Multimorbidity Score Research Articles

Future patterns of health inequalities in the population of England to 2040: a microsimulation study

Abstract Introduction The existence of wide inequalities in health across England is well-documented. Our research adds to this evidence on inequalities in self-reported health by describing current patterns and projecting future patterns of inequality in diagnosed illness across multiple conditions by deprivation. Methods We used the IMPACTNCD microsimulation model that simulates a close-to-reality synthetic population of adults in England from 2019 to 2040. This model combines individual-level data on demographics, health and mortality from linked administrative data for primary and secondary care with survey responses on individual-level risk factors and epidemiological evidence on the associations between risk factors and chronic illness. This model can be adapted for other countries based on data availability. We used the Cambridge Multimorbidity Score (CMS) as our multimorbidity measure. This assigns a weight to 20 common long-term conditions based on individuals’ healthcare use and their likelihood of death. We further focus on “major illness” which corresponds to a CMS greater than 1.5. Results In preliminary results, we project that health inequalities are not projected to improve between 2019 and 2040. In 2019, the difference in the average time spent without major illness between the most and least deprived 10% of areas in England was 10.4 years. This is projected to remain largely unchanged at 10.7 years (8.8, 11.7). We also find that in 2019, the share of working age people living with major illness in the most deprived 10% of areas in England (14.6%) was more than double the rate seen in the least deprived 10% of areas (6.3%). In 2040, we project these rates to remain largely unchanged at 15.2% (13.0%, 17.6%) and 6.8% (5.4%, 9.1%) respectively. Discussion On current trends, health inequalities are projected to persist into the future. This has significant implications not just for population health but for labour supply and wider economic growth. Key messages • If current trends in risk factors continue into the future, existing wide inequalities in diagnosed illness in England are projected to persist onto 2040. • With significant disparities in major illness among the working-age population, this has implications not just for population health but for labour supply and wider economic growth.

Projecting patterns of health inequalities in England up to 2040 using linked health data

ObjectiveThe existence of wide inequalities in self-reported health across England is well-documented. Our research adds to this evidence by describing current patterns and projecting future patterns of inequality in diagnosed illness by deprivation. ApproachWe used a microsimulation model which combines individual-level data on demographics, health and mortality from linked data for primary and secondary care with survey responses on leading modifiable risk factors and epidemiological evidence on the associations between risk factors and chronic illness. We used the Cambridge Multimorbidity Score to measure multimorbidity. This assigns a weight to 20 common long-term conditions based on individuals’ healthcare use and their likelihood of death. We further focus on “major illness” which corresponds to a score greater than 1.5. ResultsWe project that health inequalities are not projected to improve between 2019 and 2040. In 2040, we project the difference in the average time spent without major illness between the most and least deprived 10% of areas in England to be 10.7 years. This is largely unchanged from 10.4 years in 2019. In 2040, we project there will be more working age adults living with major illness in the most deprived areas, more than double the rate in the least deprived areas (15.2% versus 6.8%). These rates remain largely unchanged from 2019 at 14.6% and 6.3% respectively. Conclusion and ImplicationsOn current trends, health inequalities are projected to persist into the future. This has significant implications not just for population health but for labour supply and wider economic growth.

Impact of co-resident health and living alone on risk of hospital admission for people with Parkinson’s disease

BackgroundPeople with Parkinson's Disease (PwP) have a higher rate of hospitalisation compared to the general population. Little is known about the impact of having a co-resident and their health on hospitalisation rates of PwP. MethodsWe utilised Clinical Practice Research Datalink (CPRD) GOLD data (2010–2015) to identify PwP and co-residents. We classed either the fittest or youngest adult as the primary caregiver in each household. Caregiver health was classified by the Cambridge Multimorbidity Score (CMS), primary care utilisation and prescriptions. We calculated the hospitalisation (elective, emergency) incidence rate ratios (IRRs) for PwP who lived alone compared to those with a caregiver using negative binomial regression, and whether worse caregiver health predicted higher risk of admissions. ResultsWe identified 3254 PwP and 4007 family members. PwP who lived alone were less likely to have an elective admission (0.79; 95 % CI 0.69–0.91) and more likely to have an emergency admission (1.40; 95 % CI 1.70-1.54). Worse caregiver health, as measured by the CMS, was associated with an increased risk of emergency admission (IRR 1.35; 95 % CI 1.17–1.57), but this attenuated and was consistent with chance in the fully adjusted model (1.04; 95 % CI 0.95–1.13). No strong associations were seen between caregiver health and elective admissions. ConclusionPwP who live alone are at increased risk of emergency and less likely to have elective hospital admissions. It is important that health care providers support such people and ensure they receive equitable access to the potential benefits of elective procedures.

#1848 Body composition and multimorbidity in patients with chronic kidney disease

Abstract Background and Aims Frailty and multimorbidity are increasingly prevalent, particularly in the chronic kidney disease (CKD) population, and they seem to be more pronounced and accelerated in people receiving haemodialysis. We aimed to study the relationship between body composition, frailty and multimorbidity in people with CKD and end stage renal disease (ESRD) on haemodialysis (HD). Method This was a single centre study, involving 42 patients with CKD stage 3 to 5 (pre-dialysis) and 29 patients receiving in-centre haemodialysis. InBody 770 was used to measure body composition using bioelectrical impedance analysis. Multimorbidity of participants were assessed using the simplified Cambridge multimorbidity score. Frailty assessment was performed using the Clinical Frailty Scale. Results Phase angle was lower in later stages of CKD—mean phase angle in CKD stage 3 was 5.28°, stage 4 was 4.44 and stage 5 was 4.13 (p = 0.008). Visceral adiposity correlated with multimorbidity scores but in a multivariate regression analysis (including albumin and visceral fat area) only whole body phase angle independently predicted multimorbidity in CKD stage 4-5 (adjusted R2 for the whole model = 0.47, p = 0.007). In haemodialysis patients, there was no correlation between multimorbidity and phase angle (r = −0.149, p = 0.441). However, there was a significant correlation between frailty score and whole body phase angle in this group (r = −0.559, p = 0.002). In a univariate analysis, age (R2 = 0.2, Beta = 0.045, p = 0.015), albumin (R2 = 0.217, Beta = −0.214, p = 0.009) and skeletal muscle mass (R2 = 0.282, Beta = −0.101, p = 0.003) predicted frailty score in haemodialysis patients. In multivariate regression analysis age, albumin level and skeletal muscle mass continued to independently predict frailty scores in HD patients (adjusted R2 for the whole model = 0.503). Conclusion Phase angle measurement refers to cell membrane integrity and fat-free mass, with higher values suggesting improved cell health. Using body composition measures, in particular phase angle, is a useful measure to predict multimorbidity and frailty in CKD patients. They are quick, accessible and easy to use tools that can be incorporated in clinical practice routinely. The relationship between visceral adiposity and multimorbidity merits further investigation. Preservation of skeletal muscle mass through nutritional and exercise interventions could be a clinical target to reduce frailty in this population.

Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study

BackgroundLittle is known regarding the leading risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health.MethodsOur analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40–73 years at baseline (between 2006–2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors.ResultsDuring a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55–2.85) and 3.72(3.40–4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother’s history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers.ConclusionsOur findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother’s history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

Creating a Modified Version of the Cambridge Multimorbidity Score to Predict Mortality in People Older Than 16 Years: Model Development and Validation.

No single multimorbidity measure is validated for use in NHS (National Health Service) England's General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR), the nationwide primary care data set created for COVID-19 pandemic research. The Cambridge Multimorbidity Score (CMMS) is a validated tool for predicting mortality risk, with 37 conditions defined by Read Codes. The GDPPR uses the more internationally used Systematized Nomenclature of Medicine clinical terms (SNOMED CT). We previously developed a modified version of the CMMS using SNOMED CT, but the number of terms for the GDPPR data set is limited making it impossible to use this version. We aimed to develop and validate a modified version of CMMS using the clinical terms available for the GDPPR. We used pseudonymized data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC), which has an extensive SNOMED CT list. From the 37 conditions in the original CMMS model, we selected conditions either with (1) high prevalence ratio (≥85%), calculated as the prevalence in the RSC data set but using the GDPPR set of SNOMED CT codes, divided by the prevalence included in the RSC SNOMED CT codes or (2) conditions with lower prevalence ratios but with high predictive value. The resulting set of conditions was included in Cox proportional hazard models to determine the 1-year mortality risk in a development data set (n=500,000) and construct a new CMMS model, following the methods for the original CMMS study, with variable reduction and parsimony, achieved by backward elimination and the Akaike information stopping criterion. Model validation involved obtaining 1-year mortality estimates for a synchronous data set (n=250,000) and 1-year and 5-year mortality estimates for an asynchronous data set (n=250,000). We compared the performance with that of the original CMMS and the modified CMMS that we previously developed using RSC data. The initial model contained 22 conditions and our final model included 17 conditions. The conditions overlapped with those of the modified CMMS using the more extensive SNOMED CT list. For 1-year mortality, discrimination was high in both the derivation and validation data sets (Harrell C=0.92) and 5-year mortality was slightly lower (Harrell C=0.90). Calibration was reasonable following an adjustment for overfitting. The performance was similar to that of both the original and previous modified CMMS models. The new modified version of the CMMS can be used on the GDPPR, a nationwide primary care data set of 54 million people, to enable adjustment for multimorbidity in predicting mortality in people in real-world vaccine effectiveness, pandemic planning, and other research studies. It requires 17 variables to produce a comparable performance with our previous modification of CMMS to enable it to be used in routine data using SNOMED CT.

MULTIMORBIDITY PATTERNS AND COGNITIVE CHANGE AMONG MEXICAN OLDER ADULTS IN THE MEXICAN HEALTH AND AGING STUDY

Abstract Multimorbidity (≥ 2 chronic conditions) increases the risk of non-normative cognitive decline. Among Mexican older adults, little is known about 1) the prevalence of multimorbidity, 2) patterns of multimorbidity, and 3) the relationship between multimorbidity patterns and cognitive decline. We used representative data from the Mexican Health and Aging Study to estimate prevalence of multimorbidity, identify common multimorbidity patterns, and examine associations between multimorbidity patterns and cognitive change from 2012–2015 in Mexican adults aged ≥ 65 (n=5,079; mean age: 72.2 (SD=6.1)). Chronic conditions including hypertension, diabetes, cancer, lung disease, heart attack, stroke, and arthritis were measured in 2012, and cognitive function was assessed in 2012 and 2015 using the Cross Cultural Cognitive Examination (CCCE; range:3–96). We used descriptive analyses to estimate multimorbidity prevalence and identify disease patterns, then used weighted linear regression (adjusted for age, sex, martial/partnership status, education, literacy, and household income and wealth) to estimate associations between multimorbidity patterns and cognitive change (modeled as CCCE-2015 regressed on CCCE-2012). In 2012, 50.7% of respondents reported multimorbidity and average CCCE score was 46.6 (SD=17.2). From 2012–2015, CCCE decreased on average 2.7 units (SD=13.1). Disease patterns with ≥ 2% prevalence included hypertension+depression (6.0%), hypertension+arthritis (5.9%), hypertension+diabetes (5.8%), hypertension+arthritis+depression (5.4%), hypertension+diabetes+depression (2.8%), hypertension+diabetes+arthritis (2.7%), and arthritis+depression (2.1%). Compared to those reporting no conditions, respondents reporting arthritis+depression (b=-3.88, CI=-6.11:-1.66), hypertension+diabetes (b=-3.72, CI=-5.33:-2.11), or hypertension+diabetes+depression (b=-3.41, CI=-5.32:-1.21) experienced greater cognitive decline. Our results suggest diabetes and depression are common elements of multimorbidity associated with cognitive decline in Mexican older adults.

The interaction between geriatric and neighborhood vulnerability: Delineating prehospital risk among older adult emergency general surgery patients.

When presenting for emergency general surgery (EGS) care, older adults frequently experience increased risk of adverse outcomes owing to factors related to age ("geriatric vulnerability") and the social determinants of health unique to the places in which they live ("neighborhood vulnerability"). Little is known about how such factors collectively influence adverse outcomes. We sought to explore how the interaction between geriatric and neighborhood vulnerability influences EGS outcomes among older adults. Older adults, 65 years or older, hospitalized with an AAST-defined EGS condition were identified in the 2016 to 2019, 2021 Florida State Inpatient Database. Latent variable models combined the influence of patient age, multimorbidity, and Hospital Frailty Risk Score into a single metric of "geriatric vulnerability." Variations in geriatric vulnerability were then compared across differences in "neighborhood vulnerability" as measured by variations in Area Deprivation Index, Social Vulnerability Index, and their corresponding subthemes (e.g., access to transportation). A total of 448,968 older adults were included. For patients living in the least vulnerable neighborhoods, increasing geriatric vulnerability resulted in up to six times greater risk of death (30-day risk-adjusted hazards ratio [HR], 6.32; 95% confidence interval [CI], 4.49-8.89). The effect was more than doubled among patients living in the most vulnerable neighborhoods, where increasing geriatric vulnerability resulted in up to 15 times greater risk of death (30-day risk-adjusted HR, 15.12; 95% CI, 12.57-18.19). When restricted to racial/ethnic minority patients, the multiplicative effect was four-times as high, resulting in corresponding 30-day HRs for mortality of 11.53 (95% CI, 4.51-29.44) versus 40.67 (95% CI, 22.73-72.78). Similar patterns were seen for death within 365 days. Both geriatric and neighborhood vulnerability have been shown to affect prehospital risk among older patients. The results of this study build on that work, presenting the first in-depth look at the powerful multiplicative interaction between these two factors. The results show that where a patient resides can fundamentally alter expected outcomes for EGS care such that otherwise less vulnerable patients become functionally equivalent to those who are, at baseline, more aged, more frail, and more sick. Prognostic and Epidemiological; Level III.

Health of unpaid carers in Wales, UK: a population data linkage study.

The population of unpaid carers in Wales increased to record. There is no systematic approach to record unpaid caring status, resulting in limited quantitative evidence on unpaid carers' health. The aim of this study is to: (i) create an e-cohort of unpaid carers by linking routinely collected health and administrative datasets in Wales, UK. (ii) investigate whether long-term health conditions and multimorbidity are more prevalent amongst unpaid carers than non-carers. Unpaid carers were identified by linking primary care dataset, National Survey for Wales data with demographic characteristics in the Secure Anonymise Information Linkage Databank. The clinical codes identified in Cambridge Multimorbidity Score were used to explore the prevalence of long-term health conditions. A total of 91220 unpaid carers in Wales were identified between 1 January 2010 and 1 March 2022. Unpaid carers were found at higher risk of managing 35 of 37 long-term health conditions and multimorbidity than non-carers, exacerbated amongst younger age groups and deprived communities. The creation of the first e-cohort of unpaid carers in Wales provides opportunities to perform rapid analysis to systematically understand health needs and evaluate initiatives in future. To better support unpaid carers, flexible approaches focusing on early identification and prevention is crucial.

Correlation of frailty assessment metrics in one-year follow-up of aged care residents: a sub-study of a randomised controlled trial

IntroductionFrailty is increasingly recognised as a dynamic syndrome, with multiple causes, dimensions and consequences. There is little understanding of how those frailty assessment metrics interact over time. The aim of this study was to describe the longitudinal correlation between five frailty metrics, namely multimorbidity, muscular strength, mood alterations, cognitive capacity, and functional capacity in a cohort study of aged care (nursing home) residents.Methods248 aged care residents with Frailty Index at baseline of < 0.4 and no dementia were followed for 12 months. A multimorbidity score and an activity of daily living limitation score were created using individual items of the Frailty Index. Muscular strength was measured by grip strength. Cognitive capacity was measured using the Montreal Cognitive Assessment (MoCA) test. Mood alterations were measured using the anxiety/depression screening question from EQ-5D. We analysed the inter-individual correlation at baseline, association between baseline and future change, and within-individual correlation at baseline, 6 and 12 months.ResultsPopulation analysis shows that metrics were not associated at baseline. All of the studied metrics at baseline were associated with change in 12 months, with the exception of anxiety/depression scores. Pairwise within-individual correlation was strong between MoCA and grip strength (0.13, p = 0.02) and activity of daily living (− 0.48, p < 0.001), and between activities of daily living and multimorbidity index (0.28, p < 0.001). No within-individual correlation was found between anxiety depression score and other metrics.ConclusionThe results suggest an interdependence between comorbidities, physical capacity, cognition and activities of daily living in aged care residents. Comprehensive measurement of frailty-related metrics may provide improved understanding of frailty progression at later life stages.

Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study

BackgroundWhilst multi-morbidity is known to be a concern in people with cancer, very little is known about the risk of cancer in multi-morbid patients. This study aims to investigate the risk of being diagnosed with lung, colorectal, breast and prostate cancer associated with multi-morbidity.MethodsWe investigated the association between multi-morbidity and subsequent risk of cancer diagnosis in UK Biobank. Cox models were used to estimate the relative risks of each cancer of interest in multi-morbid participants, using the Cambridge Multimorbidity Score. The extent to which reverse causation, residual confounding and ascertainment bias may have impacted on the findings was robustly investigated.ResultsOf the 436,990 participants included in the study who were cancer-free at baseline, 21.6% (99,965) were multi-morbid (≥ 2 diseases). Over a median follow-up time of 10.9 [IQR 10.0–11.7] years, 9,019 prostate, 7,994 breast, 5,241 colorectal, and 3,591 lung cancers were diagnosed. After exclusion of the first year of follow-up, there was no clear association between multi-morbidity and risk of colorectal, prostate or breast cancer diagnosis. Those with ≥ 4 diseases at recruitment had double the risk of a subsequent lung cancer diagnosis compared to those with no diseases (HR 2.00 [95% CI 1.70–2.35] p for trend < 0.001). These findings were robust to sensitivity analyses aimed at reducing the impact of reverse causation, residual confounding from known cancer risk factors and ascertainment bias.ConclusionsIndividuals with multi-morbidity are at an increased risk of lung cancer diagnosis. While this association did not appear to be due to common sources of bias in observational studies, further research is needed to understand what underlies this association.

A hypothesis - generating Swedish extended national cross-sectional family study of multimorbidity severity and venous thromboembolism

ObjectivesVenous thromboembolism (VTE) is a common worldwide disease. The burden of multimorbidity, that is, two or more chronic diseases, has increased. Whether multimorbidity is associated with VTE risk remains to...

HYPERTENSION IN CANCER PATIENTS TREATED WITH ANTI-ANGIOGENIC BASED THERAPY: A POPULATION-BASED COHORT STUDY

Objective: Data from randomized clinical trials showed that new-onset hypertension is a common side effect of anti-angiogenic drugs. We compared the cumulative incidence of new-onset hypertension in cancer patients treated with either anti-angiogenic based therapy (AAG) or other chemotherapy only, and in patients who did not received antineoplastic agents (untreated). Design and method: Retrospective population-based cohort study based on the healthcare utilization databases of Lombardy Region (Italy). We identified the cohort of patients aged 40 years or older with a new diagnosis of cancer between 2009 and 2017. We excluded patients with antihypertensive treatment in the five years before cancer diagnosis. We 1:1:1 matched each patient who started a therapy with AAG (index case) with one patient treated with other chemotherapy only and with one untreated patient by date of cancer diagnosis, tumoral site and date of start of antineoplastic therapy. We followed-up each of the three matched patients from the date of start of AAG of the index case until the first date between onset of antihypertensive treatment with at least 3 prescriptions (the outcome of interest), death, migration or 2 years after the start of follow-up. We estimated the incidence cumulative function by considering death as competing event and we fitted a Fine and Grey regression model, adjusted for age, sex and Cancer Multimorbidity Score, in order to estimate the association between treatment and new-onset hypertension. Results: The final cohort included 3,333 1:1:1 matched patients (median age 62 years; 43.6% males). The cumulative incidence of new-onset hypertension was higher among patients treated with AAG, as compared to others. The cumulative incidence rapidly increased 1 year (26.3%) after starting therapy with AAG. The adjusted hazard ratios were 3.73 (95% CI 3.34 to 4.15) and 4.00 (3.56 to 4.48), when compared to patients treated with other chemotherapy and with those untreated, respectively. Moreover, patients treated with AAG also showed a significant increased risk of major cardiovascular events compared to others. Conclusions: Cancer patients treated with AAG showed a markedly higher risk of new-onset hypertension. The risk rapidly increased 1 year after the start of therapy.

Association of common mental disorders and related multimorbidity with subsequent labor market marginalization among refugee and Swedish-born young adults.

Common mental disorders (CMDs), multimorbidity, and refugee status are associated with poor labor market outcome. Little is known about how these factors interact in young adults. We aimed to i) investigate whether the association of CMDs and multimorbidity with labor market marginalization (LMM) differs between refugee and Swedish-born young adults and ii) identify diagnostic groups with particularly high risk for LMM. This longitudinal registry-based study included individuals aged 20-25 years followed from 2012 to 2016 in Sweden (41,516 refugees and 207,729 age and sex-matched Swedish-born individuals). LMM was defined as granted disability pension (DP) or > 180 days of unemployment (UE). A disease co-occurrence network was constructed for all diagnostic groups from 2009 to 2011 to derive a personalized multimorbidity score for LMM. Multivariate logistic regression was used to estimate odds ratios of LMM in refugee and Swedish-born youth as a function of their multimorbidity score. The relative risk (RR, 95% CI) of LMM for refugees with CMDs compared to Swedish-born with CMDs was computed in each diagnostic group. In total, 5.5% of refugees and 7.2% of Swedish-born with CMDs were granted DP; 22.2 and 9.4%, respectively received UE benefit during follow-up. While both CMDs and multimorbidity independently elevated the risk of DP considerably in Swedish-born, CMDs but not multimorbidity elevated the risk of UE. Regarding UE in refugees, multimorbidity with the presence of CMDs showed stronger estimates. Multimorbidity interacted with refugee status toward UE (p < 0.0001) and with CMDs toward DP (p = 0.0049). Two diagnostic groups that demonstrated particularly high RR of UE were schizophrenia, schizotypal and delusional disorders (RR [95% CI]: 3.46 [1.77, 6.75]), and behavioral syndromes (RR [95% CI]: 3.41 [1.90, 6.10]). To combat LMM, public health measures and intervention strategies need to be tailored to young adults based on their CMDs, multimorbidity, and refugee status.

Approach to Multimorbidity Burden Classification and Outcomes in Older Adults With Heart Failure.

The optimal approach to classifying multimorbidity burden in assessing treatment-associated outcomes using real-world data remains uncertain. We assessed whether 2 measurement approaches to characterize multimorbidity influenced observed associations of β-blocker use with outcomes in adults with heart failure (HF). We conducted a retrospective study on adults with HF from 4 integrated health care delivery systems. Multimorbidity burden was characterized by either (1) simple counts of chronic conditions or (2) a weighted multiple chronic conditions score using data from electronic health records. We assessed the impact of these 2 approaches to characterizing multimorbidity on associations between exposure to β-blockers and subsequent all-cause death, hospitalization for HF, and hospitalization for any cause. The study population characterized by a count of chronic conditions included 9988 adults with HF who had a mean (SD) age of 76.4 (12.5) years, with 48.7% women and 24.7% racial/ethnic minorities. The cohort characterized by weighted multiple chronic conditions included 10,082 adults with HF who had a mean (SD) age of 76.4 (12.4) years, 48.9% women, and 25.5% racial/ethnic minorities. The multivariable associations of risks of death or hospitalizations for HF or for any cause associated with incident β-blocker use were similar regardless of how multimorbidity burden was characterized. Simple counts of chronic conditions performed similarly to a weighted multimorbidity score in predicting outcomes using real-world data to examine clinical outcomes associated with β-blocker therapy in HF. Our findings challenge conventional wisdom that more complex measures of multimorbidity are always necessary to characterize patients in observational studies examining therapy-associated outcomes.

Leading mediators of sex differences in the incidence of dementia in community-dwelling adults in the UK Biobank: a retrospective cohort study

BackgroundLittle is known regarding whether sex assigned at birth modifies the association between several predictive factors for dementia and the risk of dementia itself.MethodsOur retrospective cohort study included 214,670 men and 214,670 women matched by age at baseline from the UK Biobank. Baseline data were collected between 2006 and 2010, and incident dementia was ascertained using hospital inpatient or death records until January 2021. Mediation analysis was tested for 133 individual factors.ResultsOver 5,117,381 person-years of follow-up, 5928 cases of incident all-cause dementia (452 cases of young-onset dementia, 5476 cases of late-onset dementia) were documented. Hazard ratios (95% CI) for all-cause, young-onset, and late-onset dementias associated with the male sex (female as reference) were 1.23 (1.17–1.29), 1.42 (1.18–1.71), and 1.21 (1.15–1.28), respectively. Out of 133 individual factors, the strongest mediators for the association between sex and incident dementia were multimorbidity risk score (percentage explained (95% CI): 62.1% (45.2–76.6%)), apolipoprotein A in the blood (25.5% (15.2–39.4%)), creatinine in urine (24.9% (16.1–36.5%)), low-density lipoprotein cholesterol in the blood (23.2% (16.2–32.1%)), and blood lymphocyte percentage (21.1% (14.5–29.5%)). Health-related conditions (percentage (95% CI) explained: 74.4% (51.3–88.9%)) and biomarkers (83.0% (37.5–97.5%)), but not lifestyle factors combined (30.1% (20.7–41.6%)), fully mediated sex differences in incident dementia. Health-related conditions combined were a stronger mediator for late-onset (75.4% (48.6–90.8%)) than for young-onset dementia (52.3% (25.8–77.6%)), whilst lifestyle factors combined were a stronger mediator for young-onset (42.3% (19.4–69.0%)) than for late-onset dementia (26.7% (17.1–39.2%)).ConclusionsOur analysis matched by age has demonstrated that men had a higher risk of all-cause, young-onset, and late-onset dementias than women. This association was fully mediated by health-related conditions or blood/urinary biomarkers and largely mediated by lifestyle factors. Our findings are important for understanding potential mechanisms of sex in dementia risk.

1942. Effect of SARS-CoV-2 Vaccination in a Frailty COVID-19 Cohort: a Real Life Experience in a Northern Italy Hospital

Abstract Background Clinical trial demonstrated that SARS-CoV-2 vaccines have the ability of reduce mortality and morbidity due to COVID-19. The aim of this study is to describe the effect of vaccination in term of mortality, type of ventilation and ICU admission among patients hospitalized for COVID-19 from May to December 2021 in a Ligurian Hospital. Methods This is a retrospective, single-center study conducted in San Martino Hospital (Genoa, Italy), including patients ≥ 18 years hospitalized for COVID-19 in Infectious Disease and Emergency Units from 1st May to 31st December 2021. We collected demographical data, multimorbidity and disability score, vaccination time (“vaccinated” all patients hospitalized ≥ 14 days after first dose or ≥ 7 days after second/third dose), therapy for COVID-19, mortality at 7 and 30 days, ICU admission, ventilation type. Characteristics of vaccinated (group A) versus non vaccinated (group B) patients were compared using Chi-squared/Fisher's exact test for categorical variables and t-test /Kruskal-Wallis test for the continuous ones. Cox proportional hazards models for death at 30 days were performed as univariate analysis as well as adjusting for age, Cumulative Illness Rating Scale [CIRS], gender, Remdesivir, Monoclonal antibodies, Tocilizumab use. Results Overall, 405 patients SARS-CoV-2 infected were enrolled. Data about timing of vaccination were available for 360 patients (89%). We compared clinical characteristics and outcomes of group A (32%) versus group B (68%). In group A patients were older (p&amp;lt; 0.001) and frailer (higher CIRS score and lower Barthel index, p&amp;lt; 0.001) than in group B. Among patients requiring oxygen, 76 (31.5%) in group B vs 26 (22.41%) in group A needed high flow ventilation (p=0.036); 33 (13.52%) vs 3 (2.59%) respectively were admitted to ICU (Figure 1). Mortality at 30 days after hospitalization was higher in group A at univariate analysis [HR(95%CI) 1.44(0.82; 2.53), p=0.208], lower at multivariate analysis [0.57(0.31; 1.02), p=0.059]. Conclusion The results of this study confirm that SARS-CoV-2 vaccination reduces rate of admission to ICU and 30 days mortality among patients hospitalized for COVID-19. In our cohort mortality among vaccinated patients remains high and we hypothesized this is due to high frailty of evaluated population. Disclosures Chiara Dentone, CD, Angelini: Advisor/Consultant|Gilead: Advisor/Consultant|Menarini: Advisor/Consultant|Novartis: Advisor/Consultant Matteo Bassetti, PhD, Angelini: Advisor/Consultant|Astellas: Grant/Research Support|Bayer: Advisor/Consultant|Bayer: Honoraria|BioMe ́ rieux: Advisor/Consultant|BioMe ́ rieux: Honoraria|Cidara: Advisor/Consultant|Cidara: Honoraria|Cipla: Advisor/Consultant|Cipla: Honoraria|Gilead: Advisor/Consultant|Gilead: Honoraria|Menarini: Advisor/Consultant|Menarini: Honoraria|MSD: Advisor/Consultant|MSD: Honoraria|Nabriva: Advisor/Consultant|Pfizer: Advisor/Consultant|Pfizer: Board Member|Pfizer: Grant/Research Support|Pfizer: Honoraria|Shionogi: Advisor/Consultant|Shionogi: Honoraria|Tetraphase: Advisor/Consultant.

Examining methodology to identify patterns of consulting in primary care for different groups of patients before a diagnosis of cancer: An exemplar applied to oesophagogastric cancer

BackgroundCurrent methods for estimating the timeliness of cancer diagnosis are not robust because dates of key defining milestones, for example first presentation, are uncertain. This is exacerbated when patients have other conditions (multimorbidity), particularly those that share symptoms with cancer. Methods independent of this uncertainty are needed for accurate estimates of the timeliness of cancer diagnosis, and to understand how multimorbidity impacts the diagnostic process. MethodsParticipants were diagnosed with oesophagogastric cancer between 2010 and 2019. Controls were matched on year of birth, sex, general practice and multimorbidity burden calculated using the Cambridge Multimorbidity Score. Primary care data (Clinical Practice Research Datalink) was used to explore population-level consultation rates for up to two years before diagnosis across different multimorbidity burdens. Five approaches were compared on the timing of the consultation frequency increase, the inflection point for different multimorbidity burdens, different aggregated time-periods and sample sizes. ResultsWe included 15,410 participants, of which 13,328 (86.5 %) had a measurable multimorbidity burden. Our new maximum likelihood estimation method found evidence that the inflection point in consultation frequency varied with multimorbidity burden, from 154 days (95 %CI 131.8–176.2) before diagnosis for patients with no multimorbidity, to 126 days (108.5–143.5) for patients with the greatest multimorbidity burden. Inflection points identified using alternative methods were closer to diagnosis for up to three burden groups. Sample size reduction and changing the aggregation period resulted in inflection points closer to diagnosis, with the smallest change for the maximum likelihood method. DiscussionExisting methods to identify changes in consultation rates can introduce substantial bias which depends on sample size and aggregation period. The direct maximum likelihood method was less prone to this bias than other methods and offers a robust, population-level alternative for estimating the timeliness of cancer diagnosis.

The Association of Epigenetic Age Acceleration and Multimorbidity at Age 90 in the Women's Health Initiative.

Epigenetic age acceleration (EAA), a measure of accelerated biological aging, has been associated with an increased risk of several age-related chronic conditions. This is the first study to prospectively examine the relationship between EAA and both multimorbidity count and a weighted multimorbidity score among long-lived postmenopausal women. We included 1951 women from the Women's Health Initiative who could have survived to age 90. EAA was estimated using the Horvath pan-tissue, Hannum, PhenoAge, and GrimAge "clocks." Twelve chronic conditions were included in the multimorbidity count. The multimorbidity score was weighted for each morbidity's relationship with mortality in the study population. Using mixed-effects Poisson andlinear regression models that included baseline covariates associated with both EAA and multimorbidity, we estimated relative risks (RRs) and 95% confidence intervals (CIs) for the relationships between each EAA measure at the study baseline with both multimorbidity count and weighted multimorbidity score at age 90, respectively. For every one standard deviation increase in AgeAccelPheno, the rate of multimorbidity accumulation increased 6% (RR=1.06; 95% CI=1.01-1.12; p=.025) and the multimorbidity score by 7% (RR=1.07; 95% CI=1.01-1.13; p=.014) for women who survived to age 90. The results for a one standard deviation increase in AgeAccelHorvath, AgeAccelHannum, and AgeAccelGrim with multimorbidity accumulation and score were weaker compared to AgeAccelPheno, and the latter 2 did not reach statistical significance. AgeAccelPheno and AgeAccelHannum may predict multimorbidity count and score at age 90 in older women and, thus, may be useful as a biomarker predictor of multimorbidity burden in the last decades of life.

Confirming Prior and Identifying Novel Correlates of Acute Calcium Pyrophosphate Crystal Arthritis.

To investigate previously identified and novel correlates of acute calcium pyrophosphate (CPP) crystal arthritis among well-characterized cases. In this case-control study, we identified cases of acute CPP crystal arthritis using a validated algorithm (positive predictive value 81%) applied in the Partners HealthCare electronic health record (EHR). Cases were matched to general patient controls on the year of first EHR encounter and index date. Prespecified potential correlates included sex, race, and comorbidities and medications previously associated with CPP deposition/acute CPP crystal arthritis in the literature. We estimated odds ratios (ORs) and 95% confidence intervals using conditional logistic regression models adjusted for demographic characteristics, comorbidities, medications prescribed in the past 90 days, health care utilization, and multimorbidity score. We identified 1,697 cases matched to 6,503 controls. Mean ± SD age was 73.7 ± 11.8 years, 56.7% were female, 80.8% were White, and 10.3% were Black. All prespecified covariates were more common in cases than controls. Osteoarthritis (OR 3.08), male sex (OR 1.35), rheumatoid arthritis (OR 2.09), gout (OR 2.83), proton pump inhibitors (OR 1.94), loop diuretics (OR 1.60), and thiazides (OR 1.46) were significantly associated with acute CPP crystal arthritis after full adjustment. Black race was associated with lower odds for acute CPP crystal arthritis compared to White race (OR 0.47). Using a validated algorithm to identify nearly 1,700 patients with acute CPP crystal arthritis, we confirmed important correlates of this acute manifestation of CPP deposition. This is the first study to report higher odds for acute CPP crystal arthritis among males.