Search Results for: Caratterizzazione dell'asma in base all'età di insorgenza: uno studio di coorte multi-database

Objectives
The inflammatory response from acute infection may trigger cardiovascular events. We aimed to estimate associations between microbiologically confirmed urinary tract infections (UTIs) and first acute myocardial infarction (MI) and stroke.

Design
We used a self-controlled case series, with risk periods 1–7, 8–14, 15–28 and 29–90 days after UTI. Included individuals experienced the outcome and exposure of interest and acted as their own controls.

Setting
We used individually linked general practice, hospital admission and microbiology data for the population of Wales held by the Secure Anonymised Information Linkage databank.

Participants
Included individuals were Welsh residents aged over 30 years with a record of a hospital admission for MI or stroke (outcomes) and evidence of a microbiologically confirmed UTI (exposure) during the study period of 1 January 2010 to 31 December 2020.

Main outcome measures
The primary outcome was acute MI or stroke identified using the International Classification of Disease V.10 codes from inpatient diagnoses recorded in the Patient Episode Database for Wales. We used Poisson regression to estimate incidence rate ratios (IRRs) and 95% CIs for MI and stroke during predefined risk periods, compared with baseline periods.

Results
During the study period, 51 660 individuals had a hospital admission for MI, of whom 2320 (4.5%) had 3900 microbiologically confirmed UTIs, and 58 150 had a hospital admission for stroke, of whom 2840 (4.9%) had 4600 microbiologically confirmed UTIs. There were 120 MIs during risk periods and 2190 during baseline periods, with an increased risk of MI for 1–7 days following UTI (IRR 2.49, 95% CI (1.65 to 3.77)). There were 200 strokes during risk periods and 2640 during baseline periods, with an increased risk of stroke for 1–7 days following UTI (IRR 2.34, 95% CI (1.61 to 3.40)).

Conclusions
UTI may be a trigger for MI or stroke. Further work is needed to understand mechanisms and test interventions to reduce the risk of cardiovascular events among people with UTIs in primary care.

Stroke, Ahead of Print. BACKGROUND:As indications for and utilization of mechanical thrombectomy continue to expand, there has been an increasing focus on developing improved tools for functional outcome prediction. We aim to evaluate the reliability of utilizing the areas of contrast staining for the Alberta Stroke Program Early Computed Tomography Score (s-ASPECTS) rating in immediate postthrombectomy flat-panel computed tomography and investigate its outcome predictive performance.METHODS:Retrospective analysis of a prospectively collected institutional mechanical thrombectomy database spanning March 2018 to February 2024. s-ASPECTS was calculated. We used ordinal logistic regression models to estimate the relationship between s-ASPECTS and the 90-day modified Rankin Scale and the additional value of these findings to the linear predictor of the MR-PREDICTS tool.RESULTS:One thousand sixty-three patients were included in this study with a mean age of 65±15 years, with 53% being male. s-ASPECTS was independently associated with functional outcomes. s-ASPECTS was observed to have more relevance in the clinical predictive model compared with baseline Alberta Stroke Program Early Computed Tomography Score, as well as to occlusion site and final expanded Thrombolysis in Cerebral Infarction grade. s-ASPECTS was lower among patients with more proximal occlusions, with a lower degree of final reperfusion, with a higher number of passes and longer procedures. The information gathered from flat-panel computed tomography added 18% of new information to MR-PREDICTS, as assessed by the ratio of the variances of the estimated probabilities of good functional outcome with an interobserver consensus score of κ=0.63.CONCLUSIONS:s-ASPECTS was reliably reported and found to be a stronger predictor of outcome compared with baseline Alberta Stroke Program Early Computed Tomography Score, characterizing it as an important prognostic tool for evaluating functional outcomes of patients following mechanical thrombectomy. Further studies are warranted.

Objectives
To develop a teaching exemplar for optimising the safe and accessible delivery of chair-based yoga to multimorbid older adult populations.

Design
A qualitative process evaluation embedded within the multi-site, randomised controlled Gentle Years Yoga trial for older adults (65+ years) with two or more long-term health conditions (trial status: completed).

Setting
Online and face-to-face interviews were conducted with participants and yoga teachers involved in the 12-week chair-based yoga intervention. Interview data were supplemented with observations of in-person and online yoga class delivery.

Participants
All yoga teachers delivering the yoga intervention were invited to take part in the interviews, together with a subsample of participants receiving the yoga intervention. Participants were purposively selected to represent the trial cohort demographics of gender, age, ethnicity, index of multiple deprivation, and number and intensity of chronic health conditions.

Results
25 yoga participants and 11 yoga teachers took part in one (N=19) or two (N=17) interviews. Participants were aged 66–91 years (mean age 74 years), with 2–8 long-term health conditions, most commonly osteoarthritis (N=15, 60%), cardiovascular disease (N=14, 56%), sensory conditions (N=9, 36%) and depression or anxiety (N=8, 32%). Yoga teachers were predominantly female (N=10, 91%), with 4–35 years yoga teaching experience across multiple yoga styles. Feedback from yoga teachers and participants was classified into six categories, generating a 21-item teaching exemplar. These covered aspects of delivery including class size and delivery formats, choosing appropriate physical content, enhancing inclusivity of personal beliefs through non-physical content, proactive teaching styles, communication tips and ways to boost visibility.

Conclusions
This 21-item list adds to the current educational base of yoga for older adults. Addressing both face-to-face and online class formats, this exemplar offers pragmatic guidance for yoga teachers to enhance the safe and accessible delivery of chair-based yoga to older adults and multimorbid populations.

Trial registration number
ISRCTN13567538.

Objectives
Low-level viremia (LLV) is a risk factor affecting the prognosis of patients with chronic hepatitis B (CHB). The objective of this study was to systematically assess the prevalence of LLV, thereby providing robust evidence-based medical insights into effective clinical interventions and preventative measures against LLV.

Design
Systematic review and meta-analysis.

Data sources
A comprehensive literature search was conducted across various databases, including China National Knowledge Infrastructure, Wanfang Data (Wanfang), China Science And Technology Journal Database (VIP-CSTJ), China Biology Medicine disc (CBMdisc), PubMed, Embase, Web of Science and the Cochrane Library, spanning from the inception of these databases up to 5 January 2024.

Eligibility criteria
The research type included either a cross-sectional study or a cohort study focusing on the Chinese population, with the outcome being LLV. The languages were limited to both Chinese and English. Studies with any of the following were excluded: subjects with other comorbidities, original articles inaccessible or data unavailable, and duplicate publications.

Data extraction and synthesis
Literature management used EndNote X9.1, and an information extraction table was created using Microsoft Excel to record research information, including first author, year of publication and study type. The prevalence of LLV was assessed via meta-analysis. Meta-analyses were conducted in RStudio using the ‘metaprop ()’ function. Subgroup analysis and sensitivity analysis were used to identify sources of heterogeneity, and funnel plots and AS-Thompson tests were employed to evaluate publication bias.

Results
18 studies, encompassing a total sample of 9773 patients, were included in the analysis. Of these, 3336 patients were identified with LLV. The meta-analysis revealed that the prevalence of LLV among treated CHB patients stands at 33.6% (95% CI 30.2 to 37.0). The antigen status, antiviral treatment regimen (type of drugs and nucleos(t)ide analogues (NAs)), treatment duration, medication adherence and baseline hepatitis B virus DNA levels all affected the prevalence of LLV. Sensitivity analysis further corroborated the stability of these meta-analysis findings. The funnel plot and AS-Thompson test indicated no significant publication bias (t = –0.01, p=0.995).

Conclusions
The prevalence of LLV among CHB patients was established at 33.7% (95% CI 29.8% to 37.6%). Thus, it is imperative for clinical decision-makers to consider the various influencing factors of LLV when formulating treatment plans in order to mitigate any potential adverse outcomes.

Risultati incoraggianti da studio fase 3 su sotatercept

‘Poche indicazioni di base e buon senso per fare la differenza’

Studio dell’Istituto nazionale tumori su terapia non chirurgica

Studio dell’Istituto nazionale tumori su terapia non chirurgica

Importance
Background rates are critical for contextualising safety signals arising from COVID-19-related interventions in investigational or real-world settings.

Objective
To estimate background rates of medical events of interest (MEI) for which COVID-19 infection and/or COVID-19 interventions may be risk factors in two US claims databases.

Design, setting and participants
This retrospective cohort study spans the pre-COVID-19 (2018–2019) and COVID-19 (2020–2021) periods. We constructed three cohorts, in each of Inovalon/HealthVerity (Inovalon/HV) and Optum databases: a COVID-19-positive adult cohort (2020–2021), a paediatric cohort (2018–2021) and a high-risk cohort (2018–2021) comprising patients at increased risk for severe COVID-19. Participants were indexed on the day they first qualified to enter each cohort during the study period. Background rates of 17 MEI were estimated per 1000 person-years (PY) with 95% CIs.

Main outcomes and measures
Annual incidence rates (IRs) of 17 MEI.

Results
Overall, 758 414 (COVID-19-positive adults; 57.8% women), 12 513 664 (high-risk adults; 56.8% women) and 8 510 627 (paediatric patients; 49.1% women) patients were identified in the HV database. IRs of MEI varied substantially by year, data source, study cohort and duration of follow-up. The IRs of MEI were highest among COVID-19-positive adults and lowest among paediatric patients. For example, IR of myocarditis/pericarditis per 1000 PY was 3.0 (95% CI: 2.6 to 3.4) in the COVID-19-positive adult cohort vs 0.36 (95% CI: 0.34 to 0.37) among high-risk adults and 0.05 (95% CI: 0.05 to 0.06) among paediatric patients. In the COVID-19-positive adult cohort, we observed higher IRs during 90-day follow-up (eg, IR of acute myocardial infarction (AMI) 26.5 (95% CI: 25.3 to 27.7)) vs 365-day follow-up (eg, IR of AMI 20.0 (95% CI: 9.2 to 20.8)) and during 2020 compared with 2021. IRs were higher in the high-risk adult and paediatric populations during the pre-COVID-19 period than during the COVID-19 pandemic.

Conclusions
Substantial variability was observed in IRs of MEI by study cohort, year, data source and follow-up duration. When generating background rates for contextualising safety signals from COVID-19 interventions, careful consideration must be given to the indicated subpopulation of interest, COVID-19-related temporal variations and data sources.

Introduction
Non-pharmacological interventions, including musculoskeletal manipulations (MMs), have been proven effective for musculoskeletal disorders.

Objectives
To evaluate if MMs, including osteopathic manipulation and chiropractic care, are effective to improve quality of life, pain intensity and function in older adults with musculoskeletal disorders.

Design
Systematic review.

Data sources
A systematic search was conducted on MEDLINE/PubMed, EMBASE, Scopus, Web of Science, CINAHL, Cochrane Library, from database inception up to 2 January 2025.

Eligibility criteria
Randomised controlled trials, controlled non-randomised trials and open label trials evaluating the efficacy and safety of MM such as osteopathic manipulation, chiropractic manipulation, myofascial release, craniosacral therapy, as monotherapy or adjunctive therapies in older people (age ≥65 years) with musculoskeletal disorders. The main outcomes included pain intensity, functionality and quality of life. Additionally, other related outcomes were considered, such as medical use duration, mood, mobility, motion, strength and endurance. Finally, we considered any adverse events.

Data extraction and synthesis
Selection and data extraction were performed independently by two authors. The effect estimates for each study were performed using Review Manager V.5.14. Continuous outcomes were analysed using the mean difference (95% CI). The methodological quality of the included studies was assessed using the Cochrane Risk of Bias tool 2 (RoB 2). No meta-analysis was performed.

Results
Five parallel randomised controlled trials were included, with a total sample size of 676 participants (41.6% women with a mean age of 77.3 years): 34 with chronic pain, 265 with neck pain and 377 with low back pain. MMs were not effective in patients with chronic pain, neither in pain intensity nor in functionality. For neck pain, considering the main outcomes, only in one of the two studies was there a statistically significant improvement in neck pain intensity only at week 12 for spinal manipulative treatment (SMT)+home exercise (HE) compared with HE alone (ES=–0.90 (95% CI –1.46 to –0.34); p=0.002). For low back pain, SMT+HE showed a statistically significant reduction in pain at 12 weeks compared with HE (ES=–0.79 (95% CI –1.39 to –0.19) p=0.010. For neck pain and low back pain, no statistically significant improvement in functional status and quality of life was observed with MM compared with any control group. RoB 2 showed a high risk of bias in three studies and some concerns in the others. At the domain level, the lowest risk was observed in the randomisation process (80% with some concerns). All five studies reported adverse events, none of which were serious.

Conclusions
This review provides limited and inconclusive evidence about MM to improve quality of life, pain management and functional status in older adults with musculoskeletal disorders. However, MM appears to be generally safe and well-tolerated.

PROSPERO registration number
CRD42023473203.

A base di cellule pancreatiche derivate da staminali, studio 1/2

Purpose
Congenital cytomegalovirus (cCMV) is an important cause of long-term childhood disability. In Australia, the identification and treatment practices and the long-term clinical and neurodevelopmental outcomes of children with cCMV are unknown. The Australasian cCMV Register (ACMVR) is a longitudinal register and resource for research that aims to describe and explore, in Australian children with cCMV: (1) their clinical characteristics over time, (2) antiviral therapy use/prescribing up to 1 year of age and (3) risk factors and potential avenues for prevention of adverse sequelae of the virus.

Participants
Children

Background
 Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial role in risk prediction and patient stratification, particularly for heart failure (HF), a condition affecting over 64 million people globally and imposing an economic burden of approximately $108 billion annually. ML applications in HF include predictive analytics for risk assessment, identifying patient subgroups with varying prognoses and optimising treatment pathways. By accurately predicting the likelihood of hospitalisation and rehospitalisation, ML tools help tailor interventions, reduce hospital visits, improve patient outcomes and lower healthcare costs.

Objective
To conduct a comprehensive review of existing ML models designed to predict hospitalisation risk in individuals with HF.

Methods
A database search including PubMed, SCOPUS and Web of Science was conducted on 31 March 2024. Studies were selected based on inclusion criteria focusing on ML models predicting hospitalisation risks in adults with HF. The data from 27 studies meeting the criteria were extracted and analysed, with a focus on the predictive performance of the ML models and the presence of economic analysis.

Results
Most studies focused on predicting readmission rather than first-time hospitalisation. All included studies employed supervised ML algorithms, with ensemble-based methods generally yielding the highest predictive performance. For 30-day hospitalisation or readmission risk, Extreme Gradient Boosting (XGBoost) achieved the highest mean area under the curve (AUC) (0.69), followed by Naïve Bayes (0.68) and Deep Unified Networks (0.66). For 90-day risk, the best-performing models were Least Absolute Shrinkage and Selection Operator and Gradient Boosting, both with a mean AUC of 0.75, followed by Random Forest (0.67). When the prediction timeframe was unspecified, Categorical Boosting achieved the highest performance with a mean AUC of 0.88, followed by Generalised Linear Model Net and XGBoost (both 0.79).
Electronic health records were the primary data source across studies; however, few models included patient-reported outcomes or socioeconomic variables.
None of the studies conducted an economic evaluation to assess the cost-effectiveness of these models.

Conclusions
ML holds substantial potential for improving HF care. However, further efforts are needed to enhance the generalisation of models, integrate diverse data sources and evaluate the cost-effectiveness of these technologies.