Risultati per: Sorveglianza nella post polipectomia nel cancro al colon-retto

Background
Up to 15% of survivors of COVID-19 infection experience long-term health effects, including fatigue, myalgia and impaired cognitive function, termed post-COVID-19 condition or long COVID. Several trials that study the benefits and harms of various interventions to manage long COVID have been published and hundreds more are planned or are ongoing. Trustworthy systematic reviews that clarify the benefits and harms of interventions are critical to promote evidence-based practice.

Objective
To create and maintain a living systematic review and network meta-analysis addressing the benefits and harms of pharmacologic and non-pharmacologic interventions for the treatment and management of long COVID.

Methods
Eligible trials will randomise adults with long COVID to pharmacologic or non-pharmacologic interventions, placebo, sham or usual care. We will identify eligible studies by searching MEDLINE, EMBASE, CINAHL, PsycINFO, AMED and CENTRAL from inception, without language restrictions.
Reviewers will work independently and in duplicate to screen search records, collect data from eligible trials, including trial and patient characteristics and outcomes of interest and assess risk of bias. Our outcomes of interest will include patient-reported fatigue, pain, postexertional malaise, changes in education or employment status, cognitive function, mental health, dyspnoea, quality of life, physical function, recovery and serious adverse events.
For each outcome, when possible, we will perform a frequentist random-effects network meta-analysis. When there are compelling reasons to suspect that certain interventions are only applicable or effective for a subtype of long COVID, we will perform separate network meta-analyses. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach will guide our assessment of the certainty of evidence.
We will update our living review biannually, on the publication of a seminal trial, or when new evidence emerges that may change clinical practice.

Conclusion
This living systematic review and network meta-analysis will provide comprehensive, trustworthy and up-to-date summaries of the evidence addressing the benefits and harms of interventions for the treatment and management of long COVID. We will make our findings available publicly and work with guideline-producing organisations to inform their recommendations.

Ethics and dissemination
The study describes the protocol for a systematic review that uses data from published trial reports. Therefore, the study is exempt from ethics review. We intend to deposit all data in a public repository and publish each iteration of the living review online.

Via a 2 fase del progetto Oms Europa coordinato in Italia da Iss

E’ partner del progetto ‘European cancer imaging – Eucaim’

Nurse-enabled, shared-care arrangements for women with early-stage breast cancer is feasible, and is as safe as specialist-led model of care. It may provide a more sustainable model of care in a longer term. GPs can meet the survivorship care needs identified breast cancer survivors. This trial can inform a large, pragmatic, hybrid effectiveness-implementation trial.

Ast Pesaro-Urbino presenta i numeri del territorio

‘Gli strumenti ci sono ma bisogna applicarli’

Lungo post della modella che sarà sul palco di Sanremo

Oncologi,ma meno del 50% cittadini riceve consigli su stili vita

Per diagnosi precoce del tumore tra i 70 e 74 anni

Stroke, Volume 56, Issue Suppl_1, Page ATP314-ATP314, February 1, 2025. Introduction:Blood pressure (BP) control after a stroke is crucial in lowering the risk of stroke recurrence. Our prior work found that over 60% of patients recently discharged from a regional health system with stroke did not achieve BP control according to current guidelines. Less is known about the impact of insurance type and co-morbidities on post-stroke BP control.Objective:To analyze the relationship between insurance type, comorbidities and post-stroke BP control among patients within a regional health system.Methods:This report is an observational cohort study. Patients were admitted between 2013-2021 for ischemic and hemorrhagic stroke and had seen a PCP/PCAPP (primary care physician/primary care advance practice provider) in a regional health system or affiliated outpatient clinics using the EPIC electronic health record. We excluded patients who died during hospitalization, were lost to follow-up, or were on dialysis.Results:The analysis included 2,750 patients. Six months after hospital discharge, the insurance coverage among stroke survivors with uncontrolled BP ( >130/80 mm Hg) was 61.1% for public, 35.8% for private, 1.9% for other/unknown, and 1.3% for self-pay. In comparison, among those with controlled BP (

Stroke, Volume 56, Issue Suppl_1, Page AWMP106-AWMP106, February 1, 2025. Introduction:An elevated urinary albumin-to-creatinine ratio (UACR), a marker of renal dysfunction, has been linked to an increased incidence of stroke. However, the interplay between UACR and demographic factors such as age, obesity, ethnicity, or education remains underexplored.Methods:We conducted a post-hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, including patients with available data. Time-to-event models were developed to examine the relation between UACR and stroke risk during up to 10 years of follow-up, adjusting for variables such as gender, age, education, and race. Because the exposure of UACR had a right skew, we transformed it into top tertile versus lowest/middle tertile.Results:We included 9,025 ACCORD participants in our analyses. Baseline demographics are seen in Table 1. Those with elevated UACR (top tertile) had a higher incidence of stroke (4.6% vs 3.4%, p

Stroke, Volume 56, Issue Suppl_1, Page AWMP113-AWMP113, February 1, 2025. Introduction:Post-stroke brain stimulation is a promising neurorestorative approach, yet the molecular mechanisms driving recovery remain unclear. Our previous work demonstrated that post-stroke optogenetic stimulations of the ipsilesional primary motor cortex (iM1) promotes functional recovery. To understand the mechanisms driving post-stroke recovery, we investigated the transcriptome of iM1 in non-stimulated and stimulated mice using RNA sequencing.Methods:C57Bl6 male mice underwent stereotaxic surgery to express Channelrhodopsin in iM1 excitatory neurons, with optical fiber implanted in the same location. After 5-6 weeks, mice underwent transient middle cerebral artery occlusion (30 minutes). Stimulated mice received optogenetic stimulations from post-stroke days (PD) 5–14. Rotating beam test was performed at pre-stroke baseline, PD4, 7 and 14. iM1 from stimulated, non-stimulated stroke mice at PD 7&15, and sham mice were processed for RNA sequencing (n=4-5/group). Expression of cholesterol enzymes such as HMGCS1 was examined using quantitative PCR and immunohistochemistry. Cholesterol levels were visualized using filipin or BODIPY.Results:iM1 stimulations enhanced recovery at PD14, with longer distance traveled and faster speed on the rotating beam test (p

Stroke, Volume 56, Issue Suppl_1, Page AWP175-AWP175, February 1, 2025. Background:Post-stroke cognitive impairment (PSCI) is a condition characterized by cognitive decline that occurs after a stroke. PSCI affects up to 60% of stroke survivors. Early detection of those at high risk for PSCI is essential for timely intervention and personalized care. Electronic health records (EHRs) contain valuable data that can be leveraged by machine learning to predict PSCI, potentially enhancing patient outcomes. This study focuses on developing and validating machine learning models to predict PSCI, aiming to enable earlier diagnosis and improve post-stroke care.Methods:7956 all-type stroke patients (including Ischemic&Hemorrhagic stroke) treated between 2012 and 2021 were extracted from Emory Healthcare system. We employed multiple methods to predict PSCI, using ICD codes and prescribed medications that were available up to the discharge of index strokes. First, we utilized traditional machine learning methods, including Logistic Regression, Support Vector Machine, and Random Forest to develop models. Then, we developed hypergraph models to enhance prediction performance. Unlike traditional graphs that only capture pair-wise relationships between pairs of entities, hypergraphs can model the more complex higher-order relationships among multiple entities, by allowing a hyperedge (encounter) to connect multiple vertices (ICD and medications) simultaneously among patient visits and EHR medical features. Finally, we compared the performance across different methods and selected the best one for the PSCI prediction task. We compared their performance on four metrics: ACC (Accuracy, the proportion of correct predictions), AUC (Area Under the ROC Curve, measuring the model’s ability to distinguish between classes), AUPR (Area Under the Precision-Recall Curve, a comprehensive measure considering both precision and recall), and Macro-F1 (a balanced measure calculated by the harmonic mean of precision and recall).Results:We included 7956 all-type stroke patients (50% female, 56% non-white) in this analysis, where 1797 (23%) had diagnostic codes often used by clinicians at Emory to document PSCI. According to the performance, the hypergraph model was associated with higher ACC, AUC, AUPR, and Macro-F1 than other models.Conclusion:By comparing the results of various machine learning methods, we found that hypergraph model approaches outperform traditional machine learning methods in utilizing EHRs for predicting PSCI after a stroke.

Stroke, Volume 56, Issue Suppl_1, Page A97-A97, February 1, 2025. Objective:To evaluate a potential relationship between post-stroke cognitive impairment (PSCI) and a radiographic measure of glymphatic function after intracerebral hemorrhage (ICH).Introduction:PSCI has been less studied in patients with ICH. Here we aim to evaluate the role of glymphatic function after ICH and its association with PSCI. Glymphatic cleanup occurs in the perivascular space (PVS) formed by astroglial end-feet loosely surrounding small arteries and veins. Here we applied non-invasive diffusion tensor imaging (DTI) to measure changes in brain diffusion due to dynamics changes of interstitial fluid (ISF) and CSF along the PVS. The application of DTI-along the perivascular space index (DTI-ALPSI) has been validated to evaluate glymphatic function. It computes the diffusivity ratio between projection and association fibers oriented orthogonally with the medullary veins at the level of the lateral ventricle body (Fig-1A).Methods:We serially imaged 18 patients with deep ICH at 9.3±9.1 (V1) and 109±28 (V2) days of onset on a 3T MRI system. Cognitive assessment was obtained via MoCA scores. Fractional anisotropy (FA) and mean diffusivity (MD) maps were registered to the T1W and SWI images. Three regions of interest (ROI), remote from a lesion, in the association and projection fibers, orthogonal to the medullary veins at PVS were used to compute diffusivity (Fig-1C). Using the equation shown, the DTI-ALPSI was calculated. DTI-ALPSI = Mean (Dx proj, Dx assoc) / Mean (Dy proj, Dz assoc)Using 3D-Flair images, hematoma (HV) and edema (EV) volumes were segmented. The ipsilesional DTI-ALPSI was correlated with MoCA, HV, and NIHSS. Contralesional DTI-ALPSI was used as a control. A non-linear regression model was used for statistical analysis.Results:We enrolled 12M/6F with an average age of 49.3±13.3y. Compared to the control, the ipsilesional DTI-ALPSI was significantly decreased (p=0.036) at V2. Temporally the MoCA scores were significantly increased (19±8.5 to 23±6.0, p