Digital assessment of cognition in neurodegenerative disease: a data driven approach leveraging artificial intelligence.

Introduction: A rapid and reliable neuropsychological protocol is essential for the efficient assessment of neurocognitive constructs related to emergent neurodegenerative diseases. We developed an AI-assisted, digitally administered/scored neuropsychological protocol that can be remotely administered in ~10 min. This protocol assesses the requisite neurocognitive constructs associated with emergent neurodegenerative illnesses. Methods: The protocol was administered to 77 ambulatory care/memory clinic patients (56.40% women; 88.50% Caucasian). The protocol includes a 6-word version of the Philadelphia (repeatable) Verbal Learning Test [P(r)VLT], three trials of 5 digits backward from the Backwards Digit Span Test (BDST), and the "animal" fluency test. The protocol provides a comprehensive set of traditional "core" measures that are typically obtained through paper-and-pencil tests (i.e., serial list learning, immediate and delayed free recall, recognition hits, percent correct serial order backward digit span, and "animal" fluency output). Additionally, the protocol includes variables that quantify errors and detail the processes used in administering the tests. It also features two separate, norm-referenced summary scores specifically designed to measure executive control and memory. Results: Using four core measures, we used cluster analysis to classify participants into four groups: cognitively unimpaired (CU; n = 23), amnestic mild cognitive impairment (MCI; n = 17), dysexecutive MCI (n = 23), and dementia (n = 14). Subsequent analyses of error and process variables operationally defined key features of amnesia (i.e., rapid forgetting, extra-list intrusions, profligate responding to recognition foils); key features underlying reduced executive abilities (i.e., BDST items and dysexecutive errors); and the strength of the semantic association between successive responses on the "animal" fluency test. Executive and memory index scores effectively distinguished between all four groups. There was over 90% agreement between how cluster analysis of digitally obtained measures classified patients compared to classification using a traditional comprehensive neuropsychological protocol. The correlations between digitally obtained outcome variables and analogous paper/pencil measures were robust. Discussion: The digitally administered protocol demonstrated a capacity to identify patterns of impaired performance and classification similar to those observed with standard paper/pencil neuropsychological tests. The inclusion of both core measures and detailed error/process variables suggests that this protocol can detect subtle, nuanced signs of early emergent neurodegenerative illness efficiently and comprehensively.

Association Between Preoperative Anemia and Cognitive Function in a Large Cohort Study of Older Patients Undergoing Elective Surgery.

BACKGROUND: The etiology of anemia has tremendous overlap with the disease states responsible for cognitive decline. We used data from a perioperative database of older adults undergoing elective surgery with anesthesia to (1) examine relationships among preoperative anemia blood markers, preoperative screeners of cognitive function, and chronic disease status; and (2) examine the relationship of these factors with operative outcomes. The primary goal of this study was to investigate the association between preoperative anemia blood markers and cognition measured by a preoperative cognitive screener. Secondary goals were to (1) examine the relationship between preoperative anemia blood markers and chronic disease states (ie, American Society of Anesthesiologists [ASA] and frailty), and (2) investigate the relationship of preoperative anemia blood markers and cognition with operative outcomes (ie, discharge disposition, 1-year mortality, number of surgical complications, length of hospital stay, and length of intensive care unit [ICU] stay). METHODS: Data were collected at the University of Florida Health Shands Presurgical Center and the Perioperative Cognitive Anesthesia Network clinic within the electronic medical record. Patients 65 years of age or older were included if they had a preoperative hemoglobin (Hgb) value and a preoperative screening. Nonparametric methods were used for bivariate analysis. Logistic regression was used for the simultaneous examination of variables associated with nonhome discharge and 1-year mortality. Primary outcomes were discharge disposition and 1-year mortality. Secondary outcomes were number of surgical complications and length of hospital and ICU stay. RESULTS: Of 14,795 patients cognitively assessed, 8643 met the inclusion criteria. Of these, 26.7% were anemic, with 16.8%, 9.5%, and 0.4% having mild, moderate, and severe anemia, respectively. The Spearman correlation coefficient [95% confidence interval, CI] between the Hgb level and the clock drawing time (CDT) was -.15 [-.17 to -.13] (P < .0001) indicating that a lower Hgb level was associated with cognitive vulnerability. Hgb was also negatively correlated with the ASA physical status classification, patient Fried Frailty Index, and hospital and ICU length of stay. In the multivariable model, age, surgical service, ASA and Fried Frailty Index significantly predicted nonhome discharge. Furthermore, age, surgical service, ASA, Fried Frailty Index, and Hgb independently predicted death within 1 year of surgery. The odds of death, adjusted for ASA, Fried Frailty, and covariates, were 2.7 times higher for those in the mild anemic group compared to those who were not anemic (odds ratio [OR], 2.7, 95% CI, [2.1-3.5]). The odds of death, adjusted for ASA, Fried Frailty, and covariates, were 3.6 times higher for those in the moderate/severe anemic group compared to those who were not anemic (OR, 3.6, 95% CI, [2.7-4.9]). CONCLUSIONS: In this first medicine study, we established relationships among anemia, preoperative markers of frailty and cognition, and chronic disease states in a large cohort of older patients undergoing elective surgery in a large tertiary medical center. We found that anemia, cognitive vulnerability, and chronic health disease states predicted death within 1 year of surgery, and that these preoperative factors negatively contribute to surgical outcomes such as time in the ICU, length of hospital stay, nonhome discharge, and 1-year mortality. The World Health Organization (WHO) and many academic medical societies have urged the adoption of patient blood management (PBM) disciplines, yet anemia is not routinely optimized as a preoperative risk factor. Given the well-defined association between preoperative anemia and postoperative morbidity and mortality, performing elective surgery on an untreated anemic patient should be considered substandard care. With established safe and effective treatment regimens, iron deficiency anemia is a modifiable preoperative risk factor that should be addressed before elective surgery.

Cannabis Use and Inhalational Anesthesia Administration in Older Adults: A Propensity Matched Retrospective Cohort Study.

BACKGROUND: Cannabis use is associated with higher intravenous anesthetic administration. Similar data regarding inhalational anesthetics are limited. With rising cannabis use prevalence, understanding any potential relationship with inhalational anesthetic dosing is crucial. We compared average intraoperative isoflurane/sevoflurane minimum alveolar concentration equivalents between older adults with and without cannabis use. METHODS: The electronic health records of 22,476 surgical patients ≥65 years old at the University of Florida Health System between 2018-2020 were reviewed. The primary exposure was cannabis use within 60 days of surgery, determined via i) a previously published natural language processing algorithm applied to unstructured notes and ii) structured data, including International Classification of Disease codes for cannabis use disorders and poisoning by cannabis, laboratory cannabinoids screening results, and RxNorm codes. The primary outcome was the intraoperative time-weighted average of isoflurane/sevoflurane minimum alveolar concentration equivalents at one-minute resolution. No a priori minimally clinically important difference was established. Patients demonstrating cannabis use were matched 4:1 to non-cannabis use controls using a propensity score. RESULTS: Among 5,118 meeting inclusion criteria, 1,340 patients (268 cannabis users and 1,072 nonusers) remained after propensity score matching. The median and interquartile range (IQR) age was 69 (67, 73) years; 872 (65.0%) were male, and 1,143 (85.3%) were non-Hispanic White. The median (IQR) anesthesia duration was 175 (118, 268) minutes. After matching, all baseline characteristics were well-balanced by exposure. Cannabis users had statistically significantly higher average minimum alveolar concentrations than nonusers [mean±SD: 0.58±0.23 versus 0.54±0.22, respectively; mean difference=0.04; 95% confidence limits, 0.01 to 0.06; p=0.020]. CONCLUSION: Cannabis use was associated with administering statistically significantly higher inhalational anesthetic minimum alveolar concentration equivalents in older adults, but the clinical significance of this difference is unclear. These data do not support the hypothesis that cannabis users require clinically meaningfully higher inhalational anesthetics doses.

Cannabis use and acute postoperative pain outcomes in older adults: a propensity matched retrospective cohort study.

INTRODUCTION: Cannabis use is increasing among older adults, but its impact on postoperative pain outcomes remains unclear in this population. We examined the association between cannabis use and postoperative pain levels and opioid doses within 24 hours of surgery. METHODS: We conducted a propensity score-matched retrospective cohort study using electronic health records data of 22 476 older surgical patients with at least 24-hour hospital stays at University of Florida Health between 2018 and 2020. Of the original cohort, 2577 patients were eligible for propensity-score matching (1:3 cannabis user: non-user). Cannabis use status was determined via natural language processing of clinical notes within 60 days of surgery and structured data. The primary outcomes were average Defense and Veterans Pain Rating Scale (DVPRS) score and total oral morphine equivalents (OME) within 24 hours of surgery. RESULTS: 504 patients were included (126 cannabis users and 378 non-users). The median (IQR) age was 69 (65-72) years; 295 (58.53%) were male, and 442 (87.70%) were non-Hispanic white. Baseline characteristics were well balanced. Cannabis users had significantly higher average DVPRS scores (median (IQR): 4.68 (2.71-5.96) vs 3.88 (2.33, 5.17); difference=0.80; 95% confidence limit (CL), 0.19 to 1.36; p=0.01) and total OME (median (IQR): 42.50 (15.00-60.00) mg vs 30.00 (7.50-60.00) mg; difference=12.5 mg; 95% CL, 3.80 mg to 21.20 mg; p=0.02) than non-users within 24 hours of surgery. DISCUSSION: This study showed that cannabis use in older adults was associated with increased postoperative pain levels and opioid doses.

Leveraging AI to improve evidence synthesis in conservation.

Systematic evidence syntheses (systematic reviews and maps) summarize knowledge and are used to support decisions and policies in a variety of applied fields, from medicine and public health to biodiversity conservation. However, conducting these exercises in conservation is often expensive and slow, which can impede their use and hamper progress in addressing the current biodiversity crisis. With the explosive growth of large language models (LLMs) and other forms of artificial intelligence (AI), we discuss here the promise and perils associated with their use. We conclude that, when judiciously used, AI has the potential to speed up and hopefully improve the process of evidence synthesis, which can be particularly useful for underfunded applied fields, such as conservation science.

Dysexecutive difficulty and subtle everyday functional disabilities: the digital Trail Making Test.

Background: Digital neuropsychological tests reliably capture real-time, process-based behavior that traditional paper/pencil tests cannot detect, enabling earlier detection of neurodegenerative illness. We assessed relations between informant-based subtle and mild functional decline and process-based features extracted from the digital Trail Making Test-Part B (dTMT-B). Methods: A total of 321 community-dwelling participants (56.0% female) were assessed with the Functional Activities Questionnaire (FAQ) and the dTMT-B. Three FAQ groups were constructed: FAQ = 0 (unimpaired); FAQ = 1-4 (subtle impairment); FAQ = 5-8 (mild impairment). Results: Compared to the FAQ-unimpaired group, other groups required longer pauses inside target circles (p < 0.050) and produced more total pen strokes to complete the test (p < 0.016). FAQ-subtle participants required more time to complete the entire test (p < 0.002) and drew individual lines connecting successive target circles slower (p < 0.001) than FAQ-unimpaired participants. Lines connecting successive circle targets were less straight among FAQ-mild, compared to FAQ-unimpaired participants (p < 0.044). Using stepwise nominal regression (reference group = FAQ-unimpaired), pauses inside target circles classified other participants into their respective groups (p < 0.015, respectively). Factor analysis using six dTMT-B variables (oblique rotation) yielded a two-factor solution related to impaired motor/cognitive operations (48.96% variance explained) and faster more efficient motor/cognitive operations (28.88% variance explained). Conclusion: Digital assessment technology elegantly quantifies occult, nuanced behavior not previously appreciated, operationally defines critical underlying neurocognitive constructs related to functional abilities, and yields selected process-based scores that outperform traditional paper/pencil test scores for participant classification. When brought to scale, the dTMT-B test could be a sensitive tool to detect subtle-to-mild functional deficits in emergent neurodegenerative illnesses.

Environmental and sociocultural factors are associated with pain-related brain structure among diverse individuals with chronic musculoskeletal pain: intersectional considerations.

Chronic musculoskeletal pain including knee osteoarthritis (OA) is a leading cause of disability worldwide. Previous research indicates ethnic-race groups differ in the pain and functional limitations experienced with knee OA. However, when socioenvironmental factors are included in analyses, group differences in pain and function wane. Pain-related brain structures are another area where ethnic-race group differences have been observed. Environmental and sociocultural factors e.g., income, education, experiences of discrimination, and social support influence brain structures. We investigate if environmental and sociocultural factors reduce previously observed ethnic-race group differences in pain-related brain structures. Data were analyzed from 147 self-identified non-Hispanic black (NHB) and non-Hispanic white (NHW), middle and older aged adults with knee pain in the past month. Information collected included health and pain history, environmental and sociocultural resources, and brain imaging. The NHB adults were younger and reported lower income and education compared to their NHW peers. In hierarchical multiple regression models, sociocultural and environmental factors explained 6-37% of the variance in pain-related brain regions. Self-identified ethnicity-race provided an additional 4-13% of explanatory value in the amygdala, hippocampus, insula, bilateral primary somatosensory cortex, and thalamus. In the rostral/caudal anterior cingulate and dorsolateral prefrontal cortex, self-identified ethnicity-race was not a predictor after accounting for environmental, sociocultural, and demographic factors. Findings help to disentangle and identify some of the factors contributing to ethnic-race group disparities in pain-related brain structures. Numerous arrays of environmental and sociocultural factors remain to be investigated. Further, the differing sociodemographic representation of our NHB and NHW participants highlights the role for intersectional considerations in future research.

Continuous Glucose Monitoring in Older Adults: What We Know and What We Have Yet to Learn.

OBJECTIVE: To assess the growing use of continuous glucose monitoring (CGM) systems by older adults and explore additional areas integration that could benefit adults with frailty. BACKGROUND: The use of CGM devices has expanded rapidly in the last decade. This has been supported by substantial data showing significant benefit in glycemic metrics: hemoglobin A1c improvements, less hypoglycemia, and improved quality of life. However, sub-populations, such as older persons, exist where available data are limited. Furthermore, frail older adults represent a heterogeneous population with their own unique challenges to the management of diabetes. This group has some of the poorest outcomes related to the sequela of diabetes. For example, hypoglycemia resulting in significant morbidity and mortality is more frequent in older person with diabetes than in younger persons with diabetes. METHOD: We present a concise literature review on CGM use in the older adult as well as expand upon glycemic and nonglycemic benefits of CGM for patients, caregivers, and providers. Retrospective analysis of inpatient glycemic data of 16,935 older adults with Type 2 diabetes mellitus at Atrium Health Wake Forest Baptist indicated those with fraility managed with insulin or sulfonylurea had the highest rates of delirium (4.8%), hypoglycemia (3.5%), cardiovascular complications (20.2%) and ED visits/hospitalizatoins (49%). In addition, we address special consideration of specific situations including inpatient, palliative and long term care settings. CONCLUSION: This review article summarizes the available data for CGM use in older adults, discusses the benefits and obstacles with CGM use in this population, and identifies areas of future research needed for improved delivery of care to older persons with diabetes.

A Network Analysis of Digital Clock Drawing for Command and Copy Conditions.

Graphomotor and time-based variables from the digital Clock Drawing Test (dCDT) characterize cognitive functions. However, no prior publications have quantified the strength of the associations between digital clock variables as they are produced. We hypothesized that analysis of the production of clock features and their interrelationships, as suggested, will differ between the command and copy test conditions. Older adults aged 65+ completed a digital clock drawing to command and copy conditions. Using a Bayesian hill-climbing algorithm and bootstrapping (10,000 samples), we derived directed acyclic graphs (DAGs) to examine network structure for command and copy dCDT variables. Although the command condition showed moderate associations between variables (µ|ßz|= 0.34) relative to the copy condition (µ|ßz| = 0.25), the copy condition network had more connections (18/18 versus 15/18 command). Network connectivity across command and copy was most influenced by five of the 18 variables. The direction of dependencies followed the order of instructions better in the command condition network. Digitally acquired clock variables relate to one another but differ in network structure when derived from command or copy conditions. Continued analyses of clock drawing production should improve understanding of quintessential normal features to aid in early neurodegenerative disease detection.

Development of a Probabilistic Boolean network (PBN) to model intraoperative blood pressure management.

BACKGROUND: Blood pressure is a vital sign for organ perfusion that anesthesiologists measure and modulate during surgery. However, current decision-making processes rely heavily on clinicians' experience, which can lead to variability in treatment across surgeries. With the advent of machine learning, we can now create models to predict the outcomes of interventions and guide perioperative decision-making. The first step in this process involves translating the clinical decision-making process into a framework understood by an algorithm. Probabilistic Boolean networks (PBNs) provide an information-rich approach to this problem. A PBN trends toward a steady state, and its decisions are easily understood via its Boolean predictor functions. We hypothesize that a PBN can be developed that corrects hemodynamic instability in patients by selecting clinical interventions to maintain blood pressure within a given range. METHODS: Data on patients over the age of 65 undergoing surgery with general anesthesia from 2018 to 2020 were drawn from the UF Health PRECEDE data set with IRB approval (IRB201700747). Parameters examined included heart rate, blood pressure, and frequency of medications given 15 min after anesthetic induction and 15 min before awakening. The medication frequency data were truncated into a 66/33 split for the training and validation set used in the PBN. The model was coded using Python 3 and evaluated by comparing the frequency of medications chosen by the program to the values in the testing set via linear regression analysis. RESULTS: The network developed successfully models a hemodynamically unstable patient and corrects the imbalance by administering medications. This is evidenced by the model achieving a stable, steady state matrix in all iterations. However, the model's ability to emulate clinical drug selection was variable. It was successful with its use of vasodilator selection but struggled with the appropriate selection of vasopressors. CONCLUSIONS: The PBN has demonstrated the ability to choose appropriate interventions based on a patient's current vitals. Additional work must be done to have the network emulate the frequency at which drugs are selected from in clinical practice. In its current state, the model provides an understanding of how a PBN behaves in the context of correcting hemodynamic instability and can aid in developing more robust models in the future.

Olfactory misinformation provides refuge to palatable plants from mammalian browsing.

Mammalian herbivores browse palatable plants of ecological and economical value. Undesirable neighbours can reduce browsing to these plants by providing 'associational refuge', but they can also compete for resources. Here we recreated the informative odour emitted by undesirable plants. We then tested whether this odour could act as virtual neighbours, providing browsing refuge to palatable eucalyptus tree seedlings. We found that protection using this method was equivalent to protection provided by real plants. Palatable seedlings were 17-20 times more likely to be eaten by herbivores without virtual, or real, neighbours. Because many herbivores use plant odour to forage, virtual neighbours could provide a useful practical management approach to help protect valued plants.

Primary Adrenal Insufficiency due to Cryptococcus With Persistent Adrenal Enlargement and Insufficiency.

Background/Objective: Infiltrative fungal infections are an unusual cause of primary adrenal insufficiency (AI). Our objective is to present a long-term follow-up of a patient with AI due to cryptococcal adrenalitis. Case Report: A 47-year-old woman presented in January 2004, with 50-lb weight loss, nausea, emesis, and headache with diplopia. During the 6 months prior to her presentation the patient had multiple admissions for evaluation of recurrent nausea and emesis. Prior to the most recent of these admissions, the patient developed a headache; evaluation of her cerebrospinal fluid revealed the presence of Cryptococcus, and she was treated with a 2-week course of amphotericin B. Physical examination demonstrated a temperature of 101.1 °F, heart rate of 110 bpm, and blood pressure of 94/65 mm Hg. She appeared ill and was underweight with dry mucous membranes and photophobia. Laboratory tests revealed random cortisol of 0.5 µg per dL. CT imaging showed bilateral adrenal gland enlargement and fine needle aspiration of the adrenal gland revealed encapsulated budding yeast. Stress dose intravenous glucocorticoids were administered and switched to oral hydrocortisone and fludrocortisone because the patient clinically improved with a second course of amphotericin B. Further evaluation in 2017 revealed persistently enlarged adrenal glands, positive cryptococcus antigen, and low IgG levels. Discussion: Our literature review noted few publications of AI caused by disseminated cryptococcus with no long-term follow-up of these cases beyond a 1- to 4-year time frame. Conclusion: Patients with AI due to disseminated fungal infection need long-term follow-up to assess for resolution of adrenal enlargement and evaluation of immunocompromised status.

Using digital assessment technology to detect neuropsychological problems in primary care settings.

Introduction: Screening for neurocognitive impairment and psychological distress in ambulatory primary and specialty care medical settings is an increasing necessity. The Core Cognitive Evaluation™ (CCE) is administered/scored using an iPad, requires approximately 8 min, assesses 3- word free recall and clock drawing to command and copy, asks questions about lifestyle and health, and queries for psychological distress. This information is linked with patients' self- reported concerns about memory and their cardiovascular risks. Methods: A total of 199 ambulatory patients were screened with the CCE as part of their routine medical care. The CCE provides several summary indices, and scores on 44 individual digital clock variables across command and copy tests conditions. Results: Subjective memory concerns were endorsed by 41% of participants. Approximately 31% of participants reported psychological distress involving loneliness, anxiety, or depression. Patients with self-reported memory concerns scored lower on a combined delay 3- word/ clock drawing index (p < 0.016), the total summary clock drawing command/ copy score (p < 0.050), and clock drawing to command Drawing Efficiency (p < 0.036) and Simple and Complex Motor (p < 0.029) indices. Patients treated for diabetes and atherosclerotic cardiovascular disease (ASCVD) scored lower on selected CCE outcome measures (p < 0.035). Factor analyses suggest that approximately 10 underlying variables can explain digital clock drawing performance. Discussion: The CCE is a powerful neurocognitive assessment tool that is sensitive to patient's subjective concerns about possible decline in memory, mood symptoms, possible cognitive impairment, and cardiovascular risk. iPad administration ensures total reliability for test administration and scoring. The CCE is easily deployable in outpatient ambulatory primary care settings.

The Impact of Multimodal Prehabilitation on Patient-Reported Outcomes for a Frail Octogenarian Undergoing Multilevel Lumbar Spinal Fusion Surgery: A Case Report.

This case report presents the perioperative optimization pathway of a frail octogenarian who underwent multilevel lumbar spinal fusion surgery. This patient was enrolled in a multimodal prehabilitation program for frail older adults. The multimodal prehabilitation program includes preoperative interventions that prevent further decline in physiological functions before spine surgery. The program focuses on physical exercise, nutritional intervention, and pain neuroscience education. Six weeks postoperatively, clinical and patient-reported outcomes improved in the categories targeted by the preoperative interventions and surgery. This report suggests that prehabilitation is feasible for preoperatively optimizing frail older adults undergoing complex spine surgery.

Perioperative Extracellular Brain Free-Water Changes for Older Adults Electing Total Knee Arthroplasty with General versus Spinal Anesthesia: A Pilot Study.

BACKGROUND: Recent research shows that older adults electing to undergo total knee arthroplasty with general anesthesia have a pre- to postoperative acute increase in molecular free-water within their cerebral white matter. It is unknown if this change is similar for individuals who elect spinal anesthesia methods. OBJECTIVE: To explore white matter microstructural changes in a pilot sample of older adults undergoing total knee arthroplasty and receiving general or spinal anesthesia. METHODS: We assessed acute perioperative changes in brain white matter free-water in a limited number of older adults electing total knee arthroplasty under spinal anesthesia (n = 5) and matched groups of older adults who received general anesthesia (n = 5) or had no surgery (n = 5). Patterns of free-water changes were also compared in the larger group of older adults electing total knee arthroplasty under general anesthesia (n = 61) and older adults with chronic knee pain who received no surgical intervention (n = 65). RESULTS: Our pilot results suggest older adults receiving general anesthesia had pre- to post-surgery free-water increases extensively throughout their white matter whereas those receiving spinal anesthesia appeared to have less consistent free-water increases. CONCLUSIONS: Our pilot results possibly suggest different patterns of perioperative brain white matter free-water changes based on anesthetic approach. We recommend future, larger studies to further examine the effects of anesthetic approach on perioperative brain free-water. The results of our study have potential implications for acute and chronic cognitive changes, perioperative complications, neurodegenerative processes including Alzheimer's disease, and understanding neuroinflammation.

FaIRClocks: Fair and Interpretable Representation of the Clock Drawing Test for mitigating classifier bias against lower educational groups.

The clock drawing test (CDT) is a neuropsychological assessment tool to evaluate a patient's cognitive ability. In this study, we developed a Fair and Interpretable Representation of Clock drawing tests (FaIRClocks) to evaluate and mitigate bias against people with lower education while predicting their cognitive status. We represented clock drawings with a 10-dimensional latent embedding using Relevance Factor Variational Autoencoder (RF-VAE) network pretrained on publicly available clock drawings from the National Health and Aging Trends Study (NHATS) dataset. These embeddings were later fine-tuned for predicting three cognitive scores: the Mini-Mental State Examination (MMSE) total score, attention composite z-score (ATT-C), and memory composite z-score (MEM-C). The classifiers were initially tested to see their relative performance in patients with low education (<= 8 years) versus patients with higher education (> 8 years). Results indicated that the initial unweighted classifiers confounded lower education with cognitive impairment, resulting in a 100% type I error rate for this group. Thereby, the samples were re-weighted using multiple fairness metrics to achieve balanced performance. In summary, we report the FaIRClocks model, which a) can identify attention and memory deficits using clock drawings and b) exhibits identical performance between people with higher and lower education levels.

Environmental and sociocultural factors are associated with pain-related brain structure among diverse individuals with chronic musculoskeletal pain.

Chronic musculoskeletal pain is a leading cause of disability worldwide. Previous research indicates ethnic/race groups are disproportionately affected by chronic pain conditions. However, when considering socioenvironmental factors these disparities are no longer observed. Ethnic/race group differences have also been reported in pain-related brain structure. Given that environmental and sociocultural factors influence biology and health outcomes, this study aimed to investigate possible environmental and sociocultural contributions to structural differences in pain-related brain regions. A total of 147 non-Hispanic black and non-Hispanic white, middle and older aged adults with knee pain in the past month and a brain MRI are included in the analyses. Individuals also provided information specific to health and pain history and environmental and sociocultural resources. In hierarchical multiple regression models, sociocultural and environmental factors explained 6%-37% of the variance in thickness of pain-related brain regions, with seven of the eight brain regions being statistically significant. In the amygdala, hippocampus, insula, bilateral primary somatosensory cortex, and thalamus, ethnicity/race provided an additional 4%-13% of explanatory value. In the rostral/caudal anterior cingulate and dorsolateral prefrontal cortex, ethnicity/race was not a predictor after accounting for environmental, sociocultural, and other demographic measures. Findings inform health disparities research by elucidating the complexity of factors contributing to previously reported ethnicity/race group differences.

Elucidating individual differences in chronic pain and whole person health with allostatic load biomarkers.

Chronic pain is a stressor that affects whole person functioning. Persistent and prolonged activation of the body's stress systems without adequate recovery can result in measurable physiological and neurobiological dysregulation recognized as allostatic load. We and others have shown chronic pain is associated with measures of allostatic load including clinical biomarker composites, telomere length, and brain structures. Less is known regarding how different measures of allostatic load align. The purpose of the study was to evaluate relationships among two measures of allostatic load: a clinical composite and pain-related brain structures, pain, function, and socioenvironmental measures. Participants were non-Hispanic black and non-Hispanic white community-dwelling adults between 45 and 85 years old with knee pain. Data were from a brain MRI, questionnaires specific to pain, physical and psychosocial function, and a blood draw. Individuals with all measures for the clinical composite were included in the analysis (n = 175). Indicating higher allostatic load, higher levels of the clinical composite were associated with thinner insula cortices with trends for thinner inferior temporal lobes and dorsolateral prefrontal cortices (DLPFC). Higher allostatic load as measured by the clinical composite was associated with greater knee osteoarthritis pathology, pain disability, and lower physical function. Lower allostatic load as indicated by thicker insula cortices was associated with higher income and education, and greater physical functioning. Thicker insula and DLPFC were associated with a lower chronic pain stage. Multiple linear regression models with pain and socioenvironmental measures as the predictors were significant for the clinical composite, insular, and inferior temporal lobes. We replicate our previously reported bilateral temporal lobe group difference pattern and show that individuals with high chronic pain stage and greater socioenvironmental risk have a higher allostatic load as measured by the clinical composite compared to those individuals with high chronic pain stage and greater socioenvironmental buffers. Although brain structure differences are shown in individuals with chronic pain, brain MRIs are not yet clinically applicable. Our findings suggest that a clinical composite measure of allostatic load may help identify individuals with chronic pain who have biological vulnerabilities which increase the risk for poor health outcomes.