Cardiovascular polypharmacy is not associated with unplanned hospitalisation: Evidence from a retrospective cohort study

This is the final version. Available from the publisher via the DOI in this record.Background: Polypharmacy is often considered suggestive of suboptimal prescribing, and is associated with adverse outcomes. It is particularly common in the context of cardiovascular disease, but it is unclear whether prescribing of multiple cardiovascular medicines, which may be entirely appropriate and consistent with clinical guidance, is associated with adverse outcome. The aim of this study was to assess the relationship between number of prescribed cardiovascular medicines and unplanned non-cardiovascular hospital admissions. Methods. A retrospective cohort analysis of 180,815 adult patients was conducted using Scottish primary care data linked to hospital discharge data. Patients were followed up for one year for the outcome of unplanned non-cardiovascular hospital admission. The association between number of prescribed cardiovascular medicines and hospitalisation was modelled using logistic regression, adjusting for key confounding factors including cardiovascular and non-cardiovascular morbidity and non-cardiovascular prescribing. Results: 25.4% patients were prescribed ≥1 cardiovascular medicine, and 5.7% were prescribed ≥5. At least one unplanned non-cardiovascular admission was experienced by 4.2% of patients. Admissions were more common in patients receiving multiple cardiovascular medicines (6.4% of patients prescribed 5 or 6 cardiovascular medicines) compared with those prescribed none (3.5%). However, after adjusting for key confounders, cardiovascular prescribing was associated with fewer non-cardiovascular admissions (OR 0.66 for 5 or 6 vs. no cardiovascular medicines, 95% CI 0.57-0.75). Conclusions: We found no evidence that increasing numbers of cardiovascular medicines were associated with an increased risk of unplanned non-cardiovascular hospitalisation, following adjustment for confounding. Assumptions that polypharmacy is hazardous and represents poor care should be moderated in the context of cardiovascular disease. © 2014 Appleton et al.; licensee BioMed Central Ltd

Adjusted indices of multiple deprivation to enable comparisons within and between constituent countries of the UK including an illustration using mortality rates

This is the final version of the article. Available from BMJ Publishing Group via the DOI in this record.Objectives Social determinants can have a major impact on health and as a consequence substantial inequalities are seen between and within countries. The study of inequalities between countries relies on having accurate and consistent measures of deprivation across the country borders. However, in the UK most socioeconomic deprivation measures are not comparable between countries. We give a method of adjusting the Indices of Multiple Deprivation (IMD) for use across the UK, describe the deprivation of each UK country, and show the problems introduced by naïvely using country-specific deprivation measures in a UK-wide analysis of mortality rates. Setting/participants 42 148 geographic areas covering the population of the UK. Outcome measures Adjusted IMD scores based on the income and employment domains of country-specific IMD scores, adjusting for the contribution of other domains. The mortality rate among people aged under 75 years standardised to the UK age structure was compared between country-specific and UK-adjusted IMD quintiles. Results Of the constituent countries of the UK, Northern Ireland was the most deprived with 37% of the population living in areas in the most deprived fifth of the UK, followed by Wales with 22% of the population living in the most deprived fifth of the UK. England and Scotland had similar levels of deprivation. Deprivation-specific mortality rates were similar in England and Wales. Northern Ireland had lower mortality rates than England for each deprivation group, with similar differences for each group. Scotland had higher mortality rates than England for each deprivation group, with larger differences for more deprived groups. Conclusions Analyses of between-country and within-country inequalities by socioeconomic position should use consistent measures; failing to use consistent measures may give misleading results. The published adjusted IMD scores we describe allow consistent analysis across the UK

Why do patients with multimorbidity in England report worse experiences in primary care? Evidence from the General Practice Patient Survey.

OBJECTIVES: To describe and explain the primary care experiences of people with multiple long-term conditions in England. DESIGN AND METHODS: Using questionnaire data from 906,578 responders to the English 2012 General Practice Patient Survey, we describe the primary care experiences of patients with long-term conditions, including 583,143 patients who reported one or more long-term conditions. We employed mixed effect logistic regressions to analyse data on six items covering three care domains (access, continuity and communication) and a single item on overall primary care experience. We controlled for sociodemographic characteristics, and for general practice using a random effect, and further, controlled for, and explored the importance of, health-related quality of life measured using the EuroQoL (EQ-5D) scale. RESULTS: Most patients with long-term conditions report a positive experience of care at their general practice (after adjusting for sociodemographic characteristics and general practice, range 74.0-93.1% reporting positive experience of care across seven questions) with only modest variation by type of condition. For all three domains of patient experience, an increasing number of comorbid conditions is associated with a reducing percentage of patients reporting a positive experience of care. For example, compared with respondents with no long-term condition, the OR for reporting a positive experience is 0.83 (95% CI 0.80 to 0.87) for respondents with four or more long-term conditions. However, this relationship is no longer observed after adjusting for health-related quality of life (OR (95% CI) single condition=1.23 (1.21 to 1.26); four or more conditions=1.31 (1.25 to 1.37)), with pain making the greatest difference among five quality of life variables included in the analysis. CONCLUSIONS: Patients with multiple long-term conditions more frequently report worse experiences in primary care. However, patient-centred measures of health-related quality of life, especially pain, are more important than the number of conditions in explaining why patients with multiple long-term conditions report worse experiences of care

Development and validation of the Cambridge Multimorbidity Score

BACKGROUND: Health services have failed to respond to the pressures of multimorbidity. Improved measures of multimorbidity are needed for conducting research, planning services and allocating resources. METHODS: We modelled the association between 37 morbidities and 3 key outcomes (primary care consultations, unplanned hospital admission, death) at 1 and 5 years. We extracted development (n = 300 000) and validation (n = 150 000) samples from the UK Clinical Practice Research Datalink. We constructed a general-outcome multimorbidity score by averaging the standardized weights of the separate outcome scores. We compared performance with the Charlson Comorbidity Index. RESULTS: Models that included all 37 conditions were acceptable predictors of general practitioner consultations (C-index 0.732, 95% confidence interval [CI] 0.731-0.734), unplanned hospital admission (C-index 0.742, 95% CI 0.737-0.747) and death at 1 year (C-index 0.912, 95% CI 0.905-0.918). Models reduced to the 20 conditions with the greatest combined prevalence/weight showed similar predictive ability (C-indices 0.727, 95% CI 0.725-0.728; 0.738, 95% CI 0.732-0.743; and 0.910, 95% CI 0.904-0.917, respectively). They also predicted 5-year outcomes similarly for consultations and death (C-indices 0.735, 95% CI 0.734-0.736, and 0.889, 95% CI 0.885-0.892, respectively) but performed less well for admissions (C-index 0.708, 95% CI 0.705-0.712). The performance of the general-outcome score was similar to that of the outcome-specific models. These models performed significantly better than those based on the Charlson Comorbidity Index for consultations (C-index 0.691, 95% CI 0.690-0.693) and admissions (C-index 0.703, 95% CI 0.697-0.709) and similarly for mortality (C-index 0.907, 95% CI 0.900-0.914). INTERPRETATION: The Cambridge Multimorbidity Score is robust and can be either tailored or not tailored to specific health outcomes. It will be valuable to those planning clinical services, policymakers allocating resources and researchers seeking to account for the effect of multimorbidity

ACE inhibitor and angiotensin receptor-II antagonist prescribing and hospital admissions with acute kidney injury: A longitudinal ecological study

This is the final version. Available from the publisher via the DOI in this record.Background: ACE Inhibitors (ACE-I) and Angiotensin-Receptor Antagonists (ARAs) are commonly prescribed but can cause acute kidney injury (AKI) during intercurrent illness. Rates of hospitalization with AKI are increasing. We aimed to determine whether hospital AKI admission rates are associated with increased ACE-I/ARA prescribing. Methods and Findings: English NHS prescribing data for ACE-I/ARA prescriptions were matched at the level of the general practice to numbers of hospital admissions with a primary diagnosis of AKI. Numbers of prescriptions were weighted for the demographic characteristics of general practices by expressing prescribing as rates where the denominator is Age, Sex, and Temporary Resident Originated Prescribing Units (ASTRO-PUs). We performed a mixed-effect Poisson regression to model the number of admissions for AKI occurring in each practice for each of 4 years from 1/4/2007. From 2007/8-2010/11, crude AKI admission rates increased from 0.38 to 0.57 per 1000 patients (51.6% increase), and national annual ACE-I/ARA prescribing rates increased by 0.032 from 0.202 to 0.234 (15.8% increase). There was strong evidence (p<0.001) that increases in practice-level prescribing of ACE-I/ARA over the study period were associated with an increase in AKI admission rates. The increase in prescribing seen in a typical practice corresponded to an increase in admissions of approximately 5.1% (rate ratio = 1.051 for a 0.03 per ASTRO-PU increase in annual prescribing rate, 95%CI 1.047-1.055). Using the regression model we predict that 1,636 (95%CI 1,540-1,780) AKI admissions would have been avoided if prescribing rates were at the 2007/8 level, equivalent to 14.8% of the total increase in AKI admissions. Conclusion: In this ecological analysis, up to 15% of the increase in AKI admissions in England over a 4-year time period is potentially attributable to increased prescribing of ACE-I and ARAs. However, these findings are limited by the lack of patient level data such as indication for prescribing and patient characteristics. © 2013 Tomlinson et al.Cambridge Biomedical Research InstituteBritish Heart Foundatio

The accuracy of diagnostic coding for acute kidney injury in England - A single centre study

This is the final version. Available on open access from BMC via the DOI in this recordBackground: Acute kidney injury (AKI) is an independent risk factor for mortality and is responsible for a significant burden of healthcare expenditure, so accurate measurement of its incidence is important. Administrative coding data has been used for assessing AKI incidence, and shows an increasing proportion of hospital bed days attributable to AKI. However, the accuracy of coding for AKI and changes in coding over time have not been studied in England. Methods. We studied a random sample of admissions from 2005 and 2010 where ICD-10 code N17 (acute renal failure) was recorded in the administrative coding data at one acute NHS Foundation Trust in England. Using the medical notes and computerised records we examined the demographic and clinical details of these admissions. Results: Against a 6.3% (95% CI 4.8-7.9%) increase in all non-elective admissions, we found a 64% increase in acute renal failure admissions (95% CI 41%-92%, p<0.001) in 2010 compared to 2005. Median age was 78 years (IQR 72-87), 11-25% had a relevant pre-admission co-morbidity and 64% (55-73%) were taking drugs known to be associated with AKI. Over both years, 95% (91-99%) of cases examined met the Kidney Disease: Improving Global Outcomes criteria for AKI. Conclusions: Patients with hospital admissions where AKI has been coded are elderly with multiple co-morbidities. Our results demonstrate a high positive predictive value of coding data for a clinical diagnosis of AKI, with no suggestion of marked changes in coding of AKI between 2005 and 2010. © 2013 Tomlinson et al; licensee BioMed Central Ltd.Cambridge Biomedical Research InstituteBritish Heart Foundatio

Aspirin reduces cardiovascular events in patients with pneumonia: a prior event rate ratio analysis in a large primary care database

This is the author accepted manuscript. The final version is available from the European Respiratory Society via the DOI in this recordData sharing and dissemination: Unfortunately, CPRD does not allow direct data-sharing due to patient confidentiality issues. The lead author would welcome informal and formal contact if required. It is not feasible to disseminate results back to individual patients within the CPRD.BACKGROUND: Ischaemic stroke and myocardial infarction (MI) are common after pneumonia and are associated with long-term mortality. Aspirin may attenuate this risk and should be explored as a therapeutic option. METHODS: We extracted all patients with pneumonia, aged over 50, from the Clinical Practice Research Datalink (CPRD), a large UK primary care database, from inception until January 2019. We then performed a prior event rate ratio analysis (PERR) with propensity score matching, an approach that allows for control of measured and unmeasured confounding, with aspirin usage as the exposure, and ischaemic events as the outcome. The primary outcome was the combined outcome of ischaemic stroke and myocardial infarction. Secondary outcomes were ischaemic stroke and myocardial infarction individually. Relevant confounders were included in the analysis (smoking, comorbidities, age, gender). FINDINGS: 48 743 patients were eligible for matching. 8099 of these were aspirin users who were matched to 8099 non-users. Aspirin users had a reduced risk of the primary outcome (adjusted hazard ratio, HR 0.64; 95% confidence interval 0.52-0.79) in the PERR analysis. For both secondary outcomes, aspirin use was also associated with a reduced risk HR 0.46 (0.30-0.72) and HR 0.70 (0.55-0.91) for myocardial infarction and stroke respectively). INTERPRETATION: This study provides supporting evidence that aspirin use is associated with reduced ischaemic events after pneumonia in a primary care setting. This drug may have a future clinical role in preventing this important complication.National Institute for Health Research (NIHR

Association of comorbidity and health service usage among patients with dementia in the UK: a population-based study

$\textbf{BACKGROUND}$: The majority of people with dementia have other long-term diseases, the presence of which may affect the progression and management of dementia. This study aimed to identify subgroups with higher healthcare needs, by analysing how primary care consultations, number of prescriptions and hospital admissions by people with dementia varies with having additional long-term diseases (comorbidity). $\textbf{METHODS}$: A retrospective cohort study based on health data from the Clinical Practice Research Datalink (CPRD) was conducted. Incident cases of dementia diagnosed in the year starting 1/3/2008 were selected and followed for up to 5 years. The number of comorbidities was obtained from a set of 34 chronic health conditions. Service usage (primary care consultations, hospitalisations and prescriptions) and time-to-death were determined during follow-up. Multilevel negative binomial regression and Cox regression, adjusted for age and gender, were used to model differences in service usage and death between differing numbers of comorbidities. $\textbf{RESULTS}$: Data from 4999 people (14 866 person-years of follow-up) were analysed. Overall, 91.7% of people had 1 or more additional comorbidities. Compared with those with 2 or 3 comorbidities, people with ≥6 comorbidities had higher rates of primary care consultations (rate ratio (RR) 1.31, 95% CI 1.25 to 1.36), prescriptions (RR 1.68, 95% CI 1.57 to 1.81), and hospitalisation (RR 1.62, 95% CI 1.44 to 1.83), and higher risk of death (HR 1.56, 95% CI 1.37 to 1.78). $\textbf{DISCUSSION}$: In the UK, people with dementia with higher numbers of comorbidities die earlier and have considerably higher health service usage in terms of primary care consultations, hospital admissions and prescribing. This study provides strong evidence that comorbidity is a key factor that should be considered when allocating resources and planning care for people with dementia

An assessment of pulse transit time for detecting heavy blood loss during surgical operation

Copyright @ Wang et al.; Licensee Bentham Open. This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.The main contribution of this paper is the use of non-invasive measurements such as electrocardiogram (ECG) and photoplethysmographic (PPG) pulse oximetry waveforms to develop a new physiological signal analysis technique for detecting blood loss during surgical operation. Urological surgery cases were considered as the control group due to its generality, and cardiac surgery as experimental group since it involves blood loss and water supply. Results show that the control group has the tendency of a reduction of the pulse transient time (PTT), and this indicates an increment in the blood flow velocity changes from slow to fast. While for the experimental group, the PTT indicates high values during blood loss, and low values during water supply. Statistical analysis shows considerable differences (i.e., P <0.05) between both groups leading to the conclusion that PTT could be a good indicator for monitoring patients' blood loss during a surgical operation.The National Science Council (NSC) of Taiwan and the Centre for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan

PGRMC1: a new biomarker for the estrogen receptor in breast cancer

Estrogen receptor (ER) status is a critical biomarker in breast cancer, in large part because the ER is the target of tamoxifen and similar drugs. In the previous issue of Breast Cancer Research, Neubauer and colleagues used a proteomic approach to identify proteins that are differentially regulated by ER in breast tumors. The authors showed that ER-negative tumors have elevated levels of PGRMC1 (progesterone receptor membrane component-1), a hormone receptor component and binding partner for P450 proteins. In contrast, PGRMC1 was phosphorylated in ER-positive tumors. The staining patterns of ER and PGRMC1 were mutually exclusive in breast tumor sections, and PGRMC1 staining was sharply increased in hypoxic areas of the tumor. The results suggest that PGRMC1 is a candidate biomarker for ER status and hypoxia in breast cancer