In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.

A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.

We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.

The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

Prior research has reported an association between divorce and suicide attempt. We aimed to clarify this complex relationship, considering sex differences, temporal factors, and underlying etiologic pathways.

We used Swedish longitudinal national registry data for a cohort born 1960–1990 that was registered as married between 1978 and 2018 (N = 1 601 075). We used Cox proportional hazards models to estimate the association between divorce and suicide attempt. To assess whether observed associations were attributable to familial confounders or potentially causal in nature, we conducted co-relative analyses.

In the overall sample and in sex-stratified analyses, divorce was associated with increased risk of suicide attempt (adjusted hazard ratios [HRs] 1.66–1.77). Risk was highest in the year immediately following divorce (HRs 2.20–2.91) and declined thereafter, but remained elevated 5 or more years later (HRs 1.41–1.51). Divorcees from shorter marriages were at higher risk for suicide attempt than those from longer marriages (HRs 3.33–3.40 and 1.20–1.36, respectively). In general, HRs were higher for divorced females than for divorced males. Co-relative analyses suggested that familial confounders and a causal pathway contribute to the observed associations.

The association between divorce and risk of suicide attempt is complex, varying as a function of sex and time-related variables. Given evidence that the observed association is due in part to a causal pathway from divorce to suicide attempt, intervention or prevention efforts, such as behavioral therapy, could be most effective early in the divorce process, and in particular among females and those whose marriages were of short duration.

Suicidal behavior and substance use disorders (SUDs) are important public health concerns. Prior suicide attempts and SUDs are two of the most consistent predictors of suicide death, and clarifying the role of SUDs in the transition from suicide attempt to suicide death could inform prevention efforts.

We used national Swedish registry data to identify individuals born 1960–1985, with an index suicide attempt in 1997–2017 (N = 74 873; 46.7% female). We assessed risk of suicide death as a function of registration for a range of individual SUDs. We further examined whether the impact of SUDs varied as a function of (i) aggregate genetic liability to suicidal behavior, or (ii) age at index suicide attempt.

In univariate models, risk of suicide death was higher among individuals with any SUD registration [hazard ratios (HRs) = 2.68–3.86]. In multivariate models, effects of specific SUDs were attenuated, but remained elevated for AUD (HR = 1.86 95% confidence intervals 1.68–2.05), opiates [HR = 1.58 (1.37–1.82)], sedatives [HR = 1.93 (1.70–2.18)], and multiple substances [HR = 2.09 (1.86–2.35)]. In secondary analyses, the effects of most, but not all, SUD were exacerbated by higher levels of genetic liability to suicide death, and among individuals who were younger at their index suicide attempt.

In the presence of a strong predictor of suicide death – a prior attempt – substantial predictive power is still attributable to SUDs. Individuals with SUDs may warrant additional suicide screening and prevention efforts, particularly in the context of a family history of suicidal behavior or early onset of suicide attempt.

Optimizing needleless connector hub disinfection practice is a key strategy in central-line–associated bloodstream infection (CLABSI) prevention. In this mixed-methods evaluation, 3 products with varying scrub times were tested for experimental disinfection followed by a qualitative nursing assessment of each.

Needleless connectors were inoculated with varying concentrations of Staphylococcus epidermidis, Pseudomonas aeruginosa, and Staphylococcus aureus followed by disinfection with a 70% isopropyl alcohol (IPA) wipe (a 15-second scrub time and a 15-second dry time), a 70% IPA cap (a 10-second scrub time and a 5-second dry time), or a 3.15% chlorhexidine gluconate with 70% IPA (CHG/IPA) wipe (a 5-second scrub time and a 5-second dry time). Cultures of needleless connectors were obtained after disinfection to quantify bacterial reduction. This was followed by surveying a convenience sample of nursing staff with intensive care unit assignments at an academic tertiary hospital on use of each product.

All products reduced overall bacterial burden when compared to sterile water controls, however the IPA and CHG/IPA wipes were superior to the IPA caps when product efficacy was compared. Nursing staff noted improved compliance with CHG/IPA wipes compared with the IPA wipes and the IPA caps, with many preferring the lesser scrub and dry times required for disinfection.

Achieving adequate bacterial disinfection of needleless connectors while maximizing healthcare staff compliance with scrub and dry times may be best achieved with a combination CHG/IPA wipe.

Previous studies have demonstrated substantial associations between substance use disorders (SUD) and suicidal behavior. The current study empirically assesses the extent to which shared genetic and/or environmental factors contribute to associations between alcohol use disorders (AUD) or drug use disorders (DUD) and suicidal behavior, including attempts and death.

The authors used Swedish national registry data, including medical, pharmacy, criminal, and death registrations, for a large cohort of twins, full siblings, and half siblings (N = 1 314 990) born 1960–1980 and followed through 2017. They conducted twin-sibling modeling of suicide attempt (SA) or suicide death (SD) with AUD and DUD to estimate genetic and environmental correlations between outcomes. Analyses were stratified by sex.

Genetic correlations between SA and SUD ranged from rA = 0.60–0.88; corresponding shared environmental correlations were rC = 0.42–0.89 but accounted for little overall variance; and unique environmental correlations were rE = 0.42–0.57. When replacing attempt with SD, genetic and shared environmental correlations with AUD and DUD were comparable (rA = 0.48–0.72, rC = 0.92–1.00), but were attenuated for unique environmental factors (rE = −0.01 to 0.31).

These findings indicate that shared genetic and unique environmental factors contribute to comorbidity of suicidal behavior and SUD, in conjunction with previously reported causal associations. Thus, each outcome should be considered an indicator of risk for the others. Opportunities for joint prevention and intervention, while limited by the polygenic nature of these outcomes, may be feasible considering moderate environmental correlations between SA and SUD.

How does genetic liability to suicide attempt (SA), suicide death (SD), major depression (MD), bipolar disorder (BD), schizophrenia (SZ), alcohol use disorder (AUD), and drug use disorder (DUD) impact on risk for SA and SD?

In the Swedish general population born 1932–1995 and followed through 2017 (n = 7 661 519), we calculate family genetic risk scores (FGRS) for SA, SD, MD, BD, SZ, AUD, and DUD. Registration for SA and SD was assessed from Swedish national registers.

In univariate and multivariate models predicting SA, FGRS were highest for SA, AUD, DUD, and MD. In univariate models predicting SD, the strongest FGRS were AUD, DUD, SA, and SD. In multivariate models, the FGRS for SA and AUD were higher in predicting SA while the FGRS for SD, BD, and SZ were higher in predicting SD. Higher FGRS for all disorders significantly predicted both younger age at first SA and frequency of attempts. For SD, higher FGRS for MD, AUD, and SD predicted later age at SD. Mediation of FGRS effects on SA and SD was more pronounced for SD than SA, strongest for AUD, DUD, and SZ FGRS and weakest for MD.

FGRS for both SA and SD and for our five psychiatric disorders impact on risk for SA and SD in a complex manner. While some of the impact of genetic risk factors for psychiatric disorders on risk for SA and SD is mediated through developing the disorders, these risks also predispose directly to suicidal behaviors.