Anticoagulation in older people with atrial fibrillation moving to care homes: a data linkage study

Background: Treatment decisions about oral anticoagulants (OAC) for atrial fibrillation (AF) are complex in older care home residents. Aim: To explore factors associated with OAC prescription. Design and Setting: Retrospective cohort study set in care homes in Wales, United Kingdom, listed in the Care Inspectorate Wales Registry 2017/18. Method: Analysis of anonymised individual-level electronic health and administrative data on people aged ≥65 years entering a care home between 1st January 2003 and 31st December 2018, provisioned from the Secure Anonymised Information Linkage Databank. Results: Between 2003 and 2018, 14,493 people with AF aged ≥65 years became new residents in care homes in Wales and 7,057 (48.7%) were prescribed OAC (32.7% in 2003 compared to 72.7% in 2018) within six months prior to care entry. Increasing age and prescription of antiplatelet therapy were associated with lower odds of OAC prescription (adjusted odds ratio [aOR] 0.96 per one year age increase [95% confidence interval [CI] 0.95 to 0.96] and aOR 0.91 [0.84 to 0.98], respectively). Conversely, prior venous thromboembolism (aOR 4.06 [3.17 to 5.20]), advancing frailty (mild: aOR 4.61 [3.95 to 5.38]; moderate: aOR 6.69 [5.74 to 7.80]; severe: aOR 8.42 [7.16 to 9.90]) and year of care home entry from 2011 onwards (aOR 1.91 [1.76 to 2.06]) were associated with higher odds of OAC prescription. Conclusions: There has been an increase in OAC prescribing in older people newly admitted to care homes with AF. This study provides an insight into the factors influencing OAC prescribing in this population

An SPR based sensor for allergens detection

A simple, sensitive and label-free optical sensor method was developed for allergens analysis using α-casein as the biomarker for cow's milk detection, to be used directly in final rinse samples of cleaning in place systems (CIP) of food manufacturers. A Surface Plasmon Resonance (SPR) sensor chip consisting of four sensing arrays enabling the measurement of samples and control binding events simultaneously on the sensor surface was employed in this work. SPR offers several advantages in terms of label free detection, real time measurements and superior sensitivity when compared to ELISA based techniques. The gold sensor chip was used to immobilise α-casein-polyclonal antibody using EDC/NHS coupling procedure. The performance of the assay and the sensor was first optimised and characterised in pure buffer conditions giving a detection limit of 58 ng mL−1 as a direct binding assay. The assay sensitivity can be further improved by using sandwich assay format and amplified with nanoparticles. However, at this stage this is not required as the detection limit achieved exceeded the required allergens detection levels of 2 µg mL−1 for α-S1-casein. The sensor demonstrated good selectivity towards the α-casein as the target analyte and adequate recoveries from CIP final rinse wash samples. The sensor would be useful tool for monitoring allergen levels after cleaning procedures, providing additional data that may better inform upon wider food allergen risk management decision(s) that are made by food manufacturer. In particular, this sensor could potentially help validate or optimise cleaning practices for a given food manufacturing process

A Measurement Invariance Analysis of the Interpersonal Needs Questionnaire and Acquired Capability for Suicide Scale in Autistic and Non-Autistic Adults.

Background: Autistic adults are more likely to engage in suicidal thoughts and behaviors, but there is little research to explore the underlying reasons. It is unclear whether self-report suicide scales that have been designed for non-autistic people accurately measure suicide risk constructs in autistic people. Therefore, this study explored, for the first time, whether the measurement properties of the self-report scales of the Interpersonal Theory of Suicide are equivalent in autistic and non-autistic adults. Methods: In this study, responses from 342 autistic and 353 non-autistic people on the Interpersonal Needs Questionnaire-10 (INQ-10) and Acquired Capability for Suicide Scale-Fearlessness about Death (ACSS-FAD) were compared by using measurement invariance analysis. Data were gathered through an online cross-sectional survey of the self-report measures. Results: Results suggest that measurement properties of the INQ-10 were different in autistic people. Autistic characteristics, such as different theory of mind and preference for concrete language, may have led the scale items to load differently on the factors in the autistic group than in the non-autistic group. The measurement properties of the ACSS-FAD were invariant between autistic and non-autistic people. Conclusions: Scores on the INQ-10 cannot be meaningfully compared between autistic and non-autistic people due to different measurement properties. Future research could explore how autistic people experience the concepts of burdensomeness and belonging, to consider how measures could accurately capture this. This would allow researchers to explore the role of these constructs in the development of suicidal thoughts and behaviors in autistic people. Clinicians should be aware that suicide risk factors may present differently in autistic people. Scores on the ACSS-FAD can be meaningfully compared, but the negatively worded scale items may pose similar response difficulties to autistic and non-autistic people

Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data

Introduction Demographic profiling is an important aspect of anonymised healthcare research to identify the population of interest. Typically, administrative data is used in conjunction with patient registers to create cohorts, but it can be a time consuming process. We describe a method using routinely collected health data to identify vulnerable populations. Objectives and Approach Using existing longitudinal data and the Residential Anonymised Linking Field (RALF) we aim to identify institutions linked to vulnerable populations. We search for specific characteristics of these institutions including the age of occupants, number of current residents, and rate of change of occupants. We also aim to compare our method to a pseudonymised national registry for care homes to ensure it is accurate. This can effectively reduce the need for repeat pseudonymisation of institutions, which is both expensive and time consuming. Results To implement our method we found the most recent address for living individuals aged 65-95. This produced 202,640 residences from 1,330,335. Of the 202,640 residences, 1347 had four or more cohabitants aged 65-95, and 172 had exactly three residents with ten or more distinct individuals registered over a 10-year period. Our final synthetic dataset therefore had 1519 unique potential care homes to compare to the national registry, which contains 1525 registered care homes. We can now link the synthetic dataset to individuals to flag their residential status, which may be a defining factor in their level of care. Furthermore, we can answer specific research questions relating to their residency, such as the time it takes to move to a care home following a hospital admission. Conclusion/Implications By using quantifiable characteristics of care homes we were able to create a synthetic care home register by searching existing data. This is a reproducible process that would be of particular benefit for projects where a registry is not available, or where time or cost would limit the availability

Routinely Identifying frailty: Implementing the electronic Frailty Index in the Secure Anonymised Information Linkage Databank

Background Aging populations with increasing frailty have major implications for health services, and evidence-based treatment becomes increasingly important. The development of the electronic Frailty Index (eFI) using routine primary care data facilitates the implementation of evidence-based interventions and care. Method Our implementation of the eFI in the Secure Anonymised Information Linkage (SAIL) databank identifies frailty based on 1574 Read codes, which are mapped amongst 36 categories known as deficits. The eFI is based on a cumulative deficit model, and each deficit contributes equally to the eFI value. Findings Although each deficit is equally weighted, only one is currently time dependent. We therefore analysed the cumulative prevalence of each deficit on a year-by-year basis. This led to the identification of time bounds for particular deficits, which will help to refine future implementations of the eFI. We also further validated the eFI using data from over 400,000 individuals held in SAIL. Conclusion The eFI is particularly useful as it uses existing data to identify frailty, meaning no additional resources are required. Furthermore, our implementation is readily available, meaning that future research related to frailty is easily achievable by others

Detecting Care Homes: Using Residential Anonymous Linking Fields to Identify Care Homes in Administrative Data

Background Demographic profiling is an important aspect of anonymised healthcare research used to identify populations of interest. Typically, administrative data is used in conjunction with patient registers to create cohorts, but it can be a time consuming process. Objectives We aim to create and apply a method of identifying care homes using existing administrative data. We also aim to test the accuracy of our method by comparing the results to a pseudonymised national care home registry. This will allow us to prove whether proxy methods may be of sufficient accuracy for data linkage research in the future. Methods (including data) Our method uses quantifiable characteristics from longitudinal data to identify potential care homes. This includes the number and age of occupants, current residence and rate of change of occupancy. Conclusions This method is a reproducible process that would be of particular benefit for projects where a registry is not available, or where time or cost would limit the availability. This method can also be generalised to any communal establishment, where often the identification of vulnerable populations (antibiotic resistance, infectious disease etc.) is particularly beneficial

Further Development and Validation of the electronic Frailty Index using the Secure Anonymised Information Linkage Databank

Introduction Aging populations with increasing frailty have major implications for health services internationally, and evidence-based treatment becomes increasingly important. The development of an electronic Frailty Index (eFI) using routine primary care data facilitates implementation of evidence-based interventions. However, the eFI does not account for time restrictions regarding when information was recorded. Objectives and Approach Our aim is to implement and further validate the eFI using the Secure Anonymised Information Linkage (SAIL) databank, introducing refinements based on time restrictions. Our implementation of the eFI identifies frailty based on 1574 Read codes, which are mapped amongst 36 categories known as deficits. The eFI is based on the internationally established cumulative deficit model, and each deficit contributes equally to the eFI value. However, although each deficit is equally weighted, only one of them is currently time dependent. We therefore analyse the time at which each deficit is identified, and propose time dependent cut-points based on our findings. Results We were able to successfully implement the eFI using data from over 400,000 individuals from the Welsh population using data held in the SAIL databank. Our results agree with the baseline characteristics and distributions of frailty found in the original development of the eFI. We also found that the percentage of individuals identified as frail increased as the number of years of records included was increased. Furthermore, the increase in percentage year by year was almost linear for a number of the deficits. This led to the identification of time bounds for particular deficits, which could help to refine future implementations of the eFI. Conclusion/Implications Our work validates and refines the eFI, which is a particularly useful resource as it uses existing primary care data to identify frailty, meaning no additional resources are required. Furthermore, our implementation is readily available, meaning that future research related to frailty is easily reproducible and achievable by others

A rate-based approach to cleaning-in-place

Fouling is a major problem in the food industry. In cases where allergens are involved, excessive cleaning of food processing equipment often takes place to ensure allergen levels are reduced to acceptable levels. Experimental trials were conducted in a pilot scale cleaning rig to assess the effect of fluid flow rate and temperature on the removal rate of milk paste during cleaning-in-place. Conductivity measurements taken during trials were analysed to produce an equation enabling calculation of the cleaning rate with water temperature, flow rate, initial deposit mass, and time. The rate of cleaning with detergent was also investigated. This methodology produces a rate based expression for cleaning which can be applied to other products, and can be used to determine the time when cleaning is complete, the extent of a cleaning process, or when the pre-rinse should be replaced with a detergent rinse. This prevents over-cleaning and therefore reduces the costs associated with over-cleaning through energy, material and loss of production time

Development of a β-Lactoglobulin sensor based on SPR for milk allergens detection

A sensitive and label-free surface plasmon resonance (SPR) based sensor was developed in this work for the detection of milk allergens. β-lactoglobulin (BLG) protein was used as the biomarker for cow milk detection. This is to be used directly in final rinse samples of cleaning in-place (CIP) systems of food manufacturers. The affinity assay was optimised and characterised before a standard curve was performed in pure buffer conditions, giving a detection limit of 0.164 µg mL−1 as a direct binding assay. The detection limit can be further enhanced through the use of a sandwich assay and amplification with nanomaterials. However, this was not required here, as the detection limit achieved exceeded the required allergen detection levels of 2 µg mL−1 for β-lactoglobulin. The binding affinities of the polyclonal antibody for BLG, expressed by the dissociation constant (KD), were equal to 2.59 × 10−9 M. The developed SPR-based sensor offers several advantages in terms of label-free detection, real-time measurements, potential on-line system and superior sensitivity when compared to ELISA-based techniques. The method is novel for this application and could be applied to wider food allergen risk management decision(s) in food manufacturing