Rheumatoid arthritis and changes on spirometry by smoking status in two prospective longitudinal cohorts.

OBJECTIVE: To compare longitudinal changes in spirometric measures between patients with rheumatoid arthritis (RA) and non-RA comparators. METHODS: We analysed longitudinal data from two prospective cohorts: the UK Biobank and COPDGene. Spirometry was conducted at baseline and a second visit after 5-7 years. RA was identified based on self-report and disease-modifying antirheumatic drug use; non-RA comparators reported neither. The primary outcomes were annual changes in the per cent-predicted forced expiratory volume in 1 s (FEV1%) and per cent predicted forced vital capacity (FVC%). Statistical comparisons were performed using multivariable linear regression. The analysis was stratified based on baseline smoking status and the presence of obstructive pattern (FEV1/FVC <0.7). RESULTS: Among participants who underwent baseline and follow-up spirometry, we identified 233 patients with RA and 37 735 non-RA comparators. Among never-smoking participants without an obstructive pattern, RA was significantly associated with more FEV1% decline (ß=-0.49, p=0.04). However, in ever smokers with ≥10 pack-years, those with RA exhibited significantly less FEV1% decline than non-RA comparators (ß=0.50, p=0.02). This difference was more pronounced among those with an obstructive pattern at baseline (ß=1.12, p=0.01). Results were similar for FEV1/FVC decline. No difference was observed in the annual FVC% change in RA versus non-RA. CONCLUSIONS: Smokers with RA, especially those with baseline obstructive spirometric patterns, experienced lower FEV1% and FEV1/FVC decline than non-RA comparators. Conversely, never smokers with RA had more FEV1% decline than non-RA comparators. Future studies should investigate potential treatments and the pathogenesis of obstructive lung diseases in smokers with RA.

Prevalence and Characteristics of Adults with Difficult-to-Treat Rheumatoid Arthritis in a Large Patient Registry.

OBJECTIVES: An estimated 5-20% of patients with rheumatoid arthritis (RA) fail multiple treatments and are considered "difficult-to-treat" (D2T), posing a substantial clinical challenge for rheumatologists. A European Alliance of Associations for Rheumatology (EULAR) task force proposed a definition of D2T-RA in 2021. We applied EULAR's D2T definition in a cohort of patients with established RA to assess prevalence and we compared clinical characteristics of participants with D2T-RA with matched comparisons. METHODS: Data from the longitudinal Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study (BRASS) registry was used. Participants were classified as D2T if they met EULAR's definition. A comparison group of non-D2T RA patients were matched 2:1 to every D2T patient, and differences in characteristics were evaluated in descriptive analyses. Prevalence rates of D2T were estimated using Poisson regression. RESULTS: We estimated the prevalence of D2T-RA to be 14.4 (95% CI: 12.8-16.3 per 100 persons) among 1,581 participants with RA, and 22.3 (95% CI: 19.9-25.0 per 100 persons) among 1,021 who were biologic/targeted synthetic DMARD experienced. We observed several differences in demographics, comorbidities, and RA disease activity between D2T-RA and non-D2T RA comparisons. Varying EULAR sub-criteria among all participants in BRASS resulted in a range of D2T-RA prevalence rates, from 0.6-17.5 per 100 persons. CONCLUSION: EULAR's proposed definition of D2T-RA identifies patients with RA who have not achieved treatment targets. Future research should explore heterogeneity in these patients and evaluate outcomes to inform the design of future studies aimed at developing more effective RA management protocols.

Comorbidity and polypharmacy among people with HIV stratified by age, sex, and race.

Background: With an increase in life expectancy of people with HIV, there is a corresponding rise in comorbidities and consequent increases in comedications. Objective: This study compared comorbidity and polypharmacy among people with HIV and people without HIV stratified by age, sex, and race. Methods: This retrospective study utilised administrative claims data to identify adult people with HIV with antiretroviral therapy (ART) claims and HIV diagnosis codes from 01 January 2018 to 31 December 2018. Index date was the earliest ART claim or HIV diagnosis in the absence of ART claims. Inclusion required continuous enrolment for ≥12-month pre-index and ≥30-day post-index, along with ≥1 HIV diagnosis during baseline or follow-up. People with HIV were matched 1:2 with people without HIV on sociodemographic. Results were compared using z-tests with robust standard errors in an ordinary least squares regression or Rao-Scott tests. Results: Study sample comprised 20,256 people with HIV and 40,512 people without HIV. Mean age was 52.3 years, 80.0% males, 45.9% Caucasian, and 28.5% African American. Comorbidities were significantly higher in younger age people with HIV than people without HIV. Female had higher comorbidity across all comorbidities especially younger age people with HIV. Polypharmacy was also significantly greater for people with HIV versus people without HIV across all age categories, and higher in females. Across races, multimorbidity and polypharmacy were significantly greater for people with HIV versus people without HIV. Conclusions: Comorbidities and polypharmacy may increase the risk for adverse drug-drug interactions and individualised HIV management for people with HIV across all demographics is warranted.

Forced vital capacity trajectories and risk of lung transplant and ILD-related mortality among patients with rheumatoid arthritis-associated interstitial lung disease.

We aimed to determine the prevalence and outcomes for forced vital capacity percent predicted (FVCpp) decline among patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). We identified patients with RA-ILD in the Mass General Brigham Healthcare system. RA-ILD diagnosis was determined by review of high-resolution computed tomography (HRCT) imaging by up to three thoracic radiologists. We abstracted FVCpp measurements, covariates, lung transplant, and ILD-related death from the medical record. We employed a relative FVCpp decline cutoff of > 10% within 24 months. We also used a group-based trajectory model to obtain patterns of change from RA-ILD diagnosis. We then assessed for associations of each FVC decline definition with risk of lung transplant or ILD-related death using multivariable logistic regression. We analyzed 172 patients with RA-ILD with a median of 6 FVCpp measurements per patient over 6.5 years of follow-up (mean age 62.2 years, 36% male). There were seven (4%) lung transplants and 44 (26%) ILD-related deaths. Ninety-eight (57%) patients had relative decline of FVCpp by > 10% in 24 months. We identified three trajectory groups of FVCpp change: rapidly declining (n = 24/168 [14%]), slowly declining (n = 90/168 [54%]), and stable/improving (n = 54/168 [32%]). The rapidly declining group and FVCpp > 10% had adjusted odds ratios (aOR) for lung transplant/ILD-related death of 19.2 (95%CI 4.9 to 75.5) and 2.8 (95%CI 1.3 to 6.1) respectively. Over half of patients with RA-ILD had declining FVCpp. The different trajectory patterns demonstrate the importance of FVC monitoring for identifying patients at the highest risk of poor outcomes. Key Points • Over half of patients with RA-ILD had declining FVCpp over a median of 6.5 years of follow-up. • The rapidly declining FVCpp trajectory group had stronger associations with lung transplant and ILD-related death compared to those with FVCpp decline by > 10%. • Clinicians can employ FVC monitoring to proactively treat patients who are at risk of poor outcomes.

Personalizing cardiovascular risk prediction for patients with systemic lupus erythematosus.

OBJECTIVE: Cardiovascular disease (CVD) risk is increased in SLE and underestimated by general population prediction algorithms. We aimed to develop a novel SLE-specific prediction tool, SLECRISK, to provide a more accurate estimate of CVD risk in SLE. METHODS: We studied patients in the Brigham and Women's Hospital SLE cohort. We collected one-year baseline data including the presence of traditional CVD factors and SLE-related features at cohort enrollment. Ten-year follow-up for the first major adverse cardiovascular event (MACE; myocardial infarction (MI), stroke, or cardiac death) began at day +1 following the baseline period (index date). ICD-9/10 codes identified MACE were adjudicated by board-certified cardiologists. Least absolute shrinkage and selection operator regression selected SLE-related variables to add to the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Risk Equations 10-year risk Cox regression model. Model fit statistics and performance (sensitivity, specificity, positive/negative predictive value, c-statistic) for predicting moderate/high 10-year risk (≥7.5 %) of MACE were assessed and compared to ACC/AHA, Framingham risk score (FRS), and modified FRS (mFRS). Optimism adjustment internal validation was performed using bootstrapping. RESULTS: We included 1,243 patients with 90 MACEs (46 MIs, 36 strokes, 19 cardiac deaths) over 8946.5 person-years of follow-up. SLE variables selected for the new prediction algorithm (SLECRISK) were SLE activity (remission/mild vs. moderate/severe), disease duration (years), creatinine (mg/dL), anti-dsDNA, anti-RNP, lupus anticoagulant, anti-Ro positivity, and low C4. The sensitivity for detecting moderate/high-risk (≥7.5 %) of MACE using SLECRISK was 0.74 (95 %CI: 0.65, 0.83), which was better than the sensitivity of the ACC/AHA model (0.38 (95 %CI: 0.28, 0.48)). It also identified 3.4-fold more moderate/high-risk patients than the ACC/AHA. Patients who were moderate/high-risk according to SLECRISK but not ACC/AHA, were more likely to be young women with severe SLE and few other traditional CVD risk factors. Model performance between SLECRISK, FRS, and mFRS were similar. CONCLUSION: The novel SLECRISK tool is more sensitive than the ACC/AHA for predicting moderate/high 10-year risk for MACE and may be particularly useful in predicting risk for young females with severe SLE. Future external validation studies utilizing cohorts with more severe SLE are needed.

Gout risk in adults with pre-diabetes initiating metformin.

OBJECTIVE: Despite the strong association between gout and pre-diabetes, the role of metformin in gout among individuals with pre-diabetes remains uncertain. We compared the incidence rates of gout in adults with pre-diabetes starting metformin with those not using antidiabetic treatments. METHODS: We conducted a new-user, propensity score-matched cohort study using electronic health records from an academic health system (2007-2022). Pre-diabetes was defined based on haemoglobin A1c levels. Metformin users were identified and followed from the first metformin prescription date. Non-users of antidiabetic medications were matched to metformin users based on propensity score and the start of follow-up. The primary outcome was incident gout. Cox proportional hazards models estimated the HR for metformin. Linear regression analyses assessed the association between metformin use and changes in serum urate (SU) or C-reactive protein (CRP). RESULTS: We identified 25 064 individuals with pre-diabetes and propensity score-matched 1154 metformin initiators to 13 877 non-users. Baseline characteristics were well balanced (all standardised mean differences <0.1). The median follow-up was 3.9 years. The incidence rate of gout per 1000 person-years was lower in metformin users 7.1 (95% CI 5.1 to 10) compared with non-users 9.5 (95% CI 8.8 to 10.2). Metformin initiation was associated with a reduced relative risk of gout (HR 0.68, 95% CI 0.48 to 0.96). No relationship was found between metformin and changes in SU or CRP. CONCLUSIONS: Metformin use was associated with a reduced risk of gout among adults with pre-diabetes, suggesting that metformin may be important in lowering gout risk in individuals with pre-diabetes.

Neuropsychiatric and Laboratory Outcomes of Hepatitis C Treatment in an Early-Treated HIV Cohort in Thailand.

Background: Hepatitis C virus (HCV) coinfection may further compromise immunological and cognitive function in people with HIV (PWH). This study compared laboratory and neuropsychiatric measures across the periods of HCV seroconversion and direct-acting antiviral (DAA) therapy with sustained virologic response (SVR) among PWH who initiated antiretroviral therapy (ART) during acute HIV infection (AHI) and acquired HCV after 24 weeks of ART. Methods: Participants from the RV254 AHI cohort underwent paired laboratory and neuropsychiatric assessments during regular follow-up. The former included measurements of CD4 + and CD8 + T-cell counts, HIV RNA, liver enzymes, and lipid profiles. The latter included the Patient Health Questionnaire-9 (PHQ-9), Distress Thermometer (DT), and a 4-test cognitive battery that evaluated psychomotor speed, executive function, fine motor speed and dexterity. The raw scores in the battery were standardized and averaged to create an overall performance (NPZ-4) score. Parameters of HCV-coinfected participants were compared across HCV seroconversion and DAA treatment groups. Results: Between 2009 and 2022, 79 of 703 RV254 participants acquired HCV after ≥ 24 weeks of ART; 53 received DAA, and 50 (94%) achieved SVR. All participants were Thai males (median age: 30 years); 34 (68%) denied past intravenous drug use, and 41 (82%) had a history of other sexually transmitted infections during follow-up. Following SVR, aspartate transferase (AST) and alanine transaminase (ALT) decreased (p < 0.001), while total cholesterol, low-density lipoprotein, and triglycerides increased (p < 0.01). The median CD4+/CD8 + ratio increased from 0.91 to 0.97 (p = 0.012). NPZ-4 improved from 0.75 to 0.91 (p = 0.004). The median DT score increased from 1.7 to 2.7 (p = 0.045), but the PHQ-9 score remained unchanged. Conclusion: HCV coinfection is common in this group of high-risk PWH, highlighting the need for regular screening, early diagnosis, and treatment. There was a modest improvement in the CD4+/CD8 + T-cell ratio and cognitive performance after DAA therapy in patients who achieved SVR. Future studies should examine potential neuropsychiatric impacts during early HCV infection as well as the longer-term neuropsychiatric outcomes after DAA treatment with SVR.

Machine learning to identify chronic cough from administrative claims data.

Accurate identification of patient populations is an essential component of clinical research, especially for medical conditions such as chronic cough that are inconsistently defined and diagnosed. We aimed to develop and compare machine learning models to identify chronic cough from medical and pharmacy claims data. In this retrospective observational study, we compared 3 machine learning algorithms based on XG Boost, logistic regression, and neural network approaches using a large claims and electronic health record database. Of the 327,423 patients who met the study criteria, 4,818 had chronic cough based on linked claims-electronic health record data. The XG Boost model showed the best performance, achieving a Receiver-Operator Characteristic Area Under the Curve (ROC-AUC) of 0.916. We selected a cutoff that favors a high positive predictive value (PPV) to minimize false positives, resulting in a sensitivity, specificity, PPV, and negative predictive value of 18.0%, 99.6%, 38.7%, and 98.8%, respectively on the held-out testing set (n = 82,262). Logistic regression and neural network models achieved slightly lower ROC-AUCs of 0.907 and 0.838, respectively. The XG Boost and logistic regression models maintained their robust performance in subgroups of individuals with higher rates of chronic cough. Machine learning algorithms are one way of identifying conditions that are not coded in medical records, and can help identify individuals with chronic cough from claims data with a high degree of classification value.

Antiretroviral therapy among people with HIV with comorbidities in the United States: a retrospective cohort study.

OBJECTIVES: To describe patterns of antiretroviral medications among people with HIV (PWH) who also have common comorbid conditions in a United States cohort. METHODS: This retrospective cohort study used Optum Research Database claims data from 01/01/2017 through 01/31/2019 to identify adult PWH (≥18 years) based on pharmacy claims for ART during 2018. The index date was defined as the first date of an ART claim. Study inclusion required ≥1 HIV/AIDS diagnosis code during the study period, and continuous health plan enrollment 12 months prior to and at least 30 days after the index date. Descriptive statistics were used to report study results. RESULTS: The study population consisted of 17,694 PWH; mean (SD) age 52.2 (12.8) years; 62.0% were ≥ 50 years old. About 50.6% of the study sample had ≥2 comorbidities at baseline. The most prevalent comorbid conditions were hypertension (33.2%), hyperlipidemia (29.7%), neuropsychiatric conditions (26.9%), and cardiovascular disease (11.5%). Most (93.5%) of PWH received a nucleotide reverse transcriptase inhibitor (NRTI) backbone regimen, including tenofovir alafenamide (41.6%), tenofovir disoproxil fumarate (28.1%), and abacavir (22.0%). The most commonly used anchor agents, 62.6%, were integrase strand transfer inhibitors (INSTIs): dolutegravir (30.4%), elvitegravir (24.2%), and raltegravir (7.3%). The proportion of PWH using specific ARTs did not vary significantly with the presence and type of comorbidities. CONCLUSION: From our analyses, ART prescribing did not appear to vary with the presence of comorbidities and potential medication contraindications. ART regimens may have comparable efficacy profiles; however, selection should be guided by each patient's comorbidities to prevent potential comedication drug toxicities.

Prospective screening for sexually transmitted infections among US service members with Chlamydia trachomatis or Neisseria gonorrhoeae infection.

BACKGROUND: Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are the most common bacterial causes of sexually transmitted infection (STI) in the United States (US). The purpose of this study was to determine the frequency of reinfection during a six-month study period and to evaluate the retesting interval for those infected with CT or NG. METHODS: We conducted a prospective, six-month follow-up study among US military personnel with new onset, laboratory-confirmed CT or NG, recruited from an STI clinic at a large military base from January 2018 to January 2020. Each participant was randomly assigned to one of four groups, which differed only by the timing of the first study-associated follow-up visit after CT or NG diagnosis. RESULTS: Of the 347 initially recruited into the study, 267 participants completed a follow-up visit prior to their scheduled, final visit 6 months after initial infection. The median age at enrollment was 22 years and 41.0% were female. There were 32 (12.0%) reinfections (30 CT and 2 NG) after treatment of an index diagnosis of CT or NG within the six-month study period. Six of the CT reinfections were only detected at the final visit. A review of medical records revealed additional CT and NG reinfections. The probability of detecting a reinfection did not vary significantly by timing of follow-up. CONCLUSIONS: The likelihood of detecting CT or NG reinfection did not differ according to time of follow up visit among study participants, thus supporting CDC guidance to retest three months post treatment. Efforts should continue to focus on STI prevention and risk reduction.

A novel household-based patient outreach pilot program to boost late-season influenza vaccination rates during the COVID-19 pandemic.

BACKGROUND: The objective of this study was to test a novel household-based approach to improve late-season influenza vaccine uptake during the 2020-2021 season, using Epic's MyChart patient portal messages and/or interactive voice response telephone calls. METHODS: This study was a non-blinded, quality improvement program using a block randomized design conducted among patients from Reliant Medical Group clinics residing in a traditional household (≥2 individuals clinically active in the Reliant system living at the same address). Households were randomized 1:1:1 into intervention arms: non-tailored communication (messaging based on CDC's seasonal influenza vaccination campaign), tailored communication (comprehensive communication including reinforcement of the importance of influenza vaccination for high-risk individuals), and standard-of-care control. Influenza vaccination during the program was captured via medical records, and the odds of vaccination among communication arms versus the control arm were assessed. A survey assessing influenza vaccination drivers was administered using MyChart. RESULTS: Influenza vaccination increased by 3.3% during the program period, and no significant differences in vaccination were observed in intervention arms relative to the control arm. Study operationalization faced substantial challenges related to the concurrent COVID-19 pandemic. Compared with vaccinated survey respondents, unvaccinated respondents less frequently reported receiving a recommendation for influenza vaccination from their healthcare provider (15.8% vs. 42.3%, p < 0.001) or awareness that vaccination could protect themselves and higher risk contacts (82.3% vs. 92.6%, p < 0.001). CONCLUSIONS: No significant effects of the interventions were observed. Survey results highlighted the importance of healthcare provider recommendations and the need for increased education around the benefits of vaccination.

Comorbidity and comedication burden among people living with HIV in the United States.

OBJECTIVE: To describe the burden of comorbid conditions and comedications among people living with HIV (PLWH) vs. people living without HIV (PLWoH). METHODS: This was a case-control study conducted among insured patients using administrative claims data. Adult PLWH were identified by antiretroviral therapy (ART) claims or HIV/AIDS diagnosis codes from 1 January 2018 to 31 December 2018 (index date was set by the earliest claim). Continuous enrollment was required for ≥12 months pre-index (baseline) and ≥30 days post-index (follow-up). Patients were required to have ≥1 HIV diagnosis during baseline or follow-up. Those with only HIV prophylaxis were excluded. PLWoH were matched 2:1 to PLWH on demographic characteristics. Study outcomes were compared using z-tests with robust standard errors in an ordinary least squares regression or Rao-Scott tests. RESULTS: The study included 20,256 PLWH and 40,512 matched PLWoH, mean age 52 years. PLWH vs. PLWoH had higher mean (SD) Charlson comorbidity index scores (0.93 [1.59] vs. 0.61 [1.28]; p < .001) and a greater proportion had ≥1 comorbidity (69.1% vs. 54.5%, p < .001). The most prevalent comorbidities included hypertension (33.9% vs. 32.2%; p < .001), hyperlipidemia (29.4% vs. 24.6%; p < .001), chronic kidney disease (13.6% vs. 9.4%, p < .001), depression (13.1% vs. 7.3%, p < .001) and substance abuse (12.8% vs. 7.1%, p < .001). Mean (SD) non-ART prescription fills were higher among PLWH vs. PLWoH (11.9 [10.1] vs. 9.2 [9.4]; p < .001). CONCLUSIONS: Multimorbidity and polypharmacy were more prevalent among PLWH vs. matched PLWoH. Findings support the need to consider comorbidities and comedications when choosing ART and to minimize drug-drug interactions and adverse events to improve patient outcomes.

Development of a natural language processing algorithm to detect chronic cough in electronic health records.

BACKGROUND: Chronic cough (CC) is difficult to identify in electronic health records (EHRs) due to the lack of specific diagnostic codes. We developed a natural language processing (NLP) model to identify cough in free-text provider notes in EHRs from multiple health care providers with the objective of using the model in a rules-based CC algorithm to identify individuals with CC from EHRs and to describe the demographic and clinical characteristics of individuals with CC. METHODS: This was a retrospective observational study of enrollees in Optum's Integrated Clinical + Claims Database. Participants were 18-85 years of age with medical and pharmacy health insurance coverage between January 2016 and March 2017. A labeled reference standard data set was constructed by manually annotating 1000 randomly selected provider notes from the EHRs of enrollees with ≥ 1 cough mention. An NLP model was developed to extract positive or negated cough contexts. NLP, cough diagnosis and medications identified cough encounters. Patients with ≥ 3 encounters spanning at least 56 days within 120 days were defined as having CC. RESULTS: The positive predictive value and sensitivity of the NLP algorithm were 0.96 and 0.68, respectively, for positive cough contexts, and 0.96 and 0.84, respectively, for negated cough contexts. Among the 4818 individuals identified as having CC, 37% were identified using NLP-identified cough mentions in provider notes alone, 16% by diagnosis codes and/or written medication orders, and 47% through a combination of provider notes and diagnosis codes/medications. Chronic cough patients were, on average, 61.0 years and 67.0% were female. The most prevalent comorbidities were respiratory infections (75%) and other lower respiratory disease (82%). CONCLUSIONS: Our EHR-based algorithm integrating NLP methodology with structured fields was able to identify a CC population. Machine learning based approaches can therefore aid in patient selection for future CC research studies.

Association Between Real-Time Continuous Glucose Monitor Use and Diabetes-Related Medical Costs for Patients with Type 2 Diabetes.

Little is known about the impact of real-time continuous glucose monitoring (rtCGM) on diabetes-related medical costs within the type 2 diabetes (T2D) population. A retrospective analysis of administrative claims data from the Optum Research Database was conducted. Changes in diabetes-related health care resource utilization costs were expressed as per-patient-per-month (PPPM) costs. A total of 571 T2D patients (90% insulin treated) met study inclusion criteria. Average PPPM for diabetes-related medical costs decreased by -$424 (95% confidence interval [CI] -$816 to -$31, P = 0.035) after initiating rtCGM. These reductions were driven, in part, by reductions in diabetes-related inpatient medical costs: -$358 (95% CI -$706 to -$10, P = 0.044). Inpatient hospital admissions were reduced on average -0.006 PPPM (P = 0.057) and total hospital days were reduced an average of -0.042 PPPM (P = 0.139). These findings provide real-world evidence that rtCGM use was associated with diabetes-related health care resource utilization cost reductions in patients with T2D.

Racial and ethnic disparity in clinical outcomes among patients with confirmed COVID-19 infection in a large US electronic health record database.

BACKGROUND: Racial and ethnic minority groups have been disproportionately affected by the US coronavirus disease 2019 (COVID-19) pandemic; however, nationwide data on COVID-19 outcomes stratified by race/ethnicity and adjusted for clinical characteristics are sparse. This study analyzed the impacts of race/ethnicity on outcomes among US patients with COVID-19. METHODS: This was a retrospective observational study of patients with a confirmed COVID-19 diagnosis in the electronic health record from 01 February 2020 through 14 September 2020. Index encounter site, hospitalization, and mortality were assessed by race/ethnicity (Hispanic, non-Hispanic Black [Black], non-Hispanic White [White], non-Hispanic Asian [Asian], or Other/unknown). Associations between racial/ethnic categories and study outcomes adjusted for patient characteristics were evaluated using logistic regression. FINDINGS: Among 202,908 patients with confirmed COVID-19, patients from racial/ethnic minority groups were more likely than White patients to be hospitalized on initial presentation (Hispanic: adjusted odds ratio 1·690, 95% CI 1·620-1·763; Black: 1·810, 1·743-1·880; Asian: 1·503, 1·381-1·636) and during follow-up (Hispanic: 1·700, 1·638-1·764; Black: 1·578, 1·526-1·633; Asian: 1·391, 1·288-1·501). Among hospitalized patients, adjusted mortality risk was lower for Black patients (0·881, 0·809-0·959) but higher for Asian patients (1·205, 1·000-1·452). INTERPRETATION: Racial/ethnic minority patients with COVID-19 had more severe disease on initial presentation than White patients. Increased mortality risk was attenuated by hospitalization among Black patients but not Asian patients, indicating that outcome disparities may be mediated by distinct factors for different groups. In addition to enacting policies to facilitate equitable access to COVID-19-related care, further analyses of disaggregated population-level COVID-19 data are needed.

Associations of insomnia symptoms with subsequent health services use among community-dwelling U.S. older adults.

STUDY OBJECTIVES: Determine the association of insomnia symptoms with subsequent health services use, in a representative sample of U.S. older adults. METHODS: Participants were 4,289 community-dwelling Medicare beneficiaries who had continuous fee-for-service Medicare coverage 30 days before, and 1 year after the National Health and Aging Trends Study (NHATS) Round 1 interview. Participants reported past-month insomnia symptoms (i.e. sleep onset latency >30 min, difficulty returning to sleep) which we categorized as 0, 1, or 2 symptoms. Outcomes were health services use within 1 year of interviews from linked Medicare claims: emergency department (ED) visits, hospitalizations, 30-day readmissions, home health care (all measured as yes/no), and number of hospitalizations and ED visits. RESULTS: Overall, 18.5% of participants were hospitalized, 28.7% visited the ED, 2.5% had a 30-day readmission, and 11.3% used home health care. After adjustment for demographics, depressive and anxiety symptoms, medical comorbidities, and BMI, compared to participants with no insomnia symptoms, those with two insomnia symptoms had a higher odds of ED visits (odds ratio [OR) = 1.60, 95% confidence interval [CI] = 1.24-2.07, p < 0.001), hospitalizations (OR = 1.29, 95% CI = 1.01-1.65, p < 0.05), and 30-day readmissions (OR = 1.88, 95% CI = 1.88-3.29, p < 0.05). Reporting 2 insomnia symptoms, versus no insomnia symptoms, was associated with a greater number of ED visits and hospitalizations (incidence rate ratio (IRR) = 1.52, 95% CI = 1.23-1.87, p < 0.001; IRR = 1.21, 95% CI = 1.02-1.44, p < 0.05, respectively) after adjusting for demographic and health characteristics. CONCLUSIONS: Among older adults, insomnia symptoms are associated with greater health services use, including emergency department use, hospitalization, and 30-day readmission. Targeting insomnia may lower health services use.

Relative vaccine efficacy of high-dose versus standard-dose influenza vaccines in preventing probable influenza in a Medicare Fee-for-Service population.

BACKGROUND: High-dose (HD) influenza vaccine, currently the most commonly used vaccine among US seniors (aged ≥ 65 years), has been shown to be more efficacious than standard-dose (SD) vaccine in multiple randomized trials. This study evaluated the real-world relative vaccine effectiveness (rVE) of HD vs SD over four influenza seasons. METHODS: This study included Medicare Fee-for-Service enrollees who received HD or SD at an outpatient clinic or pharmacy during influenza seasons 2011-2012 through 2014-2015. Probable influenza (an inpatient stay with an influenza diagnosis on the claim, or an outpatient visit with a rapid influenza test/culture followed by an antiviral prescription) was assessed among HD recipients matched 1:1 with SD recipients by location, vaccination date, age, and sex. Fine-Gray subdistribution hazard models with competing risk of death were used to adjust for residual confounding. Analyses were stratified by outpatient vs pharmacy vaccination. RESULTS: Across the four influenza seasons, there were 535,598, 1,017,552, 1,548,164, and 2,420,450 in the pharmacy cohort; and 821,662, 1,151,080, 1,559,488, and 2,421,758 in the outpatient cohort. During peak influenza season, rVEs for 2011-12 through 2014-15 were 21.8% (95% CI: -5.9%, 42.3%), 14.8% (9.3%, 19.9%), 16.9% (9.2%, 23.9%), and 17.2% (14.5%, 19.9%), respectively, in the pharmacy cohort; and 16.5% (-5.9%, 34.2%), 15.1% (10.9%, 19.1%), 10.0% (2.9%, 16.6%), and -0.2% (-3.0%, 2.5%), respectively, in the outpatient cohort. CONCLUSION: HD was consistently associated with better protection against probable influenza. The lower treatment effect observed in the outpatient cohort could reflect provider bias due to physicians triaging HD to frailer patients.

Rest-Activity Rhythms and Cognitive Decline in Older Men: The Osteoporotic Fractures in Men Sleep Study.

OBJECTIVE: To examine rest-activity circadian rhythm (RAR) and cognitive decline in older men. DESIGN: Longitudinal. SETTING: Osteoporotic Fractures in Men (MrOS) and ancillary Outcomes of Sleep Disorders in Men (MrOS Sleep) studies. PARTICIPANTS: MrOS and MrOS Sleep participants (N=2,754; mean age 76.0 ± 5.3). MEASUREMENTS: The Modified Mini-Mental State examination (3MS) was used to assess cognition at baseline (2003-05) and follow-up examinations (2005-06 and 2007-09). Wrist actigraphy was used to measure 24-hour activity counts at baseline. RAR variables included amplitude (strength of activity rhythm), mesor (mean activity level), pseudo F-statistic (overall circadian rhythm robustness), and acrophase (time of daily peak activity). RESULTS: After an average of 3.4 ± 0.5 years, men with lower amplitudes, mesors, and pseudo F-statistics had greater decline in 3MS performance (amplitude: -0.7 points Q1 vs -0.5 points Q4, p<.001; mesor: -0.5 points Q1 vs -0.2 points Q4, p=.01; pseudo F-statistic: -0.5 points Q1 vs -0.3 points Q4, p<.001). Lower amplitudes and pseudo-F statistics were associated with greater odds of clinically significant cognitive decline (≥5-point decrease) (amplitude Q1 vs. Q4: odds ratio (OR)=1.4, 95% confidence interval (CI)=1.0-1.9; pseudo-F statistic Q1 vs Q4: OR=1.4, 95% CI=1.0-1.9). Men with phase-advanced acrophase had greater odds of clinically significant cognitive decline (OR=1.8, 95% CI=1.2-2.8). Results were adjusted for multiple confounders. CONCLUSION: Several parameters of disrupted RAR (lower amplitude, pseudo F-statistic, mesor, phase-advanced acrophase) were associated with greater cognitive decline in older community-dwelling men. These findings contribute to a growing body of evidence suggesting that altered RARs are associated with cognitive decline in older adults. J Am Geriatr Soc 66:2136-2143, 2018.

A novel approach using actigraphy to quantify the level of disruption of sleep by in-home polysomnography: the MrOS Sleep Study: Sleep disruption by polysomnography.

BACKGROUND: The "first-night effect" of polysomnography (PSG) has been previously studied; however, the ability to quantify the sleep disruption level has been confounded with the use of PSG on all nights. We used actigraphy to quantify disruption level and examined characteristics associated with disruption. METHODS: Totally, 778 older men (76.2 ± 5.4 years) from a population-based study at six US centers underwent one night of in-home PSG. Actigraphy was performed on the PSG night and three subsequent nights. Actigraphically measured total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), and sleep onset latency (SOL) from the PSG night and subsequent nights were compared. Linear regression models were used to examine the association of characteristics and sleep disruption. RESULTS: On average, sleep on the PSG night was worse than the following night (p < 0.05, TST 21 ± 85 min less, SE 2.3 ± 11.3% less, WASO 4.9 ± 51.8 min more, SOL 6.6 ± 56.2 min more). Sleep on the PSG night was significantly worse than that two and three nights later. Characteristics associated with greater sleep disruption on the PSG night included older age, higher apnea-hypopnea index, worse neuromuscular function, and more depressive symptoms. Minorities and men with excessive daytime sleepiness slept somewhat better on the PSG night. CONCLUSIONS: Among older men, there was sleep disruption on the PSG night, which may lead to sleep time underestimation. The increase of sleep on the night after the PSG suggests that data from the second monitoring may overestimate sleep.

Sleep Disturbances and Risk of Hospitalization and Inpatient Days Among Older Women.

Study Objectives: Determine the associations of sleep disturbances with hospitalization risk among older women. Methods: One thousand eight hundred and twenty-seven women (mean age 83.6 years) participating in Study of Osteoporotic Fractures Year 16 (Y16) examination (2002-2004) linked with Medicare and/or HMO claims. At Y16 examination, sleep/wake parameters were measured by actigraphy (total sleep time [TST], sleep efficiency [SE], sleep latency [SL], and wake after sleep onset [WASO]) and subjective sleep measures (sleep quality [Pittsburgh Sleep Quality Index] and daytime sleepiness [Epworth Sleepiness Scale]) were assessed by questionnaire. Measures except TST were dichotomized based on clinical thresholds. Incident hospitalizations were determined from claims data. Results: Nine hundred and seventy-six women (53%) had ≥1 hospitalization in the 3 years after the Year 16 examination. Reduced SE (odds ratio [OR] = 2.39, 95% confidence interval [CI] 1.69-3.39), prolonged SL (OR = 1.41, 95% CI 1.11-1.78), greater WASO (OR = 1.57, 95% CI 1.28-1.93), shorter TST (OR = 1.98, 95% CI 1.42-2.77) and poorer sleep quality (OR = 1.33, 95% CI 1.07-1.65) were each associated with a higher age and site-adjusted odds of hospitalization; associations were attenuated after multivariable adjustment for traditional prognostic factors with the OR for reduced SE (OR = 1.60, 95% CI 1.08-2.38) and shorter TST (OR = 1.63, 95% CI 1.12-2.37) remaining significant. Among women who were hospitalized, greater WASO (rate ratio [RR] = 1.20, 95% CI 1.04-1.37) and poorer sleep quality (RR = 1.18, 95% CI 1.02-1.35) were each associated with a greater age and site-adjusted RR of inpatient days, but associations did not persist after multivariate adjustment. Conclusions: Older women with sleep disturbances have an increased risk of hospitalization partially attributable to demographics, poorer health status, and comorbidities.