Risultati per: I numeri del cancro in Italia 2019

Report Ecdc, 2.268 gravi infezioni segnalate, 241 nostro paese

Objectives
To describe clinical characteristics and prognosis related to heart failure (HF) phenotypes in a community-based population by applying a novel algorithm to obtain ejection fractions (EF) from electronic medical records.

Design
Retrospective population-based cohort study.

Setting
Data were collected for all patients with HF in Southwest Sweden. The region consists of three acute care hospitals, 40 inpatient wards, 2 emergency departments, 30 outpatient specialty clinics and 48 primary healthcare.

Participants
8902 patients had an HF diagnosis based on the International Classification of Diseases, Tenth Revision during the study period. Patients

Da test risultati positivi contro il melanoma

This study uses national cancer incidence data to evaluate calendar trends in cervical cancer incidence by age at diagnosis.

To the Editor A recent article reported a significant decline in 21 measures of hospital adverse events across 4 adverse event domains from 2010 to 2019 based on abstracted data from the Medicare Patient Safety Monitoring System (MPSMS) for patients with 4 principal diagnoses. In May 2022, the US Department of Health and Human Services, Office of Inspector General (OIG) released the results of a nationally representative medical record review with a less positive message. The OIG’s study found that 25% of Medicare patients experienced a harm event in October 2018, which was not statistically different from the rate of 27% that the OIG reported a decade ago.

In Reply In response to the OIG’s letter about our article, which concluded that there was a significant decrease in the rates of adjusted adverse events for hospital patients between 2010 and 2019, we agree that too many adverse events occurred, and efforts should be focused on lowering their frequency. However, we want to highlight important differences between their study and ours, and why we stand behind our results.

Objectives
To describe the extent to which pragmatic trials underachieved or overachieved their target sample sizes, examine explanations and identify characteristics associated with under-recruitment and over-recruitment.

Study design and setting
Secondary analysis of an existing database of primary trial reports published during 2014–2019, registered in ClinicalTrials.gov, self-labelled as pragmatic and with target and achieved sample sizes available.

Results
Of 372 eligible trials, the prevalence of under-recruitment (achieving 110% of target) was 87 (23.4%). Under-recruiting trials commonly acknowledged that they did not achieve their targets (51, 71.8%), with the majority providing an explanation, but only 11 (12.6%) over-recruiting trials acknowledged recruitment excess. The prevalence of under-recruitment in individually randomised versus cluster randomised trials was 41 (17.0%) and 30 (22.9%), respectively; prevalence of over-recruitment was 39 (16.2%) vs 48 (36.7%), respectively. Overall, 101 025 participants were recruited to trials that did not achieve at least 90% of their target sample size. When considering trials with over-recruitment, the total number of participants recruited in excess of the target was a median (Q1–Q3) 319 (75–1478) per trial for an overall total of 555 309 more participants than targeted. In multinomial logistic regression, cluster randomisation and lower journal impact factor were significantly associated with both under-recruitment and over-recruitment, while using exclusively routinely collected data and educational/behavioural interventions were significantly associated with over-recruitment; we were unable to detect significant associations with obtaining consent, publication year, country of recruitment or public engagement.

Conclusions
A clear explanation for under-recruitment or over-recruitment in pragmatic trials should be provided to encourage transparency in research, and to inform recruitment to future trials with comparable designs. The issues and ethical implications of over-recruitment should be more widely recognised by trialists, particularly when designing cluster randomised trials.

Objective
To compare the burden of multiple sclerosis disease indicators in the Asia-Pacific countries, China and globally through the Global Burden of Disease 2019 (GBD2019) Database, and to analyse the changes of multiple sclerosis disease burden in China from 1990 to 2019.

Study design
Observational study based on the Global Burden of Disease.

Setting
The relevant incidence, prevalence, death and disability-adjusted life year (DALY) rates and corresponding age-standardised rates (ASRs) and sociodemographic index (SDI) in China, globally and in Asia-Pacific countries were extracted from the GBD2019 Database to further study the age-standardised incidence, prevalence and mortality, and the relationship between DALY rate and SDI.

Results
Various disease burden indicators of multiple sclerosis in China are at low level in the world, and the prevalence, incidence and DALY rates have slowly increased from 1990 to 2019. During this period, the age-standardised prevalence rate (ASPR) of multiple sclerosis in China showed an upward trend, while the age-standardised death rate (ASDR), age-standardised DALY rate (ASR-DALY) and age-standardised incidence rate all decreased to varying degrees, which were roughly consistent with the global amplitude changes, and all indicators are similar to most countries in the Asia-Pacific region. As the value of the SDI increases, the ASPR of multiple sclerosis was trending upward, and the ASDR was trending downward.

Conclusion
Compared with other countries in the Asia-Pacific region, China is in a low state of disease burden indicators. However, as a developing country and the most populous country in the world, the total number of patients is not small, and as a rare disease, the treatment cost is relatively expensive, and the treatment cost of the complications caused by the disease is not low. The construction of the medical security system should be strengthened to reduce its burden on individuals, families and society.

Objectives
To assess the prevalence of and factors associated with the lifetime medical diagnosis of depression in Brazil.

Design
Population-based, cross-sectional study.

Setting
Analysis of data from the 2019 Brazilian National Health Survey.

Participants
90 846 individuals aged ≥15 years were included.

Outcome measure
The self-reported medical diagnosis of depression at some point in one’s life was the main outcome. Prevalence ratios (PRs) with 95% CIs were calculated by Poisson regression with robust variance. The independent variables included the geographical area of residence, sociodemographic characteristics, current smoking status, alcohol abuse, daily screen time, and the presence of physical disorders and mental health comorbidities.

Results
The self-reported lifetime prevalence of medical diagnosis of depression was 9.9% (95% CI 9.5% to 10.2%). The probability of having received a medical diagnosis of depression was higher among urban residents (PR 1.23; 95% CI 1.12 to 1.35); females (2.75; 2.52 to 2.99); those aged 20–29 years (1.17; 0.91 to 1.51), 30–39 years (1.73; 1.36 to 2.19), 40–49 years (2.30; 1.81 to 2.91), 50–59 years (2.32; 1.84 to 2.93) and 60–69 years (2.27; 1.78 to 2.90) compared with those under 20 years; white-skinned people (0.69 (0.61 to 0.78) for black-skinned people and 0.74 (0.69 to 0.80) for indigenous, yellow and brown-skinned people compared with white-skinned people); those with fewer years of education (1.33(1.12 to 1.58) among those with 9–11 years, 1.14 (0.96 to 1.34) among those with 1–8 years and 1.29 (1.11 to 1.50) among those with 0 years compared with those with ≥12 years of education); those who were separated/divorced (1.43; 1.29 to 1.59), widowed (1.06; 0.95 to 1.19) and single (1.01; 0.93 to 1.10) compared with married people; smokers (1.26; 1.14 to 1.38); heavy screen users (1.31; 1.16 to 1.48) compared with those whose usage was

Objectives
This study assesses effective coverage of diabetes and hypertension in Thailand during 2016–2019.

Design
Mixed method, analysis of National health insurance database 2016–2019 and in-depth interviews.

Setting
Beneficiaries of Universal Coverage Scheme residing outside Bangkok.

Participants
Quantitative analysis was performed by acquiring individual patient data of diabetes and hypertension cases in the Universal Coverage Scheme residing outside bangkok in 2016-2019. Qualitative analysis was conducted by in-depth interview of 85 multi-stakeholder key informants to identify challenges.

Outcomes
Estimate three indicators: detected need (diagnosed/total estimated cases), crude coverage (received health services/total estimated cases) and effective coverage (controlled/total estimated cases) were compared. Controlled diabetes was defined as haemoglobin A1C (HbA1C) below 7% and controlled hypertension as blood pressure below 140/90 mm Hg.

Results
Estimated cases were 3.1–3.2 million for diabetes and 8.7–9.2 million for hypertension. For diabetes, all indicators have shown slow improvement between 2016 and 2019 (67.4%, 69.9%, 71.9% and 74.7% for detected need; 38.7%, 43.1%, 45.1% and 49.8% for crude coverage and 8.1%, 10.5%, 11.8% and 11.7% for effective coverage). For hypertension, the performance was poorer for detection (48.9%, 50.3%, 51.8% and 53.3%) and crude coverage (22.3%, 24.7%, 26.5% and 29.2%) but was better for effective coverage (11.3%, 13.2%, 15.1% and 15.7%) than diabetes. Results were better for the women and older age groups in both diseases. Complex interplays between supply and demand side were a key challenge. Database challenges also hamper regular assessment of effective coverage. Sensitivity analysis when using at least three annual visits shows slight improvement of effective coverage.

Conclusion
Effective coverage was low for both diseases, though improving in 2016–2019, especially among men and ัyounger populations. The increasing rate of effective coverage was significantly smaller than crude coverage. Health information systems limitation is a major barrier to comprehensive measurement. To maximise effective coverage, long-term actions should address primary prevention of non-communicable disease risk factors, while short-term actions focus on improving Chronic Care Model.

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