Patient-reported outcomes and patient-reported outcome measures in liver transplantation: a scoping review.

INTRODUCTION: Generic or condition-specific Patient-reported Outcome Measures (PROMs) are used to measure physical, mental, and social aspects of health to promote patient-centered care. This scoping review aims to identify and summarize generic and condition-specific PRO domains and PROMs that have been assessed and used in liver transplant (LT) candidates and recipients. METHODS: We searched Medline, Embase, Cochrane Database of Systematic Reviews and Register of Trials, PsychInfo, and CINAHL from inception to 08/26/2020. Included studies addressed a PRO or PROM in LT candidates or recipients. RESULTS: After screening, 341 studies yielded 189 unique PRO domains. Mental health domains (depression, anxiety, and guilt) were most frequently assessed, followed by domains of physical and social health. Fifty-one generic and three condition-specific unique PROMs were identified, with only 13% (n = 45) of studies including condition-specific tools. DISCUSSION: The most frequent PROMs were the SF-36, Nottingham Health Profile, Hospital Anxiety and Depression Scale, followed by the Liver Disease Quality of Life (LDQoL). Very few studies used transplant-specific PROMs, which may partly be related to the scarcity of LT-specific instruments. We will use these results in future qualitative research to identify PROs and PROMs to build an electronic PROM toolkit to facilitate patient-centered LT care.

Developing better digital health measures of Parkinson's disease using free living data and a crowdsourced data analysis challenge.

One of the promising opportunities of digital health is its potential to lead to more holistic understandings of diseases by interacting with the daily life of patients and through the collection of large amounts of real-world data. Validating and benchmarking indicators of disease severity in the home setting is difficult, however, given the large number of confounders present in the real world and the challenges in collecting ground truth data in the home. Here we leverage two datasets collected from patients with Parkinson's disease, which couples continuous wrist-worn accelerometer data with frequent symptom reports in the home setting, to develop digital biomarkers of symptom severity. Using these data, we performed a public benchmarking challenge in which participants were asked to build measures of severity across 3 symptoms (on/off medication, dyskinesia, and tremor). 42 teams participated and performance was improved over baseline models for each subchallenge. Additional ensemble modeling across submissions further improved performance, and the top models validated in a subset of patients whose symptoms were observed and rated by trained clinicians.

Parental Education and Left Lateral Orbitofrontal Cortical Activity during N-Back Task: An fMRI Study of American Adolescents.

Introduction. The Orbitofrontal Cortex (OFC) is a cortical structure that has implications in cognition, memory, reward anticipation, outcome evaluation, decision making, and learning. As such, OFC activity correlates with these cognitive brain abilities. Despite research suggesting race and socioeconomic status (SES) indicators such as parental education may be associated with OFC activity, limited knowledge exists on multiplicative effects of race and parental education on OFC activity and associated cognitive ability. Purpose. Using functional brain imaging data from the Adolescent Brain Cognitive Development (ABCD) study, we tested the multiplicative effects of race and parental education on left lateral OFC activity during an N-Back task. In our study, we used a sociological rather than biological theory that conceptualizes race and SES as proxies of access to the opportunity structure and exposure to social adversities rather than innate and non-modifiable brain differences. We explored racial variation in the effect of parental educational attainment, a primary indicator of SES, on left lateral OFC activity during an N-Back task between Black and White 9-10 years old adolescents. Methods. The ABCD study is a national, landmark, multi-center brain imaging investigation of American adolescents. The total sample was 4290 9-10 years old Black or White adolescents. The independent variables were SES indicators, namely family income, parental education, and neighborhood income. The primary outcome was the average beta weight for N-Back (2 back versus 0 back contrast) in ASEG ROI left OFC activity, measured by functional Magnetic Resonance Imaging (fMRI) during an N-Back task. Ethnicity, age, sex, subjective SES, and family structure were the study covariates. For data analysis, we used linear regression models. Results. In White but not Black adolescents, parental education was associated with higher left lateral OFC activity during the N-Back task. In the pooled sample, we found a significant interaction between race and parental education on the outcome, suggesting that high parental education is associated with a larger increase in left OFC activity of White than Black adolescents. Conclusions. For American adolescents, race and SES jointly influence left lateral OFC activity correlated with cognition, memory, decision making, and learning. Given the central role of left lateral OFC activity in learning and memory, our finding calls for additional research on contextual factors that reduce the gain of SES for Black adolescents. Cognitive inequalities are not merely due to the additive effects of race and SES but also its multiplicative effects.

Evaluation of PROMIS Preference Scoring System (PROPr) in Patients Undergoing Hemodialysis or Kidney Transplant.

BACKGROUND AND OBJECTIVES: A preference-based health utility score (PROPr) can be calculated using Patient-Reported Outcomes Measurement Information System domain scores. We assessed the construct validity of PROPr among patients treated with KRT (hemodialysis or kidney transplant). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We performed a secondary analysis of data collected in multicenter, cross-sectional studies of adults treated with KRT, recruited between April 2016 to March 2020 in Toronto, Canada. All participants provided informed consent. The outcome was the PROPr score. Coadministered outcome variables included the Short-Form Six-Domain (SF-6D) and EuroQol Five-Domain Five-Level (EQ-5D-5L) scores. Socioeconomic and clinical variables included age, sex, diabetes, eGFR, serum albumin, hemoglobin, KRT, and Charlson Comorbidity Index. Construct validity was assessed through correlations between PROPr and SF-6D or EQ-5D-5L, and associations between PROPr and other exposure variables. Health-condition impact estimates (coefficients for health conditions compared with a referent category, e.g., dialysis versus kidney transplant) were calculated using multivariable linear regression. RESULTS: The mean (SD) age of the 524 participants was 57 (17) years, 58% were male, and 45% were White. Median (interquartile range) score was 0.39 (0.24-0.58) for PROPr, 0.69 (0.58-0.86) for SF-6D, and 0.85 (0.70-0.91) for EQ-5D-5L. Large correlations were observed between PROPr versus SF-6D (0.79; 95% confidence interval [95% CI], 0.76 to 0.82) and EQ-5D-5L (0.71; 95% CI, 0.66 to 0.75). Both PROPr and the other utility indices demonstrated health-condition impact in the expected direction. For example, the estimate for PROPr was -0.17 (95% CI, -0.13 to -0.21) for dialysis (versus kidney transplant), -0.05 (95% CI, -0.11 to 0.01; P=0.08) for kidney transplant recipients with an eGFR of <45 versus ≥45 ml/min per 1.73 m2, and -0.28 (95% CI, -0.22 to -0.33) for moderate/severe versus no/mild depressive symptoms. CONCLUSIONS: Our results support the validity of PROPr among patients treated with KRT.

Outcomes With Ultrafiltration Among Hospitalized Patients With Acute Heart Failure (from the National Inpatient Sample).

Acute heart failure (HF) management is a complex and often involves a delicate balance of both cardiac and renal systems. Although pharmacologic diuresis is a mainstay of the pharmacologic management of decompensated HF, ultrafiltration (UF) represents a nonpharmacologic approach in the setting of diuretic resistance. We conducted a cross-sectional analysis of the 2009 through 2014 hospitalization data from the National Inpatient Sample. The study population consisted of hospitalizations with a discharge Diagnosis Related Groups of HF who were older than 18 years of age, did not have end-stage kidney disease, acute kidney injury and had not undergone hemodialysis or hemofiltration. There were 6,174 hospitalizations which included UF among the 7,799,915 hospitalizations for HF. Hospitalizations which included UF were among patients significantly younger in age (68.1 ± 1.0 vs 73.8 ± 0.1 years), male (61.9% vs 47.7%), and with higher prevalence of co-morbid conditions including chronic kidney disease (58% vs 31%), diabetes mellitus (53% vs 42%), and higher rates of co-morbidity (Charlson comorbidity score ≥2, 92% vs 80%). All-cause mortality was significantly higher among hospitalizations which included an UF (4.68% vs 2.24%). Hospitalizations with UF had a longer mean length of stay (6.2 vs 4.3 days, p <0.01) average total charges ($42,035 vs 24,867 USD, p <0.01) as compared with those without UF. Hospitalizations with UF were associated with a greater adjusted odds of all-cause mortality (odds ratio: 3.36, [95% confidence interval 1.76,6.40]), greater than DRG-level target length of stay (odds ratio, 2.46; [95 confidence interval 1.65,3.67]), and a 72% increase in the average hospital charges. In conclusion, hospitalizations which included UF identified a subgroup of HF patients with more co-morbid conditions who are at higher risk of mortality and increased resource burden in terms of length of stay and costs. These findings also highlight that the need for UF may identify patients who are most likely to benefit from a multidisciplinary cardiorenal approach to alter the trajectory of their disease.

Economic Strain Deteriorates While Education Fails to Protect Black Older Adults Against Depressive Symptoms, Pain, Self-rated Health, Chronic Disease, and Sick Days.

BACKGROUND: A large body of empirical evidence on Minorities' Diminished Returns (MDRs) suggests that educational attainment shows smaller health effects for Blacks compared to Whites. At the same time, economic strain may operate as a risk factor for a wide range of undesired mental and physical health outcomes in Black communities. AIM: The current study investigated the combined effects of education and economic strain on the following five health outcomes in Black older adults in underserved areas of South Los Angeles: depressive symptoms, number of chronic diseases, pain intensity, self-rated health, and sick days. METHODS: This cross-sectional study included 619 Black older adults residing in South Los Angeles. Data on demographic factors (age and gender), socioeconomic characteristics, economic strain, health insurance, living arrangement, marital status, health behaviors, depressive symptoms, pain intensity, number of chronic diseases, sick days, and self-rated health were collected. Five linear regressions were used to analyze the data. RESULTS: Although high education was associated with less economic strain, it was the economic strain, not educational attainment, which was universally associated with depressive symptoms, pain intensity, self-rated health, chronic diseases, and sick days, independent of covariates. Similar patterns emerged for all health outcomes suggesting that the risk associated with economic strain and lack of health gain due to educational attainment are both robust and independent of type of health outcome. CONCLUSION: In economically constrained urban environments, economic strain is a more salient social determinant of health of Black older adults than educational attainment. While education loses some of its protective effects, economic strain deteriorates health of Black population across domains. There is a need for bold economic and social policies that increase access of Black communities to cash at times of emergency. There is also a need to improve the education quality in the Black communities.

Diminished Returns of Educational Attainment on Heart Disease among Black Americans.

BACKGROUND: Socioeconomic Status (SES) indicators, such as educational attainment, are social determinants of heart disease. Marginalization related Diminished Returns (MDRs) refer to smaller health benefits of high SES for racial and ethnic minorities compared to the majority group. It is still unknown, however, if MDRs also apply to the effects of education on heart disease. PURPOSE: Using a nationally representative sample, we explored racial/ethnic variation in the link between educational attainment and heart disease among American adults. METHODS: We analyzed data (n=25,659) from a nationally representative survey of American adults in 2013. The first wave of the Population Assessment of Tobacco and Health - Adult (PATH-Adult) study was used. The independent variable was education (college graduate, high school graduate, less than a high school diploma). The dependent variable was any heart disease. Age and gender were the covariates. Race, as well as ethnicity, were the moderators. Logistic regressions were used to analyze the data. RESULTS: Individuals with higher educational attainment had lower odds of heart disease. Race and ethnicity showed statistically significant interactions with education, suggesting that the protective effect of higher education on reducing odds of heart disease was smaller for Hispanic and Black people than for non-Hispanic and White individuals. CONCLUSION: Education reduces the risk of heart disease better among non-Hispanic Whites than for Hispanics and Blacks. Therefore, we may expect a disproportionately higher than expected risk of heart disease in Hispanics and Blacks with high educational attainment. Future research should test if the presence of high levels of environmental and behavioral risk factors contribute to the high risk of heart disease in highly educated Black and Hispanic Americans. Policymakers should not reduce health inequalities to just gaps in SES because disparities are present across SES levels, with high SES Blacks and Hispanics remaining at risk of health problems.

Polypharmacy Is Associated with Lower Memory Function in African American Older Adults.

Although previous research has linked polypharmacy to lower cognitive function in the general population, we know little about this association among economically challenged African American (AA) older adults. This study explored the link between polypharmacy and memory function among AA older adults. This community-based study recruited 399 AA older adults who were 65+ years old and living in economically disadvantaged areas of South Los Angeles. Polypharmacy (taking 5+ medications) was the independent variable, memory function was the outcome variable (continuous variable), and gender, age, living arrangement, socioeconomic status (educational attainment and financial strain), health behaviors (current smoking and any binge drinking), and multimorbidity (number of chronic diseases) were the covariates. Linear regression was used for data analyses. Polypharmacy was associated with lower scores on memory function, above and beyond covariates. Among AA older adults, polypharmacy may be linked to worse cognitive function. Future research should test the mechanisms by which polypharmacy is associated with lower levels of cognitive decline. There is a need for screening for memory problems in AA older adults who are exposed to polypharmacy.

Regularization of Deep Neural Networks for EEG Seizure Detection to Mitigate Overfitting.

Seizure detection is a major goal for simplifying the workflow of clinicians working on EEG records. Current algorithms can only detect seizures effectively for patients already presented to the classifier. These algorithms are hard to generalize outside the initial training set without proper regularization and fail to capture seizures from the larger population. We proposed a data processing pipeline for seizure detection on an intra-patient dataset from the world's largest public EEG seizure corpus. We created spatially and session invariant features by forcing our networks to rely less on exact combinations of channels and signal amplitudes, but instead to learn dependencies towards seizure detection. For comparison, the baseline results without any additional regularization on a deep learning model achieved an F1 score of 0.544. By using random rearrangements of channels on each minibatch to force the network to generalize to other combinations of channels, we increased the F1 score to 0.629. By using random rescale of the data within a small range, we further increased the F1 score to 0.651 for our best model. Additionally, we applied adversarial multi-task learning and achieved similar results. We observed that session and patient specific dependencies were causing overfitting of deep neural networks, and the most overfitting models learnt features specific only to the EEG data presented. Thus, we created networks with regularization that the deep learning did not learn patient and session-specific features. We are the first to use random rearrangement, random rescale, and adversarial multitask learning to regularize intra-patient seizure detection and have increased sensitivity to 0.86 comparing to baseline study.

Prefrontal Cortex Response to Threat: Race by Age Variation in 9-10 Year Old Children.

BACKGROUND: Considerable research has suggested that race and age are two major determinants of brain development, including but not limited to development of the prefrontal cortex (PFC). Minorities' Diminished Returns (MDRs), however, suggests that race (as a proxy of racism) may interact with various determinants of human and brain development. Minimal knowledge, however, exists on whether age and race also interact on shaping PFC response to threat among American children. PURPOSE: Using data from a task-based functional brain imaging study and considering race as a sociological rather than a biological construct, we investigated combined effects of race and age on prefrontal cortical (PFC) response to threat. We explored racial heterogeneities in the association between age and PFC response to threat by comparing Black and White children. METHODS: This study used the task-based functional Magnetic Resonance Imaging (fMRI) data from the Adolescents Brain Cognitive Development (ABCD) study, a national, landmark, multi-center brain imaging investigation of 9-10 years old children in the US. The primary outcomes were mean beta weights of n-back runs measuring PFC response to threating versus neutral face contrast in the following regions of interest (ROIs): left hemisphere-lateral orbito-frontal, left hemisphere -superior-frontal, right hemisphere -caudal middle frontal, and right hemisphere -superior frontal cortex. The independent variable was age. Covariates were sex, ethnicity, family socioeconomic status, and neighborhood socioeconomic status. Race was the focal moderator. To analyze the data, we used linear regression models without and with interactions and SES as covariates. RESULTS: We included 5,066 9-10 years old children. Age and race did not show direct effects on PFC response to threatening relative to neutral faces. While ethnicity, sex, and socioeconomic status were controlled, age and race showed a systematic interaction on PFC response to threatening relative to neutral faces. CONCLUSIONS: For American children, race and age do not have direct effects but multiplicative effects on PFC response to threat. The results may be reflective of social inequalities in how Black and White children are socialized and developed. The results are important given the role of the PFC in regulating the limbic system response to threat. Coordinated work of the limbic system and PFC is a core element of children's behavioral and emotional development. Future research is needed on how social stratification and racism shape emotion processing and regulation of American children in response to threat.

Neuroticism polygenic risk score predicts 20-year burden of depressive symptoms for Whites but not Blacks.

Background: Black-White differences are reported in social, psychological, behavioral, medical, and biological correlates of depression. This study was conducted to compare Black and White older adults for the association between neuroticism polygenic risk score (N-PRS) and chronicity of depressive symptoms over 20 years. Methods: Data came from the Health and Retirement Study (HRS), 1990 - 2012, a nationally representative sample of Americans above age 50. Current analysis followed 9,249 individuals (7,924 Whites and 1,325 Blacks) for up to 22 years. Depressive symptoms were measured every two years between 1992 and 2012 using the 8-item Center for Epidemiological Studies-Depression Scale (CES-D-8). The independent variable was N-PRS. The dependent variable was average depressive symptoms between 1992 and 2012. Linear regression was used for data analysis. Results: In the pooled sample, higher N-PRS was associated with higher average depressive symptoms over the 20-year follow up period [b=0.01, 95%CI=0.00 to 0.04], net of all covariates. We also found an interaction between race and N-PRS [b=-0.02, 95%CI=-0.03 to 0.00], suggesting a stronger effect of N-PRS on 20-year average depressive symptoms for Whites than Blacks. Based on our race-specific linear regression models, higher N-PRS was associated with higher depressive symptoms from 1992 to 2012 for Whites [b=0.01, 95%CI=0.01 to 0.02] but not Blacks [b=0.00, 95%CI=-0.02 to 0.02]. Conclusion: Black and White older adults may differ in the salience of the existing N-PRS for depressive symptoms, which better reflects the burden of depression for Whites than Blacks. This may be because the existing PRSs are derived from mostly or exclusively White samples, limiting their applicability in other race groups. Racial variation in psychosocial, clinical, and biological correlates of depression needs further research.

Social Determinants of Polypharmacy in First Generation Mexican Immigrants in the United States.

INTRODUCTION: Socioeconomic status (SES) indicators are among the main social determinants of health and illness. Less, however, is known about the role of SES in the epidemiology of polypharmacy in immigrant Latino Americans living in the United States. This research studied the association between three SES indicators, education, income, and employment, and polypharmacy in older first generation Latino American immigrant adults. METHODS: Data was obtained from the Sacramento Area Latino Study on Aging (SALSA, 1996-2008). A total of 632 older first generation Mexican-American immigrants to the U.S. entered this analysis. The independent variables were education, income, and employment. Polypharmacy was the outcome. Age, gender, physical health, smoking, and drinking were the covariates. Binary logistic regression was used to analyze the data. RESULTS: Employment was associated with lower odds of polypharmacy. The association between education and polypharmacy was above and beyond demographic factors, physical health, health behaviors, and health insurance. Neither education nor income were associated with polypharmacy. Other determinants of polypharmacy were poor self-rated health (SRH) and a higher number of chronic medical conditions (CMCs). CONCLUSION: Employment appears to be the major SES determinant of polypharmacy in older foreign-born Mexican Americans. Unemployed older Mexican American immigrants with multiple chronic diseases and those who have poor SRH have the highest need for an evaluation of polypharmacy. Given the age group of this population, most of them have health insurance, which provides an opportunity for reducing their polypharmacy.

Binge Drinking among Economically Disadvantaged African American Older Adults with Diabetes.

Purpose. This study investigated the effect of demographic, socioeconomic, and psychological factors as well as the role of health determinants on alcohol consumption and binge drinking among economically disadvantaged African American older adults with type 2 diabetes mellites (T2DM). Methods. This survey recruited 231 African Americans who were older adults (age 65+ years) and had T2DM. Participants were selected from economically disadvantaged areas of South Los Angeles. A structured face-to-face interview was conducted to collect data on demographic factors, objective and subjective socioeconomic status (SES) including education and financial difficulty, living arrangement, marital status, health, and drinking behaviors (drinking and binge drinking). Results. Age, gender, living alone, pain, comorbid conditions, and smoking were associated with drinking/binge drinking. Male gender, pain, and being a smoker were associated with higher odds of drinking/binge drinking, while individuals with more comorbid medical conditions had lower odds of binge drinking. Conclusion. In economically constrained urban environments, gender, pain, and smoking but not age, SES, depression, and health may predict binge drinking for African American older adults with T2DM. African Americans older adult men with T2DM with comorbid pain should be screened for binge drinking.

Polypharmacy and Depressive Symptoms in U.S.-Born Mexican American Older Adults.

BACKGROUND: Although some studies have suggested a link between polypharmacy and poor mental health, less is known about the association between polypharmacy and depressive symptomology among U.S.-born older Mexican Americans. AIM: This study aimed to test the association between polypharmacy and depressive symptoms in U.S.-born older Latino Americans. MATERIALS AND METHODS: Data came from the Sacramento Area Latino Study on Aging (SALSA 2008). A total of 691 U.S.-born older (age >= 65) Mexican Americans entered this analysis. Polypharmacy was the independent variable. Level of depressive symptoms was the outcome. Age, gender, socioeconomic status (education, income, and employment), retirement status, health (chronic medical conditions, self-rated health, and activities of daily living), language, acculturation, and smoking were the covariates. A linear regression model was used to analyze the data. RESULTS: We found a positive association between polypharmacy and depressive symptoms, which was above and beyond demographic factors, socioeconomic status, physical health, health behaviors, language, acculturation, and health insurance. CONCLUSION: Polypharmacy is linked to depressive symptoms in U.S.-born older Mexican Americans. More research is needed to test the effects of reducing inappropriate polypharmacy on mental well-being of first and second generation older Mexican Americans. There is also a need to study the role of drug-drug interaction in explaining the observed link between polypharmacy and depressive symptoms.

Associations between Polypharmacy, Self-Rated Health, and Depression in African American Older Adults; Mediators and Moderators.

Background. Despite the prevalence of multimorbidity among African American (AA) older adults, little information exists on correlates of polypharmacy (using 5+ medications) in AA older adults. There is more information available regarding the link between polypharmacy and physical aspects of health than subjective ones. Aims. In a local sample of AA older adults in Los Angeles, this study investigated the association of polypharmacy with self-rated health (SRH) and depression. We also explored gender differences in these links. Methods. This community-based study was conducted in south Los Angeles. A total number of 708 AA older adults (age ≥ 55 years) were entered into this study. From this number, 253 were AA men and 455 were AA women. Polypharmacy was the independent variable. Self-rated health (SRH) and depression were the dependent variables. Age, educational attainment, financial difficulty (difficulty paying bills, etc.), and marital status were covariates. Gender was the moderator. Multimorbidity, measured as the number of chronic diseases (CDs), was the mediator. Logistic regressions were applied for data analysis. Results. Polypharmacy was associated with worse SRH and depression. Multimorbidity fully mediated the association between polypharmacy and depressive symptoms. Multimorbidity only partially mediated the association between polypharmacy and poor SRH. Gender moderated the association between polypharmacy and SRH, as polypharmacy was associated with poor SRH in women but not men. Gender did not alter the association between polypharmacy and depression. Conclusions. AA older women with polypharmacy experience worse SRH and depression, an association which is partially due to the underlying multimorbidity. There is a need for preventing inappropriate polypharmacy in AA older adults, particularly when addressing poor SRH and depression in AA older women with multimorbidity.

Early Prediction of Sepsis in EMR Records Using Traditional ML Techniques and Deep Learning LSTM Networks.

Sepsis is a life-threatening condition caused by infection and subsequent overreaction by the immune system. Physicians effectively treat sepsis with early administration of antibiotics. However, excessive use of antibiotics on false positive cases cultivates antibiotic resistant bacterial strains and can waste resources while false negative cases result in unacceptable mortality rates. Accurate early prediction ensures correct, early antibiotic treatment; unfortunately, prediction remains daunting due to error-ridden electronic medical records (EMRs) and the inherent complexity of sepsis. We aimed to predict sepsis using only the first 24 and 36 hours of lab results and vital signs for a patient. We used the Medical Information Mart for Intensive Care III (MIMIC3) dataset to test machine learning (ML) techniques including traditional methods (i.e., random forest (RF) and logistic regression (LR)) as well as deep learning techniques (i.e., long short-term memory (LSTM) neural networks). We successfully created a data pipeline to process and clean data, identified important predictive features using RF and LR techniques, and trained LSTM networks. We found that our best performing traditional classifier, RF, had an Area Under the Curve (AUC-ROC) score of 0.696, and our LSTM networks did not outperform RF.