Search Results for: Test delle urine per la diagnosi di cancro

Grazie al progetto Telemo realizzato dal Cnr di Pisa

Stroke, Ahead of Print. BACKGROUND:Poststroke cognitive impairment is associated with disability and decreased quality of life. We assessed whether individual or collective magnetic resonance imaging (MRI) biomarkers can aid in predicting cognitive impairment after lacunar infarction (LACI).METHODS:We conducted a retrospective analysis of data from the American Stroke Association Bugher Small Vessel Study, which included 134 patients within 2 years of an acute LACI, enrolled between 2007 and 2012 at 4 North Carolina hospitals. MRI brain measures at the time of the stroke included as follows: 1, total number of LACIs (index LACI and nonindex radiographic lacunes); 2, size of the largest lacune; 3, ventricular size; 4, cerebral atrophy; 5, radiographic locations (supratentorial, infratentorial, or both); and 6, white matter disease (WMD) extent. WMD extent, cerebral atrophy, and ventricular size were graded using the CHS (Cardiovascular Health Study) scores. The primary outcomes were as follows: 1, total score on Short-Form Montreal Cognitive Assessment to assess global cognition; and 2, time to complete TRAIL Making Test Part B (TMT-B) to evaluate executive function. Regression analyses were used to assess the association between the 6 MRI measures and cognitive function adjusting for demographic and clinical variables.RESULTS:One hundred thirty-four participants completed Short-Form Montreal Cognitive Assessment testing and 100 completed TMT-B at a mean of 76.5 (SD, 172.7) days from the index LACI. There were no associations between MRI characteristics and Short-Form Montreal Cognitive Assessment. On univariable analyses, cerebral atrophy (β=35 [95% CI, 14.17–55.83];P=0.0010), ventricular size (β=40.1 [95% CI, 22.24–57.96];P

Da fatica a fotofobia, se preso per tempo.Risultati test clinici

Objectives
Caregiving has been widely recognised as a potential risk factor for caregivers’ psychological well-being in previous studies. The objective of this study is to examine the association between multiple factors of the caregiving process and the depression risk of caregivers, as well as the mediating effect of caregiver burden in these associations.

Design
Cross-sectional study.

Setting
The Hong Kong Polytechnic University in Hong Kong Special Administrative Region, China.

Participants
597 family caregivers of persons with disabilities in December 2020 under the Hong Kong governmental initiative, ‘Persons with Disabilities and Rehabilitation Program’.

Main outcome and measures
Indications of depression were assessed through the application of the World Health Organization-Five Well-being Index (1998 version).

Results
A structural equation model (SEM) was applied using Analysis of Moment Structure (AMOS) 28.0 to identify the association between a series of caregiving-related factors and depression risk, as well as test the mediating role of caregiver burden in these associations. 50% of care recipients needed assistance in all four care need categories, with daily living care being the most prominent (72.4%). Caregivers dedicated around 79.6 hours (SD: 52.2) per week on caregiving duties. Nearly 44% of the caregivers had at least one diagnosed disease. Only 5% of caregivers considered that they had a poor caregiving ability, whereas 87.2% of them reported heightened caregiving pressure during the COVID-19 pandemic. In this study, the average caregiver burden score was 6.6 (SD: 3.3), and the average depression score was 6.7 (SD: 5.1). The results of the SEM model showed that care needs of care recipients (ß (95% CI): –0.201 (–0.355, –0.083), p=0.001), weekly caregiving hours (ß (95% CI): –0.126 (–0.215, –0.067), p=0.001) and presence of emotional issues (ß (95% CI): –0.329 (–0.538, –0.184), p=0.001) were positively associated with depression risk of caregivers, fully mediated by caregiver burden. Additionally, caregivers’ health status had both direct (ß (95% CI): –0.234 (–0.388, –0.101), p=0.001) and indirect (ß (95% CI): –0.126 (–0.215, –0.067), p=0.001) effects on depression, indicating that caregiver burden partially mediated this pathway (proportion mediation is 35%). A higher self-evaluation of caregiving ability was related to a lower risk of depression (ß (95% CI): 0.281 (0.169, 0.396), p=0.001), and caregiver burden did not mediate this pathway.

Conclusions
Care needs of care recipients, weekly caregiving hours, caregivers’ health status and presence of emotional issues during the COVID-19 pandemic were adversely associated with an increased depression risk for caregivers, and these were either fully or partially mediated by caregiver burden. Additionally, caregivers’ lower self-evaluation of their caregiving ability was an independent factor that directly contributes to an increased depression risk.

Objectives
Caregiving has been widely recognised as a potential risk factor for caregivers’ psychological well-being in previous studies. The objective of this study is to examine the association between multiple factors of the caregiving process and the depression risk of caregivers, as well as the mediating effect of caregiver burden in these associations.

Design
Cross-sectional study.

Setting
The Hong Kong Polytechnic University in Hong Kong Special Administrative Region, China.

Participants
597 family caregivers of persons with disabilities in December 2020 under the Hong Kong governmental initiative, ‘Persons with Disabilities and Rehabilitation Program’.

Main outcome and measures
Indications of depression were assessed through the application of the World Health Organization-Five Well-being Index (1998 version).

Results
A structural equation model (SEM) was applied using Analysis of Moment Structure (AMOS) 28.0 to identify the association between a series of caregiving-related factors and depression risk, as well as test the mediating role of caregiver burden in these associations. 50% of care recipients needed assistance in all four care need categories, with daily living care being the most prominent (72.4%). Caregivers dedicated around 79.6 hours (SD: 52.2) per week on caregiving duties. Nearly 44% of the caregivers had at least one diagnosed disease. Only 5% of caregivers considered that they had a poor caregiving ability, whereas 87.2% of them reported heightened caregiving pressure during the COVID-19 pandemic. In this study, the average caregiver burden score was 6.6 (SD: 3.3), and the average depression score was 6.7 (SD: 5.1). The results of the SEM model showed that care needs of care recipients (ß (95% CI): –0.201 (–0.355, –0.083), p=0.001), weekly caregiving hours (ß (95% CI): –0.126 (–0.215, –0.067), p=0.001) and presence of emotional issues (ß (95% CI): –0.329 (–0.538, –0.184), p=0.001) were positively associated with depression risk of caregivers, fully mediated by caregiver burden. Additionally, caregivers’ health status had both direct (ß (95% CI): –0.234 (–0.388, –0.101), p=0.001) and indirect (ß (95% CI): –0.126 (–0.215, –0.067), p=0.001) effects on depression, indicating that caregiver burden partially mediated this pathway (proportion mediation is 35%). A higher self-evaluation of caregiving ability was related to a lower risk of depression (ß (95% CI): 0.281 (0.169, 0.396), p=0.001), and caregiver burden did not mediate this pathway.

Conclusions
Care needs of care recipients, weekly caregiving hours, caregivers’ health status and presence of emotional issues during the COVID-19 pandemic were adversely associated with an increased depression risk for caregivers, and these were either fully or partially mediated by caregiver burden. Additionally, caregivers’ lower self-evaluation of their caregiving ability was an independent factor that directly contributes to an increased depression risk.

La Campania la regione con più fumatori e sedentari

Al Villaggio salute 4mila test gratuiti per diagnosi tumore seno

Objective
Valid and reliable measurement of early childhood development (ECD) is critical for monitoring and evaluating ECD-related policies and programmes. Although ECD tools developed in high-income countries may be applicable to low- and middle-income countries (LMICs), directly applying them in LMICs can be problematic without psychometric evidence for new cultures and contexts. Our objective was to systematically appraise available evidence on the psychometric properties of tools used to measure ECD in LMIC.

Design
A systematic review following the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines.

Data sources
MEDLINE, Embase, PubMed, PsycInfo, SciELO and BVS were searched from inception to February 2025.

Eligibility criteria
We included studies that examined the reliability, validity, and measurement invariance of tools assessing ECD in children 0–6 years of age living in LMICs.

Data extraction and synthesis
Each study was independently screened by two researchers and data extracted by one randomly assigned researcher. Risk of bias was assessed using a checklist developed by the study team assessing bias due to training/administration, selective reporting and missing data. Results were synthesised narratively by country, location, age group at assessment and developmental domain.

Results
A total of 160 articles covering 117 tools met inclusion criteria. Most reported psychometric properties were internal consistency reliability (n=117, 64%), concurrent validity (n=81, 45%), convergent validity (n=74, 41%), test–retest reliability (n=73, 40%) and structural validity (n=72, 40%). Measurement invariance was least commonly reported (n=16, 9%). Most articles came from Brazil, China, India and South Africa. Most psychometric evidence was from urban (n=92, 51%) or urban–rural (n=41, 23%) contexts. Study samples focused on children aged 6–17.9 or 48–59.9 months. The most assessed developmental domains were language (n=111, 61%), motor (n=104, 57%) and cognitive (n=82, 45%). Bias due to missing data was most common.

Conclusions
Psychometric evidence is fragmented, limited and heterogeneous. More rigorous psychometric analyses, especially on measurement invariance, are needed to establish the quality and accuracy of ECD tools for use in LMICs.

PROSPERO registration number
CRD42022372305.

Introduction
Pre-eclampsia (PE) remains a major contributor to maternal morbidity and mortality globally. Early identification of risk factors and evaluation of prognostic models for severe adverse maternal outcomes are essential for improving management and reducing complications. While numerous studies have explored potential risk markers, there is still no consensus on the most reliable factors and models to use in clinical practice. This systematic review aims to consolidate research on both individual predictors and prognostic models of severe adverse maternal outcomes in PE, providing a comprehensive overview to support better clinical decision-making and patient care.

Methods and analysis
This review follows the Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Protocol 2015 checklist. A systematic search will be performed using a detailed strategy across Medline, Embase, Cochrane, ProQuest dissertations, and grey literature from inception to 2 April 2024. Eligible studies will include those investigating clinical, laboratory-based, and sociodemographic predictors of severe adverse maternal outcomes in PE. Two reviewers will independently assess titles, abstracts, full texts, and extract data and assess study quality using the Quality In Prognostic Studies (QUIPS) tool for studies on risk predictors and the Prediction model Risk of Bias Assessment Tool (PROBAST) for prognostic models. The inclusion criteria will encompass cohort, case-control, and cross-sectional studies published in English and French involving women diagnosed with PE and reporting on the risk prediction for adverse maternal outcomes. The main outcomes of interest will include severe maternal morbidity and mortality during pregnancy, delivery, or within the postpartum period. Analyses will include both narrative synthesis and, where appropriate, meta-analysis using random-effects models. Pooled estimates will be calculated, with publication bias assessed through funnel plots and statistical tests (eg, Begg’s and Egger’s). Heterogeneity will be primarily assessed through visual inspection of forest plots, supported by statistical measures, such as the I² test, with further exploration through sensitivity, subgroup, and meta-regression analyses.

Ethics and dissemination
This systematic review will be based on published data and will not require ethics approval. Results will be disseminated through peer-reviewed publications and presentations at academic conferences.

PROSPERO registration number
CRD42024517097.

Objectives
To establish the prevalence of clinically significant chronic obstructive pulmonary disease (COPD) and relevant characteristics in individuals with a significant smoking history who are hospitalised for acute myocardial infarction (MI).

Design
Cross-sectional study.

Setting
Hospital inpatients at 8 European centres (7 in Sweden, 1 in the UK).

Participants
518 men or women (302 in Sweden, 216 in the UK) hospitalised for acute MI, aged 40 years or older, with a smoking history of at least 10 pack-years.

Primary and secondary outcome measures
The primary outcome was prevalence of detected significant COPD (Global Initiative for Chronic Obstructive Lung Disease stages 2–4), defined as a ratio of forced expiratory volume in 1 and 6 s (FEV1/FEV6)

Introduction
Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected or is detected too late, worsening pregnancy complications. The gold standard for diagnosing anaemia is a clinical laboratory blood haemoglobin (Hgb) or haematocrit (Hct) test involving a venous blood draw. However, this approach presents several challenges in resource-limited settings regarding accessibility and feasibility. Although non-invasive blood Hgb testing technologies are gaining attention, they remain limited in availability, affordability and practicality. This study aims to develop and validate a mobile health (mHealth) machine learning model to reliably predict blood Hgb and Hct levels in Black African pregnant women using smartphone photos of the conjunctiva.

Methods and analysis
This is a single-centre, cross-sectional and observational study, leveraging existing antenatal care services for pregnant women aged 15 to 49 years in Kenya. The study involves collecting smartphone photos of the conjunctiva alongside conventional blood Hgb tests. Relevant clinical data related to each participant’s anaemia status will also be collected. The photo acquisition protocol will incorporate diverse scenarios to reflect real-world variability. A clinical training dataset will be used to refine a machine learning model designed to predict blood Hgb and Hct levels from smartphone images of the conjunctiva. Using a separate testing dataset, comprehensive analyses will assess its performance by comparing predicted blood Hgb and Hct levels with clinical laboratory and/or finger-prick readings.

Ethics and dissemination
This study is approved by the Moi University Institutional Research and Ethics Committee (Reference: IREC/585/2023 and Approval Number: 004514), Kenya’s National Commission for Science, Technology, and Innovation (NACOSTI Reference: 491921) and Purdue University’s Institutional Review Board (Protocol Number: IRB-2023-1235). Participants will include emancipated or mature minors. In Kenya, pregnant women aged 15 to 18 years are recognised as emancipated or mature minors, allowing them to provide informed consent independently. The study poses minimal risk to participants. Findings and results will be disseminated through submissions to peer-reviewed journals and presentations at the participating institutions, including Moi Teaching and Referral Hospital and Kenya’s Ministry of Health. On completion of data collection and modelling, this study will demonstrate how machine learning-driven mHealth technologies can reduce reliance on clinical laboratories and complex equipment, offering accessible and scalable solutions for resource-limited and at-home settings.

Objective
Multi-cancer early detection (MCED) tests are novel technologies that detect cancer signals from a broad set of cancer types using a single blood sample. The objective of this study was to estimate the effect of screening with an MCED test at different intervals on cancer stage at diagnosis and mortality endpoints.

Design
The current model is based on a previously published state-transition model that estimated the outcomes of a screening programme using an MCED test when added to usual care for persons aged 50–79. Herein, we expand this analysis to model the time of cancer diagnosis and patient mortality with MCED screening undertaken using different screening schedules. Screening intervals between 6 months and 3 years, with emphasis on annual and biennial screening, were investigated for two sets of tumour growth rate scenarios: ‘fast (dwell time=2–4 years in stage I) and ‘fast aggressive’ (dwell time=1–2 years in stage I), with decreasing dwell times for successive stages.

Setting
Inputs for the model include (1) published MCED performance measures from a large case-control study by cancer type and stage at diagnosis and (2) Surveillance, Epidemiology and End Results (SEER) data describing stage-specific incidence and cancer-specific survival for persons aged 50–79 in the US for all cancer incidence.

Outcome measures
We used the following outcome measures: diagnostic yield, stage shift, and mortality.

Results
Annual screening under the fast tumour growth scenario was associated with more favourable diagnostic yield. There were 370 more cancer signals detected/year/100,000 people screened, 49% fewer late-stage diagnoses, and 21% fewer deaths within 5 years than usual care. Biennial screening had a similar, but less substantial, impact (292 more cancer signals detected/year/100,000 people screened; 39% fewer late-stage diagnoses, and 17% fewer deaths within 5 years than usual care). Annual screening prevented more deaths within 5 years than biennial screening for the fast tumour growth scenario. However, biennial screening had a higher positive predictive value (54% vs 43%); it was also more efficient per 100,000 tests in preventing deaths within 5 years (132 vs 84), but prevented fewer deaths per year.

Conclusion
Adding MCED test screening to usual care at any interval could improve patient outcomes. Annual MCED test screening provided more overall benefit than biennial screening. Modelling the sensitivity of outcomes to different MCED screening intervals can inform timescales for investigation in trials.

Introduction
Approximately 70% of patients with stroke experience varying degrees of cognitive impairment, which imposes a substantial direct and indirect socioeconomic burden. Previous studies have shown that scalp acupuncture (SA) or repetitive transcranial magnetic stimulation (rTMS) in combination with other therapies is effective for poststroke cognitive impairment (PSCI). Limited by interstudy heterogeneity and the limited number of included studies, there is insufficient evidence of the efficacy of rTMS in combination with SA in treating PSCI. Therefore, this protocol aims to investigate the effectiveness of rTMS in conjunction with SA for patients with PSCI through a comprehensive meta-analysis.

Methods and analysis
This study will undertake a comprehensive search across nine distinct databases (Web of Science, Embase, Cochrane Library, PubMed, China National Knowledge Infrastructure, Wanfang Data, China Science and Technology Journal Database, China Biology Medicine and SCOPUS). The primary outcome will encompass the Montreal Cognitive Assessment and the Mini-Mental State Examination. The secondary outcomes are the modified Barthel Index, the Rivermead Behavioral Memory Test and the Digit Span Test. The bias risk assessment tool from the Cochrane Handbook for Systematic Reviews of Interventions will be used to evaluate bias risk, and the GRADE will be applied to gauge the quality of evidence. Furthermore, we plan to perform an analysis of subgroups to investigate the heterogeneity, employ the leave-one-out approach for sensitivity evaluation and use funnel plots and Egger’s test to determine publication bias, respectively.

Ethics and dissemination
Ethical approval is not required in systematic review and meta-analysis. The review will be published in a peer-reviewed journal.

PROSPERO registration number
CRD42024571762.

Introduction
Excessive sedentary time (ST) is linked to dementia risk, poorer attentional control and episodic memory. These cognitive decrements have been associated with decreased functional connectivity (FC) in the frontoparietal network (FPN) and default mode networks (DMN) with ageing. Physical activity (PA) interventions can enhance FC in these networks, but these interventions are not designed to decrease ST among older adults. Prolonged sitting (ie, sitting continuously for ≥20 min) can acutely reduce frontoparietal brain function and attentional control, while a single PA bout lasting at least 20 min can enhance them. It has been theorised that stimulation of the cerebral norepinephrine release through peripheral increase in catecholamines may explain this effect. In contrast, the effects of shorter (

L’incidenza di certi tumori più alta rispetto ai coetanei maschi