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At least 19 recordsLinked to original sources
PubMedDate not supplied

[The efficacy of personal prevention measures in controlling the exposure to metals of welders].

Biological monitoring of welders employed in a power plant showed urinary nickel levels largely exceeding the reference values (Ni-U welders mean = 43.2, S.D. = 22.1 micrograms/24 h; Ni-U reference values mean = 2.7, S.D. = 1.4 micrograms/24 h). Subsequently urinary excretion levels of other metals (Cr, Zn, Fe, Mn, Cu, Al, Pb) were measured for a more complete assessment of occupational exposure of these subjects; only aluminum and lead were found to slightly exceed the reference values and correlate with urinary nickel levels. As a consequence of these results, some adjustments in personal prevention measures were introduced at the workplace; the subsequent biological monitoring checks showed a progressive reduction in urinary nickel excretion levels over time in all welders.

Adult↗
PubMedDate not supplied

Aspects of preventive health care for older persons.

Preventive health care for older persons is considered in terms of primary, secondary and tertiary prevention and examples of relevant services are provided both from Canada and from other countries. Three areas of concern are identified, namely communication, quality assurance and funding. It is suggested that various approaches used in other countries, such as Home Visitor Programs, be examined and more generally that comparisons with health care services in other countries be carried out, particularly with respect to evaluations and possible economic steering effects.

Aged↗
PubMed2026

Two-sample Mendelian randomization study of gut microbiota and inflammatory proteins: Predictive, preventive, and personalized treatment for migraine.

The human gut microbiota is increasingly recognized as a significant factor in the pathogenesis of migraine, potentially via inflammatory pathways. Identifying specific human gut microbiota components associated with migraines, along with the investigation of particular inflammatory proteins, is essential for advancing primary prediction, targeted prevention, and personalized treatment strategies for migraines. We conducted a two-sample Mendelian randomization study using publicly available summary statistics from genome-wide association studies. Data for 473 human gut microbiota taxa were obtained from the Finnish national health survey conducted by the National Institute for Health and Welfare study (FINRISK, n = 5959 European participants). Genome-wide association study data (https://www.ebi.ac.uk/gwas/) for 91 circulating inflammatory proteins were obtained from 14,824 participants across 11 cohorts using the Olink Target 96 Inflammation panel. Migraine outcome data were obtained from the FinnGen R12 release, with cases defined using ICD-10 code G43. All genome-wide association study analyses were adjusted for sex, age, genotyping batch, and 10 genetic principal components to control population stratification (genomic inflation factors: 1.00–1.05). Inverse variance-weighted Mendelian randomization was the primary analysis method, with Mendelian randomization-Egger, weighted median, and mode-based methods as sensitivity analyses. Two-step Mendelian randomization mediation analysis quantified the proportion of the effects of human gut microbiota on migraine that are mediated through inflammatory proteins. Thirty-seven bacterial genera were found to be associated with migraine using the inverse variance-weighted method. Of these, 18 genera exhibited a negative association, while 19 genera demonstrated a positive association with migraine risk. Additionally, eight inflammatory proteins were found to increase the risk of migraine. Among human gut microbiota, four were observed to reduce inflammatory protein levels, whereas another four were associated with increased inflammatory protein levels. Additionally, five gut microbiota were identified to influence migraine through inflammatory proteins in both Mendelian randomization analyses. Specifically, Actinobacteria, Brachyspiraceae, CAG-269 sp001915995, and Paraglaciecola were found to affect migraine outcomes via inflammatory proteins, with mediation proportions of 12%, 19%, 15.5%, and 6.7%, respectively. Lawsonibacter sp002161175 was identified to influence migraine risk through Oncostatin-M and SLAM, with mediation proportions of 15.6% and 11.3%, respectively. Our study elucidated the role of specific human gut microbiota alterations in the pathogenesis of migraine and highlighted the mediating effects of inflammatory proteins. Targeting these particular human gut microbiota alterations offers a promising strategy for predictive, preventive, and personalized medicine in migraine management, resulting in substantial clinical advancements.

causality↗
PubMed1992

Prevention and control of tuberculosis among homeless persons. Recommendations of the Advisory Council for the Elimination of Tuberculosis.

Because tuberculosis (TB) is a major problem among homeless persons, the Advisory Council for the Elimination of Tuberculosis has developed recommendations to assist health-care providers, health departments, shelter operators and workers, social service agencies, and homeless persons prevent and control TB in this population. TB should be suspected in any homeless person with a fever and a productive cough of more than 1-3 weeks' duration, and appropriate diagnostic studies should be undertaken. Confirmed or suspected TB in a homeless person should be immediately reported to the health department so that a treatment plan can be decided upon and potentially exposed persons located and examined. Patients with TB should be counseled and voluntarily tested for human immunodeficiency virus (HIV) infection because TB treatment recommendations are different for HIV-seropositive and HIV-seronegative persons (1). TB therapy should be directly observed whenever possible. This may require the establishment of special shelters or other long-term-care arrangements for homeless persons with TB. For each person with an infectious case, an investigation should be conducted to identify exposed persons, and those found to be infected should be considered for preventive therapy. Shelter staff should receive a tuberculin skin test when they start work and every 6-12 months thereafter. Those with positive skin test results should be considered for preventive therapy according to current guidelines. Shelters for the homeless should be adequately ventilated. The installation of ultraviolet lamps also may be useful to further reduce the risk of TB transmission.

Adult↗
PubMed2025

The Application of Preventive Medicine in the Future Digital Health Era.

A number of seismic shifts are expected to reshape the future of medicine. The global population is rapidly aging, significantly impacting the global disease burden. Medicine is undergoing a paradigm shift, defining and diagnosing diseases at earlier stages and shifting the health care focus from treating diseases to preventing them. The application and purview of digital medicine are expected to broaden significantly. Furthermore, the COVID-19 pandemic has further accelerated the shift toward predictive, preventive, personalized, and participatory (P4) medicine, and has identified health care accessibility, affordability, and patient empowerment as core values in the future digital health era. This "left shift" toward preventive care is anticipated to redefine health care, emphasizing health promotion over disease treatment. In the future, the traditional triad of preventive medicine-primary, secondary, and tertiary prevention-will be realized with technologies such as genomics, artificial intelligence, bioengineering and wearable devices, and telemedicine. Breast cancer and diabetes serve as case studies to demonstrate how these technologies such as personalized risk assessment, artificial intelligence-assisted and app-based technologies, have been developed and commercialized to provide personalized preventive care, identifying those at a higher risk and providing instructions and interventions for healthier lifestyles and improved quality of life. Overall, preventive medicine and the use of advanced technology will hold great potential for improving health care outcomes in the future.

Humans↗
PubMedDate not supplied

[Prevention of atopic diseases: recent findings and personal data].

Prevention of IgE-mediated diseases relies on the skill necessary to overcome the natural forces unceasingly working to sensitize humans to produce IgE antibodies. The phenotypic expression of allergic disease ensues from an elaborate inter-relationship between the atopy-prone genetic constitution of a child and the experienced environment surrounding it. Prevention of atopy could potentially by met by selectively interfering with the genetic and environmental factors that appear to be responsible in concert for the final phenotypic expression of atopy. As no ideal cow's milk substitute exists, and all the suggested formulas could cause allergy, the currently available foods for children are soy milk, hydrolyzed protein, and home-made meat-based formulas. From a nutritional point of view, soy milk formulas are adequate, however in IgE mediated forms and atopic dermatitis reactions to hydrolyzed protein are more common. Although no long-term studies on the nutritional value of hydrolyzed protein are available, some formulae have shown a satisfactory growth rate in short term clinical trials. Meat-based formulas, such as the home-made lamb formula are well accepted and economical.

Humans↗
PubMed2026

Toward personalized interventions for preventing depression in primary care: Qualitative and quantitative findings from the e-predictD pilot study.

BACKGROUND: The predictD intervention, delivered by family physicians (FPs), has demonstrated effectiveness and cost-efficiency in preventing depression and anxiety. The e-predictD study aims to design, develop, and evaluate a novel personalized intervention for depression prevention by integrating information and communication technologies (ICTs), risk prediction algorithms, and decision support systems (DSS) for both patients and FPs. OBJECTIVE: To evaluate the satisfaction, usability, and acceptability, of a beta version of the e-predictD intervention in primary care settings. METHODS: The e-predictD intervention follows a biopsychosocial approach, including an initial patient-FP interview, specific FP training, and an app. A β-version was tested in a pilot study without a control group over three months. The app integrates a validated depression risk prediction algorithm, decision algorithms, and a monitoring system supporting the DSS. The DSS generates a personalized prevention plan (PPP) from eight intervention modules: physical exercise, social relationships, problem-solving, communication skills, decision-making, assertiveness, sleep improvement, and cognitive restructuring. Patients and FPs discussed the PPP in a 15-minute baseline interview, selecting modules for implementation over three months. Semi-structured interviews gathered feedback. Assessments included depression (PHQ-9), anxiety (GAD-7), quality of life (SF-12), and major depression risk (predictD algorithm). RESULTS: Six FPs from six Spanish cities enrolled 56 non-depressed patients at moderate-to-high risk of depression; 47 (84%) completed follow-up. The app was used for a median of six days (interquartile range: 1-30). Both FPs and patients expressed satisfaction, leading to incorporated improvements. After three months, significant reductions in major depression risk and anxiety symptoms were observed, alongside improved mental quality of life. However, no significant changes were found in depressive symptoms or physical quality of life. CONCLUSION: This pilot study supports the feasibility and acceptability of the e-predictD β-version, despite lower-than-expected app usability. Health improvements were observed, warranting confirmation in a randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03990792.

Adult↗
PubMed1975

Is an application form useful to select patients with epilepsy who may drive?

Of 1,268 persons who claimed to have epilepsy and were therefore disqualified for military service, 55% had a driving license 5 years later. Only 58% had applied for a driving license. Of those 14% who had answered truthfully the question "have you had fits, epilepsy etc." in the application form, 63% received a license. Fewer persons with epilepsy had a driving license after about 5 years (55%) than did age-matched controls (73%). The application form is of no use in preventing persons with epilepsy from obtaining a driving license. Adequate instruction of the patient and of his physician is to be preferred to the use of an application form.

Adolescent↗
PubMed2026

AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study.

BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfunction and fluctuating levels of consciousness. POD is associated with prolonged hospitalization, long-term cognitive decline, reduced quality of life, and increased mortality. Despite its clinical relevance, the underlying pathophysiological mechanisms remain poorly understood, and reliable biomarkers for early prediction and prevention are lacking. OBJECTIVE: The CONFUSED study aims to identify molecular and clinical predictors of POD by integrating clinical data with proteomic, transcriptomic, and epigenetic analyses. The primary objective is to develop predictive models for POD using multimodal data. Secondary objectives include the identification of delirium-associated genes, proteins, and epigenetic signatures, as well as the exploration of patient subgroups at increased risk for POD. METHODS: CONFUSED is a prospective observational cohort study conducted at a German university hospital. Adult patients undergoing major surgery under general anesthesia will be enrolled until 100 cases of POD have been observed, which is expected to require a total sample size of approximately 200 to 300 patients. Blood samples are collected at 4 predefined time points: before premedication, immediately after surgery, and on postoperative days 2 and 5. Samples undergo comprehensive proteomic profiling, transcriptomic analysis using RNA microarrays, DNA methylation analysis, and genotyping of selected polymorphisms. Clinical data, including demographics, comorbidities, perioperative variables, medications, and delirium assessments using the Confusion Assessment Method (CAM) and CAM for the intensive care unit, are systematically recorded. Statistical analyses include univariate and multivariate methods, as well as machine learning approaches such as random forests and support vector machines, to identify relevant biomarkers and develop predictive models. The study protocol follows STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines and was approved by the responsible ethics committees. RESULTS: The study was registered in the German Clinical Trials Register (DRKS00033854) on March 18, 2024. Recruitment started in January 2024 and is ongoing at the time of manuscript submission. As of now, 135 patients have been enrolled. Sample collection and laboratory analyses are ongoing. Data analysis began in January 2026, with first results anticipated in July 2026. Final data lock is anticipated after the completion of recruitment. CONCLUSIONS: By integrating multimodal molecular data with clinical parameters and applying advanced machine learning techniques, the CONFUSED study aims to improve the prediction and understanding of POD. The results are expected to support the development of personalized preventive strategies and contribute to improved perioperative care for patients at risk of POD.

Humans↗
PubMed2026

Large-Scale Plasma Proteomics Identifies Early Molecular Deviations and Improves Risk Prediction for Heart Failure Among Individuals With Obesity.

AIMS: Heart failure (HF) is a major global public health challenge, with obesity being one of its key risk factors. Although several HF risk prediction models have been developed in the general population, few are specifically tailored to individuals with obesity. This underscores the urgent need for precise biomarkers to improve individual risk stratification and enable personalized prevention strategies. We aimed to develop and validate a plasma proteomics-based protein risk score (PRS) to predict incident HF among individuals with obesity. MATERIALS AND METHODS: We analysed 9831 participants with obesity (BMI ≥ 30 kg/m2) from the UK Biobank with baseline measurements of 2911 circulating proteins and up to 16 years of follow-up. Multivariable Cox regression identified proteins associated with incident HF after comprehensive covariate adjustment. A PRS was constructed using LASSO regression and evaluated in a held-out test set. Protein trajectories before HF onset were reconstructed using LOESS modelling. To enhance clinical feasibility, a minimal protein panel was identified using LightGBM with forward feature selection. RESULTS: A total of 727 participants developed HF during follow-up. Multivariable cox analyses identified 578 proteins significantly associated with HF. LASSO regression further selected 81 proteins to build the PRS, which showed a strong association with HF risk in both training (HR 3.57; 95% CI 3.19-4.00) and test cohorts (HR 2.45; 95% CI 2.20-2.74). Adding the PRS improved prediction beyond age and sex (ΔC = 0.091) and beyond the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) model (ΔC = 0.052), with consistent gains in NRI and IDI. Proteomic deviations were detectable up to 16 years before diagnosis. A four-protein panel (GDF15, NT-proBNP, TNFRSF10B, CTHRC1) achieved robust discrimination (AUC 0.789), outperforming NT-proBNP alone (AUC 0.695) and complementing the PCP-HF model (combined AUC 0.803). DISCUSSION: Large-scale plasma proteomics substantially improves HF risk prediction in individuals with obesity and reveals long-standing molecular alterations preceding clinical onset. A simplified four-protein panel maintains robust predictive accuracy and provides a practical approach for the early detection and targeted prevention of obesity-related HF.

Humans↗