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.

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.

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.

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.

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.

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.

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.

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.

Obesity-Related Differences in Pathomechanism and Outcomes in Patients With HFpEF: A CMR Study.

Background: Clinical significance of an integrated evaluation of epicardial adipose tissue (EAT) and the right ventricle (RV) in heart failure with preserved ejection fraction (HFpEF) is unknown. Objectives: The authors investigated the potential of EAT and RV quantification for obesity-related pathophysiology and risk stratification in obese HFpEF patients using cardiovascular magnetic resonance (CMR). Methods: A total of 150 patients (obese, body mass index ≥30 kg/m2; n = 73, nonobese, body mass index <30 kg/m2; n = 77) with a clinical diagnosis of HFpEF undergoing CMR were retrospectively identified. EAT volume surrounding both ventricles were quantified with manual delineation on cine images. Total RV volume (TRVV) was calculated as the sum of RV cavity and mass at end-diastole. The endpoint was the composite of all-cause mortality and first HF hospitalization. Results: During a median follow-up of 46 months, 39 nonobese patients (51%) and 32 obese patients (44%) experienced the endpoint. EAT was a prognostic biomarker regardless of obesity and was independently correlated with TRVV. In obese HFpEF, EAT correlated with RV longitudinal strain (r = 0.32, P = 0.006), and increased amount of EAT and TRVV was associated with greater left ventricular end-diastolic eccentric index (r = 0.36, P = 0.002). The integration of RV quantification into EAT provided improved risk stratification with a C-statistic increase from 0.70 to 0.79 in obese HFpEF. Obese patients with EAT<130 ml and TRVV<180 ml had low risk (annual event rate 3.2%), while those with increased EAT ≥130 ml and TRVV ≥180 ml had significantly higher risk (annual event rate 11.8%; P < 0.001). Conclusions: CMR quantification of EAT and RV structure provides additive risk stratification for adverse outcomes in obese HFpEF.

Assessment of potential selection bias in neuroimaging studies of postoperative delirium and cognitive decline: lessons from the SAGES study.

Due to cost and participant burden, neuroimaging studies are often performed in relatively small samples of voluntary participants. This may lead to selection bias. It is important to identify factors associated with participation in neuroimaging studies and understand their effect on outcome measures. We investigated the effect of postoperative delirium on long-term (over 48 months) cognitive decline (LTCD) in 560 older surgical patients (≥ 70 years), including a nested MRI cohort (n = 146). We observed a discrepancy in the effect of delirium on cognitive decline as a function of MRI participation. Although overall difference in cognitive decline due to delirium was not greater than what might be expected due to chance (p = .21), in the non-MRI group delirium was associated with a faster pace of LTCD (-0.063, 95% CI -0.094 to -0.032, p < .001); while in the MRI group the effect of delirium was less and not significant (-0.023, 95% CI -0.076, 0.030, p = .39). Since this limits our ability to investigate the neural correlates of delirium and cognitive decline using MRI data, we attempted to mitigate the observed discrepancy using inverse probability weighting for MRI participation. The approach was not successful and the difference of the effect of delirium in slope was essentially unchanged. There was no evidence that the MRI sub-group experienced delirium that differed in severity relative to MRI non-participants. We could not attribute the observed discrepancy to selection bias based on measured factors. It may reflect a power issue due to the smaller MRI subsample or selection bias from unmeasured factors.

Proteome-Wide Analysis Using SOMAscan Identifies and Validates Chitinase-3-Like Protein 1 as a Risk and Disease Marker of Delirium Among Older Adults Undergoing Major Elective Surgery.

BACKGROUND: Delirium (an acute change in cognition) is a common, morbid, and costly syndrome seen primarily in aging adults. Despite increasing knowledge of its epidemiology, delirium remains a clinical diagnosis with no established biomarkers to guide diagnosis or management. Advances in proteomics now provide opportunities to identify novel markers of risk and disease progression for postoperative delirium and its associated long-term consequences (eg, long-term cognitive decline and Alzheimer's disease [AD]). METHODS: In a nested matched case-control study (18 delirium/no-delirium pairs) within the Successful Aging after Elective Surgery study (N = 556), we evaluated the association of 1305 plasma proteins preoperatively [PREOP] and on postoperative day 2 [POD2]) with delirium using SOMAscan. Generalized linear models were applied to enzyme-linked immunosorbant assay (ELISA) validation data of one protein across the full cohort. Multi-protein modeling included delirium biomarkers identified in prior work (C-reactive protein, interleukin-6 [IL6]). RESULTS: We identified chitinase-3-like-protein-1 (CHI3L1/YKL-40) as the sole delirium-associated protein in both a PREOP and a POD2 predictor model, a finding confirmed by ELISA. Multi-protein modeling found high PREOP CHI3L1/YKL-40 and POD2 IL6 increased the risk of delirium (relative risk [95% confidence interval] Quartile [Q]4 vs Q1: 2.4[1.2-5.0] and 2.1[1.1-4.1], respectively). CONCLUSIONS: Our identification of CHI3L1/YKL-40 in postoperative delirium parallels reports of CHI3L1/YKL-40 and its association with aging, mortality, and age-related conditions including AD onset and progression. This highlights the type 2 innate immune response, involving CHI3L1/YKL-40, as an underlying mechanism of postoperative delirium, a common, morbid, and costly syndrome that threatens the independence of older adults.

Comparative Implementation of a Brief App-Directed Protocol for Delirium Identification by Hospitalists, Nurses, and Nursing Assistants : A Cohort Study.

BACKGROUND: Systematic screening improves delirium identification among hospitalized older adults. Little data exist on how to implement such screening. OBJECTIVE: To test implementation of a brief app-directed protocol for delirium identification by physicians, nurses, and certified nursing assistants (CNAs) in real-world practice relative to a research reference standard delirium assessment (RSDA). DESIGN: Prospective cohort study. SETTING: Large urban academic medical center and small rural community hospital. PARTICIPANTS: 527 general medicine inpatients (mean age, 80 years; 35% with preexisting dementia) and 399 clinicians (53 hospitalists, 236 nurses, and 110 CNAs). MEASUREMENTS: On 2 study days, enrolled patients had an RSDA. Subsequently, CNAs performed an ultra-brief 2-item screen (UB-2) for delirium, whereas physicians and nurses performed a 2-step protocol consisting of the UB-2 followed in those with a positive screen result by the 3-Minute Diagnostic Assessment for the Confusion Assessment Method. RESULTS: Delirium was diagnosed in 154 of 924 RSDAs (17%) and in 114 of 527 patients (22%). The completion rate for clinician protocols exceeded 97%. The CNAs administered the UB-2 in a mean of 62 seconds (SD, 51). The 2-step protocols were administered in means of 104 seconds (SD, 99) by nurses and 106 seconds (SD, 105) by physicians. The UB-2 had sensitivities of 88% (95% CI, 72% to 96%), 87% (CI, 73% to 95%), and 82% (CI, 65% to 91%) when administered by CNAs, nurses, and physicians, respectively, with specificities of 64% to 70%. The 2-step protocol had overall accuracy of 89% (CI, 83% to 93%) and 87% (CI, 81% to 91%), with sensitivities of 65% (CI, 48% to 79%) and 63% (CI, 46% to 77%) and specificities of 93% (CI, 88% to 96%) and 91% (CI, 86% to 95%), for nurses and physicians, respectively. Two-step protocol sensitivity for moderate to severe delirium was 78% (CI, 54% to 91%). LIMITATION: Two sites; limited diversity. CONCLUSION: An app-directed protocol for delirium identification was feasible, brief, and accurate, and CNAs and nurses performed as well as hospitalists. PRIMARY FUNDING SOURCE: National Institute on Aging.

Plasma and cerebrospinal fluid inflammation and the blood-brain barrier in older surgical patients: the Role of Inflammation after Surgery for Elders (RISE) study.

BACKGROUND: Our understanding of the relationship between plasma and cerebrospinal fluid (CSF) remains limited, which poses an obstacle to the identification of blood-based markers of neuroinflammatory disorders. To better understand the relationship between peripheral and central nervous system (CNS) markers of inflammation before and after surgery, we aimed to examine whether surgery compromises the blood-brain barrier (BBB), evaluate postoperative changes in inflammatory markers, and assess the correlations between plasma and CSF levels of inflammation. METHODS: We examined the Role of Inflammation after Surgery for Elders (RISE) study of adults aged ≥ 65 who underwent elective hip or knee surgery under spinal anesthesia who had plasma and CSF samples collected at baseline and postoperative 1 month (PO1MO) (n = 29). Plasma and CSF levels of three inflammatory markers previously identified as increasing after surgery were measured using enzyme-linked immunosorbent assay: interleukin-6 (IL-6), C-reactive protein (CRP), and chitinase 3-like protein (also known as YKL-40). The integrity of the BBB was computed as the ratio of CSF/plasma albumin levels (Qalb). Mean Qalb and levels of inflammation were compared between baseline and PO1MO. Spearman correlation coefficients were used to determine the correlation between biofluids. RESULTS: Mean Qalb did not change between baseline and PO1MO. Mean plasma and CSF levels of CRP and plasma levels of YKL-40 and IL-6 were higher on PO1MO relative to baseline, with a disproportionally higher increase in CRP CSF levels relative to plasma levels (CRP tripled in CSF vs. increased 10% in plasma). Significant plasma-CSF correlations for CRP (baseline r = 0.70 and PO1MO r = 0.89, p < .01 for both) and IL-6 (PO1MO r = 0.48, p < .01) were observed, with higher correlations on PO1MO compared with baseline. CONCLUSIONS: In this elective surgical sample of older adults, BBB integrity was similar between baseline and PO1MO, plasma-CSF correlations were observed for CRP and IL-6, plasma levels of all three markers (CRP, IL-6, and YKL-40) increased from PREOP to PO1MO, and CSF levels of only CRP increased between the two time points. Our identification of potential promising plasma markers of inflammation in the CNS may facilitate the early identification of patients at greatest risk for neuroinflammation and its associated adverse cognitive outcomes.

Targeted metabolomics analysis of postoperative delirium.

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Identification of Plasma Proteome Signatures Associated With Surgery Using SOMAscan.

OBJECTIVES: To characterize the proteomic signature of surgery in older adults and association with postoperative outcomes. SUMMARY OF BACKGROUND DATA: Circulating plasma proteins can reflect the physiological response to and clinical outcomes after surgery. METHODS: Blood plasma from older adults undergoing elective surgery was analyzed for 1305 proteins using SOMAscan. Surgery-associated proteins underwent Ingenuity Pathways Analysis. Selected surgery-associated proteins were independently validated using Luminex or enzyme-linked immunosorbent assay methods. Generalized linear models estimated correlations with postoperative outcomes. RESULTS: Plasma from a subcohort (n = 36) of the Successful Aging after Elective Surgery (SAGES) study was used for SOMAscan. Systems biology analysis of 110 proteins with Benjamini-Hochberg (BH) corrected P value ≤0.01 and an absolute foldchange (|FC|) ≥1.5 between postoperative day 2 (POD2) and preoperative (PREOP) identified functional pathways with major effects on pro-inflammatory proteins. Chitinase-3-like protein 1 (CHI3L1), C-reactive protein (CRP), and interleukin-6 (IL-6) were independently validated in separate validation cohorts from SAGES (n = 150 for CRP, IL-6; n = 126 for CHI3L1). Foldchange CHI3L1 and IL-6 were associated with increased postoperative complications [relative risk (RR) 1.50, 95% confidence interval (95% CI) 1.21-1.85 and RR 1.63, 95% CI 1.18-2.26, respectively], length of stay (RR 1.35, 95% CI 0.77-1.92 and RR 0.98, 95% CI 0.52-1.45), and risk of discharge to postacute facility (RR 1.15, 95% CI 1.04-1.26 and RR 1.11, 95% CI 1.04-1.18); POD2 and PREOP CRP difference was associated with discharge to postacute facility (RR 1.14, 95% CI 1.04-1.25). CONCLUSION: SOMAscan can identify novel and clinically relevant surgery-induced protein changes. Ultimately, proteomics may provide insights about pathways by which surgical stress contributes to postoperative outcomes.

Efficacy of cognitive behavioral therapy for insomnia in breast cancer: A meta-analysis.

Insomnia is highly prevalent among patients with breast cancer (BC). Although cognitive behavioral therapy for insomnia (CBT-I) is available in integrative oncology settings, it poses unique challenges for BC survivors. Our review aimed to assess the evidence for the therapeutic effects of CBT-I on insomnia in BC. Randomized controlled trials (RCTs) that included patients/survivors with BC and insomnia, and at least one validated self-report measure of sleep quality were included in the review. Of the 14 included RCTs (total N = 1363), the most common components incorporated in CBT-I interventions were sleep hygiene, stimulus control and sleep restriction. Pooled effect sizes favored CBT-I at post-intervention (Hedges' g = -0.779, 95% CI = -0.949, -0.609), short-term follow-up (within six months, Hedges' g = -0.653, 95% CI = -0.808, -0.498), and long-term follow-up (12 mo, Hedges' g = -0.335, 95% CI = -0.532, -0.139). In sub-analyses, CBT-I had similar effect sizes regardless of potential modifiers (comparison design, delivery formats, etc.). As an integrative oncology intervention, CBT-I is efficacious for reducing insomnia and improving sleep quality in women treated for BC, with medium-to-large effect sizes that persist after intervention delivery ends. Given the variability in the CBT-I components tested in RCTs, future studies should investigate the optimal integration of CBT-I components for managing insomnia during BC survivorship.

The Growth Rate of Subsolid Lung Adenocarcinoma Nodules at Chest CT.

Background Confirming that subsolid adenocarcinomas show exponential growth is important because it would justify using volume doubling time to assess their growth. Purpose To test whether the growth of lung adenocarcinomas manifesting as subsolid nodules at chest CT is accurately represented by an exponential model. Materials and Methods Patients with lung adenocarcinomas manifesting as subsolid nodules surgically resected between January 2005 and May 2018, with three or more longitudinal CT examinations before resection, were retrospectively included. Overall volume (for all nodules) and solid component volume (for part-solid nodules) were measured over time. A linear mixed-effects model was used to identify the growth pattern (linear, exponential, quadratic, or power law) that best represented growth. The interactions between nodule growth and clinical, CT morphologic, and pathologic parameters were studied. Results Sixty-nine patients (mean age, 70 years ± 9 [standard deviation]; 48 women) with 74 lung adenocarcinomas were evaluated. Overall growth and solid component growth were better represented by an exponential model (adjusted R2 = 0.89 and 0.95, respectively) than by a quadratic model (r2 = 0.88 and 0.93, respectively), a linear model (r2 = 0.87 and 0.92, respectively), or a power law model (r2 = 0.82 and 0.93, respectively). Faster overall volume growth was associated with a history of lung cancer (P < .001), a baseline nodule volume less than 500 mm3 (P = .03), and histologic findings of invasive adenocarcinoma (P < .001). The median volume doubling time of noninvasive adenocarcinoma was significantly longer than that of invasive adenocarcinoma (939 days [interquartile range, 588-1563 days] vs 678 days [interquartile range, 392-916 days], respectively; P = .01). Conclusion The overall volume growth of adenocarcinomas manifesting as subsolid nodules at chest CT was best represented by an exponential model compared with the other tested models. This justifies the use of volume doubling time for the growth assessment of these nodules. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuriyama and Yanagawa in this issue.

Readiness, Availability and Utilization of Rural Vietnamese Health Facilities for Community Based Primary Care of Non-communicable Diseases: A CrossSectional Survey of 3 Provinces in Northern Vietnam.

BACKGROUND: Vietnam's network of commune health centers (CHCs) have historically managed acute infectious diseases and implemented national disease-specific vertical programs. Vietnam has undergone an epidemiological transition towards non-communicable diseases (NCDs). Limited data exist on Vietnamese CHC capacity to prevent, diagnose, and treat NCDs. In this paper, we assess NCD service readiness, availability, and utilization at rural CHCs in 3 provinces in northern Vietnam. METHODS: Between January 2014 and April 2014, we conducted a cross-sectional survey of a representative sample of 89 rural CHCs from 3 provinces. Our study outcomes included service readiness, availability of equipment and medications, and utilization for five NCD conditions: hypertension, diabetes, chronic pulmonary diseases, cancer, and mental illnesses. RESULTS: NCD service availability was limited, except for mental health. Only 25% of CHCs indicated that they conducted activities focused on NCD prevention. Patient utilization of CHCs was approximately 223 visits per month or 8 visits per day. We found a statistically significant difference (P<.05) for NCD service availability, medication availability and CHC utilization among the 3 provinces studied. CONCLUSION: This is the first multi-site study on NCD service availability in Vietnam and the first study in a mountainous region consisting predominately of ethnic minorities. Despite strong government support for NCD prevention and control, Vietnam's current network of CHCs has limited NCD service capacity.