Reference values for leg effort during incremental cycle ergometry in non-trained healthy men and women, aged 19-85.

Heightened sensation of leg effort contributes importantly to poor exercise tolerance in patient populations. We aim to provide a sex- and age-adjusted frame of reference to judge symptom's normalcy across progressively higher exercise intensities during incremental exercise. Two-hundred and seventy-five non-trained subjects (130 men) aged 19-85 prospectively underwent incremental cycle ergometry. After establishing centiles-based norms for Borg leg effort scores (0-10 category-ratio scale) versus work rate, exponential loss function identified the centile that best quantified the symptom's severity individually. Peak O2 uptake and work rate (% predicted) were used to threshold gradually higher symptom intensity categories. Leg effort-work rate increased as a function of age; women typically reported higher scores at a given age, particularly in the younger groups (p < 0.05). For instance, "heavy" (5) scores at the 95th centile were reported at ~200 W (<40 years) and ~90 W (≥70 years) in men versus ~130 W and ~70 W in women, respectively. The following categories of leg effort severity were associated with progressively lower exercise capacity: ≤50th ("mild"), >50th to <75th ("moderate"), ≥75th to <95th ("severe"), and ≥ 95th ("very severe") (p < 0.05). Although most subjects reporting peak scores <5 were in "mild" range, higher scores were not predictive of the other categories (p > 0.05). This novel frame of reference for 0-10 Borg leg effort, which considers its cumulative burden across increasingly higher exercise intensities, might prove valuable to judging symptom's normalcy, quantifying its severity, and assessing the effects of interventions in clinical populations.

Exploratory pilot study to characterize the immune landscapes of malignant pleural effusions and their corresponding primary tumors from patients with breast carcinoma and lung adenocarcinoma.

INTRODUCTION: Malignant pleural effusion (MPE) is a frequent complication of advanced malignancies. In this pilot study, we characterized the immune landscapes of MPEs, compared them to their primary tumor (PT) samples from breast carcinoma (BC) and lung adenocarcinoma (LADC), and tested the utility of multiplexed image technology in cytological samples. MATERIALS AND METHODS: We evaluated the immune contexture of 6 BC and 5 LADC MPEs and their PTs using 3 multiplex immunofluorescence panels. We explored the associations between sample characteristics and pleural effusion-free survival. RESULTS: No MPE samples had positive programmed death-ligand 1 expression in malignant cells, although 3 of 11 PTs has positive programmed death-ligand 1 expression (more than 1% expression in malignant cells). Overall, in LADC samples, cluster of differentiation 3 (CD3)+ T cells and CD3+CD8+ cytotoxic T cells predominated (median percentages for MPEs versus PTs: 45.6% versus 40.7% and 4.7% versus 6.6%, respectively) compared with BC. CD68+ macrophages predominated in the BC samples (medians for MPEs 61.2% versus PTs for 57.1%) but not in the LADC samples. Generally in PTs, CD3+CD8+ forkhead box P3+ T cells and the median distances from the malignant cells to CD3+CD8+Ki67+ and CD3+ programmed cell death protein 1 + T cells correlated to earlier MPE after PT diagnosis. CONCLUSIONS: The immune cell phenotypes in the MPEs and PTs were similar within each cancer type but different between BC versus LADC. An MPE analysis can potentially be used as a substitute for a PT analysis, but an expanded study of this topic is essential.

Mindful awareness and resilience skills for adolescents (MARS-A): a mixed-methods study of a mindfulness-based intervention for a heterogeneous adolescent clinical population.

OBJECTIVES: Mindful Awareness and Resilience Skills for Adolescents (MARS-A) is a mindfulness-based intervention adapted for the adolescent population. While previous studies have explored the benefits of MARS-A in various single-diagnosis populations, the aim of this study was to assess MARS-A for a heterogenous clinical adolescent population with mental health and/or chronic diagnoses, focusing on the underlying suffering present in all these conditions rather than its effects on a single diagnosis itself. METHODS: Qualitative data was collected through interviews to understand post-intervention participant perspectives and experiences. Quantitative data was collected through measures to investigate preliminary secondary outcomes. RESULTS: After participating in MARS-A, participants reported qualitative benefits in enhanced well-being, including coping with difficult emotions and managing sleep and/or pain. Quantitative results showed a reduction in functional disability, psychological distress, perceived stress, and depressive symptoms; increase in positive affect; and benefit in coping with pain and chronic conditions. CONCLUSIONS: MARS-A shows great potential in a heterogeneous clinical adolescent population.

Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.

Purpose: Advances in artificial intelligence have enabled the development of predictive models for glaucoma. However, most work is single-center and uncertainty exists regarding the generalizability of such models. The purpose of this study was to build and evaluate machine learning (ML) approaches to predict glaucoma progression requiring surgery using data from a large multicenter consortium of electronic health records (EHR). Design: Cohort study. Participants: Thirty-six thousand five hundred forty-eight patients with glaucoma, as identified by International Classification of Diseases (ICD) codes from 6 academic eye centers participating in the Sight OUtcomes Research Collaborative (SOURCE). Methods: We developed ML models to predict whether patients with glaucoma would progress to glaucoma surgery in the coming year (identified by Current Procedural Terminology codes) using the following modeling approaches: (1) penalized logistic regression (lasso, ridge, and elastic net); (2) tree-based models (random forest, gradient boosted machines, and XGBoost), and (3) deep learning models. Model input features included demographics, diagnosis codes, medications, and clinical information (intraocular pressure, visual acuity, refractive status, and central corneal thickness) available from structured EHR data. One site was reserved as an "external site" test set (N = 1550); of the patients from the remaining sites, 10% each were randomly selected to be in development and test sets, with the remaining 27 999 reserved for model training. Main Outcome Measures: Evaluation metrics included area under the receiver operating characteristic curve (AUROC) on the test set and the external site. Results: Six thousand nineteen (16.5%) of 36 548 patients underwent glaucoma surgery. Overall, the AUROC ranged from 0.735 to 0.771 on the random test set and from 0.706 to 0.754 on the external test site, with the XGBoost and random forest model performing best, respectively. There was greatest performance decrease from the random test set to the external test site for the penalized regression models. Conclusions: Machine learning models developed using structured EHR data can reasonably predict whether glaucoma patients will need surgery, with reasonable generalizability to an external site. Additional research is needed to investigate the impact of protected class characteristics such as race or gender on model performance and fairness. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders.

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density-phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4-/CD8- double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.

Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.

PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may be used. We assessed whether natural language processing (NLP), as an alternative approach, could more accurately identify lens pathology. DESIGN: Database study comparing the accuracy of NLP versus ICD billing codes to properly identify lens pathology. METHODS: We developed an NLP algorithm capable of searching free-text lens exam data in the electronic health record (EHR) to identify the type(s) of cataract present, cataract density, presence of intraocular lenses, and other lens pathology. We applied our algorithm to 17.5 million lens exam records in the Sight Outcomes Research Collaborative (SOURCE) repository. We selected 4314 unique lens-exam entries and asked 11 clinicians to assess whether all pathology present in the entries had been correctly identified in the NLP algorithm output. The algorithm's sensitivity at accurately identifying lens pathology was compared with that of the ICD codes. RESULTS: The NLP algorithm correctly identified all lens pathology present in 4104 of the 4314 lens-exam entries (95.1%). For less common lens pathology, algorithm findings were corroborated by reviewing clinicians for 100% of mentions of pseudoexfoliation material and 99.7% for phimosis, subluxation, and synechia. Sensitivity at identifying lens pathology was better for NLP (0.98 [0.96-0.99] than for billing codes (0.49 [0.46-0.53]). CONCLUSIONS: Our NLP algorithm identifies and classifies lens abnormalities routinely documented by eye-care professionals with high accuracy. Such algorithms will help researchers to properly identify and classify ocular pathology, broadening the scope of feasible research using real-world data.

Mobile Critical Care Recovery Program for Survivors of Acute Respiratory Failure: A Randomized Clinical Trial.

Importance: Over 50% of Acute Respiratory Failure (ARF) survivors experience cognitive, physical, and psychological impairments that negatively impact their quality of life (QOL). Objective: To evaluate the efficacy of a post-intensive care unit (ICU) program, the Mobile Critical Care Recovery Program (m-CCRP) consisting of a nurse care coordinator supported by an interdisciplinary team, in improving the QOL of ARF survivors. Design, Setting, and Participants: This randomized clinical trial with concealed outcome assessments among ARF survivors was conducted from March 1, 2017, to April 30, 2022, with a 12-month follow-up. Patients were admitted to the ICU services of 4 Indiana hospitals (1 community, 1 county, 2 academic), affiliated with the Indiana University School of Medicine. Intervention: A 12-month nurse-led collaborative care intervention (m-CCRP) supported by an interdisciplinary group of clinicians (2 intensivists, 1 geriatrician, 1 ICU nurse, and 1 neuropsychologist) was compared with a telephone-based control. The intervention comprised longitudinal symptom monitoring coupled with nurse-delivered care protocols targeting cognition, physical function, personal care, mobility, sleep disturbances, pain, depression, anxiety, agitation or aggression, delusions or hallucinations, stress and physical health, legal and financial needs, and medication adherence. Main Outcomes and Measures: The primary outcome was QOL as measured by the 36-item Medical Outcomes Study Short Form Health Survey (SF-36) physical component summary (PCS) and mental component summary (MCS), with scores on each component ranging from 0-100, and higher scores indicating better health status. Results: In an intention-to-treat analysis among 466 ARF survivors (mean [SD] age, 56.1 [14.4] years; 250 [53.6%] female; 233 assigned to each group), the m-CCRP intervention for 12 months did not significantly improve the QOL compared with the control group (estimated difference in change from baseline between m-CCRP and control group: 1.61 [95% CI, -1.06 to 4.29] for SF-36 PCS; -2.50 [95% CI, -5.29 to 0.30] for SF-36 MCS. Compared with the control group, the rates of hospitalization were higher in the m-CCRP group (117 [50.2%] vs 95 [40.8%]; P = .04), whereas the 12-month mortality rates were not statistically significantly lower (24 [10.3%] vs 38 [16.3%]; P = .05). Conclusions and Relevance: Findings from this randomized clinical trial indicated that a nurse-led 12-month comprehensive interdisciplinary care intervention did not significantly improve the QOL of ARF survivors after ICU hospitalization. These results suggest that further research is needed to identify specific patient groups who could benefit from tailored post-ICU interventions. Trial Registration: ClinicalTrials.gov Identifier: NCT03053245.

Spatial transcriptomic patterns underlying amyloid-ß and tau pathology are associated with cognitive dysfunction in Alzheimer's disease.

Amyloid-ß (Aß) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aß and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aß (gene-to-Aß associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aß and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aß and the gene-to-tau associations. These findings may explain the discordance between regional Aß and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.

Risk factors for dementia in older intensive care unit (ICU) survivors.

INTRODUCTION: As the number of older intensive care unit (ICU) survivors grows, there is an urgent need to identify modifiable risk factors for post-ICU dementia. METHODS: We performed a secondary data analysis of 3144 ICU patients ≥ 50 years of age without a history of dementia or severe mental illness who were screened as part of the Pharmacological Management of Delirium (PMD) study. Delirium was assessed using the Confusion Assessment Method for the ICU. Dementia was identified using International Classification of Diseases Ninth and Tenth revision codes for dementia or prescription of anti-dementia medication. RESULTS: Average age (standard deviation) was 65.2 ± 9.5 years; 50.4% were female; and 37.3% were Black. Analyses identified stroke (adjusted hazard ratio [HR] 2.49; 95% confidence interval [CI: 1.52, 4.07], P < 0.001), and depression (adjusted HR 3.03; 95% CI [1.80, 5.10], P < 0.001) as post-ICU risk factors for dementia. DISCUSSION: Future studies will need to examine whether interventions targeting post-ICU stroke and depression can lower dementia incidence in ICU survivors. HIGHLIGHTS: Risk factors for post-intensive care unit (ICU) dementia were distinct from those of Alzheimer's disease. Cardiovascular risk factors were not associated with dementia in older ICU survivors. Post-ICU stroke was associated with a higher risk of dementia in older ICU survivors. Post-ICU depression was associated with a higher risk of dementia in older ICU survivors.

Impact of Type 2 diabetes mellitus and insulin use on progression to glaucoma surgery in primary open angle glaucoma.

PURPOSE: To investigate outcomes of primary open-angle glaucoma (POAG) patients with and without type 2 diabetes mellitus (T2DM). METHODS: Retrospective observational study using U.S. nationwide healthcare insurance claims database. Patients ≥40 years old with at least one HbA1c within one year of POAG diagnosis were included. Diabetic factors associated with POAG progression requiring glaucoma surgery were evaluated using multivariable Cox proportional hazards regression models adjusted for demographic, diabetic and glaucoma factors. T2DM diagnosis and use of either oral hypoglycaemic agents or insulin therapy were assessed in association with POAG progression requiring glaucoma surgery. RESULTS: 104,515 POAG patients were included, of which 70,315 (67%) had T2DM. The mean age was 68.9 years (Standard deviation 9.2) and 55% were female. Of those with T2DM, 93% were taking medication (65,468); 95% (62,412) taking oral hypoglycaemic agents, and 34% (22,028) were on insulin. In multivariable analyses, patients with T2DM had a higher hazard of requiring glaucoma surgery (Hazard ratio, HR 1.15, 95% CI 1.09-1.21, p < 0.001). Higher mean HbA1c was also a significant predictor of progression requiring glaucoma surgery (HR 1.02, 95% CI 1.01-1.03, p < 0.001). When evaluating only patients who were taking antidiabetic medication, after adjusting for confounders, insulin use was associated with a 1.20 higher hazard of requiring glaucoma surgery compared to oral hypoglycaemic agents (95% CI 1.14-1.27, p < 0.001), but when stratified by HbA1c, this effect was only significant for those with HbA1c > 7.5%. CONCLUSIONS: Higher baseline HbA1c, particularly in patients taking insulin may be associated with higher rates of glaucoma surgery in POAG.

Serum proteomic analysis in esophagectomy patients with postoperative delirium: A case-control study.

BACKGROUND: Postoperative delirium occurs in up to 80% of patients undergoing esophagectomy. We performed an exploratory proteomic analysis to identify protein pathways that may be associated with delirium post-esophagectomy. OBJECTIVES: Identify proteins associated with delirium and delirium severity in a younger and higher-risk surgical population. METHODS: We performed a case-control study using blood samples collected from patients enrolled in a negative, randomized, double-blind clinical trial. English speaking adults aged 18 years or older, undergoing esophagectomy, who had blood samples obtained were included. Cases were defined by a positive delirium screen after surgery while controls were patients with negative delirium assessments. Delirium was assessed using Richmond Agitation Sedation Scale and Confusion Assessment Method for the Intensive Care Unit, and delirium severity was assessed by Delirium Rating Scale-Revised-98. Blood samples were collected pre-operatively and on post-operative day 1, and discovery proteomic analysis was performed. Between-group differences in median abundance ratios were reported using Wilcoxon-Mann-Whitney Odds (WMWodds1) test. RESULTS: 52 (26 cases, 26 controls) patients were included in the study with a mean age of 64 (SD 9.6) years, 1.9% were females and 25% were African American. The median duration of delirium was 1 day (IQR: 1-2), and the median delirium/coma duration was 2.5 days (IQR: 2-4). Two proteins with greater relative abundance ratio in patients with delirium were: Coagulation factor IX (WMWodds: 1.89 95%CI: 1.0-4.2) and mannosyl-oligosaccharide 1,2-alpha-mannosidase (WMWodds: 2.4 95%CI: 1.03-9.9). Protein abundance ratios associated with mean delirium severity at postoperative day 1 were Complement C2 (Spearman rs = -0.31, 95%CI [-0.55, -0.02]) and Mannosyl-oligosaccharide 1,2-alpha-mannosidase (rs = 0.61, 95%CI = [0.29, 0.81]). CONCLUSIONS: We identified changes in proteins associated with coagulation, inflammation, and protein handling; larger, follow-up studies are needed to confirm our hypothesis-generating findings.

Automated Recognition of Visual Acuity Measurements in Ophthalmology Clinical Notes Using Deep Learning.

Purpose: Visual acuity (VA) is a critical component of the eye examination but is often only documented in electronic health records (EHRs) as unstructured free-text notes, making it challenging to use in research. This study aimed to improve on existing rule-based algorithms by developing and evaluating deep learning models to perform named entity recognition of different types of VA measurements and their lateralities from free-text ophthalmology notes: VA for each of the right and left eyes, with and without glasses correction, and with and without pinhole. Design: Cross-sectional study. Subjects: A total of 319 756 clinical notes with documented VA measurements from approximately 90 000 patients were included. Methods: The notes were split into train, validation, and test sets. Bidirectional Encoder Representations from Transformers (BERT) models were fine-tuned to identify VA measurements from the progress notes and included BERT models pretrained on biomedical literature (BioBERT), critical care EHR notes (ClinicalBERT), both (BlueBERT), and a lighter version of BERT with 40% fewer parameters (DistilBERT). A baseline rule-based algorithm was created to recognize the same VA entities to compare against BERT models. Main Outcome Measures: Model performance was evaluated on a held-out test set using microaveraged precision, recall, and F1 score for all entities. Results: On the human-annotated subset, BlueBERT achieved the best microaveraged F1 score (F1 = 0.92), followed by ClinicalBERT (F1 = 0.91), DistilBERT (F1 = 0.90), BioBERT (F1 = 0.84), and the baseline model (F1 = 0.83). Common errors included labeling VA in sections outside of the examination portion of the note, difficulties labeling current VA alongside a series of past VAs, and missing nonnumeric VAs. Conclusions: This study demonstrates that deep learning models are capable of identifying VA measurements from free-text ophthalmology notes with high precision and recall, achieving significant performance improvements over a rule-based algorithm. The ability to recognize VA from free-text notes would enable a more detailed characterization of ophthalmology patient cohorts and enhance the development of models to predict ophthalmology outcomes. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The Association Between Frailty and Visual Field Loss in US Adults.

PURPOSE: To describe the association between visual field loss and frailty in a nationally representative cohort of US adults. DESIGN: Retrospective cross-sectional study. METHODS: The cohort included adults 40 years or older with complete eye examination data from the 2005-2006 and 2007-2008 National Health and Nutrition Examination Surveys (NHANES). Visual field loss (VFL) was determined by frequency doubling technology and a 2-2-1 algorithm. A 36-item deficit accumulation-based frailty index was used to divide subjects into 4 categories of increasing frailty severity. RESULTS: Of the 4897 participants, 4402 (93.2%) had no VFL, 301 (4.1%) had unilateral VFL, and 194 (2.73%) had bilateral VFL. Within the sample, 2 subjects197 (53.1%) were categorized as non-frail, 1659 (31.3%) as vulnerable, 732 (11.3%) as mildly frail, and 312 (4.3%) as most frail. In multivariable models adjusted for demographics, visual acuity, and history of cataract surgery, subjects with unilateral VFL had higher adjusted odds of being in a more frail category (adjusted odds ratio [aOR], 2.07; 95% CI, 1.42-3.02) than subjects without VFL. Subjects with bilateral VFL also had higher odds of a more frail category compared to subjects without VFL (aOR, 1.74; 95% CI, 1.20-2.52). CONCLUSIONS: In the 2005-2008 NHANES adult population, VFL is associated with higher odds of frailty, independent of central visual acuity loss. Frail individuals may be more susceptible to diseases that can cause VFL, and/or VFL may predispose to frailty. Additional studies are needed to determine the directionality of this relationship and to assess potential interventions.

BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity.

The BrainAGE method is used to estimate biological brain age using structural neuroimaging. However, the stability of the model across different scan parameters and races/ethnicities has not been thoroughly investigated. Estimated brain age was compared within- and across- MRI field strength and across voxel sizes. Estimated brain age gap (BAG) was compared across demographically matched groups of different self-reported races and ethnicities in ADNI and IMAS cohorts. Longitudinal ComBat was used to correct for potential scanner effects. The brain age method was stable within field strength, but less stable across different field strengths. The method was stable across voxel sizes. There was a significant difference in BAG between races, but not ethnicities. Correction procedures are suggested to eliminate variation across scanner field strength while maintaining accurate brain age estimation. Further studies are warranted to determine the factors contributing to racial differences in BAG.

Prospective analysis of sleep characteristics, chronotype, and risk of breast cancer in the california teachers study.

PURPOSE: Poor sleep quality and evening chronotype were associated with increased risk of breast cancer in a previous retrospective study in the California Teachers Study (CTS). The present analysis examines these sleep factors prospectively in the same cohort of women. METHODS: From the CTS, we included 1,085 incident breast cancer cases and 38,470 cancer-free participants from 2012 through 2019. We calculated time at risk and used Cox proportional hazards regression models to estimate the hazard ratios (HRs) and control for risk factors such as age, race, body mass index, family history of breast cancer, and reproductive history. The sleep factors examined were quality, latency, duration, disturbance, and sleep medication use, based on a shortened version of the Pittsburgh Sleep Quality Index, as well as chronotype (preference for morning or evening activity). This analysis was limited to women who were post-menopausal at the time they answered these sleep-related questions. RESULTS: Measures of sleep quality did not appear to be associated with subsequent breast cancer risk. The HR for evening chronotypes compared to morning chronotypes was somewhat elevated (HR 1.19, 95% CI 1.04, 1.36). CONCLUSION: While the measures of sleep quality and duration were not associated with post-menopausal breast cancer risk in this prospective analysis, the modestly elevated risk observed for evening chronotypes was consistent with the prior retrospective analysis.

Social Determinants of Health and Perceived Barriers to Care in Diabetic Retinopathy Screening.

Importance: Regular screening for diabetic retinopathy often is crucial for the health of patients with diabetes. However, many factors may be barriers to regular screening and associated with disparities in screening rates. Objective: To evaluate the associations between visiting an eye care practitioner for diabetic retinopathy screening and factors related to overall health and social determinants of health, including socioeconomic status and health care access and utilization. Design, Setting, and Participants: This retrospective cross-sectional study included adults aged 18 years or older with type 2 diabetes who answered survey questions in the All of Us Research Program, a national multicenter cohort of patients contributing electronic health records and survey data, who were enrolled from May 1, 2018, to July 1, 2022. Exposures: The associations between visiting an eye care practitioner and (1) demographic and socioeconomic factors and (2) responses to the Health Care Access and Utilization, Social Determinants of Health, and Overall Health surveys were investigated using univariable and multivariable logistic regressions. Main Outcome and Measures: The primary outcome was whether patients self-reported visiting an eye care practitioner in the past 12 months. The associations between visiting an eye care practitioner and demographic and socioeconomic factors and responses to the Health Care Access and Utilization, Social Determinants of Health, and Overall Health surveys in All of Us were investigated using univariable and multivariable logistic regression. Results: Of the 11 551 included participants (54.55% cisgender women; mean [SD] age, 64.71 [11.82] years), 7983 (69.11%) self-reported visiting an eye care practitioner in the past year. Individuals who thought practitioner concordance was somewhat or very important were less likely to have seen an eye care practitioner (somewhat important: adjusted odds ratio [AOR], 0.83 [95% CI, 0.74-0.93]; very important: AOR, 0.85 [95% CI, 0.76-0.95]). Compared with financially stable participants, individuals with food or housing insecurity were less likely to visit an eye care practitioner (food insecurity: AOR, 0.75 [95% CI, 0.61-0.91]; housing insecurity: AOR, 0.86 [95% CI, 0.75-0.98]). Individuals who reported fair mental health were less likely to visit an eye care practitioner than were those who reported good mental health (AOR, 0.84; 95% CI, 0.74-0.96). Conclusions and Relevance: This study found that food insecurity, housing insecurity, mental health concerns, and the perceived importance of practitioner concordance were associated with a lower likelihood of receiving eye care. Such findings highlight the self-reported barriers to seeking care and the importance of taking steps to promote health equity.

Genetic hypogonadal mouse model reveals niche-specific influence of reproductive axis and sex on intestinal microbial communities.

BACKGROUND: The gut microbiome has been linked to many diseases with sex bias including autoimmune, metabolic, neurological, and reproductive disorders. While numerous studies report sex differences in fecal microbial communities, the role of the reproductive axis in this differentiation is unclear and it is unknown how sex differentiation affects microbial diversity in specific regions of the small and large intestine. METHODS: We used a genetic hypogonadal mouse model that does not produce sex steroids or go through puberty to investigate how sex and the reproductive axis impact bacterial diversity within the intestine. Using 16S rRNA gene sequencing, we analyzed alpha and beta diversity and taxonomic composition of fecal and intestinal communities from the lumen and mucosa of the duodenum, ileum, and cecum from adult female (n = 20) and male (n = 20) wild-type mice and female (n = 17) and male (n = 20) hypogonadal mice. RESULTS: Both sex and reproductive axis inactivation altered bacterial composition in an intestinal section and niche-specific manner. Hypogonadism was significantly associated with bacteria from the Bacteroidaceae, Eggerthellaceae, Muribaculaceae, and Rikenellaceae families, which have genes for bile acid metabolism and mucin degradation. Microbial balances between males and females and between hypogonadal and wild-type mice were also intestinal section-specific. In addition, we identified 3 bacterial genera (Escherichia Shigella, Lachnoclostridium, and Eggerthellaceae genus) with higher abundance in wild-type female mice throughout the intestinal tract compared to both wild-type male and hypogonadal female mice, indicating that activation of the reproductive axis leads to female-specific differentiation of the gut microbiome. Our results also implicated factors independent of the reproductive axis (i.e., sex chromosomes) in shaping sex differences in intestinal communities. Additionally, our detailed profile of intestinal communities showed that fecal samples do not reflect bacterial diversity in the small intestine. CONCLUSIONS: Our results indicate that sex differences in the gut microbiome are intestinal niche-specific and that sampling feces or the large intestine may miss significant sex effects in the small intestine. These results strongly support the need to consider both sex and reproductive status when studying the gut microbiome and while developing microbial-based therapies.

Microbial communities in the intestinal tract, known as the gut microbiome, regulate many critical aspects of host physiology. Previous studies have shown that the diversity of the gut microbiome differs between the sexes. There are also many diseases with a sex bias linked to the gut microbiome, including autoimmune, metabolic, neurological, and reproductive disorders. The gut microbiome differentiates during puberty, but it is unknown if the reproductive axis, the system responsible for sexual maturation and production of gonadal sex hormones, is critical for this process. Furthermore, since most studies use feces to examine the gut microbiome, it is unknown how sex influences the microbial communities within different segments of the small and large intestine. To address this gap in knowledge, we used DNA-based molecular methods to compare the intestinal-specific microbiomes of a mouse model with a genetically inactivated reproductive axis to that of wild-type mice. We found that both sex and the reproductive axis impacted gut microbial diversity in an intestinal section-specific manner. We also detected significant differences in intestinal microbial diversity between male and female mutant mice, suggesting that sex chromosome factors also affect the gut microbiome. We also showed that fecal samples were dissimilar to small intestine microbial communities, indicating that studies only sampling feces likely miss sex differences specific to the small intestine. Our results strongly support the need to consider both sex and reproductive status when studying the gut microbiome and while developing microbial-based therapies.

Associations of circulating saturated long-chain fatty acids with risk of mild cognitive impairment and Alzheimer's disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.

BACKGROUND: No study has examined the associations between peripheral saturated long-chain fatty acids (LCFAs) and conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). This study aimed to examine whether circulating saturated LCFAs are associated with both risks of incident MCI from cognitively normal (CN) participants and incident AD progressed from MCI in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. METHODS: We conducted analysis of data from older adults aged 55-90 years who were recruited at 63 sites across the USA and Canada. We examined associations between circulating saturated LCFAs (i.e., C14:0, C16:0, C18:0, C20:0) and risk for incident MCI in CN participants, and incident AD progressed from MCI. FINDINGS: 829 participants who were enrolled in ADNI-1 had data on plasma saturated LCFAs, of which 618 AD-free participants were included in our analysis (226 with normal cognition and 392 with MCI; 60.2% were men). Cox proportional-hazards models were used to account for time-to-event/censor with a 48-month follow-up period for the primary analysis. Other than C20:0, saturated LCFAs were associated with an increased risk for AD among participants with MCI at baseline (Hazard ratios (HRs) = 1.3 to 2.2, P = 0.0005 to 0.003 in fully-adjusted models). No association of C20:0 with risk of AD among participants with MCI was observed. No associations were observed between saturated LCFAs and risk for MCI among participants with normal cognition. INTERPRETATION: Saturated LCFAs are associated with increased risk of progressing from MCI to AD. This finding holds the potential to facilitate precision prevention of AD among patients with MCI. FUNDING: National Institutes of Health.

Association between Change in the peripheral biomarkers of inflammation, astrocyte activation, and neuroprotection at one week of critical illness and hospital mortality in patients with delirium: A prospective cohort study.

OBJECTIVE: In critically ill adults with delirium, biomarkers of systemic inflammation, astrocyte activation, neuroprotection, and systemic inflammation measured at one week of critical illness may be associated with mortality. DESIGN: Prospective observational study. SETTING: Intensive care unit (ICU). PATIENTS: 178 ICU patients with delirium, alive and remaining in ICU at one week. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Blood samples collected for a pair of previously published, negative, clinical trials were utilized. Samples were collected at study enrollment/ICU admission (Day 1 sample) and one week later (Day 8 sample), and analyzed for interleukins (IL)-6, 8, 10, Insulin-like Growth Factor (IGF), S100 Binding Protein (S100B), Tumor Necrosis Factor Alpha (TNF-A) and C-Reactive Protein (CRP). Delirium, delirium severity, and coma were assessed twice daily using Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), CAM-ICU-7, and Richmond Agitation-Sedation Scale (RASS), respectively. Mortality was assessed until discharge using the electronic medical record. Logistic regression models adjusting for age, sex, severity of illness, comorbidities, sepsis, and randomization status, were used to assess the relationship among biomarkers and mortality. Higher IL-10 quartiles at day 8 were associated with increased odds of hospital mortality (IL-10: OR 2.00 95%CI: 1.1-3.65, p = 0.023). There was a significant interaction between day 1 and day 8 biomarker quartiles only for IL-6. Patients with IL-6 values in the first three quartiles on admission to the ICU that transitioned to higher IL-6 quartiles at day 8 had increased probability of hospital mortality. CONCLUSION: In this hypothesis-generating study, higher IL-6 and IL-10 quartiles at one week, and increase in IL-6 from day 1 to day 8 were associated with increased hospital mortality. Studies with larger sample sizes are needed to confirm the mechanisms for these observations.