BackgroundSystolic inter-arm difference in blood pressure (IAD) and cognitive decline are both associated with cardiovascular disease; therefore, it was hypothesised that IAD may be predictive of cognitive decline.AimTo examine associations of IAD with cognitive decline in a community population.Design and settingA prospective study of older Italian adults enrolled in the InCHIANTI study.MethodUnivariable and multivariable associations of IAD were explored with declines in mini mental state examination (MMSE) scores, Trail Making Test A and B scores, and a composite outcome representing substantial decline in any of these scores. Backward stepwise regression was used to adjust observed associations of IAD with cognitive decline.ResultsThe rate of decline for MMSE scores in 1133 participants was greater with IAD ≥5 mmHg or ≥10 mmHg. On univariable analyses continuous IAD was associated with the composite outcome (odds ratio [OR] 1.16 per 5 mmHg of IAD, 95% confidence interval [CI] = 1.02 to 1.31). Substantial decline in MMSE score was seen with IAD ≥5 mmHg (OR 1.41, 95% CI = 1.03 to 1.93), and in the composite outcome with IAD ≥5 mmHg (OR 1.44, 95% CI = 1.10 to 1.89) or ≥10 mmHg (OR 1.39, 95% CI = 1.03 to 1.88). After multivariable adjustment, an IAD ≥ 5 mmHg remained associated with reductions in the composite outcome, reflecting declining cognitive performance (OR 1.46, 95% CI = 1.05 to 2.03).ConclusionAn IAD ≥5 mmHg is associated with cognitive decline in a representative older population. Given that systolic inter-arm differences in blood pressure are easily measured, confirmation of these findings could inform individualised treatment for the prevention of cognitive decline and dementia.

ObjectivesFalls are a common problem in older people. Postural hypotension contributes to falls but is often asymptomatic. In the absence of symptoms, postural hypotension is only infrequently checked for in clinical practice. We undertook this study to derive, validate and explore the prospective associations of a prediction tool to identify people likely to have unrecognised postural hypotension.Design and settingCross-sectional and prospective multivariable cohort analysis.Participants1317 participants of the Invecchiare in Chianti study, a population-based cohort representative of the older Italian population.Primary outcome measuresPredictive value of score to suggest presence of postural hypotension.MethodsSubjects were randomised 1:1 to derivation or validation cohorts. Within the derivation cohort, univariable associations for candidate predictors of postural hypotension were tested. Variables with p<0.1 entered multivariable linear regression models. Factors retaining multivariable significance were incorporated into unweighted and weighted Detecting Risk Of Postural hypotension (DROP) scores. These scores were tested in the validation cohort against prediction of postural hypotension, cognitive decline and mortality over 9 years of follow-up.ResultsPostural hypotension was present in 203 (15.4%) of participants. Factors predicting postural hypotension were: digoxin use, Parkinson’s disease, hypertension, stroke or cardiovascular disease and an interarm systolic blood pressure difference. Area under the curve was consistent at 0.65 for all models, with significant ORs of 1.8 to 2.4 per unit increase in score for predicting postural hypotension. For a DROP score ≥1, five cases need to be tested to identify one with postural hypotension.Increasing DROP scores predicted mortality (OR 1.8 to 2.8 per unit rise) and increasing rates of decline of Mini Mental State Examination score (analysis of variance p<0.001) over 9 years of follow-up.ConclusionsThe DROP score provides a simple method to identify people likely to have postural hypotension and increased risks to health who require further evaluation.

Background: Increasing pressure in the United Kingdom (UK) urgent care system has led to Emergency Departments (EDs) failing to meet the national requirement that 95% of patients are admitted, discharged or transferred within 4-h of arrival. Despite the target being the same for all acute hospitals, individual Trusts organise their services in different ways. The impact of this variation on patient journey time and waiting is unknown. Our study aimed to apply the Lean technique of Value Stream Mapping (VSM) to investigate care processes and delays in patient journeys at four contrasting hospitals.Methods: VSM timing data were collected for patients accessing acute care at four hospitals in South West England. Data were categorised according to waits and activities, which were compared across sites to identify variations in practice from the patient viewpoint. We included Public and Patient Involvement (PPI) to fully interpret our findings; observations and initial findings were considered in a PPI workshop.Results: One hundred eight patients were recruited, comprising 25,432 min of patient time containing 4098 episodes of care or waiting. The median patient journey was 223 min (3 h, 43 min); just within the 4-h target. Although total patient journey times were similar between sites, the stage where the greatest proportion of waiting occurred varied. Reasons for waiting were dominated by waits for beds, investigations or results to be available. From our sample we observed that EDs without a discharge/clinical decision area exhibited a greater proportion of waiting time following an admission or discharge decision. PPI interpretation indicated that patients who experience waits at the beginning of their journey feel more anxious because they are 'not in the system yet'.Conclusions: The novel application of VSM analysis across different hospitals, coupled with PPI interpretation, provides important insight into the impact of care provision on patient experience. Measures that could reduce patient waiting include automatic notification of test results, and the option of discharge/clinical decision areas for patients awaiting results or departure. To enhance patient experience, good communication with patients and relatives about reasons for waits is essential.

Objective: Over three million people aged over 65 fall each year in the UK. Postural hypotension (PH) is a risk factor for falls. It is associated with excess mortality, and may affect cognition. PH is not routinely checked for in UK clinical practice. We studied the InCHIANTI dataset to derive and validate a simple prediction tool designed to facilitate identification of subjects to be checked for PH. Design and method: InCHIANTI is a population-based study of ageing. It recruited subjects from population registries in Chianti, Italy in 1998 and they were followed up triennially. Blood pressure (BP) at recruitment was measured after resting supine, and one and three minutes after standing, using a mercury sphygmomanometer. Systolic PH was defined as a > = 20 mmHg fall in supine BP on standing. Subjects were randomised to derivation or validation cohorts; allocation was undertaken blinded to PH status and medical history. Candidate predictor variables identified from literature searches were tested for univariable cross sectional associations with PH using χ2 tests. Those with significant associations were entered into multivariable linear regression models, and used to derive simple and weighted prediction scores (DROP scores). DROP scores were tested in the validation cohort for prediction of PH, future falls, cognitive decline and mortality rates. Results: PH was present in 56/726 (7.7%) of the derivation cohort and 45/727 (6.2%) of the validation cohort (p = 0.25). PH was associated with age > = 65, falls in the preceding year, diabetes, previous stroke, hypertension and Parkinson's disease. A simple score summing numbers of these variables performed equally well as weighted scores (AUROC 0.67 (0.59 to 0.74); p < 0.001). Rising DROP scores were incrementally predictive of future falls (χ2 for trend p < 0.01), increasing rates of decline in mini mental state examination (ANOVA p < 0.001) and mortality (HR 1.8 (1.6 to 2.0) per unit increment in DROP score; p < 0.001; figure).Conclusions: The DROP score can predict presence of PH, future falls, and increased rates of mortality and cognitive decline. Application of the score could facilitate detection and management of PH. External validation of the DROP score is underway.

Background: Hospital emergency admissions have risen annually, exacerbating pressures on emergency departments (EDs) and acute medical units. These pressures have an adverse impact on patient experience and potentially lead to suboptimal clinical decision-making. In response, a variety of innovations have been developed, but whether or not these reduce inappropriate admissions or improve patient and clinician experience is largely unknown. Aims: To investigate the interplay of service factors influencing decision-making about emergency admissions, and to understand how the medical assessment process is experienced by patients, carers and practitioners. Methods: The project used a multiple case study design for a mixed-methods analysis of decision-making about admissions in four acute hospitals. The primary research comprised two parts: value stream mapping to measure time spent by practitioners on key activities in 108 patient pathways, including an embedded study of cost; and an ethnographic study incorporating data from 65 patients, 30 carers and 282 practitioners of different specialties and levels. Additional data were collected through a clinical panel, learning sets, stakeholder workshops, reading groups and review of site data and documentation. We used a realist synthesis approach to integrate findings from all sources. Findings: Patients’ experiences of emergency care were positive and they often did not raise concerns, whereas carers were more vocal. Staff’s focus on patient flow sometimes limited time for basic care, optimal communication and shared decision-making. Practitioners admitted or discharged few patients during the first hour, but decision-making increased rapidly towards the 4-hour target. Overall, patients’ journey times were similar, although waiting before being seen, for tests or after admission decisions, varied considerably. The meaning of what constituted an ‘admission’ varied across sites and sometimes within a site. Medical and social complexity, targets and ‘bed pressure’, patient safety and risk, each influenced admission/discharge decision-making. Each site responded to these pressures with different initiatives designed to expedite appropriate decision-making. New ways of using hospital ‘space’ were identified. Clinical decision units and observation wards allow potentially dischargeable patients with medical and/or social complexity to be ‘off the clock’, allowing time for tests, observation or safe discharge. New teams supported admission avoidance: an acute general practitioner service filtered patients prior to arrival; discharge teams linked with community services; specialist teams for the elderly facilitated outpatient treatment. Senior doctors had a range of roles: evaluating complex patients, advising and training juniors, and overseeing ED activity. Conclusions: This research shows how hospitals under pressure manage complexity, safety and risk in emergency care by developing ‘ground-up’ initiatives that facilitate timely, appropriate and safe decision-making, and alternative care pathways for lower-risk, ambulatory patients. New teams and ‘off the clock’ spaces contribute to safely reducing avoidable admissions; frontline expertise brings value not only by placing senior experienced practitioners at the front door of EDs, but also by using seniors in advisory roles. Although the principal limitation of this research is its observational design, so that causation cannot be inferred, its strength is hypothesis generation. Further research should test whether or not the service and care innovations identified here can improve patient experience of acute care and safely reduce avoidable admissions. Funding: The National Institute for Health Research (NIHR) Health Services and Delivery Research programme (project number 10/1010/06). This research was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care South West Peninsula.

Objective: In the UK 7% of those aged over 65 have dementia. Current interventions to treat dementia are of limited efficacy therefore prevention and pre-symptomatic detection are important. Systolic inter-arm differences (IAD) in blood pressure (BP) >/=10 mmHg are associated with increased cardiovascular mortality. Both Alzheimer's disease and vascular dementia include vascular disease in their aetiology. We hypothesised that IAD may also be prospectively associated with increased risks of cognitive decline. Design and method: InCHIANTI is a prospective study of ageing in older Italian adults. Participants undergo a detailed medical history and examination at recruitment and at 3 yearly follow up intervals. Assessments include sequential bilateral BP readings and cognitive assessments including Mini Mental State Examinations (MMSE). Those exhibiting a decline in MMSE >/=5 points over follow up were considered to exhibit substantial cognitive decline. We used univariable cross-sectional and regression analyses to explore associations between IAD, mortality, cognitive decline, and rate of change in MMSE over time. Significant univariable associations, and known cardiovascular or dementia epidemiological risk factors, were combined in a multivariable model. Results: There were 1,142 participants without dementia at baseline. On univariable analysis risks of substantial cognitive decline were non-significantly higher with an IAD >/=10 mmHg at each of the follow-up assessments (RR 1.6 (95% CI 1.0 to 2.5) at 3 years, 1.2 (0.8 to 1.9) at 6 years and 1.3 (0.9 to 1.8) at 9 years). Mean rate of decline in MMSE scores was higher at 0.5 points per year with an IAD >/=10 mmHg compared to 0.3 per year for IAD <10 mmHg (p = 0.02). On multivariable modelling no significant associations of cognitive decline with IAD were observed. Conclusions: To our knowledge this is the first report examining the association of IAD with cognitive decline. Our findings suggest a potential association of IAD with higher rates of cognitive decline. IAD in this study was measured by a sequential method, which we have found to underestimate survival associations compared to simultaneous measurement techniques. Therefore further studies using robust methods of measurement are indicated to clarify whether detection of an IAD can predict future substantial cognitive decline.