Application of a data continuity prediction algorithm to an electronic health record-based pharmacoepidemiology study.

BACKGROUND AND OBJECTIVES: Use of algorithms to identify patients with high data-continuity in electronic health records (EHRs) may increase study validity. Practical experience with this approach remains limited. METHODS: We developed and validated four algorithms to identify patients with high data continuity in an EHR-based data source. Selected algorithms were then applied to a pharmacoepidemiologic study comparing rates of COVID-19 hospitalization in patients exposed to insulin versus noninsulin antidiabetic drugs. RESULTS: A model using a short list of five EHR-derived variables performed as well as more complex models to distinguish high- from low-data continuity patients. Higher data continuity was associated with more accurate ascertainment of key variables. In the pharmacoepidemiologic study, patients with higher data continuity had higher observed rates of the COVID-19 outcome and a large unadjusted association between insulin use and the outcome, but no association after propensity score adjustment. DISCUSSION: We found that a simple, portable algorithm to predict data continuity gave comparable performance to more complex methods. Use of the algorithm significantly impacted the results of an empirical study, with evidence of more valid results at higher levels of data continuity.

Leveraging home health aides to improve outcomes in heart failure: A pilot study protocol.

Heart failure (HF) affects six million people in the U.S., is associated with high morbidity, mortality, and healthcare utilization.(1, 2) Despite a decade of innovation, the majority of interventions aimed at reducing hospitalization and readmissions in HF have not been successful.(3-7) One reason may be that most have overlooked the role of home health aides and attendants (HHAs), who are often highly involved in HF care.(8-13) Despite their contributions, studies have found that HHAs lack specific HF training and have difficulty reaching their nursing supervisors when they need urgent help with their patients. Here we describe the protocol for a pilot randomized control trial (pRCT) assessing a novel stakeholder-engaged intervention that provides HHAs with a) HF training (enhanced usual care arm) and b) HF training plus a mobile health application that allows them to chat with a nurse in real-time (intervention arm). In collaboration with the VNS Health of New York, NY, we will conduct a single-site parallel arm pRCT with 104 participants (HHAs) to evaluate the feasibility, acceptability, and effectiveness (primary outcomes: HF knowledge; HF caregiving self-efficacy) of the intervention among HHAs caring for HF patients. We hypothesize that educating and better integrating HHAs into the care team can improve their ability to provide support for patients and outcomes for HF patients as well (exploratory outcomes include hospitalization, emergency department visits, and readmission). This study offers a novel and potentially scalable way to leverage the HHA workforce and improve the outcomes of the patients for whom they care. Clinical trial.gov registration: NCT04239911.

Association of Healthy Lifestyle and Incident Polypharmacy.

BACKGROUND: Polypharmacy, commonly defined as taking ≥5 medications, is an undesirable state associated with lower quality of life. Strategies to prevent polypharmacy may be an important priority for patients. We sought to examine the association of healthy lifestyle, a modifiable risk factor, with incident polypharmacy. METHODS: We performed a secondary analysis of the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study, including 15,478 adults aged ≥45 years without polypharmacy at baseline. The primary exposure was healthy lifestyle at baseline as measured by the Healthy Behavior Score (HBS), a cumulative assessment of diet, exercise frequency, tobacco smoking, and sedentary time. HBS ranges from 0-8, whereby 0-2 indicates low HBS, 3-5 indicates moderate HBS, and 6-8 indicates high HBS. We used multinomial logistic regression to examine the association between HBS and incident polypharmacy, survival without polypharmacy, and death. RESULTS: Higher HBS (i.e., healthier lifestyle) was inversely associated with incident polypharmacy after adjusting for sociodemographic and baseline health variables. Compared with participants with low HBS, those with moderate HBS had lower odds of incident polypharmacy (odds ratio [OR] 0.85; 95% confidence interval [CI], 0.73-0.98) and lower odds of dying (OR 0.74; 95% CI, 0.65-0.83). Participants with high HBS had even lower odds of both incident polypharmacy (OR 0.75; 95% CI, 0.64-0.88) and death (OR 0.62; 95% CI, 0.54-0.70). There was an interaction for age, where the association between HBS and incident polypharmacy was most pronounced for participants aged ≤65 years. CONCLUSIONS: Healthier lifestyle was associated with lower risk for incident polypharmacy.

Risk Prediction for Atherosclerotic Cardiovascular Disease With and Without Race Stratification.

Importance: Use of race-specific risk prediction in clinical medicine is being questioned. Yet, the most commonly used prediction tool for atherosclerotic cardiovascular disease (ASCVD)-pooled cohort risk equations (PCEs)-uses race stratification. Objective: To quantify the incremental value of race-specific PCEs and determine whether adding social determinants of health (SDOH) instead of race improves model performance. Design, Setting, and Participants: Included in this analysis were participants from the biracial Reasons for Geographic and Racial Differences in Stroke (REGARDS) prospective cohort study. Participants were aged 45 to 79 years, without ASCVD, and with low-density lipoprotein cholesterol level of 70 to 189 mg/dL or non-high-density lipoprotein cholesterol level of 100 to 219 mg/dL at baseline during the period of 2003 to 2007. Participants were followed up to 10 years for incident ASCVD, including myocardial infarction, coronary heart disease death, and fatal and nonfatal stroke. Study data were analyzed from July 2022 to February 2023. Main outcome/measures: Discrimination (C statistic, Net Reclassification Index [NRI]), and calibration (plots, Nam D'Agostino test statistic comparing observed to predicted events) were assessed for the original PCE, then for a set of best-fit, race-stratified equations including the same variables as in the PCE (model C), best-fit equations without race stratification (model D), and best-fit equations without race stratification but including SDOH as covariates (model E). Results: This study included 11 638 participants (mean [SD] age, 61.8 [8.3] years; 6764 female [58.1%]) from the REGARDS cohort. Across all strata (Black female, Black male, White female, and White male participants), C statistics did not change substantively compared with model C (Black female, 0.71; 95% CI, 0.68-0.75; Black male, 0.68; 95% CI, 0.64-0.73; White female, 0.77; 95% CI, 0.74-0.81; White male, 0.68; 95% CI, 0.64-0.71), in model D (Black female, 0.71; 95% CI, 0.67-0.75; Black male, 0.68; 95% CI, 0.63-0.72; White female, 0.76; 95% CI, 0.73-0.80; White male, 0.68; 95% CI, 0.65-0.71), or in model E (Black female, 0.72; 95% CI, 0.68-0.76; Black male, 0.68; 95% CI, 0.64-0.72; White female, 0.77; 95% CI, 0.74-0.80; White male, 0.68; 95% CI, 0.65-0.71). Comparing model D with E using the NRI showed a net percentage decline in the correct assignment to higher risk for male but not female individuals. The Nam D'Agostino test was not significant for all race-sex strata in each model series, indicating good calibration in all groups. Conclusions: Results of this cohort study suggest that PCE performed well overall but had poorer performance in both BM and WM participants compared with female participants regardless of race in the REGARDS cohort. Removal of race or the addition of SDOH did not improve model performance in any subgroup.

Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning.

BACKGROUND: Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory. METHOD: One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics. RESULTS: Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model. CONCLUSIONS: Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Improved outcomes for depressed elder abuse victims with video-delivered psychotherapy during COVID-19.

OBJECTIVE: There is a lack of evidence-based scalable therapies for elder abuse victims, with no current remotely delivered tailored psychotherapy. The purpose of this manuscript is to (a) examine the effectiveness of a brief therapy for depression for elder abuse victims, and (b) to compare remote intervention delivery via phone or video to the traditional in-person delivery. METHOD: PROTECT, Providing Options to Elderly Clients Together, is a brief therapy developed in collaboration with partners at the Department for the Aging (DFTA) of New York City. During the COVID-19 outbreak, PROTECT delivery shifted from in-person to phone or video delivery. Depression severity was tracked using the Patient Health Questionaire-9 (PHQ-9). Reduction in depression severity was evaluated using a linear mixed effects model with non-inferiority test to compare the effectiveness of video vs in-person delivery of PROTECT. RESULTS: PROTECT reduced depression (average 5.15 PHQ-9 points). Video and phone delivery were non-inferior to in-person delivery. The video group completed therapy more quickly than the in-person group and had a more rapid improvement in depression symptoms. CONCLUSIONS: PROTECT therapy delivered remotely reduces depression among diverse elder abuse victims. Video delivery of PROTECT could increase reach and scalability to serve more vulnerable older depressed victims.

Effects of Geography on Risk for Future Suicidal Ideation and Attempts Among Children and Youth.

Objective: Geography may influence the relationships of predictors for suicidal ideation (SI) and suicide attempts (SA) in children and youth. Method: This is a nationwide retrospective cohort study of 124,424 individuals less than 25 years of age using commercial claims data (2011-2015) from the Health Care Cost Institute. Outcomes were time to SI or SA within 3 months after the indexed mental health or substance use disorder (MH/SUD) outpatient visit. Predictors included sociodemographic and clinical characteristics up to 3 years before the index event. Results: At each follow-up time period, rates of SI and SA varied by the US geographic division (p < .001), and the Mountain Division consistently had the highest rates for both SI and SA (5.44%-10.26% for SI; 0.70%-2.82% for SA). Having MH emergency department (ED) visits in the past year increased the risk of SI by 28% to 65% for individuals residing in the New England, Mid-Atlantic, East North Central, West North Central, and East South Central Divisions. The main effects of geographic divisions were significant for SA (p<0.001). Risk of SA was lower in New England, Mid-Atlantic, South Atlantic, and Pacific (hazard ratios = 0.57, 0.51, 0.67, and 0.79, respectively) and higher in the Mountain Division (hazard ratio = 1.46). Conclusion: To understand the underlying mechanisms driving the high prevalence of SI and SA in the Mountain Division and the elevated risk of SI after having MH ED visits, future research examining regional differences in risks for SI and SA should include indicators of access to MH ED care and other social determinants of health.

Longitudinal Trajectories of Symptom Change During Antidepressant Treatment Among Managed Care Patients with Co-Occurring Depression and Anxiety.

Depression and anxiety are highly correlated, yet little is known about the course of each condition when presenting concurrently. This study aimed to identify longitudinal patterns and changes in depression and anxiety symptoms during antidepressant treatment, and evaluate clinical factors associated with each response pattern. Self-report Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7) scores were used to track the courses of depression and anxiety respectively over a three-month window, and group-based trajectory modeling was used to derive subgroups of patients who have similar response patterns. Multinomial regression was used to associate various clinical variables with trajectory subgroup membership. Of the 577 included adults, 373 (64.6%) were women, and the mean age was 39.3 (SD: 12.9) years. Six depression and six anxiety trajectory subgroups were computationally derived; three depression subgroups demonstrated symptom improvement, and three exhibited nonresponse. Similar patterns were observed in the six anxiety subgroups. Factors associated with treatment nonresponse included higher pretreatment depression and anxiety severity and poorer sleep quality, while better overall health and younger age were associated with higher rates of remission. Synchronous and asynchronous paths to improvement were also observed between depression and anxiety. High baseline depression or anxiety severity alone may be an insufficient predictor of treatment nonresponse. These findings have the potential to motivate clinical strategies aimed at treating depression and anxiety simultaneously.

Allostatic load and incident heart failure in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study.

BACKGROUND: Allostatic load (AL) is the physiologic "wear and tear" on the body from stress. Yet, despite stress being implicated in the development heart failure (HF), it is unknown whether AL is associated with incident HF events. METHODS: We examined 16,765 participants without HF at baseline from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. The main exposure was AL score quartile. AL was determined according to 11 physiologic parameters, whereby each parameter was assigned points (0-3) based on quartiles within the sample, and points were summed to create a total AL score ranging from 0-33. The outcome was incident HF event. We examined the association between AL quartile (Q1-Q4) and incident HF events using Cox proportional hazards models, adjusted for demographics, socioeconomic factors, and lifestyle. RESULTS: The mean age was 64 ± 9.6 years, 61.5% were women, and 38.7% were Black participants. Over a median follow up of 11.4 years, we observed 750 incident HF events (635 HF hospitalizations and 115 HF deaths). Compared to the lowest AL quartile (Q1), the fully adjusted hazards of an incident HF event increased in a graded fashion: Q2 HR 1.49 95% CI 1.12-1.98; Q3 HR 2.47 95% CI 1.89-3.23; Q4 HR 4.28 95% CI 3.28-5.59. The HRs for incident HF event in the fully adjusted model that also adjusted for CAD were attenuated, but remained significant and increased in a similar, graded fashion by AL quartile. There was a significant age interaction (p-for-interaction < 0.001), whereby the associations were observed across each age stratum, but the HRs were highest among those aged < 65 years. CONCLUSION: AL was associated with incident HF events, suggesting that AL could be an important risk factor and potential target for future interventions to prevent HF.

Disparities in Guideline Concordant Statin Treatment in Individuals With Chronic Obstructive Pulmonary Disease.

Rationale: Cardiovascular disease (CVD) affects the prognosis of patients with chronic obstructive pulmonary disease (COPD). Black women with COPD have a disproportionate risk of CVD-related mortality, yet disparities in CVD prevention in COPD are unknown. Objectives: We aimed to identify race-sex differences in the receipt of statin treatment for CVD prevention, and whether these differences were explained by factors influencing health care utilization in the REasons for Geographic And Racial Differences in Stroke (REGARDS) COPD study sub-cohort. Methods: We conducted a cross-sectional analysis among REGARDS Medicare beneficiaries with COPD. Our primary outcome was the presence of statin on in-home pill bottle review among individuals with an indication. Prevalence ratios (PR) for statin treatment among race-sex groups compared to White men were estimated using Poisson regression with robust variance. We then adjusted for covariates previously shown to impact health care utilization. Results: Of the 2032 members within the COPD sub-cohort with sufficient data, 1435 participants (19% Black women, 14% Black men, 28% White women, and 39% White men) had a statin indication. All race-sex groups were less likely to receive statins than White men in unadjusted models. After adjusting for covariates that influence health care utilization, Black women (PR 0.76, 95% confidence interval [CI] 0.67 to 0.86) and White women (PR 0.84 95% CI 0.76 to 0.91) remained less likely to be treated compared to White men. Conclusions: All race-sex groups were less likely to receive statin treatment in the REGARDS COPD sub-cohort compared to White men. This difference persisted in women after controlling for individual health care utilization factors, suggesting structural interventions are needed.

Positive valence system function and anhedonia in middle-aged and older adults at high suicide risk.

Positive valence systems are disrupted in late-life depression and in individuals at risk for suicide. The reward positivity (RewP) is an event-related potential measure of positive valence system function that relates to depression and anhedonia in children and young adults. However, it is unclear whether a reliable RewP signal can be elicited in middle-aged and older adults at high risk for suicide and, if so, whether this signal is similarly associated with clinical symptoms. In the current study, a RewP was elicited with a standard gambling task in middle-aged and older adults (N = 31) at discharge from a hospitalization for suicidal thought or behaviors. The resulting electrocortical response differed significantly for monetary wins compared to losses. Internal reliability of the RewP and the feedback negativity (FN) to monetary loss was good to excellent. Internal reliability of difference measures was lower but still largely acceptable, with residualized differences scores demonstrating stronger reliability than subtraction-based scores. A smaller residualized RewP, after accounting for the influence of the FN, was associated with greater severity of lassitude, an index of appetitive anhedonia. These findings set the groundwork for future studies of positive valence system function and depression in middle-aged and older adults at high risk for suicide.

Risk stratification models for predicting preventable hospitalization in commercially insured late middle-aged adults with depression.

BACKGROUND: A significant number of late middle-aged adults with depression have a high illness burden resulting from chronic conditions which put them at high risk of hospitalization. Many late middle-aged adults are covered by commercial health insurance, but such insurance claims have not been used to identify the risk of hospitalization in individuals with depression. In the present study, we developed and validated a non-proprietary model to identify late middle-aged adults with depression at risk for hospitalization, using machine learning methods. METHODS: This retrospective cohort study involved 71,682 commercially insured older adults aged 55-64 years diagnosed with depression. National health insurance claims were used to capture demographics, health care utilization, and health status during the base year. Health status was captured using 70 chronic health conditions, and 46 mental health conditions. The outcomes were 1- and 2-year preventable hospitalization. For each of our two outcomes, we evaluated seven modelling approaches: four prediction models utilized logistic regression with different combinations of predictors to evaluate the relative contribution of each group of variables, and three prediction models utilized machine learning approaches - logistic regression with LASSO penalty, random forests (RF), and gradient boosting machine (GBM). RESULTS: Our predictive model for 1-year hospitalization achieved an AUC of 0.803, with a sensitivity of 72% and a specificity of 76% under the optimum threshold of 0.463, and our predictive model for 2-year hospitalization achieved an AUC of 0.793, with a sensitivity of 76% and a specificity of 71% under the optimum threshold of 0.452. For predicting both 1-year and 2-year risk of preventable hospitalization, our best performing models utilized the machine learning approach of logistic regression with LASSO penalty which outperformed more black-box machine learning models like RF and GBM. CONCLUSIONS: Our study demonstrates the feasibility of identifying depressed middle-aged adults at higher risk of future hospitalization due to burden of chronic illnesses using basic demographic information and diagnosis codes recorded in health insurance claims. Identifying this population may assist health care planners in developing effective screening strategies and management approaches and in efficient allocation of public healthcare resources as this population transitions to publicly funded healthcare programs, e.g., Medicare in the US.

A single-center, open-label, randomized, parallel-group trial to pilot the effectiveness of a peer coach behavioral intervention versus an active control in reducing anxiety and depression in patients scheduled for total knee replacement.

BACKGROUND: Moving Well is a behavioral intervention for patients with knee osteoarthritis (KOA) scheduled for a total knee replacement (TKR). The objective of this intervention is to help patients with KOA mentally and physically prepare for and recover from TKR. METHODS: This is an open-label pilot randomized clinical trial that will test the feasibility and effectiveness of the Moving Well intervention compared to an attention control group, Staying Well, to reduce symptoms of anxiety and depression in patients with KOA undergoing TKR. The Moving Well intervention is guided by Social Cognitive Theory. During this 12-week intervention, participants will receive 7 weekly calls before surgery and 5 weekly calls after surgery from a peer coach. During these calls, participants will be coached to use principles of cognitive behavioral therapy (CBT), stress reduction techniques, and will be assigned an online exercise program, and self-monitoring activities to complete on their own time throughout the program. Staying Well participants will receive weekly calls of similar duration from research staff to discuss a variety of health topics unrelated to TKR, CBT, or exercise. The primary outcome is the difference in levels of anxiety and/or depression between participants in the Moving Well and Staying Well groups 6 months after TKR. DISCUSSION: This study will pilot test the feasibility and effectiveness of Moving Well, a peer coach intervention, alongside principles of CBT and home exercise, to help patients with KOA mentally and physically prepare for and recover from TKR. TRIAL REGISTRATION: Clinicaltrials.gov. NCT05217420; Registered: January 31, 2022.

Course of Subtypes of Late-Life Depression Identified by Bipartite Network Analysis During Psychosocial Interventions.

Importance: Approximately half of older adults with depression remain symptomatic at treatment end. Identifying discrete clinical profiles associated with treatment outcomes may guide development of personalized psychosocial interventions. Objective: To identify clinical subtypes of late-life depression and examine their depression trajectory during psychosocial interventions in older adults with depression. Design, Setting, and Participants: This prognostic study included older adults aged 60 years or older who had major depression and participated in 1 of 4 randomized clinical trials of psychosocial interventions for late-life depression. Participants were recruited from the community and outpatient services of Weill Cornell Medicine and the University of California, San Francisco, between March 2002 and April 2013. Data were analyzed from February 2019 to February 2023. Interventions: Participants received 8 to 14 sessions of (1) personalized intervention for patients with major depression and chronic obstructive pulmonary disease, (2) problem-solving therapy, (3) supportive therapy, or (4) active comparison conditions (treatment as usual or case management). Main Outcomes and Measures: The main outcome was the trajectory of depression severity, assessed using the Hamilton Depression Rating Scale (HAM-D). A data-driven, unsupervised, hierarchical clustering of HAM-D items at baseline was conducted to detect clusters of depressive symptoms. A bipartite network analysis was used to identify clinical subtypes at baseline, accounting for both between- and within-patient variability across domains of psychopathology, social support, cognitive impairment, and disability. The trajectories of depression severity in the identified subtypes were compared using mixed-effects models, and time to remission (HAM-D score ≤10) was compared using survival analysis. Results: The bipartite network analysis, which included 535 older adults with major depression (mean [SD] age, 72.7 [8.7] years; 70.7% female), identified 3 clinical subtypes: (1) individuals with severe depression and a large social network; (2) older, educated individuals experiencing strong social support and social interactions; and (3) individuals with disability. There was a significant difference in depression trajectories (F2,2976.9 = 9.4; P < .001) and remission rate (log-rank χ22 = 18.2; P < .001) across clinical subtypes. Subtype 2 had the steepest depression trajectory and highest likelihood of remission regardless of the intervention, while subtype 1 had the poorest depression trajectory. Conclusions and Relevance: In this prognostic study, bipartite network clustering identified 3 subtypes of late-life depression. Knowledge of patients' clinical characteristics may inform treatment selection. Identification of discrete subtypes of late-life depression may stimulate the development of novel, streamlined interventions targeting the clinical vulnerabilities of each subtype.

Evidence-based objective performance criteria for the evaluation of hip and knee replacement devices and technologies.

BACKGROUND: Objective performance criteria (OPC) is a novel method to provide minimum performance standards and improve the regulated introduction of original or incremental device innovations in order to prevent patients from being exposed to potentially inferior designs whilst allowing timely access to improvements. We developed 2-year safety and effectiveness OPC for total hip and knee replacement (THR and TKR). METHODS: Analyses of large databases were conducted using various data sources: a systematic literature review; a direct data analysis from The Functional Outcomes Research for Comparative Effectiveness in Total Joint Replacement and Quality Improvement Registry (FORCE-TJR) and the Kaiser Permanente Implant Registry (KPIR); and claims data analyses from longitudinal discharge data in New York and California states. The literature review included U.S. patients (≥18 years) who received THR or TKR for primary end-stage osteoarthritis and prospectively collected data on patient-reported outcome measures (PROMs) from at least 100 subjects and/or 2-year implant survival for at least 250 implants. Random effects models were used for meta-analysis. RESULTS: Data were available from a total of 951 100 patients. After screening of 7979 abstracts, 294 studies underwent full-text review and 31 studies contributed to the evidence synthesis (333 995 implants). Direct data analysis of FORCE-TJR contributed 9223 joint replacement patients to the construction of OPC for effectiveness; KPIR contributed 262 044 patients for the construction of OPC for safety. Claims database analysis contributed 345 838 patients to the construction of safety OPC. OPC for safety were constructed for cumulative incidences of 2-year all-cause and septic revision (THR/TKR 2.0%/1.6% and 0.6%/0.7%), and OPC for effectiveness were constructed based on four disease-specific and three general health-related quality of life PROMs (HOOS/KOOS 87.1/80.6; HSS/KSS function 94.4/90.6; SF-12/SF-36, PCS 46.5/41.9, EQ-5D 0.88/0.84). CONCLUSION: This study is the first to construct a 2-year OPC for the safety and effectiveness of THR and TKR based on U.S. real-world data. Based on these OPC, potential benchmarks for (single-arm study) evaluation of new device innovations are suggested for a regulated and safe introduction to the (commercial) market.

Effects of social deprivation on risk factors for suicidal ideation and suicide attempts in commercially insured US youth and adults.

We used US nationwide commercial insurance claims data (2011-2015) to study the effect of social deprivation on clinical and demographic risk factors for suicidal ideation (SI) and suicide attempts (SA) among US youth and adults < 65 years, after having a mental health or substance use disorder-related outpatient encounter. Neighborhood social deprivation level was summarized by the quintile of social deprivation index (SDI) at individuals' zip code level. Cox proportional hazard models were used to evaluate the effect of social deprivation on demographic and clinical risk factors for SI and SA. The study cohort consisted of 317,383 individuals < 65 years, with 124,424 aged < 25 (youth) and 192,959 aged between 25 and 64 (adults). Neighborhood social deprivation impacted risk factors for SI and SA differently for youth and adults. Among youth, SDI interacted with multiple risk factors for both SI and SA. The effects of the risk factors were larger on youth from middle socioeconomic neighborhoods. Among adults, risk of SI was the strongest in the most deprived neighborhoods, but risk of SA did not vary by neighborhood deprivation level. Our findings suggest community-based suicide prevention initiatives should be tailored according to neighborhood deprivation level and the targeted individual's age to maximize the impact.

Influence of social deprivation index on in-hospital outcomes of COVID-19.

While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient's residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70-0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71-0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79-0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79-0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.

Predictive Modeling for Suicide-Related Outcomes and Risk Factors among Patients with Pain Conditions: A Systematic Review.

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000-12 September 2020, we evaluated existing suicide prediction models' (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (n = 3 studies) ranged 0.67-0.84, overall accuracy(n = 5): 0.78-0.96, sensitivity(n = 2): 0.65-0.91, and positive predictive values(n = 3): 0.01-0.43. Using the modified Quality in Prognosis Studies tool to assess the risk of biases, four SPM studies had moderate-to-high risk of biases. This systematic review identified a comprehensive list of risk factors that may improve predicting suicidal risks for patients with pain conditions. Future studies need to examine reasons for performance variations and SPM's clinical utility.

Race and Sex Differences in Mortality in Individuals with Chronic Obstructive Pulmonary Disease.

Rationale: Despite differences in chronic obstructive pulmonary disease (COPD) comorbidities, race- and sex-based differences in all-cause mortality and cause-specific mortality are not well described. Objectives: To examine mortality differences in COPD by race-sex and underlying mechanisms. Methods: Medicare claims were used to identify COPD among REGARDS (Reasons for Geographic and Racial Differences in Stroke) cohort participants. Mortality rates were calculated using adjudicated causes of death. Hazard ratios (HRs) for mortality comparing race-sex groups were modeled with Cox proportional hazards regression. Results: In the 2,148-member COPD subcohort, 49% were women, and 34% were Black individuals; 1,326 deaths occurred over a median 7.5 years (interquartile range, 3.9-10.5 yr) follow-up. All-cause mortality per 1,000 person-years comparing Black versus White men was 101.1 (95% confidence interval [CI], 88.3-115.8) versus 93.9 (95% CI, 86.3-102.3; P = 0.99); comparing Black versus White women, all-cause mortality per 1,000 person-years was 74.2 (95% CI, 65.0-84.8) versus 70.6 (95% CI, 63.5-78.5; P = 0.99). Cardiovascular disease (CVD) was the leading cause-specific mortality among all race-sex groups. HR for CVD and chronic lung disease mortality were nonsignificant comparing Black versus White men. HR for CVD death was higher in Black compared with White women (HR, 1.44; 95% CI, 1.06-1.95), whereas chronic lung disease death was lower (HR, 0.44; 95% CI, 0.25-0.77). These differences were attributable to higher CVD risk factor burden among Black women. Conclusions: In the REGARDS COPD cohort, there were no race-sex differences in all-cause mortality. CVD was the most common cause of death for all race-sex groups with COPD. Black women with COPD had a higher risk of CVD-related mortality than White women. CVD comorbidity management, especially among Black individuals, may improve mortality outcomes.