Nasal fentanyl alone plus buccal midazolam: an open-label, randomised, controlled feasibility study in the dying

Introduction: Many patients want to stay at home to die. They invariably become unable to take oral medication during their terminal phase. Symptoms are usually controlled by subcutaneous medications. There have been no studies on nasal fentanyl (NF) or buccal midazolam (BM) to control symptoms in the dying.Objective: To establish how best to conduct a definitive, randomised controlled trial (RCT) to determine whether NF and BM administered by families, for patients dying at home, lead to faster and better symptom control and fewer community nursing visits than standard breakthrough medication by healthcare professionals.Methods: This open-label mixed-method feasibility RCT compared the efficacy of NF and BM by family members to standard breakthrough medication by nurses for the terminally ill in a specialist palliative care unit. Partway through the study, a third observational arm was introduced where BM alone was used. The primary outcomes were whether recruitment and randomisation were possible, assessment of withdrawal and drop-out, and whether the methods were acceptable and appropriate.Results: Administration of NF and BM was acceptable to patients and families. Both were well tolerated. We were unable to obtain quality of life data consistently but did get time period data for dose-controlled symptoms.Conclusions: Study participation in a hospice population of the dying was acceptable. The results will help guide future community study planning

Eliciting and prioritising determinants of improved care in multimorbidity: A modified online Delphi study

BACKGROUND: Multimorbidity is a major challenge to health and social care systems around the world. There is limited research exploring the wider contextual determinants that are important to improving care for this cohort. In this study, we aimed to elicit and prioritise determinants of improved care in people with multiple conditions. METHODS: A three-round online Delphi study was conducted in England with health and social care professionals, data scientists, researchers, people living with multimorbidity and their carers. RESULTS: Our findings suggest a care system which is still predominantly single condition focused. 'Person-centred and holistic care' and 'coordinated and joined up care', were highly rated determinants in relation to improved care for multimorbidity. We further identified a range of non-medical determinants that are important to providing holistic care for this cohort. CONCLUSIONS: Further progress towards a holistic and patient-centred model is needed to ensure that care more effectively addresses the complex range of medical and non-medical needs of people living with multimorbidity. This requires a move from a single condition focused biomedical model to a person-based biopsychosocial approach, which has yet to be achieved

Case-finding and genetic testing for familial hypercholesterolaemia in primary care

Objective: Familial Hypercholesterolaemia (FH) is a common inherited disorder causing premature heart disease and death. We have developed novel case-finding algorithms (FAMCAT version 1 & 2) for application in primary care, to improve detection of FH and have evaluated their performance, at 95% specificity, to detect genetically-confirmed FH in the general population. We also compared these algorithms to established clinical case-finding criteria. Methods: Prospective validation study, in 14 general practices, recruiting participants from the general adult population with cholesterol documented. For 260 participants with available health records, we determined possible FH cases based on FAMCAT thresholds, Dutch Lipid Clinic Network (DLCN) score, Simon-Broome criteria and national recommended cholesterol thresholds (total cholesterol > 9.0 mmol/L if ≥30 years or > 7.5 mmol/L i

Understanding social care need through primary care big data: a rapid scoping review

Background A more comprehensive understanding and measurement of adult social care need could contribute to efforts to develop more effective, holistic personalised care, particularly for those with Multiple Long Term Conditions. Progress in this area faces the challenge of a lack of clarity in the literature relating to how social care need is assessed and coded within variables included in primary care databases.Aim To explore how social care need is assessed and coded within variables included in primary care databases.Design & setting An exploratory rapid scoping review of peer-reviewed articles and grey literature.Method Articles were screened and extracted onto a charting sheet and findings were summarised descriptively. Articles were included if published in English, related to primary care and social care using data from national primary care databases.Results The search yielded 4,010 articles. Twenty-seven were included. Six articles used the term ‘social care need’, although related terminology was identified including ‘need factors’, ‘social support’ and ‘social care support’. Articles mainly focused on specific components of social care need, including levels of social care usage/service utilisation and costs incurred to social care, primary care and other providers in addressing needs. A limited range of database variables were found measuring social care need.Conclusion Further research is needed on how social care need has been defined in a UK context and captured in primary care big databases. There is potential scope to broaden the definition of social care need, which captures social service needs and wider social needs

Lipid levels and major adverse cardiovascular events in patients initiated on statins for primary prevention: an international population-based cohort study protocol

Background Clinical guidelines recommend specific targets for low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) for primary prevention of cardiovascular disease (CVD). Furthermore, individual variability in lipid response to statin therapy requires assessment of the association in diverse populations.Aim To assess whether lower concentrations of LDL-C and non-HDL-C are associated with a reduced risk of major adverse cardiovascular events (MACE) in primary prevention of CVD.Design & setting An international, new-user, cohort study will be undertaken. It will use data from three electronic health record databases from three global regions: Clinical Practice Research Datalink, UK; PREDICT-CVD, New Zealand (NZ); and the Clinical Data and Analysis Reporting System, Hong Kong (HK).Method New statin users without a history of atherosclerotic CVD, heart failure, or chronic kidney disease, with baseline and follow-up lipid levels will be eligible for inclusion. Patients will be classified according to LDL-C ([less than]1.4, 1.4–1.7, 1.8–2.5, and ≥2.6 mmol/l) and non-HDL-C ([less than] 2.2, 2.2–2.5, 2.6–3.3, and ≥3.4 mmol/l) concentrations 24 months after initiating statin therapy. The primary outcome of interest is MACE, defined as the first occurrence of coronary heart disease, stroke, or cardiovascular death. Secondary outcomes include all-cause mortality and the individual components of MACE. Sensitivity analyses will be conducted using lipid levels at 3 and 12 months after starting statin therapy.Conclusion Results will inform clinicians about the benefits of achieving guideline recommended concentrations of LDL-C for primary prevention of CVD

Determining propensity for sub-optimal low-density lipoprotein cholesterol response to statins and future risk of cardiovascular disease

Background: Variability in low-density lipoprotein cholesterol (LDL-C) response to statins is underappreciated. We characterised patients by their statin response (SR), baseline risk of cardiovascular disease (CVD) and 10-year CVD outcomes.Methods and Results: A multivariable model was developed using 183,213 United Kingdom (UK) patients without CVD to predict probability of sub-optimal SR, defined by guidelines as <40% reduction in LDL-C. We externally validated the model in a Hong Kong (HK) cohort (n=170,904). Patients were stratified into four groups by predicted SR and 10-year CVD risk score: [SR1] optimal SR & low risk; [SR2] sub-optimal SR & low risk; [SR3] optimal SR & high risk; [SR4] sub-optimal SR & high risk; and 10-year hazard ratios (HR) determined for first major adverse cardiovascular event (MACE).Our SR model included 12 characteristics, with an area under the curve of 0.70 (95% confidence interval [CI] 0.70–0.71; UK) and 0.68 (95% CI 0.67–0.68; HK). HRs for MACE in predicted sub-optimal SR with low CVD risk groups (SR2 to SR1) were 1.39 (95% CI 1.35–1.43, p<0.001; UK) and 1.14 (95% CI 1.11–1.17, p<0.001; HK). In both cohorts, patients with predicted sub-optimal SR with high CVD risk (SR4 to SR3) had elevated risk of MACE (UK HR 1.36, 95% CI 1.32–1.40, p<0.001: HK HR 1.25, 95% CI 1.21–1.28, p<0.001). Conclusions: Patients with sub-optimal response to statins experienced significantly more MACE, regardless of baseline CVD risk. To enhance cholesterol management for primary prevention, statin response should be considered alongside risk assessment

Prevalence and distributions of severely elevated low-density lipoprotein cholesterol (LDL-c) according to age, gender and clinic location among patients in the Malaysian primary care

BackgroundAdults with severely elevated low-density lipoprotein cholesterol (LDL-c) may have familial hypercholesterolaemia (FH) and are at high risk of atherosclerotic cardiovascular disease (ASCVD). The prevalence of elevated LDL-c in primary care clinics in Malaysia is not known. Therefore, this study aimed to determine the prevalence and distributions of severely elevated LDL-c among adult patients attending public primary care clinics in Malaysia.MethodsA cross-sectional study was conducted at 11 public primary care clinics in the central states of Malaysia, among adults ≥18 years old with LDL-c recorded in the electronic medical record. Sociodemographic and LDL-c data from 2018 to 2020 were extracted. Severely elevated LDL-c was defined as ≥4 mmol/L, which were further classified into: 4.0–4.9, 5.0–5.9, 6.0–6.9 and ≥ 7 mmol/L.ResultsOut of 139,702 patients, 44,374 (31.8 %) had severely elevated LDL-c of ≥4 mmol/L of which the majority were females (56.7 %). The mean (±SD) age of patients with severely elevated LDL-c was younger at 56.3 (±13.2) years compared to those with LDL-c of <4.0 mmol/L at 59.3 (±14.5) years. In terms of LDL-c levels, 30,751 (69.3 %), 10,412 (23.5 %), 2,499 (5.6 %) and 712 (1.6 %) were in the 4.0–4.9, 5.0–5.9, 6.0–6.9 and ≥ 7 mmol/L categories, respectively.ConclusionThe prevalence of severely elevated LDL-c of ≥4.0 mmol/L among adult patients in public primary care clinics was high. These patients need to be further investigated for secondary and inherited causes such as FH. Therapeutic lifestyle modification and pharmacological management are pivotal to prevent ASCVD in these patients

Stratifying stroke severity: towards a personalised medicine application for primary care

Stroke remains a major cause of death and disability worldwide, despite advances in prevention and treatment. Improvements in acute care have led to many surviving after an incident stroke event. However, the prognosis after surviving remains compromised. This is due to the high risk of recurrent adverse cardiovascular events, greatest during the first year but persisting over one’s lifetime. Reducing long-term residual cardiovascular risk and improving quality of life are primary goals for clinical practice and research. Identifying patients at the greatest risk of subsequent major adverse cardiovascular events (MACE) could help clinicians and policymakers determine which patients need to be prioritised. This thesis research aimed to identify clinical phenotypes (that is, patient characteristics and distinct patient clusters) that correlate with subsequent MACE outcomes (defined as a diagnosis of either CHD, recurrent stroke, PVD, heart failure, or CVD-related mortality) in adults with an incident stroke diagnosis. Firstly, a systematic review was completed to identify and summarise the available evidence on prognostic models and assess their accuracy for predicting MACE outcomes in an adult with established stroke. Forty (40) full-text articles with 23 distinct prognostic models for predicting MACE outcomes in adults with established stroke were identified by the systematic review. There were 11 prognostic model developments and 77 external validations of models reported. Among the 23 models, the most frequently used predictors were age, sex, history of transient ischaemic attack, hypertension (blood pressure), and diabetes. Critical appraisal identified methodological limitations, in particular: inadequate sample size, improper handling of missing data, and incomplete evaluation of model performance. The Clinical Practice Research Datalink (CPRD GOLD), a longitudinal database of anonymised electronic health records (UK primary care data) linked to Hospital Episode Statistics (HES APC), national death registry, and social deprivation data was then used to undertake a series of data-related studies. Four cohort studies were completed using patients aged ³18 years with an incident stroke diagnosis between 1 January 1998 and 31 December 2017, and no prior history of either CHD, PVD or heart failure, to assess the risk of subsequent cardiovascular morbidity and mortality outcomes. In the analysis of 9,997,376 individual records in CPRD GOLD database, there were 82,774 non-fatal incident stroke events recorded in either primary care or hospital data – a stroke incident rate of 109.20 per 100,000 person-years (95% CI: 108.46 – 109.95). Of the 82,774 patients, 13,879 (16.8%) patients had a prior history of major adverse outcomes (CHD, PVD, and heart failure) and were excluded. Subsequent MACE was recorded in 47,500 (69.0%) of the remaining 68,877 patients. In the UK, the incidence of stroke and subsequent major adverse cardiovascular morbidity and mortality outcomes were higher in women, older populations, and people living in socially deprived areas. After excluding patients with stroke not-otherwise specified (n=36,551) and adjusting for potential confounders, patients with incident haemorrhagic stroke (n=6,535, 20.4%) had no significantly different risk of subsequent cardiovascular morbidity, compared with patients with incident ischaemic stroke (n=25,556, 79.6%) – CHD [HR 0.86, 95% CI 0.56 – 1.32], recurrent stroke [HR 0.92, 95% CI 0.83 – 1.02], PVD [HR 1.15, 95% CI 0.56 – 2.38], or heart failure [HR 1.03, 95% CI 0.61 – 1.74]. However, patients with incident haemorrhagic stroke had a significantly higher risk of subsequent CVD-related mortality [HR 2.35, 95% CI 2.04 – 2.72] and all-cause mortality [HR 2.16, 95% CI 1.94 – 2.41]. Propensityscore matched analysis of 1,039 patients with haemorrhagic stroke and 1,039 with ischaemic stroke showed similar risk in subsequent cardiovascular morbidity outcomes – CHD, recurrent stroke, PVD and heart failure. Obesity, a risk factor for stroke and is also a risk factor for hypertension and diabetes (known risk factors for CVD), is commonly measured using body mass index (BMI). In a multivariable analysis of a cohort of 30,702 patients with incident stroke and BMI record, individuals in higher BMI categories were associated with lower risk of subsequent: • MACE [overweight (BMI: 25.0-29.9 kg/m2): HR 0.96, 95% CI 0.93 – 0.99)], • PVD [overweight: HR 0.65, 95% CI 0.49 – 0.85; obesity class III (BMI: ³40 kg/m2): HR 0.19, 95% CI 0.50 – 0.77], • CVD-related mortality [overweight: HR 0.80, 95% CI 0.74 – 0.86; obesity class I (BMI: 30.0-34.9 kg/m2): HR 0.79, 95% 0.71 – 0.88; class II (BMI: 35.0-39.9 kg/m2): HR 0.80, 95% CI 0.67 – 0.96]; and • all-cause mortality [overweight: HR 0.75, 95% CI 0.71 – 0.79; obesity class I: HR 0.75, 95% CI 0.70 – 0.81; class II: HR 0.77, 95% CI 0.68 – 0.86] when compared with those with normal BMI. The results were similar irrespective of sex, smoking status, history of diabetes mellitus or cancer at the time of incident stroke. Using a combination of data-driven feature selection approaches and clinical expert opinion, 39 out of 336 characteristics (clinical features including sociodemographic, biochemical, comorbid conditions, and prescribed medications related to stroke or CVD) at the time of incident stroke were selected. An unsupervised machine learning approach [clustering algorithm for mixed (both categorical and continuous) data] was used to identify 4 phenotypic clusters for a cohort of 48,114 patients with incident stroke and subsequent outcomes occurring 30 days after incident stroke. Cluster 1 (n=5,201, 10.8%) was a cohort with high prevalence of CHD-related risk factors and prescribed medications; cluster 2 (n=18,655, 38.8%) a cohort with low prevalence of multiple long-term conditions (MLTC); cluster 3 (n=10,244, 21.3%) a cohort with high prevalence of MLTC; and cluster 4 (n=14,014, 29.1%), the oldest population cohort and predominantly female. The phenotypic clusters had different incidences and risks for subsequent cardiovascular morbidity and mortality outcomes. For instance, the incidence of the composite outcome of recurrent stroke and CVD-related mortality was lowest in cluster 1 and highest in cluster 4 (15.13 and 23.17 per 100 person-years, respectively). The risk of subsequent recurrent stroke + CVD-related mortality was significantly increased in cluster 2 (HR 1.07, 95% CI 1.02 – 1.12); cluster 3 (HR 1.20, 95% CI 1.14 – 1.26), and cluster 4 (HR 1.29, 95% CI 1.26 – 1.33), when compared with cluster 1. Findings from this thesis research indicate patients with incident stroke experience considerable heterogeneity in subsequent clinical outcomes. In particular, women, older patients, and those living in socially deprived areas are at greater risk of subsequent major adverse outcomes. Additionally, age at incident stroke, blood pressure, LDL cholesterol level, a diagnosis of hypertension and potency of prescribed statin were identified as key indicators of patients’ phenotypic clusters and associated risk for subsequent clinical outcomes. The studies add to growing and wider evidence to identify those who may most benefit from, and be least likely to be harmed by, preventive treatment. Stratifying patients with stroke early, could lower the burden of subsequent adverse clinical outcomes, improve patients’ long-term outcomes, and reduce the associated economic burden. This should, therefore, be a continuing research and public health priority