Age, sex, and socioeconomic differences in multimorbidity measured in four ways:UK primary care cross-sectional analysis

Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised. Aim: To examine variation in prevalence using different definitions of multimorbidity. Design and setting: Cross-sectional study of 1 168 620 people in England. Method: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental–physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions. Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental–physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental–physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental–physical MM at 40–45 years younger, followed by MM2+ at 15–20 years younger, and MM3+ and MM3+ from 3+ at 10–15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental–physical MM. Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies

The impact of varying the number and selection of conditions on estimated multimorbidity prevalence::a cross-sectional study using a large, primary care population dataset

Background: Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. Methods and findings: We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as ≥2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in ≥1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p < 0.001) when considering all 80 conditions. The threshold number of conditions at which multimorbidity prevalence was >99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of “comorbidity.” Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. Conclusions: In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence

Heat shock proteins expressed in the marsupial Tasmanian devil are potential antigenic candidates in a vaccine against devil facial tumour disease

The Tasmanian devil (Sarcophilus harrisii), the largest extant carnivorous marsupial and endemic to Tasmania, is at the verge of extinction due to the emergence of a transmissible cancer known as devil facial tumour disease (DFTD). DFTD has spread over the distribution range of the species and has been responsible for a severe decline in the global devil population. To protect the Tasmanian devil from extinction in the wild, our group has focused on the development of a prophylactic vaccine. Although this work has shown that vaccine preparations using whole DFTD tumour cells supplemented with adjuvants can induce anti-DFTD immune responses, alternative strategies that induce stronger and more specific immune responses are required. In humans, heat shock proteins (HSPs) derived from tumour cells have been used instead of whole-tumour cell preparations as a source of antigens for cancer immunotherapy. As HSPs have not been studied in the Tasmanian devil, this study presents the first characterisation of HSPs in this marsupial and evaluates the suitability of these proteins as antigenic components for the enhancement of a DFTD vaccine. We show that tissues and cancer cells from the Tasmanian devil express constitutive and inducible HSP. Additionally, this study suggests that HSP derived from DFTD cancer cells are immunogenic supporting the future development of a HSP-based vaccine against DFTD.Cesar Tovar, Amanda L. Patchett, Vitna Kim, Richard Wilson, Jocelyn Darby, A. Bruce Lyons, Gregory M. Wood

Effect on life expectancy of temporal sequence in a multimorbidity cluster of psychosis, diabetes, and congestive heart failure among 1·7 million individuals in Wales with 20-year follow-up : a retrospective cohort study using linked data

Funding: This work was supported by Health Data Research UK (HDRUK) Measuring and Understanding Multimorbidity using Routine Data in the UK (MUrMuRUK; award numbers HDR-9006 and CFC0110). HDRUK is funded by the UK Medical Research Council (MRC), Engineering and Physical Sciences Research Council, Economic and Social Research Council, NIHR (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, and Wellcome Trust. This work also was co-funded by the MRC and NIHR (grant number MR/S027750/1). The work was supported by the Administrative Data Research (ADR) Wales programme of work, part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). RKO is supported by a Springboard award (SBF006\1122) funded by the Academy of Medical Sciences, Wellcome Trust, Government Department of Business, Energy and Industrial Strategy, British Heart Foundation, and Diabetes UK. SS is part funded by the NIHR Applied Research Collaboration West Midlands, the NIHR Health Protection Research Unit (HPRU) in Gastrointestinal Infections, and the NIHR HPRU in Genomics and Enabling Data.Background To inform targeted public health strategies, it is crucial to understand how coexisting diseases develop over time and their associated impacts on patient outcomes and health-care resources. This study aimed to examine how psychosis, diabetes, and congestive heart failure, in a cluster of physical–mental health multimorbidity, develop and coexist over time, and to assess the associated effects of different temporal sequences of these diseases on life expectancy in Wales. Methods In this retrospective cohort study, we used population-scale, individual-level, anonymised, linked, demographic, administrative, and electronic health record data from the Wales Multimorbidity e-Cohort. We included data on all individuals aged 25 years and older who were living in Wales on Jan 1, 2000 (the start of follow-up), with follow-up continuing until Dec 31, 2019, first break in Welsh residency, or death. Multistate models were applied to these data to model trajectories of disease in multimorbidity and their associated effect on all-cause mortality, accounting for competing risks. Life expectancy was calculated as the restricted mean survival time (bound by the maximum follow-up of 20 years) for each of the transitions from the health states to death. Cox regression models were used to estimate baseline hazards for transitions between health states, adjusted for sex, age, and area-level deprivation (Welsh Index of Multiple Deprivation [WIMD] quintile). Findings Our analyses included data for 1 675 585 individuals (811 393 [48·4%] men and 864 192 [51·6%] women) with a median age of 51·0 years (IQR 37·0–65·0) at cohort entry. The order of disease acquisition in cases of multimorbidity had an important and complex association with patient life expectancy. Individuals who developed diabetes, psychosis, and congestive heart failure, in that order (DPC), had reduced life expectancy compared with people who developed the same three conditions in a different order: for a 50-year-old man in the third quintile of the WIMD (on which we based our main analyses to allow comparability), DPC was associated with a loss in life expectancy of 13·23 years (SD 0·80) compared with the general otherwise healthy or otherwise diseased population. Congestive heart failure as a single condition was associated with mean a loss in life expectancy of 12·38 years (0·00), and with a loss of 12·95 years (0·06) when preceded by psychosis and 13·45 years (0·13) when followed by psychosis. Findings were robust in people of older ages, more deprived populations, and women, except that the trajectory of psychosis, congestive heart failure, and diabetes was associated with higher mortality in women than men. Within 5 years of an initial diagnosis of diabetes, the risk of developing psychosis or congestive heart failure, or both, was increased. Interpretation The order in which individuals develop psychosis, diabetes, and congestive heart failure as combinations of conditions can substantially affect life expectancy. Multistate models offer a flexible framework to assess temporal sequences of diseases and allow identification of periods of increased risk of developing subsequent conditions and death.Publisher PDFPeer reviewe

Trajectories in chronic disease accrual and mortality across the lifespan in Wales, UK (2005-2019), by area deprivation profile : linked electronic health records cohort study on 965,905 individuals

Funding: This work was supported by Health Data Research UK (HDRUK) Measuring and Understanding Multimorbidity using Routine Data in the UK (MUrMuRUK, HDR-9006; CFC0110). Health Data Research UK (HDR-9006) is funded by: UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, the National Institute for Health Research (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, and Wellcome Trust. This work also was co-funded by the Medical Research Council (MRC) and the National Institute for Health Research (NIHR) through grant number MR/S027750/1. The work was supported by the ADR Wales programme of work, part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1).Background  Understanding and quantifying the differences in disease development in different socioeconomic groups of people across the lifespan is important for planning healthcare and preventive services. The study aimed to measure chronic disease accrual, and examine the differences in time to individual morbidities, multimorbidity, and mortality between socioeconomic groups in Wales, UK. Methods  Population-wide electronic linked cohort study, following Welsh residents for up to 20 years (2000-2019). Chronic disease diagnoses were obtained from general practice and hospitalisation records using the CALIBER disease phenotype register. Multi-state models were used to examine trajectories of accrual of 132 diseases and mortality, adjusted for sex, age and area-level deprivation. Restricted mean survival time was calculated to measure time spent free of chronic disease(s) or mortality between socioeconomic groups. Findings  In total, 965,905 individuals aged 5-104 were included, from a possible 2·9m individuals following a 5-year clearance period, with an average follow-up of 13·2 years (12·7 million person-years). Some 673,189 (69·7 %) individuals developed at least one chronic disease or died within the study period. From ages 10 years upwards, the individuals living in the most deprived areas consistently experienced reduced time between health states, demonstrating accelerated transitions to first and subsequent morbidities and death compared to their demographic equivalent living in the least deprived areas. The largest difference were observed in 10 and 20 year old males developing multimorbidity (-0·45 years (99%CI:-0·45,-0·44)) and in 70 year old males dying after developing multimorbidity (-1·98 years (99%CI:-2·01,-1·95)). Interpretation  This study adds to the existing literature on health inequalities by demonstrating that individuals living in more deprived areas consistently experience accelerated time to diagnosis of chronic disease and death across all ages, accounting for competing risks.Publisher PDFPeer reviewe

Long-term follow-up of breast cancer survivors with post-mastectomy pain syndrome

Post-mastectomy pain syndrome (PMPS) is a recognised complication of breast surgery although little is known about the long-term outcome of this chronic pain condition. In 1996, Smith et al identified a prevalence rate of PMPS of 43% among 408 women in the Grampian Region, Northeast Scotland. The aim of this study was to assess long-term outcome at 7–12 years postoperatively in this cohort of women, to describe the natural history of PMPS and impact of pain upon quality of life. Chronic pain and quality of life were assessed using the McGill Pain Questionnaire (MPQ) and Short Form-36 (SF-36). Of 175 women reporting PMPS in 1996, 138 were eligible for questionnaire follow-up in 2002. Mean time since surgery was 9 years (s.d. 1.8 years). A response rate of 82% (113 out of 138) was achieved; 59 out of 113 (52%) women reported continued PMPS and 54 out of 113 (48%) women reported their PMPS had resolved since the previous survey in 1996. Quality of life scores were significantly lower in women with persistent PMPS compared to those women whose pain had resolved. However, for women with persistent PMPS, SF-36 scores had improved over time. Risk factors for persistent PMPS included younger age and heavier weight. This study found that, of women reporting PMPS in 1996, half of those surveyed in 2002 continued to experience PMPS at a mean of 9 years after surgery

Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland

Funding: CMC: This work was supported by Health Data Research UK (HDR UK) Measuring and Understanding Multimorbidity using Routine Data in the UK (HDR-9006; CFC0110). Health Data Research UK (HDR-9006) is funded by: UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, the National Institute for Health Research (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, and Wellcome Trust.There is still limited understanding of how chronic conditions co-occur in patients with multimorbidity and what are the consequences for patients and the health care system. Most reported clusters of conditions have not considered the demographic characteristics of these patients during the clustering process. The study used data for all registered patients that were resident in Fife or Tayside, Scotland and aged 25 years or more on 1st January 2000 and who were followed up until 31st December 2018. We used linked demographic information, and secondary care electronic health records from 1st January 2000. Individuals with at least two of the 31 Elixhauser Comorbidity Index conditions were identified as having multimorbidity. Market basket analysis was used to cluster the conditions for the whole population and then repeatedly stratified by age, sex and deprivation. 318,235 individuals were included in the analysis, with 67,728 (21·3%) having multimorbidity. We identified five distinct clusters of conditions in the population with multimorbidity: alcohol misuse, cancer, obesity, renal failure, and heart failure. Clusters of long-term conditions differed by age, sex and socioeconomic deprivation, with some clusters not present for specific strata and others including additional conditions. These findings highlight the importance of considering demographic factors during both clustering analysis and intervention planning for individuals with multiple long-term conditions. By taking these factors into account, the healthcare system may be better equipped to develop tailored interventions that address the needs of complex patients.Publisher PDFPeer reviewe

Upper limits on the strength of periodic gravitational waves from PSR J1939+2134

The first science run of the LIGO and GEO gravitational wave detectors presented the opportunity to test methods of searching for gravitational waves from known pulsars. Here we present new direct upper limits on the strength of waves from the pulsar PSR J1939+2134 using two independent analysis methods, one in the frequency domain using frequentist statistics and one in the time domain using Bayesian inference. Both methods show that the strain amplitude at Earth from this pulsar is less than a few times $10^{-22}$.Comment: 7 pages, 1 figure, to appear in the Proceedings of the 5th Edoardo Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July 200