Re-examining the Classification of Older Adults with Diabetes by Comorbidities and Relationship with Frailty, Disability, and 5-year Mortality

Background Limited research has been conducted to risk stratify older adults with diabetes. Our objective was to re-examine the 2005-06 classification systems in participants who are now five years older. Methods We examined a subsample of 884 community-residing older adults with the diagnosis of diabetes from the National Social Life, Health, and Aging Project (NSHAP). The primary objective was to utilize a latent class analysis (LCA) to fit a model to 11 comorbidities, comparing the 2010-11 LCA model to that of 2005-6. The secondary objective was to evaluate the association of the identified classes with frailty, disability, and five-year mortality. Results Both 2005-6 LCA and the 2010-11 LCA model fit three similar comorbidity profiles: Class 1 with the lowest rates of nearly all comorbidities, Class 2 had highest rates of obesity, hypertension, arthritis, and incontinence, and Class 3 had the higher rates of myocardial infarctions, congestive heart failure, and stroke. When compared to the healthier Class 1 (class probability=0.67), participants with a comorbidity profile with more prevalent cardiovascular conditions (Class 3; 0.09) were at higher risk of frailty and mortality, but not disability; whereas participants with a comorbidity profile with more prevalent geriatric syndrome conditions (Class 2; 0.24) were at higher risk of frailty and disability, but not mortality. Conclusions We reconfirmed three latent-classes with distinct comorbidity profiles among older adults with diabetes. However, the complex relationships between comorbidity classes with frailty, disability, and mortality will likely require revision of the current rationale for stratified goal setting and treatment selection.

Profile and Trends in Comorbidity for Patients Undergoing Hip and Knee Arthroplasty Using the Rx-Risk Measure with Pharmaceutical Dispensing Records

IntroductionPatient comobidity at time of primary joint replacement (JR) impacts on outcomes including revision and mortality. Understanding changes in comorbidity profiles is important when assessing change in outcomes over time. Most arthroplasty registries have limited comorbidity information due to their minimum dataset. One approach to obtaining additional comorbidity data is linking registry data with national administrative data. Objectives and ApproachObjectives were to quantify pre-operative comorbidity profile of patients undergoing primary total hip replacement (THR) and total knee replacement (TKR) for osteoarthritis. Also, to examine temporal trends in individual comorbidities for THR and TKR patients. National pharmaceutical dispensing data were linked with THR and TKR arthroplasty patients. Medication dispensing histories in 12-months preceding JR (2003-2017) for 237,333 THR and 394,965 TKR patients, were mapped to 47 comorbidity classes using the Rx-Risk-V measure - a pharmacy-based measure of comorbidity. Comorbidity scores were calculated by summing comorbidity categories for individual patients. Trends in comorbidity scores/categories were described, with comorbidity information presented by PBS beneficiary category (concessional/general), stratified by age (<65/≥65 years). ResultsMedian (interquartile range) comorbidity scores were higher in concessional patients ≥65y, THR:5(3-6), TKR:5(3-7); <65y,TKR:5(3-6) but not THR:4(2-6). Comparative scores for general patients (both ages) were THR:4(2-6) and TKR:3(2-5). Trends in median comorbidity scores were consistent across study period, THR:4- 5(concessional)/2-3(general) and TKR:4-5(concessional)/4(general). Commonly identified comorbidities in younger concessional THR patients were pain, measured by opioid use (62.4%), inflammation/pain, measured by use of non-steroidal anti-inflammatories (62.2%), GORD (36.2%) and hypertension (36.1%). Individual comorbidities remained generally stable over time. However, increased patient proportions were seen in THR concessionals <65y for opioid pain (59.1%-71.1%), depression (24.5-42.5%), whilst inflammation/pain (82.1-56.1%) and antiplatelet use (≥65y:23.5-9.2%) declined. Conclusion / Implicationsn THR or TKR patients no appreciable change in comorbidity score or comorbidity profile occurred over time. This suggests that improving JR outcomes over time are unlikely due solely to variation in patient comorbidity profiles.

Risk management in patients with atrial fibrillation and comorbid conditions: potentialities of edoxaban

The review article presents current data on the clinical and prognostic significance, as well as on the prevalence of comorbidities in patients with atrial fibrillation (AF). The prevalence of hypertension, diabetes and heart failure in patients with AF is discussed according to the Russian and foreign registry studies, randomized clinical trials. The problem of the effect of comorbidity on the risk of embolism and bleeding in AF is outlined. Potentialities of a novel oral anticoagulant edoxaban (based on the ENGAGE AF-TIMI 48 trial) for managing the risks of thromboembolic and bleeding events in AF and comorbidities. Sub-analyzes of the ENGAGE AF-TIMI 48 trial were discussed, which demonstrated efficacy comparable to warfarin in the embolism prevention and higher safety against bleeding, regardless of the comorbidity profile.

1514. Mortality and Readmission in Adults during the First Year Following Hospitalization for Community-Acquired Pneumonia in the US

Background Increasing evidence suggests that the impact of community-acquired pneumonia (CAP) extends beyond discharge from the hospital and the acute phase of illness. We sought to characterize mortality and hospital readmission across the adult age span and spectrum of comorbidities. Methods A retrospective cohort design and data from Optum’s de-identified Integrated Claims-Clinical dataset (2009-2018) were employed. Study population comprised all adults who, between 1.1.2013 and 12.31.2017, had ≥ 1 acute-care hospitalization for CAP; each qualifying CAP hospitalization separated by ≥ 365 days was included as a unique observation in analyses. Study outcomes included acute-care hospital readmission for any reason and death for any reason. Hospital readmission was ascertained during the 360-day period following discharge from the CAP hospitalization; death was ascertained during the CAP hospitalization as well as during the same 360-day period. Cumulative rates of mortality and readmission were summarized for all patients as well as subgroups defined on age and comorbidity profile (i.e., healthy, at-risk, high-risk). Results Study population totaled 37,006 patients who contributed 38,809 CAP hospitalizations; mean age was 71 years, 51% were female, and 88% had an at-risk (33%) or high-risk (55%) condition. Hospital readmission was 12.5% during the 30-day post-discharge period, and 42.3% during the 360-day post-discharge period. Mortality was 3.5% in hospital, 8.2% from admission to 30 days post-discharge, and 17.7% from admission to 360 days post-discharge. Mortality rates increased with age and severity of comorbidity profile; readmission rates were highest for persons aged 65-74 years and high-risk persons. Rates of readmission and mortality among adults hospitalized for CAP Conclusion All-cause mortality up to 1 year following hospital admission for CAP was substantial, and was associated with increasing age and worsening comorbidity profile. Both readmission and mortality were greater at all ages in high-risk and at-risk groups compared with their healthy counterparts. Strategies that prevent pneumonia and/or the pathophysiologic changes that follow CAP, especially among individuals with comorbid conditions, have the potential to reduce morbidity and mortality following CAP as well as healthcare costs associated with readmission. Disclosures Reiko Sato, PhD, Pfizer, Inc (Employee, Shareholder) Derek Weycker, PhD, Pfizer Inc. (Consultant, Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Melody Shaff, BA, Pfizer, Inc. (Consultant, Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Ahuva Hanau, BS, Pfizer, Inc. (Consultant, Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Alexander Lonshteyn, PhD, Pfizer, Inc. (Consultant, Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Stephen I. Pelton, MD, Merck vaccine (Consultant, Grant/Research Support)Pfizer (Consultant, Grant/Research Support)Sanofi Pasteur (Consultant, Other Financial or Material Support, DSMB)Seqirus Vaccine Ltd. (Consultant)