Tag: pubmed

Popul Health Metr. 2025 Jun 6;23(1):22. doi: 10.1186/s12963-025-00386-w.

ABSTRACT

BACKGROUND: In this scoping review, we aimed to examine evidence on methods used to construct disability indicators in linked administrative datasets and describe the approaches used to assess the validity of the indicators.

METHODS: Medline (Ovid) and Embase (Ovid) were searched for studies published between January 2010 and June 2023. Original, peer-reviewed studies that aimed to construct a disability indicator using linked administrative data sources were included. Studies identifying any types of disability were included, but not those which defined the target population in terms of specific health conditions. We produced a narrative synthesis of findings related to disability indicator construction methods and validation approaches.

RESULTS: Thirty-six relevant studies were included, with 30 of those identifying a cohort of people with intellectual and/or developmental disability. Health data sources were most commonly used for indicator construction, with 33 of the studies using at least one health data source. Disability and education sector data sources were also commonly used. Diagnostic codes were used for disability identification in 34 of the 36 studies; 16 used diagnostic codes alone and 18 used diagnostic codes along with other information. A subgroup of 19 studies had a primary aim to create a disability cohort or estimate disability prevalence. Thirteen of these 19 studies compared their estimated prevalence rates with previously published estimates. Only five studies conducted testing to investigate the extent to which their derived disability indicator captured the intended target population.

DISCUSSION: We found a paucity of evidence on methods for identifying a target population of people with diverse disabilities. In the existing literature, diagnostic information is relied upon heavily for disability identification, likely due to a lack of other types of disability-relevant information in administrative data sources. Use of derived disability indicators within linked data holds potential to advance research regarding people with disability. It is crucial, however, to conduct and report validation testing to understand the strengths and limitations of the indicators and inform their use for specific purposes.

PMID:40481580 | DOI:10.1186/s12963-025-00386-w

BMC Nurs. 2025 Jun 6;24(1):650. doi: 10.1186/s12912-025-03311-6.

ABSTRACT

BACKGROUND & AIM: Migration is a phenomenon that both developed and developing countries are struggling with. Given that the decision to migrate is formed during the student period, the present study aimed to compare the degree of intention to migrate and related factors in undergraduate nursing students at universities of medical sciences in Kerman, Iran and Erbil, Iraq in 2023.

METHODS: This cross-sectional descriptive study focused on a sample of nursing students from Kerman University of Medical Sciences, Polytechnic, and Hawler University of Iraq. To ensure a representative sample, a simple random sampling method was utilized. The sample size conducted on 487 nursing students. 272 students selected from Kerman University of Medical Sciences and 215 students from Erbil University in Iraq. Data collection was performed using a structured questionnaire, which included items related to the intention to migrate, factors influencing this intention, and demographic information. The collected data were analyzed using both descriptive and correletional statistical methods, And SPSS-22 software was used.

FINDINGS: The data revealed that 69.5% of Iranian nursing students and 58.1% of Iraqi nursing students intended to emigrate. The most important reasons for the intention to migrate among Iranian students were better quality of life (4.39), the balance between income and living expenses (4.35), and economic and social stability (4.34). In addition, Iraqi students reported better quality of life (3.89), professors’ behavior with students (3.70), and professors’ teaching methods (3.56) as the reasons behind their intention to migrate.

CONCLUSION: Iranian and Iraqi nursing students had a significant intention to migrate. Thus, effective policies should be adopted to reduce the intention to migrate among nursing students. Moreover, interventional studies need to explore the factors that can motivate this group of students to stay in the country.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40481576 | DOI:10.1186/s12912-025-03311-6

Diabetol Metab Syndr. 2025 Jun 7;17(1):198. doi: 10.1186/s13098-025-01729-1.

ABSTRACT

BACKGROUND: Serum Klotho, a biomarker associated with anti-aging, has been implicated in kidney disease. However, there is a lack of robust evidence for the relationship between the serum Klotho and diabetic kidney disease (DKD). This study aimed to investigate the association of the serum Klotho levels with DKD and assess the relationship between serum Klotho and all-cause mortality in individuals with DKD.

METHODS: We utilized data from the 2007-2016 National Health and Nutrition Examination Survey (NHANES), incorporating both cross-sectional and cohort study designs. The association between the serum Klotho and DKD was examined using weighted logistic regression models. To estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause mortality, weighted Çox proportional hazards models were applied. Restricted cubic spline analysis was used to assess the linear or nonlinear relationships between the serum Klotho and DKD or all-cause mortality. Additionally, mediation analysis was conducted to determine whether the systemic immune-inflammatory index (SII) mediated the effect of serum Klotho on all-cause mortality.

RESULTS: Our findings revealed a significant reverse association between serum Klotho and DKD after adjusting for sociodemographic and lifestyle factors in Model 2 (odds ratio [OR] 0.65, 95% CI 0.47-0.90, P = 0.01). However, this association was attenuated and lost statistical significance after further adjustment for comorbidities, SII, estimated glomerular filtration rate, and urine albumin/creatinine ratio in Model 3 (OR 0.65, 95% CI 0.32-1.31, P = 0.2). During an average follow-up period of 76 months, a total of 795 individuals (34%) experienced mortality. Weighted multivariate Cox regression models indicated that each one-unit increase in the serum Klotho was associated with a reduced risk of all-cause mortality (HR 0.48, 95% CI 0.29-0.82, P = 0.008) in DKD patients. Furthermore, restricted cubic spline analysis identified a nonlinear relationship between the serum Klotho and DKD (P for nonlinearity < 0.001), while a linear relationship was observed between serum Klotho and all-cause mortality (P for nonlinearity = 0.3480) among DKD populations. Stratified and interaction analysis confirmed the robustness of these core findings. Additionally, SII was found to partially mediate the association between serum Klotho and all-cause mortality, accounting for 5.7% of the effect.

CONCLUSIONS: Serum Klotho is inversely associated with the prevalence of DKD and is also linked to reduced all-cause mortality in individuals with DKD.

PMID:40481564 | DOI:10.1186/s13098-025-01729-1

Arch Public Health. 2025 Jun 6;83(1):143. doi: 10.1186/s13690-025-01633-0.

ABSTRACT

BACKGROUND: SARS-CoV-2 (COVID-19) has emerged as a significant global public health challenge, revealing critical vulnerabilities within health systems worldwide. While extensive data on COVID-19 is available from high-income countries, information remains scarce in lower-income regions, particularly regarding its impact on pregnant women. This study aims to evaluate the burden of COVID-19 among pregnant women and its effects on maternal and birth outcomes during the third wave in Benin.

METHODS: A cross-sectional, hospital-based survey was conducted from May 19 to September 19, 2022, at the Lagune Mother and Child Teaching Hospital. A standardized questionnaire was administered, and nasal swabs along with serological analysis were performed on 437 pregnant women. Multivariate logistic regression was used to assess risk factors and evaluate the impact of previous or current COVID-19 exposure on maternal and birth adverse outcomes.

RESULTS: SARS-CoV-2 was detected in less than 1% of pregnant women through PCR testing of nasal swab samples. Among the study population, 14.4% of women were vaccinated against COVID-19. A total of 81.1% of women tested positive for antibodies, suggesting prior exposure or infection to SARS-CoV-2 or vaccination. Notably, 78.6% of unvaccinated women had detectable antibodies, which serves as a more accurate proxy for infection prevalence. No significant association was found between prior COVID-19 exposure and adverse maternal and birth outcomes (aOR: 0.48, 95% CI 0.15-1.51).

CONCLUSIONS: Although PCR testing revealed a low incidence of active SARS-CoV-2 infection, the high prevalence of IgG antibodies among pregnant women suggests widespread prior exposure or infection. Vaccination was identified as a strong predictor of detectable IgG antibodies. Notably, despite the presence of antibodies, no significant association was found between prior COVID-19 exposure and adverse maternal or birth outcomes. These findings highlight the need for further research to explore the potential long-term effects of COVID-19 infection on pregnancy outcomes and to better understand the relationship between antibody presence and maternal and fetal health.

PMID:40481557 | DOI:10.1186/s13690-025-01633-0

Chin Med. 2025 Jun 6;20(1):80. doi: 10.1186/s13020-025-01127-9.

ABSTRACT

This study addresses limitations of mainstream approaches in traditional Chinese medicine (TCM) data mining by developing the SinoMedminer R package and its Shiny web application. The R package’s core functionalities include data cleaning, transformation, TCM attribute statistics, association rule exploration and analysis, clustering analysis, co-occurrence network analysis, formula similarity analysis, formula identification, and dosage analysis. This package enables efficient project analyses without requiring complex coding. The accompanying Shiny web application provides an interactive, menu-driven interface for users without programming knowledge. SinoMedminer combines the computational power of a programming language with user-friendly accessibility, significantly enhancing the efficiency and standardization of TCM data mining research. A deployed server platform further simplifies access and usability by allowing direct utilization of the Shiny application. By optimizing data processing and analysis workflows, SinoMedminer enhances big data handling capabilities, accelerates research progress and product development, and promotes the integration of digital technologies into TCM research and clinical practice.

PMID:40481553 | DOI:10.1186/s13020-025-01127-9

Inj Epidemiol. 2025 Jun 6;12(1):31. doi: 10.1186/s40621-025-00583-z.

ABSTRACT

BACKGROUND: The injury rate is a common measure of injury occurrence in epidemiological surveillance and is used to express the incidence of injuries as a function of both the population at risk as well as at-risk exposure time. Traditional approaches to surveillance-based injury rates use a frequentist perspective; here, we discuss the Bayesian perspective and present a practical framework on how to apply a Bayesian analysis to estimate injury rates. We estimated finescale injury rates across a broad range of categories for men’s and women’s soccer, applying a Bayesian methodology and using injury surveillance data captured within the National Collegiate Athletic Association Injury Surveillance Program from 2014/15-2018/19.

RESULTS: Through an iterative process of assessing model fidelity, we found that a negative binomial model was an effective choice for modeling surveillance-based injury rates. We also found differences between schools to be a key driver of variation in injury rates.

CONCLUSIONS: Our findings indicate that the Bayesian framework naturally characterizes injury rates by modeling injury counts as outcomes of an underlying data-generation process that explicitly incorporates inherent uncertainty, complementing traditional frequentist approaches. Key benefits of the Bayesian approach in this context are the ability to test model suitability in a variety of methods, and to be able to generate plausible estimates with sparse data.

PMID:40481549 | DOI:10.1186/s40621-025-00583-z

BMC Nutr. 2025 Jun 6;11(1):113. doi: 10.1186/s40795-025-01090-6.

ABSTRACT

BACKGROUND: Coconut oil has been suggested as a potential dietary intervention for weight management. However, the evidence regarding the effects of coconut oil supplementation on anthropometric measures (body weight, body mass index (BMI) and waist circumference (WC)) remains inconclusive.

OBJECTIVE: we aimed to assess the overall effect of coconut oil supplementation on these anthropometric parameters and explore potential sources of heterogeneity.

METHODS: We comprehensively searched electronic databases using appropriate keywords. We included 15 studies with the following criteria: (1) clinical trials in adults, with parallel or cross-over design, (2) evaluated the effect of coconut oil on body weight, BMI or WC, (3) compared the effect of a specific dose of coconut oil against a coconut oil-free diet or other types of oils, (4) considered the change in anthropometric parameters as the primary or one of the secondary outcomes, (5) provided mean and standard deviation (SD) of change in anthropometric parameters across study arms, (6) reported the number of participants in each study arm.

RESULTS: The trials included 620 participants and assessed the effects of coconut oil supplementation on body weight, BMI and WC. Our meta-analysis revealed statistically significant effects of coconut oil supplementation on weight and BMI, with mean differences of 0.04 kg (95% CI: 0.01 to 0.08 kg) and 0.01 kg/m2 (95% CI: 0.00 to 0.02). However, the effects were not clinically meaningful. There was no significant effect of coconut oil on WC. Subgroup analyses suggested that the duration of the intervention may influence the effect of coconut oil on body weight. In the sensitivity analysis, we found that the result of one study influenced the associations between coconut oil supplementation and weight or BMI.

CONCLUSIONS: Overall, our findings suggest no clinically significant effects of coconut oil supplementation on weight loss. Further research is needed to clarify the issue.

SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD420251031291.

PMID:40481535 | DOI:10.1186/s40795-025-01090-6

Orphanet J Rare Dis. 2025 Jun 6;20(1):284. doi: 10.1186/s13023-025-03729-w.

ABSTRACT

BACKGROUND: Neurofibromatosis type 1 is a genetic disease with an autosomal dominant pattern. One of its clinical features is the presence of disfiguring neurofibromas. Most adults with Neurofibromatosis type 1 have visible neurofibromas depending on the severity of their skin related clinic that can affect their body image, and body image influencing psychological assistance and social support. This research explored Body image, the negative perception of the appearance of neurofibromas and skin severity in Neurofibromatosis type 1 patients; assessed its association with quality of life; and the role of social support and psychological assistance.

RESULTS: Two hundred five patients with Neurofibromatosis type 1 (16-74 years) were included in the study. They responded to questionnaires about their quality of life, body image and other sociodemographic data. Correlations and simple and multiple regressions were used to assess the relationships between variables. The results showed that body image problems increased if Neurofibromatosis type 1 patients were concerned about the aspects of their neurofibromas (B = 4.544; p < 0.001) and if they had severe skin conditions (B = 4.262; p < .001). Despite this, statistical analysis showed that only body image impairments reduced quality of life by 0.605 (p < 0.001), while skin severity and the negative perception of the appearance of neurofibromas were not clearly related. Patients with body image impairments are more likely to seek psychological assistance (ρ = 0.218; p < 0.01), but they are less likely to report having social support. The results also showed that when patients with Neurofibromatosis type 1 retrieved they have social support (ρ = -0.210, p < 0.01) or they inform doing psychological assistance (ρ = -0.238; p < 0.001), they have lower quality of life.

CONCLUSION: Body image concerns, rather than skin severity, are a key feature for detecting quality of life impairments in these patients. When healthcare professionals detect body image impairments, it is crucial for them to collaborate with patients and either provide or refer them to psychological interventions. This approach helps improve social support, enabling patients to benefit from both their professional and personal environments.

PMID:40481533 | DOI:10.1186/s13023-025-03729-w

Crit Care. 2025 Jun 6;29(1):230. doi: 10.1186/s13054-025-05468-7.

ABSTRACT

BACKGROUND: Large language models (LLMs) have demonstrated potential in assisting clinical decision-making. However, studies evaluating LLMs’ diagnostic performance on complex critical illness cases are lacking. We aimed to assess the diagnostic accuracy and response quality of an artificial intelligence (AI) model, and evaluate its potential benefits in assisting critical care residents with differential diagnosis of complex cases.

METHODS: This prospective comparative study collected challenging critical illness cases from the literature. Critical care residents from tertiary teaching hospitals were recruited and randomly assigned to non-AI-assisted physician and AI-assisted physician groups. We selected a reasoning model, DeepSeek-R1, for our study. We evaluated the model’s response quality using Likert scales, and we compared the diagnostic accuracy and efficiency between groups.

RESULTS: A total of 48 cases were included. Thirty-two critical care residents were recruited, with 16 residents assigned to each group. Each resident handled an average of 3 cases. DeepSeek-R1’s responses received median Likert grades of 4.0 (IQR 4.0-5.0; 95% CI 4.0-4.5) for completeness, 5.0 (IQR 4.0-5.0; 95% CI 4.5-5.0) for clarity, and 5.0 (IQR 4.0-5.0; 95% CI 4.0-5.0) for usefulness. The AI model’s top diagnosis accuracy was 60% (29/48; 95% CI 0.456-0.729), with a median differential diagnosis quality score of 5.0 (IQR 4.0-5.0; 95% CI 4.5-5.0). Top diagnosis accuracy was 27% (13/48; 95% CI 0.146-0.396) in the non-AI-assisted physician group versus 58% (28/48; 95% CI 0.438-0.729) in the AI-assisted physician group. Median differential quality scores were 3.0 (IQR 0-5.0; 95% CI 2.0-4.0) without and 5.0 (IQR 3.0-5.0; 95% CI 3.0-5.0) with AI assistance. The AI model showed higher diagnostic accuracy than residents, and AI assistance significantly improved residents’ accuracy. The residents’ diagnostic time significantly decreased with AI assistance (median, 972 s; IQR 570-1320; 95% CI 675-1200) versus without (median, 1920 s; IQR 1320-2640; 95% CI 1710-2370).

CONCLUSIONS: For diagnostically difficult critical illness cases, DeepSeek-R1 generates high-quality information, achieves reasonable diagnostic accuracy, and significantly improves residents’ diagnostic accuracy and efficiency. Reasoning models are suggested to be promising diagnostic adjuncts in intensive care units.

PMID:40481529 | DOI:10.1186/s13054-025-05468-7

Acta Epileptol. 2025 Jun 6;7(1):35. doi: 10.1186/s42494-025-00224-4.

ABSTRACT

The effectiveness of treatment for the chronic phase of febrile infection-related epilepsy syndrome (FIRES) remains uncertain. This study aimed to evaluate the therapeutic efficacy of minocycline in patients with chronic FIRES who had a poor response to conventional antiseizure medications. Three patients received 100 mg of minocycline (100 mg twice daily for 12 weeks), with effectiveness assessed based on seizure frequency, duration, type, and quality of life (using the quality of life in epilepsy-31, QOLIE-31), alongside adverse event monitoring. Results showed that one patient (Patient 3) exhibited a significant reduction in seizure duration and improved QOLIE-31 scores, with focal seizures being the only type observed after treatment. However, there was no statistically significant change in overall seizure frequency among the three patients. Additionally, a short literature review was conducted to explore various management strategies for chronic FIRES, including IL-1 receptor antagonist (anakinra) and IL-6 receptor antagonist (tocilizumab), centro-median thalamic nuclei deep brain stimulation, cannabidiol, responsive neurostimulation, intrathecal dexamethasone, ketogenic diet, and vagus nerve stimulation. In conclusion, considering the existing research on the etiological mechanisms of FIRES and based on our preliminary findings on the anti-inflammatory and antiepileptic properties of minocycline, early initiation of minocycline therapy in the chronic phase of FIRES should be explored further.Trial registrationClinicaltrials.gov (NCT05958069, retrospectively registered 22 July 2023).

PMID:40481521 | DOI:10.1186/s42494-025-00224-4