Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy.

BACKGROUND: Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy. METHODS: We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol included native and postcontrast T1 mapping and late gadolinium enhancement (LGE). Radiomic features were computed from the midseptal myocardium, near the biopsy region, on native T1, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of radiomic features to 5 principal radiomics. Moreover, a correlation analysis was conducted to identify radiomic features exhibiting a strong correlation (r>0.9) with the 5 principal radiomics. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation. RESULTS: Four histopathological phenotypes were identified: low collagen (n=20), noncollagenous ECS expansion (n=49), mild to moderate collagenous ECS expansion (n=42), and severe collagenous ECS expansion (n=21). Noncollagenous expansion was associated with the highest risk of myocardial inflammation (65%). Although native T1 and ECV provided high diagnostic performance in differentiating severe fibrosis (C statistic, 0.90 and 0.90, respectively), their performance in differentiating between noncollagen and mild to moderate collagenous expansion decreased (C statistic: 0.59 and 0.55, respectively). Integration of ECV principal radiomics provided better discrimination and reclassification between noncollagen and mild to moderate collagen (C statistic, 0.79; net reclassification index, 0.83 [95% CI, 0.45-1.22]; P<0.001). There was a similar trend in the addition of native T1 principal radiomics (C statistic, 0.75; net reclassification index, 0.93 [95% CI, 0.56-1.29]; P<0.001) and LGE principal radiomics (C statistic, 0.74; net reclassification index, 0.59 [95% CI, 0.19-0.98]; P=0.004). Five radiomic features per sequence were identified with correlation analysis. They showed a similar improvement in performance for differentiating between noncollagen and mild to moderate collagen (native T1, ECV, LGE C statistic, 0.75, 0.77, and 0.71, respectively). These improvements remained significant when confined to a single radiomic feature (native T1, ECV, LGE C statistic, 0.71, 0.70, and 0.64, respectively). CONCLUSIONS: Radiomic features extracted from native T1, ECV, and LGE provide incremental information that improves our capability to discriminate noncollagenous expansion from mild to moderate collagen and could be useful for detecting subtle chronic inflammation in patients with dilated cardiomyopathy.

An interactive, online decision aid assessing patient goals and preferences for treatment of aortic stenosis to support physician-led shared decision-making: Early feasibility pilot study.

BACKGROUND: Guidelines recommend shared decision making when choosing treatment for severe aortic stenosis but implementation has lagged. We assessed the feasibility and impact of a novel decision aid for severe aortic stenosis at point-of-care. METHODS: This prospective multi-site pilot cohort study included adults with severe aortic stenosis and their clinicians. Patients were referred by their heart team when scheduled to discuss treatment options. Outcomes included shared decision-making processes, communication quality, decision-making confidence, decisional conflict, knowledge, stage of decision making, decision quality, and perceptions of the tool. Patients were assessed at baseline (T0), after using the intervention (T1), and after the clinical encounter (T2); clinicians were assessed at T2. Before the encounter, patients reviewed the intervention, Aortic Valve Improved Treatment Approaches (AVITA), an interactive, online decision aid. AVITA presents options, frames decisions, clarifies patient goals and values, and generates a summary to use with clinicians during the encounter. RESULTS: 30 patients (9 women [30.0%]; mean [SD] age 70.4 years [11.0]) and 14 clinicians (4 women [28.6%], 7 cardiothoracic surgeons [50%]) comprised 28 clinical encounters Most patients [85.7%] and clinicians [84.6%] endorsed AVITA. Patients reported AVITA easy to use [89.3%] and helped them choose treatment [95.5%]. Clinicians reported the AVITA summary helped them understand their patients' values [80.8%] and make values-aligned recommendations [61.5%]. Patient knowledge significantly improved at T1 and T2 (p = 0.004). Decisional conflict, decision-making stage, and decision quality improved at T2 (p = 0.0001, 0.0005, and 0.083, respectively). Most patients [60%] changed treatment preference between T0 and T2. Initial treatment preferences were associated with low knowledge, high decisional conflict, and poor decision quality; final preferences were associated with high knowledge, low conflict, and high quality. CONCLUSIONS: AVITA was endorsed by patients and clinicians, easy to use, improved shared decision-making quality and helped patients and clinicians arrive at a treatment that reflected patients' values. TRIAL REGISTRATION: Trial ID: NCT04755426, Clinicaltrials.gov/ct2/show/NCT04755426.

Pre-diagnostic plasma proteomics profile for hepatocellular carcinoma.

OBJECTIVE: Proteomics may discover pathophysiological changes related to hepatocellular carcinoma (HCC), an aggressive and lethal type of cancer with low sensitivity for early-stage diagnosis. DESIGN: We measured 1,305 pre-diagnostic (median 12.7 years) SOMAscan proteins from 54 pairs of healthy individuals who subsequently developed HCC and matched non-HCC controls from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Candidate proteins were validated in the independent, prospective UK Biobank Pharma Proteomics Project (UKB-PPP). RESULTS: In NHS/HPFS, we identified 56 elevated proteins in HCC with absolute fold-change >1.2 and Wald test P < .05 in conditional logistic regression analysis. Ingenuity Pathway Analysis identified enrichment of pathways associated with cell viability, adhesion, proteolysis, apoptosis, and inflammatory response. Four proteins, chitinase-3-like protein 1, growth/differentiation factor 15, interleukin-1 receptor antagonist protein, and E-selectin, showed strong positive associations with HCC and were thus validated by ELISA (odds ratio ranged 2.48-14.7, all P < .05) in the NHS/HPFS and by Olink platform (hazard ratio ranged 1.90-3.93, all P < .05) in the UKB-PPP. Adding these four proteins to a logistic regression model of traditional HCC risk factors increased the area under the curve (AUC) from 0.67 to 0.87 in the NHS/HPFS. Consistently, model AUC was 0.88 for HCC risk prediction in the UKB-PPP. CONCLUSION: However, the limited number of HCC cases in the cohorts necessitates caution in interpreting our findings, emphasizing the need for further validation in high-risk populations.

Racial and Ethnic Disparities in Opioid Prescribing on Hospital Discharge Among Older Adults: A National Retrospective Cohort Study.

BACKGROUND: Disparities in opioid prescribing among racial and ethnic groups have been observed in outpatient and emergency department settings, but it is unknown whether similar disparities exist at discharge among hospitalized older adults. OBJECTIVE: To determine filled opioid prescription rates on hospital discharge by race/ethnicity among Medicare beneficiaries. DESIGN: Retrospective cohort study. PARTICIPANTS: Medicare beneficiaries 65 years or older discharged from hospital in 2016, without opioid fills in the 90 days prior to hospitalization (opioid-naïve). MAIN MEASURES: Race/ethnicity was categorized by the Research Triangle Institute (RTI), grouped as Asian/Pacific Islander, Black, Hispanic, other (American Indian/Alaska Native/unknown/other), and White. The primary outcome was an opioid prescription claim within 2 days of hospital discharge. The secondary outcome was total morphine milligram equivalents (MMEs) among adults with a filled opioid prescription. KEY RESULTS: Among 316,039 previously opioid-naïve beneficiaries (mean age, 76.8 years; 56.2% female), 49,131 (15.5%) filled an opioid prescription within 2 days of hospital discharge. After adjustment, Black beneficiaries were 6% less likely (relative risk [RR] 0.94, 95% CI 0.91-0.97) and Asian/Pacific Islander beneficiaries were 9% more likely (RR 1.09, 95% CI 1.03-1.14) to have filled an opioid prescription when compared to White beneficiaries. Among beneficiaries with a filled opioid prescription, mean total MMEs were lower among Black (356.9; adjusted difference - 4%, 95% CI - 7 to - 1%), Hispanic (327.0; adjusted difference - 7%, 95% CI - 10 to - 4%), and Asian/Pacific Islander (328.2; adjusted difference - 8%, 95% CI - 12 to - 4%) beneficiaries when compared to White beneficiaries (409.7). CONCLUSIONS AND RELEVANCE: Black older adults were less likely to fill a new opioid prescription after hospital discharge when compared to White older adults and received lower total MMEs. The factors contributing to these differential prescribing patterns should be investigated further.

Incidence and survival of secondary malignancies after external beam radiotherapy for prostate cancer in the SEER database.

INTRODUCTION: We investigated the incidence of secondary bladder (BCa) and rectal cancers (RCa) after external beam radiotherapy (EBRT) for prostate cancer (PCa) compared to radical prostatectomy (RP) alone, and compared cancer-specific survival (CSS) of these secondary neoplasms to their primary counterparts. METHODS: This retrospective cohort study included men in the SEER cancer registry with a diagnosis of non-metastatic, clinically node-negative PCa treated with either RP or EBRT from 1995-2011 and allowed a minimum five-year lag period for the development of secondary BCa or RCa. Patients were divided into two eras, 1995-2002 and 2003-2011, to examine differences in incidence of secondary malignancies over time. Univariable and multivariable competing risk analyses with Fine-Gray subdistribution hazard and cause-specific hazard models were used to examine the risk of developing a secondary BCa or RCa. Competing risks analyses were used to compare CSS of primary vs. secondary BCa and RCa. RESULTS: A total of 198 184 men underwent RP and 190 536 underwent EBRT for PCa. The cumulative incidence of secondary BCa at 10 years was 1.71% for RP, and 3.7% for EBRT (p<0.001), while that of RCa was 0.52% for RP and 0.99% for EBRT (p<0.001). EBRT was associated with almost twice the risk of developing a secondary BCa and RCa compared to RP. The hazard of secondary BCa following EBRT delivered during 2003-2011 was 20% less than from 1995-2002 (p<0.09, Fine-Gray model), while that of secondary RCa was 31% less (p<0.001) (hazard ratio 0.78, p<0.001) for Fine-Gray and cause-specific hazard models. In the Fine-Gray model, the risk of death from BCa was 27% lower for secondary BCa after RP compared to primary BCa, while the risk of death was 9% lower for secondary BCa after EBRT compared to primary BCa. There was no difference in RCa-specific survival between primary or secondary RCa after RP or EBRT. CONCLUSIONS: The risk of BCa and RCa is almost twice as high for men undergoing EBRT for localized PCa vs. RP, but that risk is declining, likely reflecting advances in radiation delivery. The development of secondary RCa or BCa does not confer elevated risk of death compared to their primary counterparts.

Biomarkers of neurodegeneration and neural injury as potential predictors for delirium.

OBJECTIVES: Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. METHODS: In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N = 70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aß)42 , Aß40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. RESULTS: Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p = 0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aß40 and Aß42 . CONCLUSIONS: These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.

MRI Assessment of Myocardial Deformation for Risk Stratification of Major Arrhythmic Events in Patients With Non-Ischemic Cardiomyopathy Eligible for Primary Prevention Implantable Cardioverter Defibrillators.

BACKGROUND: Implantable cardioverter-defibrillator (ICD) intervention is an established prophylactic measure. Identifying high-benefit patients poses challenges. PURPOSE: To assess the prognostic value of cardiac magnetic resonance imaging (MRI) parameters including myocardial deformation for risk stratification of ICD intervention in non-ischemic cardiomyopathy (NICM) while accounting for competing mortality risk. STUDY TYPE: Retrospective and prospective. POPULATION: One hundred and fifty-nine NICM patients eligible for primary ICD (117 male, 54 ± 13 years) and 49 control subjects (38 male, 53 ± 5 years). FIELD STRENGTH/SEQUENCE: Balanced steady state free precession (bSSFP) and three-dimensional phase-sensitive inversion-recovery late gadolinium enhancement (LGE) sequences at 1.5 T or 3 T. ASSESSMENT: Patients underwent MRI before ICD implantation and were followed up. Functional parameters, left ventricular global radial, circumferential and longitudinal strain, right ventricular free wall longitudinal strain (RV FWLS) and left atrial strain were measured (Circle, cvi42). LGE presence was assessed visually. The primary endpoint was appropriate ICD intervention. Models were developed to determine outcome, with and without accounting for competing risk (non-sudden cardiac death), and compared to a baseline model including LGE and clinical features. STATISTICAL TESTS: Wilcoxon non-parametric test, Cox's proportional hazards regression, Fine-Gray competing risk model, and cumulative incidence functions. Harrell's c statistic was used for model selection. A P value <0.05 was considered statistically significant. RESULTS: Follow-up duration was 1176 ± 960 days (median: 896). Twenty-six patients (16%) met the primary endpoint. RV FWLS demonstrated a significant difference between patients with and without events (-12.5% ± 5 vs. -16.4% ± 5.5). Univariable analyses showed LGE and RV FWLS were significantly associated with outcome (LGE: hazard ratio [HR] = 3.69, 95% CI = 1.28-10.62; RV FWLS: HR = 2.04, 95% CI = 1.30-3.22). RV FWLS significantly improved the prognostic value of baseline model and remained significant in multivariable analysis, accounting for competing risk (HR = 1.73, 95% CI = 1.12-2.66). DATA CONCLUSIONS: In NICM, RV FWLS may provide additional predictive value for predicting appropriate ICD intervention. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 5.

Validating a model for predicting breast cancer and nonbreast cancer death in women aged 55 years and older.

BACKGROUND: To support mammography screening decision making, we developed a competing-risk model to estimate 5-year breast cancer risk and 10-year nonbreast cancer death for women aged 55 years and older using Nurses' Health Study data and examined model performance in the Black Women's Health Study (BWHS). Here, we examine model performance in predicting 10-year outcomes in the BWHS, Women's Health Initiative-Extension Study (WHI-ES), and Multiethnic Cohort (MEC) and compare model performance to existing breast cancer prediction models. METHODS: We used competing-risk regression and Royston and Altman methods for validating survival models to calculate our model's calibration and discrimination (C index) in BWHS (n = 17 380), WHI-ES (n = 106 894), and MEC (n = 49 668). The Nurses' Health Study development cohort (n = 48 102) regression coefficients were applied to the validation cohorts. We compared our model's performance with breast cancer risk assessment tool (Gail) and International Breast Cancer Intervention Study (IBIS) models by computing breast cancer risk estimates and C statistics. RESULTS: When predicting 10-year breast cancer risk, our model's C index was 0.569 in BWHS, 0.572 in WHI-ES, and 0.576 in MEC. The Gail model's C statistic was 0.554 in BWHS, 0.564 in WHI-ES, and 0.551 in MEC; IBIS's C statistic was 0.547 in BWHS, 0.552 in WHI-ES, and 0.562 in MEC. The Gail model underpredicted breast cancer risk in WHI-ES; IBIS underpredicted breast cancer risk in WHI-ES and in MEC but overpredicted breast cancer risk in BWHS. Our model calibrated well. Our model's C index for predicting 10-year nonbreast cancer death was 0.760 in WHI-ES and 0.763 in MEC. CONCLUSIONS: Our competing-risk model performs as well as existing breast cancer prediction models in diverse cohorts and predicts nonbreast cancer death. We are developing a website to disseminate our model.

Radiomics of Late Gadolinium Enhancement Reveals Prognostic Value of Myocardial Scar Heterogeneity in Hypertrophic Cardiomyopathy.

BACKGROUND: Late gadolinium enhancement (LGE) scar burden by cardiac magnetic resonance is a major risk factor for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). However, there is currently limited data on the incremental prognostic value of integrating myocardial LGE radiomics (ie, shape and texture features) into SCD risk stratification models. OBJECTIVES: The purpose of this study was to investigate the incremental prognostic value of myocardial LGE radiomics beyond current European Society of Cardiology (ESC) and American College of Cardiology (ACC)/American Heart Association (AHA) models for SCD risk prediction in HCM. METHODS: A total of 1,229 HCM patients (62% men; age 52 ± 16 years) from 3 medical centers were included. Left ventricular myocardial radiomic features were calculated from LGE images. Principal component analysis was used to reduce the radiomic features and calculate 3 principal radiomics (PrinRads). Cox and logistic regression analyses were then used to evaluate the significance of the extracted PrinRads of LGE images, alone or in combination with ESC or ACC/AHA models, to predict SCD risk. The ACC/AHA risk markers include LGE burden using a dichotomized 15% threshold of LV scar. RESULTS: SCD events occurred in 30 (2.4%) patients over a follow-up period of 49 ± 28 months. Risk prediction using PrinRads resulted in higher c-statistics than the ESC (0.69 vs 0.57; P = 0.02) and the ACC/AHA (0.69 vs 0.67; P = 0.75) models. Risk predictions were improved by combining the 3 PrinRads with ESC (0.73 vs 0.57; P < 0.01) or ACC/AHA (0.76 vs 0.67; P < 0.01) risk scores. The net reclassification index was improved by combining the PrinRads with ESC (0.25 [95% CI: 0.08-0.43]; P = 0.005) or ACC/AHA (0.05 [95% CI: -0.07 to 0.16]; P = 0.42) models. One PrinRad was a significant predictor of SCD risk (HR: 0.57 [95% CI: 0.39-0.84]; P = 0.01). LGE heterogeneity was a major component of PrinRads and a significant predictor of SCD risk (HR: 0.07 [95% CI: 0.01-0.75]; P = 0.03). CONCLUSIONS: Myocardial LGE radiomics are strongly associated with SCD risk in HCM and provide incremental risk stratification beyond current ESC or AHA/ACC risk models. Our proof-of-concept study warrants further validation.

Comparison of the frailty index and frailty phenotype and their associations with postoperative delirium incidence and severity.

BACKGROUND: Recent studies have reported an association between presurgical frailty and postoperative delirium. However, it remains unclear whether the frailty-delirium relationship differs by measurement tool (e.g., frailty index vs. frailty phenotype) and whether frailty is associated with delirium, independent of preoperative cognition. METHODS: We used the successful aging after elective surgery (SAGES) study, a prospective cohort of older adults age ≥70 undergoing major non-cardiac surgery (N = 505). Preoperative measurement of the modified mini-mental (3MS) test, frailty index and frailty phenotype were obtained. The confusion assessment method (CAM), supplemented by chart review, identified postoperative delirium. Delirium feature severity was measured by the sum of CAM-severity (CAM-S) scores. Generalized linear models were used to determine the relative risk of each frailty measure with delirium incidence and severity. Subsequent models adjusted for age, sex, surgery type, Charlson comorbidity index, and 3MS. RESULTS: On average, patients were 76.7 years old (standard deviation 5.22), 58.8% of women. For the frailty index, the incidence of delirium was 14% in robust, 17% in prefrail, and 31% in frail patients (p < 0.001). For the frailty phenotype, delirium incidence was 13% in robust, 21% in prefrail, and 27% in frail patients (p = 0.016). Frailty index, but not phenotype, was independently associated with delirium after adjustment for comorbidities (relative risk [RR] 2.13, 95% confidence interval [CI] 1.23-3.70; RR 1.61, 95% CI 0.77-3.37, respectively). Both frailty measures were associated with delirium feature severity. After adjustment for preoperative cognition, only the frailty index was associated with delirium incidence; neither index nor phenotype was associated with delirium feature severity. CONCLUSION: Both the frailty index and phenotype were associated with the development of postoperative delirium. The index showed stronger associations that remained significant after adjusting for baseline comorbidities and preoperative cognition. Measuring frailty prior to surgery can assist in identifying patients at risk for postoperative delirium.

Partnering with Patients and Families to Improve Diagnostic Safety through the OurDX Tool: Effects of Race, Ethnicity, and Language Preference.

BACKGROUND: Patients and families at risk for health disparities may also be at higher risk for diagnostic errors but less likely to report them. OBJECTIVES: This study aimed to explore differences in race, ethnicity, and language preference associated with patient and family contributions and concerns using an electronic previsit tool designed to engage patients and families in the diagnostic process (DxP). METHODS: Cross-sectional study of 5,731 patients and families presenting to three subspecialty clinics at an urban pediatric hospital May to December 2021 who completed a previsit tool, codeveloped and tested with patients and families. Prior to each visit, patients/families were invited to share visit priorities, recent histories, and potential diagnostic concerns. We used logistic regression to determine factors associated with patient-reported diagnostic concerns. We conducted chart review on a random subset of visits to review concerns and determine whether patient/family contributions were included in the visit note. RESULTS: Participants provided a similar mean number of contributions regardless of patient race, ethnicity, or language preference. Compared with patients self-identifying as White, those self-identifying as Black (odds ratio [OR]: 1.70; 95% confidence interval [CI]: [1.18, 2.43]) or "other" race (OR: 1.48; 95% CI: [1.08, 2.03]) were more likely to report a diagnostic concern. Participants who preferred a language other than English were more likely to report a diagnostic concern than English-preferring patients (OR: 2.53; 95% CI: [1.78, 3.59]. There were no significant differences in physician-verified diagnostic concerns or in integration of patient contributions into the note based on race, ethnicity, or language preference. CONCLUSION: Participants self-identifying as Black or "other" race, or those who prefer a language other than English were 1.5 to 2.5 times more likely than their counterparts to report potential diagnostic concerns when proactively asked to provide this information prior to a visit. Actively engaging patients and families in the DxP may uncover opportunities to reduce the risk of diagnostic errors and potential safety disparities.

Implementing Shared Decision-Making for Multiple Sclerosis: The MS-SUPPORT Tool.

BACKGROUND: Disease modifying therapies (DMTs) offer opportunities to improve the course of multiple sclerosis (MS), but decisions about treatment are difficult. People with multiple sclerosis (pwMS) want more involvement in decisions about DMTs, but new approaches are needed to support shared decision-making (SDM) because of the number of treatment options and the range of outcomes affected by treatment. We designed a patient-centered tool, MS-SUPPORT, to facilitate SDM for pwMS. We sought to evaluate the feasibility and impact of MS-SUPPORT on decisions about disease modifying treatments (DMTs), SDM processes, and quality-of-life. METHODS: This multisite randomized controlled trial compared the SDM intervention (MS-SUPPORT) to control (usual care) over a 12-month period. English-speaking adults with relapsing MS were eligible if they had an upcoming MS appointment and an email address. To evaluate clinician perspectives, participants' MS clinicians were invited to participate. Patients were referred between November 11, 2019 and October 23, 2020 by their MS clinician or a patient advocacy organization (the Multiple Sclerosis Association of America). MS-SUPPORT is an online, interactive, evidence-based decision aid that was co-created with pwMS. It clarifies patient treatment goals and values and provides tailored information about MS, DMTs, and adherence. Viewed by patients before their clinic appointment, MS-SUPPORT generates a personalized summary of the patient's treatment goals and preferences, adherence, DMT use, and clinical situation to share with their MS clinician. Outcomes (DMT utilization, adherence, quality-of-life, and SDM) were assessed at enrollment, post-MS-SUPPORT, post-appointment, and quarterly for 1 year. RESULTS: Participants included 501 adults with MS from across the USA (84.6% female, 83% white) and 34 of their MS clinicians (47% neurologists, 41% Nurse Practitioners, 12% Physician Assistants). Among the 203 patients who completed MS-SUPPORT, most (88.2%) reported they would recommend it to others and that it helped them talk to their doctor (85.2%), understand their options (82.3%) and the importance of taking DMTs as prescribed (82.3%). Among non-users of DMTs at baseline, the probability ratio of current DMT use consistently trended higher over one-year follow-up in the MS-SUPPORT group (1.30 [0.86-1.96]), as did the cumulative probability of starting a DMT within 6-months, with shorter time-to-start (46 vs 90 days, p=0.24). Among the 222 responses from 34 participating clinicians, more clinicians in the MS-SUPPORT group (vs control) trended towards recommending their patient start a DMT (9 of 108 (8%) vs 5 of 109 (5%), respectively, p=0.26). Adherence (no missed doses) to daily-dosed DMTs was higher in the MS-SUPPORT group (81.25% vs 56.41%, p=.026). Fewer patients forgot their doses (p=.046). The MS-SUPPORT group (vs control) reported 1.7 fewer days/month of poor mental health (p=0.02). CONCLUSIONS: MS-SUPPORT was strongly endorsed by patients and is feasible to use in clinical settings. MS-SUPPORT increased the short-term probability of taking and adhering to a DMT, and improved long-term mental health. Study limitations include selection bias, response bias, social desirability bias, and recall bias. Exploring approaches to reinforcement and monitoring its implementation in real-world settings should provide further insights into the value and utility of this new SDM tool.

Risk Factors for Opioid-Related Adverse Drug Events Among Older Adults After Hospitalization for Major Orthopedic Procedures.

OBJECTIVES: Older adults undergoing orthopedic procedures are commonly discharged from the hospital on opioids, but risk factors for postdischarge opioid-related adverse drug events (ORADEs) have not been previously examined. We aimed to identify risk factors for ORADEs after hospital discharge following orthopedic procedures. METHODS: This is a retrospective cohort study of a national sample of Medicare beneficiaries 65 years or older, who underwent major orthopedic surgery during hospitalization in 2016 and had an opioid fill within 2 days of discharge. We excluded beneficiaries with hospice claims and those admitted from or discharged to a facility. We used billing codes and medication claims to define potential ORADEs requiring a hospital revisit within 30 days of discharge. RESULTS: Among 30,514 hospitalizations with a major orthopedic procedure (89.7% arthroplasty, 5.6% treatment of fracture of dislocation, 4.7% other) and an opioid claim, a potential ORADE requiring hospital revisit occurred in 750 (2.5%). Independent risk factors included age of 80 years or older (hazard ratio [HR], 1.65; 95% confidence interval, 1.38-1.97), female sex (HR, 1.34 [1.16-1.56]), and clinical conditions, including heart failure (HR, 1.34 [1.10-1.62]), respiratory illness (HR, 1.23 [1.03-1.46]), kidney disease (HR, 1.23 [1.04-1.47]), dementia/delirium (HR, 1.63 [1.26-2.10]), anxiety disorder (HR, 1.42 [1.18-1.71]), and musculoskeletal/nervous system injuries (HR, 1.54 [1.24-1.90]). Prior opioid use, coprescribed sedating medications, and opioid prescription characteristics were not associated with ORADEs after adjustment for patient characteristics. CONCLUSIONS: Potential ORADEs occurred in 2.5% of older adults discharged with opioids after orthopedic surgery. These risk factors can inform clinician decision making, conversations with older adults, and targeting of harm reduction strategies.

Standing Blood Pressure and Risk of Falls, Syncope, Coronary Heart Disease, and Mortality.

BACKGROUND: ACC/AHA guidelines caution against the use of antihypertensive therapy in the setting of low standing systolic BP (SBP) < 110 mm Hg due to unclear benefits. METHODS: The Atherosclerosis Risk in Communities (ARIC) Study measured supine and standing SBP in adults aged 45-64 years between 1987 and 1989. We used Cox regression to evaluate the associations of low standing SBP (<110 mm Hg) with risk of falls, syncope, coronary heart disease (CHD), and mortality through December 31, 2019. Falls and syncope were ascertained by hospitalization and outpatient claims; CHD events were adjudicated. Associations were examined overall and in strata of hypertension stage, 10-year atherosclerotic cardiovascular disease (ASCVD) risk, age, and sex. RESULTS: Among 12,467 adults followed a median of 24 years (mean age at enrollment 54.1 ±â€…5.8 years, 55% women, 26% Black adults), 3,000 (24%) had a standing SBP < 110 mm Hg. A standing SBP < 110 mm Hg compared to standing SBP ≥ 110 mm Hg was not significantly associated with falls or syncope, and was associated with a lower risk of CHD events and mortality with HRs of 1.02 (95% CI 0.94, 1.11), 1.02 (0.93, 1.11), 0.88 (0.80, 0.97), and 0.91 (0.86, 0.97), respectively. There were no clinically meaningful differences when stratified by hypertension stage, 10-year ASCVD risk, age, and sex. CONCLUSIONS: In this community-based population, low standing SBP was common and not significantly associated with falls or syncope, but was associated with a lower risk of CHD and mortality. These findings do not support screening for low standing BP as a risk factor for adverse events.

Daily intranasal insulin at 40IU does not affect food intake and body composition: A placebo-controlled trial in older adults over a 24-week period with 24-weeks of follow-up.

Centrally administered insulin stimulates the reward system to reduce appetite in response to food intake in animal studies. In humans, studies have shown conflicting results, with some studies suggesting that intranasal insulin (INI) in relatively high doses may decrease appetite, body fat, and weight in various populations. These hypotheses have not been tested in a large longitudinal placebo-controlled study. Participants in the Memory Advancement with Intranasal Insulin in Type 2 Diabetes (MemAID) trial were enrolled in this study. This study on energy homeostasis enrolled 89 participants who completed baseline and at least 1 intervention visit (42 women; age 65 ± 9 years; 46 INI, 38 with type 2 diabetes) and 76 completed treatment (16 women, age 64 ± 9; 38 INI, 34 with type 2 diabetes). The primary outcome was the INI effect on food intake. Secondary outcomes included the effect of INI on appetite and anthropometric measures, including body weight and body composition. In exploratory analyses, we tested the interaction of treatment with gender, body mass index (BMI), and diagnosis of type 2 diabetes. There was no INI effect on food intake or any of the secondary outcomes. INI also showed no differential effect on primary and secondary outcomes when considering gender, BMI, and type 2 diabetes. INI did not alter appetite or hunger nor cause weight loss when used at 40 I.U. intranasally daily for 24 weeks in older adults with and without type 2 diabetes.

Six-Year Cognitive Trajectory in Older Adults Following Major Surgery and Delirium.

Importance: The study results suggest that delirium is the most common postoperative complication in older adults and is associated with poor outcomes, including long-term cognitive decline and incident dementia. Objective: To examine the patterns and pace of cognitive decline up to 72 months (6 years) in a cohort of older adults following delirium. Design, Setting, and Participants: This was a prospective, observational cohort study with long-term follow-up including 560 community-dwelling older adults (older than 70 years) in the ongoing Successful Aging after Elective Surgery study that began in 2010. The data were analyzed from 2021 to 2022. Exposure: Development of incident delirium following major elective surgery. Main Outcomes and Measures: Delirium was assessed daily during hospitalization using the Confusion Assessment Method, which was supplemented with medical record review. Cognitive performance using a comprehensive battery of neuropsychological tests was assessed preoperatively and across multiple points postoperatively to 72 months of follow-up. We evaluated longitudinal cognitive change using a composite measure of neuropsychological performance called the general cognitive performance (GCP), which is scaled so that 10 points on the GCP is equivalent to 1 population SD. Retest effects were adjusted using cognitive test results in a nonsurgical comparison group. Results: The 560 participants (326 women [58%]; mean [SD] age, 76.7 [5.2] years) provided a total of 2637 person-years of follow-up. One hundred thirty-four participants (24%) developed postoperative delirium. Cognitive change following surgery was complex: we found evidence for differences in acute, post-short-term, intermediate, and longer-term change from the time of surgery that were associated with the development of postoperative delirium. Long-term cognitive change, which was adjusted for practice and recovery effects, occurred at a pace of about -1.0 GCP units (95% CI, -1.1 to -0.9) per year (about 0.10 population SD units per year). Participants with delirium showed significantly faster long-term cognitive change with an additional -0.4 GCP units (95% CI, -0.1 to -0.7) or -1.4 units per year (about 0.14 population SD units per year). Conclusions and Relevance: This cohort study found that delirium was associated with a 40% acceleration in the slope of cognitive decline out to 72 months following elective surgery. Because this is an observational study, we cannot be sure whether delirium directly causes subsequent cognitive decline, or whether patients with preclinical brain disease are more likely to develop delirium. Future research is needed to understand the causal pathway between delirium and cognitive decline.

Partnering with patients and families living with chronic conditions to coproduce diagnostic safety through OurDX: a previsit online engagement tool.

OBJECTIVE: Patients and families are key partners in diagnosis, but methods to routinely engage them in diagnostic safety are lacking. Policy mandating patient access to electronic health information presents new opportunities. We tested a new online tool ("OurDX") that was codesigned with patients and families, to determine the types and frequencies of potential safety issues identified by patients/families with chronic health conditions and whether their contributions were integrated into the visit note. METHODS: Patients/families at 2 US healthcare sites were invited to contribute, through an online previsit survey: (1) visit priorities, (2) recent medical history/symptoms, and (3) potential diagnostic concerns. Two physicians reviewed patient-reported diagnostic concerns to verify and categorize diagnostic safety opportunities (DSOs). We conducted a chart review to determine whether patient contributions were integrated into the note. We used descriptive statistics to report implementation outcomes, verification of DSOs, and chart review findings. RESULTS: Participants completed OurDX reports in 7075 of 18 129 (39%) eligible pediatric subspecialty visits (site 1), and 460 of 706 (65%) eligible adult primary care visits (site 2). Among patients reporting diagnostic concerns, 63% were verified as probable DSOs. In total, probable DSOs were identified by 7.5% of pediatric and adult patients/families with underlying health conditions, respectively. The most common types of DSOs were patients/families not feeling heard; problems/delays with tests or referrals; and problems/delays with explanation or next steps. In chart review, most clinician notes included all or some patient/family priorities and patient-reported histories. CONCLUSIONS: OurDX can help engage patients and families living with chronic health conditions in diagnosis. Participating patients/families identified DSOs and most of their OurDX contributions were included in the visit note.

A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old.

BACKGROUND: Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women's breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women's individualized BC risk and life expectancy. METHODS: Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses' Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women's Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk. RESULTS: Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784-0.796) in NHS and 0.768 (0.757-0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538-0.641) in NHS and 0.573 (0.536-0.611) in BWHS. CONCLUSIONS: We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening.

Patterns and Persistence of Perioperative Plasma and Cerebrospinal Fluid Neuroinflammatory Protein Biomarkers After Elective Orthopedic Surgery Using SOMAscan.

BACKGROUND: The neuroinflammatory response to surgery can be characterized by peripheral acute plasma protein changes in blood, but corresponding, persisting alterations in cerebrospinal fluid (CSF) proteins remain mostly unknown. Using the SOMAscan assay, we define acute and longer-term proteome changes associated with surgery in plasma and CSF. We hypothesized that biological pathways identified by these proteins would be in the categories of neuroinflammation and neuronal function and define neuroinflammatory proteome changes associated with surgery in older patients. METHODS: SOMAscan analyzed 1305 proteins in blood plasma (n = 14) and CSF (n = 15) samples from older patients enrolled in the Role of Inflammation after Surgery for Elders (RISE) study undergoing elective hip and knee replacement surgery with spinal anesthesia. Systems biology analysis identified biological pathways enriched among the surgery-associated differentially expressed proteins in plasma and CSF. RESULTS: Comparison of postoperative day 1 (POD1) to preoperative (PREOP) plasma protein levels identified 343 proteins with postsurgical changes ( P < .05; absolute value of the fold change [|FC|] > 1.2). Comparing postoperative 1-month (PO1MO) plasma and CSF with PREOP identified 67 proteins in plasma and 79 proteins in CSF with altered levels ( P < .05; |FC| > 1.2). In plasma, 21 proteins, primarily linked to immune response and inflammation, were similarly changed at POD1 and PO1MO. Comparison of plasma to CSF at PO1MO identified 8 shared proteins. Comparison of plasma at POD1 to CSF at PO1MO identified a larger number, 15 proteins in common, most of which are regulated by interleukin-6 (IL-6) or transforming growth factor beta-1 (TGFB1) and linked to the inflammatory response. Of the 79 CSF PO1MO-specific proteins, many are involved in neuronal function and neuroinflammation. CONCLUSIONS: SOMAscan can characterize both short- and long-term surgery-induced protein alterations in plasma and CSF. Acute plasma protein changes at POD1 parallel changes in PO1MO CSF and suggest 15 potential biomarkers for longer-term neuroinflammation that warrant further investigation.