiomed.2024.109484

Burns. 2024 Nov 9;51(1):107311. doi: 10.1016/j.burns.2024.107311. Online ahead of print.

ABSTRACT

INTRODUCTION: Burn-related fatalities pose a significant global public health challenge, with a substantial impact on the elderly population. This study examines two decades of burn-related mortality data in the United States, aiming to understand the trends, disparities, and contributing factors among adults aged 65 and older.

OBJECTIVES: The primary objectives of this study are to (1) analyze the trends in burn-related mortality rates among older adults, (2) investigate disparities based on gender, race and geographic regions, and (3) identify comorbidities and complications associated with burn-related deaths in this demographic.

METHODS: Data were obtained from the Centers for Disease Control and Prevention (CDC) using the National Center for Health Statistics database. The study cohort consists of individuals aged 65 and older who experienced burn-related deaths between 1999 and 2020. Various demographic variables, including age, sex, race/ethnicity, and location of death, were considered. The study also examined urban-rural classifications and regional differences. Mortality rates were calculated and adjusted for age. Joinpoint regression analysis was employed to assess trends in age-adjusted mortality rates over time. Modes of death and common comorbidities and complications were analyzed.

RESULTS: Between 1999 and 2020, a total of 96,498 older adults succumbed to burn injuries in the United States. Analysis revealed a concerning increase in burn-related mortality rates from 2012 onwards. Demographic disparities were evident, with older men consistently exhibiting higher mortality rates compared to women. Racial disparities were observed, with Black individuals experiencing the highest mortality burden. Geographic analysis indicated elevated mortality rates in Western states and rural areas. Accidents emerged as the leading cause of death, with ischemic heart disease and hypertensive diseases being prevalent comorbidities. Complications, with septicemia being the most common, contribute significantly to mortality.

CONCLUSION: Our analysis of 20 years of burn-related mortality data from the CDC reveals alarming trends in the United States. Unlike global trends, mortality rates have stagnated from 1999 to 2020, indicating a persistent public health challenge. Black individuals aged over 65 bear the brunt of burn-related mortality, facing the highest age-adjusted rates among all racial groups. Regional disparities are stark, with states in the top 90 % exhibiting significantly higher age-adjusted mortality rates compared to those in the bottom 10 %. Moreover, rural areas consistently report higher mortality rates than urban areas. Ischemic heart disease, hypertensive diseases, and other heart-related conditions emerge as prevalent comorbidities. To effectively reduce burn-related injuries and fatalities, targeted public health policies are imperative. These interventions must prioritize high-risk populations and adopt culturally sensitive approaches to promote safety. Additionally, enhancing access to healthcare and fire safety education is vital for mitigating the burden of burn-related mortality among the elderly population.

PMID:39622090 | DOI:10.1016/j.burns.2024.107311

Ann Intern Med. 2024 Dec 3. doi: 10.7326/M23-3166. Online ahead of print.

ABSTRACT

BACKGROUND: Accounting for race and ethnicity in estimating disease risk may improve the accuracy of predictions but may also encourage a racialized view of medicine.

OBJECTIVE: To present a decision analytic framework for considering the potential benefits of race-aware over race-unaware risk predictions, using cardiovascular disease, breast cancer, and lung cancer as case studies.

DESIGN: Cross-sectional study.

SETTING: NHANES (National Health and Nutrition Examination Survey), 2011 to 2018, and NLST (National Lung Screening Trial), 2002 to 2004.

PATIENTS: U.S. adults.

MEASUREMENTS: Starting with risk predictions from clinically recommended race-aware models, the researchers generated race-unaware predictions via statistical marginalization. They then estimated the utility gains of the race-aware over the race-unaware models, based on a simple utility function that assumes constant costs of screening and constant benefits of disease detection.

RESULTS: The race-unaware predictions were substantially miscalibrated across racial and ethnic groups compared with the race-aware predictions as the benchmark. However, the clinical net benefit at the population level of race-aware predictions over race-unaware predictions was smaller than expected. This result stems from 2 empirical patterns: First, across all 3 diseases, 95% or more of individuals would receive the same decision regardless of whether race and ethnicity are included in risk models; second, for those who receive different decisions, the net benefit of screening or treatment is relatively small because these patients have disease risks close to the decision threshold (that is, the theoretical “point of indifference”). When used to inform rationing, race-aware models may have a more substantial net benefit.

LIMITATIONS: For illustrative purposes, the race-aware models were assumed to yield accurate estimates of risk given the input variables. The researchers used a simplified approach to generate race-unaware risk predictions from the race-aware models and a simple utility function to compare models.

CONCLUSION: The analysis highlights the importance of foregrounding changes in decisions and utility when evaluating the potential benefit of using race and ethnicity to estimate disease risk.

PRIMARY FUNDING SOURCE: The Greenwall Foundation.

PMID:39622056 | DOI:10.7326/M23-3166

J Med Internet Res. 2024 Dec 2;26:e54127. doi: 10.2196/54127.

ABSTRACT

BACKGROUND: The project of scaling up noncommunicable disease (NCD) interventions in Southeast Asia aimed to strengthen the prevention and control of hypertension and diabetes, focusing on primary health care and community levels. In Vietnam, health volunteers who were members of the Intergenerational Self-Help Clubs (ISHCs) implemented community-based NCD screening and health promotion activities in communities. The ISHC health volunteers used an app based on District Health Information Software, version 2 (DHIS2) tracker (Society for Health Information Systems Programmes, India) to record details of participants during screening and other health activities.

OBJECTIVE: This study aimed to assess the strengths, barriers, and limitations of the NCD screening app used by the ISHC health volunteers on tablets and to provide recommendations for further scaling up.

METHODS: A mixed methods observational study with a convergent parallel design was performed. For the quantitative data analysis, 2 rounds of screening data collected from all 59 ISHCs were analyzed on completeness and quality. For the qualitative analysis, 2 rounds of evaluation of the screening app were completed. Focus group discussions with ISHC health volunteers and club management boards and in-depth interviews with members of the Association of the Elderly and Commune Health Station staff were performed.

RESULTS: In the quantitative analysis, data completeness of all 6704 screenings (n=3485 individuals) was very high. For anthropomorphic measurements, such as blood pressure, body weight, and abdominal circumference, less than 1% errors were found. The data on NCD risk factors were not adequately recorded in 1908 (29.5%) of the screenings. From the qualitative analysis, the NCD screening app was appreciated by ISHC health volunteers and supervisors, as an easier and more efficient way to report to higher levels, secure data, and strengthen relationships with relevant stakeholders, using tablets to connect to the internet and internet-based platforms to access information for self-learning and sharing to promote a healthy lifestyle as the strengths. The barriers and limitations reported by the respondents were a non-age-friendly app, incomplete translation of parts of the app into Vietnamese, some issues with the tablet’s display, lack of sharing of responsibilities among the health volunteers, and suboptimal involvement of the health sector; limited digital literacy among ISHC health volunteers. Recommendations are continuous capacity building, improving app issues, improving tablet issues, and involving relevant stakeholders or younger members in technology adoption to support older people.

CONCLUSIONS: The implementation of the NCD screening app by ISHC volunteers can be an effective way to improve community-led NCD screening and increase the uptake of NCD prevention and management services at the primary health care level. However, our study has shown that some barriers need to be addressed to maximize the efficient use of the app by ISHC health volunteers to record, report, and manage the screening data.

PMID:39622043 | DOI:10.2196/54127

J Med Internet Res. 2024 Dec 2;26:e54015. doi: 10.2196/54015.

ABSTRACT

BACKGROUND: There is a pressing need to understand the implications of the rapid adoption of virtual primary care for people with opioid use disorder. Potential impacts, including disruptions to opiate agonist therapies, and the prospect of improved service accessibility remain underexplored.

OBJECTIVE: This scoping review synthesized current literature on virtual primary care for people with opioid use disorder with a specific focus on benefits, challenges, and strategies.

METHODS: We followed the Joanna Briggs Institute methodological approach for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist for reporting our findings. We conducted searches in MEDLINE, Web of Science, CINAHL Complete, and Embase using our developed search strategy with no date restrictions. We incorporated all study types that included the 3 concepts (ie, virtual care, primary care, and people with opioid use disorder). We excluded research on minors, asynchronous virtual modalities, and care not provided in a primary care setting. We used Covidence to screen and extract data, pulling information on study characteristics, health system features, patient outcomes, and challenges and benefits of virtual primary care. We conducted inductive content analysis and calculated descriptive statistics. We appraised the quality of the studies using the Quality Assessment With Diverse Studies tool and categorized the findings using the Consolidated Framework for Implementation Research.

RESULTS: Our search identified 1474 studies. We removed 36.36% (536/1474) of these as duplicates, leaving 938 studies for title and abstract screening. After a double review process, we retained 3% (28/938) of the studies for extraction. Only 14% (4/28) of the studies were conducted before the COVID-19 pandemic, and most (15/28, 54%) used quantitative methodologies. We summarized objectives and results, finding that most studies (18/28, 64%) described virtual primary care delivered via phone rather than video and that many studies (16/28, 57%) reported changes in appointment modality. Through content analysis, we identified that policies and regulations could either facilitate (11/28, 39%) or impede (7/28, 25%) the provision of care virtually. In addition, clinicians’ perceptions of patient stability (5/28, 18%) and the heightened risks associated with virtual care (10/28, 36%) can serve as a barrier to offering virtual services. For people with opioid use disorder, increased health care accessibility was a noteworthy benefit (13/28, 46%) to the adoption of virtual visits, whereas issues regarding access to technology and digital literacy stood out as the most prominent challenge (12/28, 43%).

CONCLUSIONS: The available studies highlight the potential for enhancing accessibility and continuous access to care for people with opioid use disorder using virtual modalities. Future research and policies must focus on bridging gaps to ensure that virtual primary care does not exacerbate or entrench health inequities.

PMID:39622042 | DOI:10.2196/54015

Nurs Adm Q. 2025 Jan-Mar 01;49(1):35-43. doi: 10.1097/NAQ.0000000000000661. Epub 2024 Dec 3.

ABSTRACT

This systematic review aims to evaluate the effectiveness of simulation in enhancing the knowledge and skills required for preventing, managing, and treating pressure injuries (PIs) among nursing students. A systematic review of English articles published between January 1, 2014, and March 31, 2024, was conducted to determine the effectiveness of simulation in PI education. PubMed, Cochrane Library, Medline (OVID), Scopus, Web of Science, CINAHL, and Science Direct databases were searched using the keywords “simulation”, “pressure ulcer”, “pressure injury”, “nursing”, and “nursing education”. The study data were analyzed using the content analysis method. Of the 101 articles retrieved from the databases, 5 met the eligibility criteria. The study found that simulation in PI prevention and management education increased students’ knowledge and skill levels, enhanced their satisfaction and communication skills, and was more effective than traditional didactic education. This systematic review supports the use of simulation as an educational tool for nursing students in preventing, implementing protective interventions, and managing PI. Furthermore, it encourages further research to explore the role and effectiveness of different formats of simulation, particularly high-fidelity simulation, in PI management education and their impact on student achievement and clinical practice.

PMID:39622032 | DOI:10.1097/NAQ.0000000000000661

JMIR Public Health Surveill. 2024 Dec 2;10:e63195. doi: 10.2196/63195.

ABSTRACT

BACKGROUND: Suicide remains a public health priority worldwide with over 700,000 deaths annually, ranking as a leading cause of death among young adults. Traditional research methodologies have often fallen short in capturing the multifaceted nature of suicide, focusing on isolated risk factors rather than the complex interplay of individual, social, and environmental influences. Recognizing these limitations, there is a growing recognition of the value of dynamic simulation modeling to inform suicide prevention planning.

OBJECTIVE: This systematic review aims to provide a comprehensive overview of existing dynamic models of population-level suicide and suicide-related behaviors, and to summarize their methodologies, applications, and outcomes.

METHODS: Eight databases were searched, including MEDLINE, Embase, PsycINFO, Scopus, Compendex, ACM Digital Library, IEEE Xplore, and medRxiv, from inception to July 2023. We developed a search strategy in consultation with a research librarian. Two reviewers independently conducted the title and abstract and full-text screenings including studies using dynamic modeling methods (eg, System Dynamics and agent-based modeling) for suicide or suicide-related behaviors at the population level, and excluding studies on microbiology, bioinformatics, pharmacology, nondynamic modeling methods, and nonprimary modeling reports (eg, editorials and reviews). Reviewers extracted the data using a standardized form and assessed the quality of reporting using the STRESS (Strengthening the Reporting of Empirical Simulation Studies) guidelines. A narrative synthesis was conducted for the included studies.

RESULTS: The search identified 1574 studies, with 22 studies meeting the inclusion criteria, including 15 System Dynamics models, 6 agent-based models, and 1 microsimulation model. The studies primarily targeted populations in Australia and the United States, with some focusing on hypothetical scenarios. The models addressed various interventions ranging from specific clinical and health service interventions, such as mental health service capacity increases, to broader social determinants, including employment programs and reduction in access to means of suicide. The studies demonstrated the utility of dynamic models in identifying the synergistic effects of combined interventions and understanding the temporal dynamics of intervention impacts.

CONCLUSIONS: Dynamic modeling of suicide and suicide-related behaviors, though still an emerging area, is expanding rapidly, adapting to a range of questions, settings, and contexts. While the quality of reporting was overall adequate, some studies lacked detailed reporting on model transparency and reproducibility. This review highlights the potential of dynamic modeling as a tool to support decision-making and to further our understanding of the complex dynamics of suicide and its related behaviors.

TRIAL REGISTRATION: PROSPERO CRD42022346617; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346617.

PMID:39622024 | DOI:10.2196/63195

JMIR Form Res. 2024 Dec 2;8:e51470. doi: 10.2196/51470.

ABSTRACT

BACKGROUND: The implementation of COVID-19 lockdown measures had immediate and delayed psychological effects. From March 27, 2022, to June 1, 2022, the Shanghai government enforced a city-wide lockdown that affected 25 million residents. During this period, mental health services were predominantly provided through digital platforms. However, limited knowledge exists regarding the general population’s intention to use mental health services during this time.

OBJECTIVE: This study aimed to assess the intention of Shanghai residents to use mental health services during the 2022 Shanghai lockdown and identify factors associated with the intention to use mobile mental health services.

METHODS: An online survey was distributed from April 29 to June 1, 2022, using a purposive sampling approach across 16 districts in Shanghai. Eligible participants were adults over 18 years of age who were physically present in Shanghai during the lockdown. Multivariable logistic regression was used to estimate the associations between demographic factors, lockdown-related stressors and experiences, physical and mental health status, and study outcomes-mobile mental health service use intention (mobile applications and WeChat Mini Programs [Tencent Holdings Limited]).

RESULTS: The analytical sample comprised 3230 respondents, among whom 29.7% (weighted percentage; n=1030) screened positive for depression or anxiety based on the 9-item Patient Health Questionnaire or the 7-item Generalized Anxiety Disorder Scale. Less than one-fourth of the respondents (24.4%, n=914) expressed an intention to use any form of mental health services, with mobile mental health service being the most considered option (19.3%, n=728). Only 10.9% (n=440) used digital mental health services during the lockdown. Factors associated with increased odds of mobile mental health service use intention included being female, being employed, being a permanent resident, experiencing COVID-19-related stressors (such as loss of income, food insecurity, and potentially traumatic experiences), and having social and financial support. Individuals with moderate or severe anxiety, as well as those with comorbid anxiety and depression, demonstrated a higher intention to use mobile mental health services. However, individuals with depression alone did not exhibit a significantly higher intention compared with those without common mental disorders.

CONCLUSIONS: Despite a high prevalence of common mental disorders among Shanghai residents, less than one-fourth of the study respondents expressed an intention to use any form of mental health services during the lockdown. Mobile apps or WeChat Mini Programs were the most considered mental health service formats. The study provided insights for developing more person-centered mobile mental health services to meet the diverse needs of different populations.

PMID:39622023 | DOI:10.2196/51470

J Urol. 2024 Dec 2:101097JU0000000000004348. doi: 10.1097/JU.0000000000004348. Online ahead of print.

ABSTRACT

PURPOSE: Post-operative prognostic tools allow for improved prediction of future recurrence risk, patient counselling, assessment of eligibility for adjuvant treatments, and ensure appropriate follow-up surveillance. The purpose of this analysis is to validate existing prognostic models for patients with kidney cancer.

MATERIALS AND METHODS: The Canadian Kidney Cancer Information System (CKCis) is a prospective cohort of patients managed at 14 institutions since January 1, 2011, to present. CKCis was used to assess 15 predictive models for kidney cancer recurrence, 6 for cancer specific mortality, and 4 for all-cause mortality in patients with a solitary, non-metastatic kidney tumor treated with surgery (partial or radical nephrectomy). Discrimination was measured using c-statistics, 5-year calibration plots for calibration, and decision curve analysis at 5-years post-surgery for net-benefit when considering adjuvant therapy.

RESULTS: 7,174 patients were included. For kidney cancer recurrence, c-statistics ranged from 0.62 to 0.83, depending on whether the model was derived, and applied, to all patients without further stratification, specific risk groups, or to specific histological subtypes. Cancer specific mortality models had c-statistics ranging from 0.60 to 0.89 and all-cause mortality models from 0.60 to 0.73. Using decision curve analysis in clear-cell patients, the best models for choosing adjuvant therapy to prevent recurrence and cancer-related death were the Mayo Clinic prediction models.

CONCLUSIONS: Model performance varied considerably with some suitable for clinical use. If using prediction models to select adjuvant therapy, the Mayo Clinic models were best when applied to a large contemporary cohort of Canadian patients.

TAKE HOME MESSAGE: The performance of kidney cancer predictive models varied greatly when applied to a large contemporary cohort. We identified the most accurate models to use when counseling patients about prognosis and adjuvant therapy.

PMID:39622017 | DOI:10.1097/JU.0000000000004348

Neural Comput. 2024 Dec 2:1-33. doi: 10.1162/neco_a_01730. Online ahead of print.

ABSTRACT

Hebbian learning theory is rooted in Pavlov’s classical conditioning While mathematical models of the former have been proposed and studied in the past decades, especially in spin glass theory, only recently has it been numerically shown that it is possible to write neural and synaptic dynamics that mirror Pavlov conditioning mechanisms and also give rise to synaptic weights that correspond to the Hebbian learning rule. In this letter we show that the same dynamics can be derived with equilibrium statistical mechanics tools and basic and motivated modeling assumptions. Then we show how to study the resulting system of coupled stochastic differential equations assuming the reasonable separation of neural and synaptic timescale. In particular, we analytically demonstrate that this synaptic evolution converges to the Hebbian learning rule in various settings and compute the variance of the stochastic process. Finally, drawing from evidence on pure memory reinforcement during sleep stages, we show how the proposed model can simulate neural networks that undergo sleep-associated memory consolidation processes, thereby proving the compatibility of Pavlovian learning with dreaming mechanisms.

PMID:39622007 | DOI:10.1162/neco_a_01730