Risk of suicide attempts and intentional self-harm on alprazolam.

BACKGROUND: From 2000-2021, U.S. suicide deaths have risen 36 %. Identification of pharmacological agents associated with increased suicide risk and safer alternatives may help reduce this trend. METHODS: An exposure-only within-subject time-to-event pharmacoepidemiologic study of the dynamic association between alprazolam treatment and suicide attempts over 2-years. Parallel analyses were conducted for diazepam, lorazepam and buspirone. Data for 2,495,520 patients were obtained from U.S. private insurance medical claims MarketScan from 2010 to 2019. FINDINGS: Alprazolam was associated with over a doubling of risk of suicide attempts (HR=2.21, 95 % CI=2.06,2.38). A duration-response analysis for the modal dose (0.5 mg) revealed a 5 % increase in suicidal events per additional month of treatment (HR=1.05, 95 % CI=1.04,1.07). Parallel analyses with long-acting (diazepam) and short-acting (lorazepam), found similar associations (diazepam HR=2.87, 95 % CI=2.56,3.21; lorazepam HR=1.83, 95 % CI=1.69,2.00), whereas the non-benzodiazepine anxiolytic, buspirone, showed significantly less risk (HR=1.25, 95 % CI=1.13,1.38), and no increased risk in patients with an attempt history (HR=1.05, 95 % CI=0.70,1.59). INTERPRETATION: This study confirmed an earlier signal linking alprazolam to increased suicide attempt risk. The increased risk extends to benzodiazepines in general, regardless of half-life and risk of withdrawal seizure. Buspirone appears to be a safer treatment than benzodiazepines, particularly in patients at increased risk for suicide.

Personalized mood prediction from patterns of behavior collected with smartphones.

Over the last ten years, there has been considerable progress in using digital behavioral phenotypes, captured passively and continuously from smartphones and wearable devices, to infer depressive mood. However, most digital phenotype studies suffer from poor replicability, often fail to detect clinically relevant events, and use measures of depression that are not validated or suitable for collecting large and longitudinal data. Here, we report high-quality longitudinal validated assessments of depressive mood from computerized adaptive testing paired with continuous digital assessments of behavior from smartphone sensors for up to 40 weeks on 183 individuals experiencing mild to severe symptoms of depression. We apply a combination of cubic spline interpolation and idiographic models to generate individualized predictions of future mood from the digital behavioral phenotypes, achieving high prediction accuracy of depression severity up to three weeks in advance (R2 ≥ 80%) and a 65.7% reduction in the prediction error over a baseline model which predicts future mood based on past depression severity alone. Finally, our study verified the feasibility of obtaining high-quality longitudinal assessments of mood from a clinical population and predicting symptom severity weeks in advance using passively collected digital behavioral data. Our results indicate the possibility of expanding the repertoire of patient-specific behavioral measures to enable future psychiatric research.

Initial Validation of a Computerized Adaptive Test for Substance Use Disorder Identification in Adolescents.

PURPOSE: Computerized adaptive tests (CATs) are highly efficient assessment tools that couple low patient and clinician time burden with high diagnostic accuracy. A CAT for substance use disorders (CAT-SUD-E) has been validated in adult populations but has yet to be tested in adolescents. The purpose of this study was to perform initial evaluation of the K-CAT-SUD-E (i.e., Kiddy-CAT-SUD-E) in an adolescent sample compared to a gold-standard diagnostic interview. METHODS: Adolescents (N = 156; aged 11-17) with diverse substance use histories completed the K-CAT-SUD-E electronically and the substance related disorders portion of a clinician-conducted diagnostic interview (K-SADS) via tele-videoconferencing platform. The K-CAT-SUD-E assessed both current and lifetime overall SUD and substance-specific diagnoses for nine substance classes. RESULTS: Using the K-CAT-SUD-E continuous severity score and diagnoses to predict the presence of any K-SADS SUD diagnosis, the classification accuracy ranged from excellent for current SUD (AUC = 0.89, 95% CI = 0.81, 0.95) to outstanding (AUC = 0.93, 95% CI = 0.82, 0.97) for lifetime SUD. Regarding current substance-specific diagnoses, the classification accuracy was excellent for alcohol (AUC = 0.82), cannabis (AUC = 0.83) and nicotine/tobacco (AUC = 0.90). For lifetime substance-specific diagnoses, the classification accuracy ranged from excellent (e.g., opioids, AUC = 0.84) to outstanding (e.g., stimulants, AUC = 0.96). K-CAT-SUD-E median completion time was 4 min 22 s compared to 45 min for the K-SADS. CONCLUSIONS: This study provides initial support for the K-CAT-SUD-E as a feasible accurate diagnostic tool for assessing SUDs in adolescents. Future studies should further validate the K-CAT-SUD-E in a larger sample of adolescents and examine its acceptability, feasibility, and scalability in youth-serving settings.

Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1.

Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.

Folic acid prescription and suicide attempt prevention: effect of past suicidal behaviour, psychiatric diagnosis and psychotropic medication.

We previously showed that folic acid prescriptions for any indication were associated with lower rates of suicidal behaviour. Given that future randomised clinical trials are likely to focus on psychiatric disorders carrying elevated risk for suicide, we now report on the moderating effects of prior suicidal behaviour, psychiatric diagnoses and psychotropic medications on potential antisuicidal effects of folic acid. Data were obtained from the MarketScan Commercial Claims and Encounters databases that cover 164 million insured persons from 2005-2017, from which a cohort of 866 586 patients was derived. Analysis revealed no significant moderation effects on the antisuicidal effect of folic acid. These findings indicate that the potential benefit of folic acid for preventing suicidal behaviour is comparable in psychiatric populations at higher risk of suicide and that it may be additive to any benefit from psychotropic medications.

A randomized controlled trial on using predictive algorithm to adapt level of psychological care for community college students: STAND triaging and adapting to level of care study protocol.

BACKGROUND: There is growing interest in using personalized mental health care to treat disorders like depression and anxiety to improve treatment engagement and efficacy. This randomized controlled trial will compare a traditional symptom severity decision-making algorithm to a novel multivariate decision-making algorithm for triage to and adaptation of mental health care. The stratified levels of care include a self-guided online wellness program, coach-guided online cognitive behavioral therapy, and clinician-delivered psychotherapy with or without pharmacotherapy. The novel multivariate algorithm will be comprised of baseline (for triage and adaptation) and time-varying variables (for adaptation) in four areas: social determinants of mental health, early adversity and life stressors, predisposing, enabling, and need influences on health service use, and comprehensive mental health status. The overarching goal is to evaluate whether the multivariate algorithm improves adherence to treatment, symptoms, and functioning above and beyond the symptom-based algorithm. METHODS/DESIGN: This trial will recruit a total of 1000 participants over the course of 5 years in the greater Los Angeles Metropolitan Area. Participants will be recruited from a highly diverse sample of community college students. For the symptom severity approach, initial triaging to level of care will be based on symptom severity, whereas for the multivariate approach, the triaging will be based on a comprehensive set of baseline measures. After the initial triaging, level of care will be adapted throughout the duration of the treatment, utilizing either symptom severity or multivariate statistical approaches. Participants will complete computerized assessments and self-report questionnaires at baseline and up to 40 weeks. The multivariate decision-making algorithm will be updated annually to improve predictive outcomes. DISCUSSION: Results will provide a comparison on the traditional symptom severity decision-making and the novel multivariate decision-making with respect to treatment adherence, symptom improvement, and functional recovery. Moreover, the developed multivariate decision-making algorithms may be used as a template in other community college settings. Ultimately, findings will inform the practice of level of care triage and adaptation in psychological treatments, as well as the use of personalized mental health care broadly. TRIAL REGISTRATION: ClinicalTrials.gov NCT05591937, submitted August 2022, published October 2022.

Population Health Management Approach to Depression Symptom Monitoring in Primary Care via Patient Portal: A Randomized Controlled Trial.

Depression is undertreated in primary care. Using patient portals to administer regular symptom assessments could facilitate more timely care. At an urban academic medical center outpatient clinic, patients with active portal accounts and depression on their problem list or a positive screen in the past year were randomized to assessment during triage at visits (usual care) versus usual care plus assessment via portal (population health care). Portal invitations were sent regardless of whether patients had scheduled appointments. More patients completed assessments in the population health care arm than usual care: 59% versus 18%, P < 0.001. Depression symptoms were more common among patients who completed their initial assessment via the portal versus in the clinic. In the population health care arm, 57% (N = 80/140) of patients with moderate-to-severe symptoms completed at least 1 follow-up assessment versus 37% (N = 13/35) in usual care. A portal-based population health approach could improve depression monitoring in primary care.

Social Vulnerability and Risk of Suicide in US Adults, 2016-2020.

Importance: There were over 45 000 suicides in the US in 2020, making suicide the 12th leading cause of death. If social vulnerability is associated with suicide rates, targeted interventions for at-risk segments of the population may reduce US suicide rates. Objective: To determine the association between social vulnerability and suicide in adults. Design, Setting, and Participants: This cohort study analyzed 2 county-level social vulnerability measures (the Social Vulnerability Index [SVI] and the Social Vulnerability Metric [SVM]) and US Centers for Disease Control and Prevention-reported county-level suicides from 2016 to 2020. Data were analyzed November and December 2022. Exposures: County-level variability in social vulnerability. Main Outcomes and Measures: The primary outcome measure was number of county-level adult suicides from 2016 to 2020, offset by county adult population during those years. The association between social vulnerability (measured using the SVI and the newly created SVM for 2018) and suicide was modeled using a bayesian-censored Poisson regression model to account for the CDC's suppression of county-level suicide counts of less than 10, adjusted for age, racial and ethnic minority, and urban-rural county characteristics. Results: From 2016 to 2020, there were a total of 222 018 suicides in 3141 counties. Comparing the least socially vulnerable (0% to 10%) to the most socially vulnerable (90% to 100%) counties, there was a 56% increase in suicide rate (17.3 per 100 000 persons to 27.0 per 100 000 persons) as measured by the SVI (incidence rate ratio, 1.56; 95% credible interval, 1.51-1.60) and an 82% increase in suicide rate (13.8 per 100 000 persons to 25.1 per 100 000 persons) as measured by the SVM (incidence rate ratio, 1.82; 95% credible interval, 1.72-1.92). Conclusions and Relevance: This cohort study found that social vulnerability had a direct association with risk for adult suicide. Reducing social vulnerability may lead to life-saving reduction in the rate of suicide.

Prediction of Suicide Attempts and Suicide-Related Events Among Adolescents Seen in Emergency Departments.

Importance: Screening adolescents in emergency departments (EDs) for suicidal risk is a recommended strategy for suicide prevention. Comparing screening measures on predictive validity could guide ED clinicians in choosing a screening tool. Objective: To compare the Ask Suicide-Screening Questions (ASQ) instrument with the Computerized Adaptive Screen for Suicidal Youth (CASSY) instrument for the prediction of suicidal behavior among adolescents seen in EDs, across demographic and clinical strata. Design, Setting, and Participants: The Emergency Department Study for Teens at Risk for Suicide is a prospective, random-series, multicenter cohort study that recruited adolescents, oversampled for those with psychiatric symptoms, who presented to the ED from July 24, 2017, through October 29, 2018, with a 3-month follow-up to assess the occurrence of suicidal behavior. The study included 14 pediatric ED members of the Pediatric Emergency Care Applied Research Network and 1 Indian Health Service ED. Statistical analysis was performed from May 2021 through January 2023. Main Outcomes and Measures: This study used a prediction model to assess outcomes. The primary outcome was suicide attempt (SA), and the secondary outcome was suicide-related visits to the ED or hospital within 3 months of baseline; both were assessed by an interviewer blinded to baseline information. The ASQ is a 4-item questionnaire that surveys suicidal ideation and lifetime SAs. A positive response or nonresponse on any item indicates suicidal risk. The CASSY is a computerized adaptive screening tool that always includes 3 ASQ items and a mean of 8 additional items. The CASSY's continuous outcome is the predicted probability of an SA. Results: Of 6513 adolescents available, 4050 were enrolled, 3965 completed baseline assessments, and 2740 (1705 girls [62.2%]; mean [SD] age at enrollment, 15.0 [1.7] years; 469 Black participants [17.1%], 678 Hispanic participants [24.7%], and 1618 White participants [59.1%]) completed both screenings and follow-ups. The ASQ and the CASSY showed a similar sensitivity (0.951 [95% CI, 0.918-0.984] vs 0.945 [95% CI, 0.910-0.980]), specificity (0.588 [95% CI, 0.569-0.607] vs 0.643 [95% CI, 0.625-0.662]), positive predictive value (0.127 [95% CI, 0.109-0.146] vs 0.144 [95% CI, 0.123-0.165]), and negative predictive value (both 0.995 [95% CI, 0.991-0.998], respectively). Area under the receiver operating characteristic curve findings were similar among patients with physical symptoms (ASQ, 0.88 [95% CI, 0.81-0.95] vs CASSY, 0.94 [95% CI, 0.91-0.96]). Among patients with psychiatric symptoms, the CASSY performed better than the ASQ (0.72 [95% CI, 0.68-0.77] vs 0.57 [95% CI, 0.55-0.59], respectively). Conclusions and Relevance: This study suggests that both the ASQ and the CASSY are appropriate for universal screening of patients in pediatric EDs. For the small subset of patients with psychiatric symptoms, the CASSY shows greater predictive validity.

Benztropine and suicide attempts and intentional self-harm.

BACKGROUND: This large-scale pharmacoepidemiologic study was conducted to confirm a previous signal for decreased risk of suicide attempt following prescription fills for benztropine. METHODS: We used a within-person exposure-only cohort design to study the dynamic association between benztropine prescription fills over a 12-month period and suicidal events (suicide attempts and intentional self-harm) in 62,493 patients with private health insurance (MarketScan - MS) who filled a new benztropine prescription between 2011 and 2019. A discrete-time survival analysis was used to analyze the data, adjusting for age, sex, diagnoses related to suicidal behavior, Parkinson's disease, medical comorbidities, history of suicide attempts, concomitant CNS medications, and time-varying antipsychotic use. RESULTS: Overall, there were 486 suicidal events (0.8%) following the index end-date of the one-year baseline period. Benztropine use was associated with fewer suicidal events (HR=0.63, 95% CI = 0.50, 0.80). Patients treated with antipsychotics and benztropine had a similar reduction in suicidal events as patients treated with benztropine alone in both within-subject and between-subject analyses. Similar associations were found for patients with bipolar disorder or schizophrenia, and those treated with newer versus older generation antipsychotics. Dose-response and duration response relationships were found, with an overall 6% reduction in suicidal events per 1 mg equivalent dosage per month, that was similar in those treated and those not treated with antipsychotics. INTERPRETATIONS: Benztropine was found to lower suicidal event rates, comparably in those receiving or not receiving antipsychotic medications, regardless of the presence of major psychiatric disorders. This observation warrants testing in a randomized clinical trial. FUNDING: No funding sources were utilized for this manuscript.

The Association Between USMLE Step 2 Clinical Knowledge Scores and Residency Performance: A Systematic Review and Meta-Analysis.

PURPOSE: With the change in Step 1 score reporting, Step 2 Clinical Knowledge (CK) may become a pivotal factor in resident selection. This systematic review and meta-analysis seeks to synthesize existing observational studies that assess the relationship between Step 2 CK scores and measures of resident performance. METHOD: The authors searched MEDLINE, Web of Science, and Scopus databases using terms related to Step 2 CK in 2021. Two researchers identified studies investigating the association between Step 2 CK and measures of resident performance and included studies if they contained a bivariate analysis examining Step 2 CK scores' association with an outcome of interest: in-training examination (ITE) scores, board certification examination scores, select Accreditation Council for Graduate Medical Education core competency assessments, overall resident performance evaluations, or other subjective measures of performance. For outcomes that were investigated by 3 or more studies, pooled effect sizes were estimated with random-effects models. RESULTS: Among 1,355 potential studies, 68 met inclusion criteria and 43 were able to be pooled. There was a moderate positive correlation between Step 2 CK and ITE scores (0.52, 95% CI 0.45-0.59, P < .01). There was a moderate positive correlation between Step 2 CK and ITE scores for both nonsurgical (0.59, 95% CI 0.51-0.66, P < .01) and surgical specialties (0.41, 95% CI 0.33-0.48, P < .01). There was a very weak positive correlation between Step 2 CK scores and subjective measures of resident performance (0.19, 95% CI 0.13-0.25, P < .01). CONCLUSIONS: This study found Step 2 CK scores have a statistically significant moderate positive association with future examination scores and a statistically significant weak positive correlation with subjective measures of resident performance. These findings are increasingly relevant as Step 2 CK scores will likely become more important in resident selection.

The social vulnerability metric (SVM) as a new tool for public health.

OBJECTIVE: To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level. DATA SOURCES AND STUDY SETTING: The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments. STUDY DESIGN: The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity. DATA COLLECTION/EXTRACTION METHODS: The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments. PRINCIPAL FINDINGS: The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago. CONCLUSIONS: The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.

Association between prescribed opioid dose and risk of motor vehicle crashes.

ABSTRACT: Opioid-involved motor vehicle traffic fatalities have increased over the past 2 decades. However, the extent to which prescribed opioids increase the risk of motor vehicle crashes remains uncertain. This study used real-world healthcare claims data to examine the association between prescription opioid dose and motor vehicle crash risk. Using nationwide US commercial insurance claims data for 2010 to 2018, we identified 772,404 adults who received incident, noncancer opioid therapy. We examined associations between daily prescription opioid dose, calculated in morphine milligram equivalents (MME) from filled prescription claims, and risk of motor vehicle crashes, assessed as diagnoses of motor vehicle injuries in claims for emergency visits, inpatient hospitalizations, and ambulance transportation. We estimated associations using a within-individual design, which ruled out all time-stable confounding. We complemented the design with time-varying statistical adjustment for other pharmacotherapies and a negative control pain pharmacotherapy analysis (with incident cyclic antidepressant prescriptions). During 2,150,009 person-years of follow-up, there were 12,123 motor vehicle crashes (5.64 crashes per 1000 person-years). In within-individual comparisons, crash risk was greater during opioid prescription periods involving doses ≤60 MME/day (odds ratio [OR], 3.86; 95% confidence interval [CI], 3.54, 4.21), >60 to 120 MME/day (OR, 5.46; 95% CI, 4.44, 6.73), and >120 MME/day (OR, 3.45; 95% CI, 2.31, 5.15) than during off-treatment periods. The negative control analysis supported the specificity of the results to opioids rather than to other processes associated with pharmacologic pain management. These findings suggest that the receipt of prescription opioids, even at doses ≤60 MME/day, is associated with an increased risk of motor vehicle crashes.

Pragmatic Clinical Trial of Population Health, Portal-Based Depression Screening: the PORTAL-Depression Study.

BACKGROUND: A population health approach to depression screening using patient portals may be a promising strategy to proactively engage and identify patients with depression. OBJECTIVE: To determine whether a population health approach to depression screening is more effective than screening during clinic appointments alone for identifying patients with depression. DESIGN: A pragmatic clinical trial at an adult outpatient internal medicine clinic at an urban, academic, tertiary care center. PATIENTS: Eligible patients (n = 2713) were adults due for depression screening with active portal accounts. Patients with documented depression or bipolar disorder and those who had been screened in the year prior to the study were excluded. INTERVENTION: Patients were randomly assigned to usual (n = 1372) or population healthcare (n = 1341). For usual care, patients were screened by medical assistants during clinic appointments. Population healthcare patients were sent letters through the portal inviting them to fill out an online screener regardless of whether they had a scheduled appointment. The same screening tool, the Computerized Adaptive Test for Mental Health (CAT-MH™), was used for clinic- and portal-based screening. MAIN MEASURES: The primary outcome was the depression screening rate. KEY RESULTS: The depression screening rate in the population healthcare arm was higher than that in the usual care arm (43% (n = 578) vs. 33% (n = 459), p < 0.0001). The rate of positive screens was also higher in the population healthcare arm compared to that in the usual care (10% (n = 58) vs. 4% (n = 17), p < 0.001). CONCLUSION: Findings suggest depression screening via a portal as part of a population health approach can increase screening and case identification, compared to usual care. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03832283.

Use of central nervous system drugs in combination with selective serotonin reuptake inhibitor treatment: A Bayesian screening study for risk of suicidal behavior.

Background: Using other central nervous system (CNS) medications in combination with selective serotonin reuptake inhibitor (SSRI) treatment is common. Despite this, there is limited evidence on the impact on suicidal behavior of combining specific medications. We aim to provide evidence on signals for suicidal behavior risk when initiating CNS drugs during and outside of SSRI treatment. Materials and methods: Using a linkage of Swedish national registers, we identified a national cohort of SSRI users aged 6-59 years residing in Sweden 2006-2013. We used a two-stage Bayesian Poisson model to estimate the incidence rate ratio (IRR) of suicidal behavior in periods up to 90 days before and after a CNS drug initiation during SSRI treatment, while accounting for multiple testing. For comparison, and to assess whether there were interactions between SSRIs and other CNS drugs, we also estimated the IRR of initiating the CNS drug without SSRI treatment. Results: We identified 53 common CNS drugs initiated during SSRI treatment, dispensed to 262,721 individuals. We found 20 CNS drugs with statistically significant IRRs. Of these, two showed a greater risk of suicidal behavior after versus before initiating the CNS drug (alprazolam, IRR = 1.39; flunitrazepam, IRR = 1.83). We found several novel signals of drugs that were statistically significantly associated with a reduction in the suicidal behavior risk. We did not find evidence of harmful interactions between SSRIs and the selected CNS drugs. Conclusion: Several of the detected signals for reduced risk correspond to drugs where there is previous evidence of benefit for antidepressant augmentation (e.g., olanzapine, quetiapine, lithium, buspirone, and mirtazapine). Novel signals of reduced suicidal behavior risk, including for lamotrigine, valproic acid, risperidone, and melatonin, warrant further investigation.

Association between vitamin D supplementation and COVID-19 infection and mortality.

Vitamin D deficiency has long been associated with reduced immune function that can lead to viral infection. Several studies have shown that Vitamin D deficiency is associated with increases the risk of infection with COVID-19. However, it is unknown if treatment with Vitamin D can reduce the associated risk of COVID-19 infection, which is the focus of this study. In the population of US veterans, we show that Vitamin D2 and D3 fills were associated with reductions in COVID-19 infection of 28% and 20%, respectively [(D3 Hazard Ratio (HR) = 0.80, [95% CI 0.77, 0.83]), D2 HR = 0.72, [95% CI 0.65, 0.79]]. Mortality within 30-days of COVID-19 infection was similarly 33% lower with Vitamin D3 and 25% lower with D2 (D3 HR = 0.67, [95% CI 0.59, 0.75]; D2 HR = 0.75, [95% CI 0.55, 1.04]). We also find that after controlling for vitamin D blood levels, veterans receiving higher dosages of Vitamin D obtained greater benefits from supplementation than veterans receiving lower dosages. Veterans with Vitamin D blood levels between 0 and 19 ng/ml exhibited the largest decrease in COVID-19 infection following supplementation. Black veterans received greater associated COVID-19 risk reductions with supplementation than White veterans. As a safe, widely available, and affordable treatment, Vitamin D may help to reduce the severity of the COVID-19 pandemic.

Computer adaptive testing to assess impairing behavioral health problems in emergency department patients with somatic complaints.

Objectives: To assess: (1) the prevalence of mental health and substance use in patients presenting to the emergency department (ED) through use of a computer adaptive test (CAT-MH), (2) the correlation among CAT-MH scores and self- and clinician-reported assessments, and (3) the association between CAT-MH scores and ED utilization in the year prior and 30 days after enrollment. Methods: This was a single-center observational study of adult patients presenting to the ED for somatic complaints (97%) from May 2019 to March 2020. The main outcomes were computer-adaptive-assessed domains of suicidality, depression, anxiety, post-traumatic stress disorder (PTSD), and substance use. We conducted Pearson correlations and logistic regression for objectives 2 and 3, respectively. Results: From a sample of 794 patients, the proportion of those at moderate/severe risk was: 24.1% (suicidality), 8.3% (depression), 16.5% (anxiety), 12.3% (PTSD), and 20.4% (substance use). CAT-MH domains were highly correlated with self-report assessments (r = 0.49-0.79). Individuals who had 2 or more ED visits in the prior year had 62% increased odds of being in the intermediate-high suicide risk category (odds ratio [OR], 1.62; 95% confidence interval [CI], 1.07-2.44) compared to those with zero prior ED visits. Individuals who scored in the intermediate-high-suicide risk group had 63% greater odds of an ED visit within 30 days after enrollment compared to those who scored as low risk (OR, 1.63; 95% CI, 1.09, 2.44). Conclusion: The CAT-MH documented that a considerable proportion of ED patients presenting for somatic problems had mental health conditions, even if mild. Mental health problems were also associated with ED utilization.

Radiological risk assessment of the Hunters Point Naval Shipyard (HPNS).

Hunters Point Naval Shipyard in San Francisco, California was deemed a Superfund site by the USEPA in 1989 due to chemical and radiological contamination resulting from U.S. Navy operations from 1939 to 1974. During characterization and remediation efforts, over 50,000 radiological soil samples and 19,000 air samples were collected. This risk assessment, conducted in accordance with federal guidelines, represents the first comprehensive evaluation of past, present, and future health risks associated with radionuclides present at the site. The assessment indicated that before site remediation, most radionuclide soil concentrations were at or near local background concentrations. Had such low remedial goals not been established, significant remediation of surface soils would not have been necessary to protect human health. The pre-remediation lifetime incremental cancer morbidity risks for on-site workers and theoretical on-site residents due to radionuclide contamination were found to be 1.3 × 10-6 and 3.2 × 10-6, respectively. The post-remediation risks to future on-site residents were found to be 6.3 × 10-8 (without durable cover) and 3.7 × 10-8 (with durable cover), while post-remediation risks to on-site workers were found to be 2.6 × 10-8 (without durable cover) and 1.6 × 10-8 (with durable cover). Risk estimates for all scenarios were found to be significantly below the acceptable risk of 3 × 10-4 approved by regulatory agencies. Upwind and downwind air samples collected during remediation indicate that remediation activities never posed a measurable risk to off-site residents. This risk assessment emphasizes the importance of establishing clear and scientifically rigorous soil remedial goals at sites as well as understanding local radionuclide background concentrations.