We reviewed outcomes in all 36 consecutive children <5 kg supported with the Berlin Heart pulsatile ventricular assist device at the University of Florida, comparing those with acquired heart disease (n = 8) to those with congenital heart disease (CHD) (n = 28).

The primary outcome was mortality. The Kaplan-Meier method and log-rank tests were used to assess group differences in long-term survival after ventricular assist device insertion. T-tests using estimated survival proportions were used to compare groups at specific time points.

Of 82 patients supported with the Berlin Heart at our institution, 49 (49/82 = 59.76%) weighed <10 kg and 36 (36/82 = 43.90%) weighed <5 kg. Of 36 patients <5 kg, 26 (26/36 = 72.22%) were successfully bridged to transplantation. (The duration of support with ventricular assist device for these 36 patients <5 kg was [days]: median = 109, range = 4–305.) Eight out of 36 patients <5 kg had acquired heart disease, and all eight [8/8 = 100%] were successfully bridged to transplantation. (The duration of support with ventricular assist device for these 8 patients <5 kg with acquired heart disease was [days]: median = 50, range = 9–130.) Twenty-eight of 36 patients <5 kg had congenital heart disease. Eighteen of these 28 [64.3%] were successfully bridged to transplantation. (The duration of support with ventricular assist device for these 28 patients <5 kg with congenital heart disease was [days]: median = 136, range = 4–305.) For all 36 patients who weighed <5 kg: 1-year survival estimate after ventricular assist device insertion = 62.7% (95% confidence interval = 48.5–81.2%) and 5-year survival estimate after ventricular assist device insertion = 58.5% (95% confidence interval = 43.8–78.3%). One-year survival after ventricular assist device insertion = 87.5% (95% confidence interval = 67.3–99.9%) in acquired heart disease and 55.6% (95% confidence interval = 39.5–78.2%) in CHD, P = 0.036. Five-year survival after ventricular assist device insertion = 87.5% (95% confidence interval = 67.3–99.9%) in acquired heart disease and 48.6% (95% confidence interval = 31.6–74.8%) in CHD, P = 0.014.

Pulsatile ventricular assist device facilitates bridge to transplantation in neonates and infants weighing <5 kg; however, survival after ventricular assist device insertion in these small patients is less in those with CHD in comparison to those with acquired heart disease.

Global healthcare systems have been particularly impacted by the COVID-19 pandemic. Healthcare workers (HCWs) are widely reported to have experienced increased levels of baseline psychological distress relative to the general population, and the COVID-19 pandemic may have had an additive effect. However, previous studies are typically restricted to physicians and nurses with limited data available on hospital HCWs. We aimed to conduct a cross-sectional, psychological evaluation of Irish HCWs during COVID-19.

HCWs across five adult acute level-4 Dublin-based hospitals completed an online survey of wellbeing and COVID-19 experience.

There were 1898 HCWs who commenced the survey representing 10% of the total employee base. The sample comprised nurses (33%), doctors (21%), Health and Social Care Professionals (HSCPs) (24%) and ‘Other’ disciplines (22%), and 81% identified as female. Clinical levels of depression, anxiety and PTSD symptoms were endorsed by 31%, 34% and 28% of respondents, respectively. Professional grouping effects included: nurses reporting significantly greater levels of COVID-19 exposure, infection, COVID-fear, moral injury, and post-traumatic distress; HSCPs were significantly less likely to report mood dysfunction. In terms of gender, males were significantly less likely to report negative pandemic experiences, low resilience, and significantly more likely to endorse ‘minimal’ depression, anxiety, and traumatic distress. Logistic regression modelling revealed mental health outcomes (depression, anxiety and PTSD symptoms) were associated with increased frontline exposure, fewer career years’ experience, elevated pre-pandemic stress, and female gender.

To our knowledge, this is the largest evaluation of psychological wellbeing amongst HCWs in acute hospitals in the Dublin region. Our findings have implications for healthcare workforce wellbeing and future service delivery.

Publication bias has the potential to adversely impact clinical decision making and patient health if alternative decisions would have been made had there been complete publication of evidence.

The objective of our analysis was to determine if earlier publication of the complete evidence on rosiglitazone’s risk of myocardial infarction (MI) would have changed clinical decision making at an earlier point in time. We tested several methods for adjustment of publication bias to assess the impact of potential time delays to identifying the MI effect. We then performed a cumulative meta-analysis (CMA) for both published studies (published-only data set) and all studies performed (comprehensive data set). We then created an adjusted data set using existing methods of adjustment for publication bias (Harbord regression, Peter’s regression, and the nonparametric trim and fill method) applied to the limited data set. Finally, we compared the time to the decision threshold for each data set using CMA.

Although published-only and comprehensive data sets did not provide notably different final summary estimates [OR = 1.4 (95 percent confidence interval [CI]: .95–2.05) and 1.42 (95 percent CI: 1.03–1.97)], the comprehensive data set reached the decision threshold 36 months earlier than the published-only data set. All three adjustment methods tested did not show a differential time to decision threshold versus the published-only data set.

Complete access to studies capturing MI risk for rosiglitazone would have led to the evidence reaching a clinically meaningful decision threshold 3 years earlier.

We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes.

To improve the BSEEG method by introducing a new EEG device.

In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed.

We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality.

We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

We evaluated the early impact of a new hospital-based health technology assessment (HB-HTA) program, called Smart Innovation, at the University of Washington Medical Center (UWMC).

We compared the UWMC's utilization trends for two surgical procedures to control hospitals by evaluating the difference before and after adoption decisions: (i) a new filter for transcatheter aortic valve replacement (TAVR) procedures that treat aortic valve stenosis and (ii) microwave ablation (MWA) for treating hepatocellular carcinoma. We used descriptive statistics to assess the difference between the UWMC and controls for TAVR and MWA procedures and multivariate difference-in-differences (DID) analyses to test for statistical significance.

The UWMC experienced a 10 percent reduction in TAVR procedures compared with controls following the implementation of the TAVR Sentinel filter. The DID regression model indicated a 1.5 reduction in the number of TAVR procedures per quarter at the UWMC between the pre- and post period, which was not statistically significant (p-value: .87). The UWMC experienced a 51 percent reduction in utilization when compared with controls for MWA procedures in the pre- and post periods. The DID model for MWA indicated an 18.8 decrease in utilization per quarter during the study period for the UWMC, which was statistically significant (p-value: .0007). For MWA procedures, the UWMC experienced a $647,658 dollar reduction in total costs in the post period compared with controls.

When the UWMC used HB-HTA methods for technology adoption, there was a reduction in utilization and total costs when compared with controls; however, when the UWMC adopted a new technology without using HB-HTA methods, there was no difference in utilization.

We designed, developed, and implemented a new hospital-based health technology assessment (HB-HTA) program called Smart Innovation. Smart Innovation is a decision framework that reviews and makes technology adoption decisions. Smart Innovation was meant to replace the fragmented and complex process of procurement and adoption decisions at our institution. Because use of new medical technologies accounts for approximately 50 percent of the growth in healthcare spending, hospitals and integrated delivery systems are working to develop better processes and methods to sharpen their approach to adoption and management of high cost medical innovations.

The program has streamlined the decision-making process and added a robust evidence review for new medical technologies, aiming to balance efficiency with rigorous evidence standards. To promote system-wide adoption, the program engaged a broad representation of leaders, physicians, and administrators to gain support.

To date, Smart Innovation has conducted eleven HB-HTAs and made clinician-led adoption decisions that have resulted in over $5 million dollars in cost avoidance. These are comprised of five laboratory tests, three software-assisted systems, two surgical devices, and one capital purchase.

Smart Innovation has achieved cost savings, avoided uncertain or low-value technologies, and assisted in the implementation of new technologies that have strong evidence. The keys to its success have been the program's collaborative and efficient decision-making systems, partnerships with clinicians, executive support, and proactive role with vendors.

Race, psychiatric history, and adverse life events have all been independently associated with postpartum depression (PPD). However, the role these play together in Black and Latina women remains inadequately studied. Therefore, we performed a case–control study of PPD, including comprehensive assessments of symptoms and biomarkers, while examining the effects of genetic ancestry.

We recruited our sample (549 cases, 968 controls) at 6 weeks postpartum from obstetrical clinics in North Carolina. PPD status was determined using the MINI-plus. Psychiatric history was extracted from medical records. Participants were administered self-report instruments to assess depression (Edinburgh Postnatal Depression Scale) and adverse life events. Levels of estradiol, progesterone, brain-derived neurotrophic factor, oxytocin, and allopregnanalone were assayed. Principal components from genotype data were used to estimate genetic ancestry and logistic regression was used to identify predictors of PPD.

This population was racially diverse (68% Black, 13% Latina, 18% European). Genetic ancestry was not a predictor of PPD. Case status was predicted by a history of major depression (p = 4.01E-14), lifetime anxiety disorder diagnosis (p = 1.25E-34), and adverse life events (p = 6.06E-06). There were no significant differences between groups in any hormones or neurosteroids.

Psychiatric history and multiple exposures to adverse life events were significant predictors of PPD in a population of minority and low-income women. Genetic ancestry and hormone levels were not predictive of case status. Increased genetic vulnerability in conjunction with risk factors may predict the onset of PPD, whereas genetic ancestry does not appear predictive.

Universal screening for postpartum depression is recommended in many countries. Knowledge of whether the disclosure of depressive symptoms in the postpartum period differs across cultures could improve detection and provide new insights into the pathogenesis. Moreover, it is a necessary step to evaluate the universal use of screening instruments in research and clinical practice. In the current study we sought to assess whether the Edinburgh Postnatal Depression Scale (EPDS), the most widely used screening tool for postpartum depression, measures the same underlying construct across cultural groups in a large international dataset.

Ordinal regression and measurement invariance were used to explore the association between culture, operationalized as education, ethnicity/race and continent, and endorsement of depressive symptoms using the EPDS on 8209 new mothers from Europe and the USA.

Education, but not ethnicity/race, influenced the reporting of postpartum depression [difference between robust comparative fit indexes (∆*CFI) < 0.01]. The structure of EPDS responses significantly differed between Europe and the USA (∆*CFI > 0.01), but not between European countries (∆*CFI < 0.01).

Investigators and clinicians should be aware of the potential differences in expression of phenotype of postpartum depression that women of different educational backgrounds may manifest. The increasing cultural heterogeneity of societies together with the tendency towards globalization requires a culturally sensitive approach to patients, research and policies, that takes into account, beyond rhetoric, the context of a person's experiences and the context in which the research is conducted.

An argument often used to support the view that psychotic experiences (PEs) in general population samples are a valid phenotype for studying the aetiology of schizophrenia is that risk factors for schizophrenia show similar patterns of association with PEs. However, PEs often co-occur with depression, and no study has explicitly tested whether risk factors for schizophrenia are shared between PEs and depression, or are psychopathology specific, while jointly modelling both outcomes.

We used data from 7030 subjects from a birth cohort study. Depression and PEs at age 18 years were assessed using self-report questionnaires and semi-structured interviews. We compared the extent to which risk factors for schizophrenia across sociodemographic, familial, neurodevelopmental, stress–adversity, emotional–behavioural and substance use domains showed different associations with PEs and depression within bivariate models that allowed for their correlation.

Most of the exposures examined were associated, to a similar degree, with an increased risk of both outcomes. However, whereas female sex and family history of depression showed some discrimination as potential risk factors for depression and PEs, with stronger associations in the former, markers of abnormal neurodevelopment showed stronger associations with PEs.

The argument that PEs are valid markers for studying the aetiology of schizophrenia, made simply on the basis that they share risk factors in common, is not well supported. PEs seem to be a weak index of genetic and environmental risk for schizophrenia; however, studies disentangling aetiological pathways to PEs from those impacting upon co-morbid psychopathology might provide important insights into the aetiology of psychotic disorders.

Attention deficit hyperactivity disorder (ADHD) symptoms and autistic traits often occur together. The pattern and etiology of co-occurrence are largely unknown, particularly in adults. This study investigated the co-occurrence between both traits in detail, and subsequently examined the etiology of the co-occurrence, using two independent adult population samples.

Data on ADHD traits (Inattention and Hyperactivity/Impulsivity) were collected in a population sample (S1, n = 559) of unrelated individuals. Data on Attention Problems (AP) were collected in a population-based family sample of twins and siblings (S2, n = 560). In both samples five dimensions of autistic traits were assessed (social skills, routine, attentional switching, imagination, patterns).

Hyperactive traits (S1) did not correlate substantially with the autistic trait dimensions. For Inattention (S1) and AP (S2), the correlations with the autistic trait dimensions were low, apart from a prominent correlation with the attentional switching scale (0.47 and 0.32 respectively). Analyses in the genetically informative S2 revealed that this association could be explained by a shared genetic factor.

Our findings suggest that the co-occurrence of ADHD traits and autistic traits in adults is not determined by problems with hyperactivity, social skills, imagination or routine preferences. Instead, the association between those traits is due primarily to shared attention-related problems (inattention and attentional switching capacity). As the etiology of this association is purely genetic, biological pathways involving attentional control could be a promising focus of future studies aimed at unraveling the genetic causes of these disorders.