Experiences of Mothers of Preterm Infants in the Neonatal Intensive Care Unit During the COVID-19 Pandemic.

BACKGROUND: The neonatal intensive care unit (NICU) stay following the birth of a preterm infant can be stressful and traumatic for families. During the COVID-19 pandemic, the NICU environment changed precipitously as infection control and visitor restriction measures were implemented. PURPOSE: Our study aimed to examine the impact of the pandemic policies on the experiences of mothers of preterm infants during their stay in the NICU. METHODS: Semistructured interviews were conducted with mothers of preterm infants hospitalized in a Canadian tertiary-level NICU. Informed by interpretive description methodology, interview content was transcribed and analyzed using a thematic analysis approach. The identified themes were validated, clarified, or refined using investigator triangulation. RESULTS: Nine English-speaking mothers, aged 28 to 40 years, were interviewed. Four themes emerged from the analysis of their experiences: (1) disrupted family dynamic, support, and bonding; (2) physical and emotional isolation; (3) negative psychological impact compounded by added concerns, maternal role change, and survival mode mentality; and (4) positive aspects of the pandemic management measures. IMPLICATIONS FOR PRACTICE: During the pandemic, the way that care was provided in the NICU changed. This study helps to explore how neonatal clinicians can foster individual and organizational resilience to keep patients and families at the center of care, even when the healthcare system is under intense stress. IMPLICATIONS FOR RESEARCH: : Our results show that these changes heightened mothers' distress, but also had a modest positive impact. Further research about long-term consequences of pandemic policies on the mother and preterm infant after NICU discharge is warranted.

The brain frequency tuning function for facial emotion discrimination: An ssVEP study.

Steady-state visual evoked potentials have only been applied recently to the study of face perception. We used this method to study the spatial and temporal dynamics of expression perception in the human brain and test the prediction that, as in the case of identity perception, the optimal frequency for facial expression would also be in the range of 5-6 Hz. We presented facial expressions at different flickering frequencies (2-8 Hz) to human observers while recording their brain electrical activity. Our modified adaptation paradigm contrasted blocks with varying expressions versus blocks with a constant neutral expression, while facial identity was kept constant. The presentation of different expressions created a larger steady-state response only at 5 Hz, corresponding to a cycle of 200 ms, over right occipito-temporal electrodes. Source localization using a time-domain analysis showed that the effect localized to the right occipito-temporal cortex, including the superior temporal sulcus and fusiform gyrus.

Interactions between the perception of age and ethnicity in faces: an event-related potential study.

Face perception models propose that different facial attributes are processed by anatomically distinct neural pathways that partially overlap. Whether these attributes interact functionally is an open question. Our goal was to determine if there are interactions between age and ethnicity processing and, if so, at what temporal epoch these interactions are evident. We monitored event-related potentials on electroencephalography while subjects categorized faces by age or ethnicity in two conditions: a baseline in which the other of these two properties not being categorized was held constant and an interference condition in which it also varied, as modelled after the Garner interference paradigm. We found that, when participants were categorizing faces by age, variations in ethnicity increased the amplitude of the right face-selective N170 component. When subjects were categorizing faces by ethnicity, variations in age did not alter the N170. We concluded that there is an asymmetric pattern of influence between age and ethnicity on early face-specific stages of visual processing, which has parallels with behavioural evidence of asymmetric interactions between identity and expression processing of faces.

Temporal dynamics of the face familiarity effect: bootstrap analysis of single-subject event-related potential data.

Prior event-related potential studies using group statistics within a priori selected time windows have yielded conflicting results about familiarity effects in face processing. Our goal was to evaluate the temporal dynamics of the familiarity effect at all time points at the single-subject level. Ten subjects were shown faces of anonymous people or celebrities. Individual results were analysed using a point-by-point bootstrap analysis. While familiarity effects were less consistent at later epochs, all subjects showed them between 130 and 195 ms in occipitotemporal electrodes. However, the relation between the time course of familiarity effects and the peak latency of the N170 was variable. We concluded that familiarity effects between 130 and 195 ms are robust and can be shown in single subjects. The variability of their relation to the timing of the N170 potential may lead to underestimation of familiarity effects in studies that use group-based statistics.

COVID-19 Outbreak: Understanding Moral-Distress Experiences Faced by Healthcare Workers in British Columbia, Canada.

Pandemic-management plans shift the care model from patient-centred to public-centred and increase the risk of healthcare workers (HCWs) experiencing moral distress (MD). This study aimed to understand HCWs' MD experiences during the COVID-19 pandemic and to identify HCWs' preferred coping strategies. Based on a qualitative research methodology, three surveys were distributed at different stages of the pandemic response in British Columbia (BC), Canada. The thematic analysis of the data revealed common MD themes: concerns about ability to serve patients and about the risks intrinsic to the pandemic. Additionally, it revealed that COVID-19 fatigue and collateral impact of COVID-19 were important ethical challenges faced by the HCWs who completed the surveys. These experiences caused stress, anxiety, increased/decreased empathy, sleep disturbances, and feelings of helplessness. Respondents identified self-care and support provided by colleagues, family members, or friends as their main MD coping mechanisms. To a lesser extent, they also used formal sources of support provided by their employer and identified additional strategies they would like their employers to implement (e.g., improved access to mental health and wellness resources). These results may help inform pandemic policies for the future.

Whole blood genome-wide transcriptome profiling and metagenomics next-generation sequencing in young infants with suspected sepsis in a low-and middle-income country: A study protocol.

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression.

Importance: Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient's response to treatment could significantly reduce the burden of depression. Objective: To estimate how accurately an outcome of escitalopram treatment can be predicted from electroencephalographic (EEG) data on patients with depression. Design, Setting, and Participants: This prognostic study used a support vector machine classifier to predict treatment outcome using data from the first Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study. The CAN-BIND-1 study comprised 180 patients (aged 18-60 years) diagnosed with major depressive disorder who had completed 8 weeks of treatment. Of this group, 122 patients had EEG data recorded before the treatment; 115 also had EEG data recorded after the first 2 weeks of treatment. Interventions: All participants completed 8 weeks of open-label escitalopram (10-20 mg) treatment. Main Outcomes and Measures: The ability of EEG data to predict treatment outcome, measured as accuracy, specificity, and sensitivity of the classifier at baseline and after the first 2 weeks of treatment. The treatment outcome was defined in terms of change in symptom severity, measured by the Montgomery-Åsberg Depression Rating Scale, before and after 8 weeks of treatment. A patient was designated as a responder if the Montgomery-Åsberg Depression Rating Scale score decreased by at least 50% during the 8 weeks and as a nonresponder if the score decrease was less than 50%. Results: Of the 122 participants who completed a baseline EEG recording (mean [SD] age, 36.3 [12.7] years; 76 [62.3%] female), the classifier was able to identify responders with an estimated accuracy of 79.2% (sensitivity, 67.3%; specificity, 91.0%) when using only the baseline EEG data. For a subset of 115 participants who had additional EEG data recorded after the first 2 weeks of treatment, use of these data increased the accuracy to 82.4% (sensitivity, 79.2%; specificity, 85.5%). Conclusions and Relevance: These findings demonstrate the potential utility of EEG as a treatment planning tool for escitalopram therapy. Further development of the classification tools presented in this study holds the promise of expediting the search for optimal treatment for each patient.

Relationship between work functioning and self-reported cognitive complaints in patients with major depressive disorder treated with desvenlafaxine.

Patients with major depressive disorder (MDD) often report that cognitive difficulties, such as memory problems or poor concentration, interfere with their work functioning. We examined the association between self-reported cognitive complaints and work functioning in employed patients with MDD treated with desvenlafaxine. A sample of 36 adult outpatients with MDD completed subjective cognition (British Columbia Cognitive Complaints Inventory [BC-CCI]) and functioning scales (Sheehan Disability Scale [SDS]; Lam Employment Absence and Productivity Scale [LEAPS]; and Health and Work Performance Questionnaire [HPQ]) before and after 8 weeks of open-label treatment with flexibly-dosed desvenlafaxine (50-100 mg/day). Multiple regression analyses were used to assess the relationship between subjective cognitive measures and work functioning scales. Patients showed significant improvements in clinical, cognitive, and work functioning measures following treatment with desvenlafaxine. A predictive association was found between the BC-CCI and both the SDS and LEAPS, but not with the HPQ, when adjusted for depression severity. Self-report cognitive questionnaires can provide useful information to monitor changes in cognitive functioning over time and to predict improvement in work functioning outcomes.

The 6 Hz fundamental stimulation frequency rate for individual face discrimination in the right occipito-temporal cortex.

What is the stimulus presentation rate at which the human brain can discriminate each exemplar of a familiar visual category? We presented faces at 14 frequency rates (1.0-16.66 Hz) to human observers while recording high-density electroencephalogram (EEG). Different face exemplars elicited a larger steady-state visual evoked (ssVEP) response than when the same face was repeated, but only for stimulation frequencies between 4 and 8.33 Hz, with a maximal difference at 5.88 Hz (170 ms cycle). The effect was confined to the exact stimulation frequency and localized over the right occipito-temporal cortex. At high frequency rates (>10 Hz), the response to different and identical exemplars did not differ, suggesting that the fine-grained analysis needed for individual face discrimination cannot be completed before the next face interrupts, or competes, with the processed face. At low rates (<3 Hz), repetition suppression could not be identified at the stimulation frequency, suggesting that the neural response to an individual face is temporally dispersed and distributed over different processes. These observations indicate that at a temporal rate of 170 ms (6 faces/s) the face perception network is able to fully discriminate between each individual face presented, providing information about the temporal bottleneck of individual face discrimination in humans. These results also have important practical implications for optimizing paradigms that rely on repetition suppression, and open an avenue for investigating complex visual processes at an optimal range of stimulation frequency rates.