Suchergebnisse

BackgroundAccurate assessment of childhood adversity is fundamental in understanding risk and resilient factors that can inform appropriate intervention and prevention strategies. Different statistical and methodological approaches (e.g., prospective, selfreported data) have been used to assess pathways and outcomes associated with childhood adversity, however, each is limited in a number of ways.
ObjectivesLinking administrative data to population-based studies provides a powerful tool to overcome some of the challenges in trauma research and permits the estimation of temporally ordered models of risk. The current study seeks to assess the effect of childhood adversity on a diagnosis of traumatic disorder (TD).
MethodsData were collected from a Danish national study in 2008/2009. A sample of 4,718 young adults were randomly selected from the birth cohort of children born in 1984. Structured interviews were conducted on 2,980 participants. This data was then linked with parental data (including 4 years prior to birth of child) and a ICD 10 diagnosis of a TD using information from the Danish registries.
FindingsHierarchical regression analysis was used to examine parental risk factors, self-reported child maltreatment, experiencing violence in young adulthood and risk of a TD diagnosis at age 28. Findings indicated the dominant factor associated with TD was self-reported PTSD symptoms at age 24 (OR =3.82); followed by a parental mental health diagnosis (OR = 2.80). Being of female gender (OR = 2.42) and experiencing violence in young adulthood (OR = 1.94) also increased risk of a TD diagnosis.
ConclusionThis study highlights the benefits of incorporating administrative data with self-report data to provide a more nuanced understanding of childhood adversity across different developmental stages. These findings have important conceptual and methodological implications and may be useful in informing future trauma studies.

Abstract
Background
Patients presenting to Emergency Department (ED) with self-harm are recognized to be at high risk of suicide and other causes of death in the immediate period following ED presentation. It is also recognized that there is a large variation in the management and care pathways that these patients experience at EDs.

Aims
This study asks if there is a significant variation in mortality risk according to hospital attended and if this is explained by differences in care management.

Methods
Population-wide data from the Northern Ireland Registry of Self-Harm from April 2012 were linked with centrally held mortality records to December 2019, providing data on self-harm type and ED care. Cox proportional hazards models analyzed mortality risk, coded as suicide, all-external causes and all-cause mortality.

Results
Analysis of the 64,350 ED presentations for self-harm by 30,011 individuals confirmed a marked variation across EDs in proportion of patients receiving mental health assessment and likelihood of admission to general and psychiatric wards. There was a significant variation in suicide risk following attendance according to ED attended with the three-fold range between the lowest (HRadj 0.32 95% CIs 0.16, 0.67) and highest. These differences persisted even after adjustment for patient characteristics, variation in types of self-harm, and care management at the ED.

Conclusions
This study suggests that while the management of self-harm cases in the ED is important, it is the availability and access to, and level of engagement with, the subsequent management and care in the community rather than the immediate care at EDs that is most critical for patients presenting to ED with self-harm. However, the initial care in ED is an important gateway in initiating referrals to these services.

Funding: This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (HDRUK2020.146). EAVE II is funded by the Medical Research Council (MC_PC_19075) and supported by the Scottish Government. This work is supported by BREATHE - The Health Data Research Hub for Respiratory Health (MC_PC_19004). BREATHE is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. ConCOV is supported by the Medical Research Council (MR/V028367/1); Health Data Research UK (HDR-9006) which receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust; and Administrative Data Research UK which is funded by the Economic and Social Research Council (grant ES/S007393/1). ; Introduction : The novel coronavirus SARS-CoV-2, which emerged in December 2019, has caused millions of deaths and severe illness worldwide. Numerous vaccines are currently under development of which a few have now been authorised for population-level administration by several countries. As of 20 September 2021, over 48 million people have received their first vaccine dose and over 44 million people have received their second vaccine dose across the UK. We aim to assess the uptake rates, effectiveness, and safety of all currently approved COVID-19 vaccines in the UK. Methods and analysis : We will use prospective cohort study designs to assess vaccine uptake, effectiveness and safety against clinical outcomes and deaths. Test-negative case–control study design will be used to assess vaccine effectiveness (VE) against laboratory confirmed SARS-CoV-2 infection. Self-controlled case series and retrospective cohort study designs will be carried out to assess vaccine safety against mild-to-moderate and severe adverse events, respectively. Individual-level pseudonymised data from primary care, secondary care, laboratory test and death records will be linked and analysed in secure research environments in each UK nation. Univariate and multivariate logistic regression models will be carried out to estimate vaccine uptake levels in relation to various population characteristics. VE estimates against laboratory confirmed SARS-CoV-2 infection will be generated using a generalised additive logistic model. Time-dependent Cox models will be used to estimate the VE against clinical outcomes and deaths. The safety of the vaccines will be assessed using logistic regression models with an offset for the length of the risk period. Where possible, data will be meta-analysed across the UK nations. Ethics and dissemination : We obtained approvals from the National Research Ethics Service Committee, Southeast Scotland 02 (12/SS/0201), the Secure Anonymised Information Linkage independent Information Governance Review Panel project number 0911. Concerning English data, University of Oxford is compliant with the General Data Protection Regulation and the National Health Service (NHS) Digital Data Security and Protection Policy. This is an approved study (Integrated Research Application ID 301740, Health Research Authority (HRA) Research Ethics Committee 21/HRA/2786). The Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub meets NHS Digital's Data Security and Protection Toolkit requirements. In Northern Ireland, the project was approved by the Honest Broker Governance Board, project number 0064. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journals. ; Publisher PDF ; Peer reviewed