The effect of SARS-COV-2 variant on non-respiratory features and mortality among vaccinated and non-fully vaccinated patients.

OBJECTIVE: To determine the effect of SARS-CoV-2 variants on non-respiratory features of COVID-19 in vaccinated and not fully vaccinated patients using a University of California database. METHODS: A longitudinal retrospective review of medical records (n = 63,454) from 1/1/2020-4/26/2022 using the UCCORDS database was performed to compare non-respiratory features, vaccination status, and mortality between variants. Chi-square tests were used to study the relationship between categorical variables using a contingency matrix. RESULTS: Fever was the most common feature across all variants. Fever was significantly higher in not fully vaccinated during the Delta and Omicron waves (p = 0.001; p = 0.001). Cardiac features were statistically higher in not fully vaccinated during Omicron; tachycardia was only a feature of not fully vaccinated during Delta and Omicron; diabetes and GI reflux were features of all variants regardless of vaccine status. Odds of death were significantly increased among those not fully vaccinated in the Delta and Omicron variants (Delta OR: 1.64, p = 0.052; Omicron OR: 1.96, p < 0.01). Vaccination was associated with a decrease in the frequency of non-respiratory features. CONCLUSIONS: Risk of non-respiratory features of COVID-19 is statistically higher in those not fully vaccinated across all variants. Risk of death and correlation with vaccination status varied.

Parenting Expectations, NICU Experiences, and Maternal Psychological Outcomes: An Exploratory Mixed-Methods Study.

BACKGROUND: Infant neonatal intensive care unit (NICU) hospitalization increases maternal risk for psychological distress. However, no universal screening standards exist and predicting maternal risk remains challenging. Reconceptualizing maternal distress in relation to differences between parenting expectations and NICU experiences may illuminate commonalities across a range of experiences. PURPOSE: This study explored parenting expectation-experience differences (EEDs) among NICU mothers and assessed correlations between EED scores and psychological outcomes 1 to 5 years post-NICU hospitalization. METHODS: A 3-phase explanatory sequential mixed-methods design was used. Pearson's correlation coefficients were used to measure relationships between EED scores and maternal psychological outcomes. Reflexive thematic analysis of one-on-one, semi-structured interviews contextualized EED scores. RESULTS: Most participants (92.9%) reported negative EED scores, indicating NICU experiences fell short of parenting expectations. Significant inverse correlations were found between EED scores and maternal outcomes, including depression ( r = -0.25, P < .01), anxiety ( r = -0.25, P < .01) and posttraumatic stress disorder symptoms ( r = -0.41, P < .001), and perceived parenting self-efficacy ( r = -0.28, P < .01). Major qualitative themes included unexpected versus prepared, lost parenting experiences, and surviving and thriving. Data synthesis contextualized EED scores and revealed key differences in meaning ascribed to unmet parenting expectations. IMPLICATIONS FOR PRACTICE AND RESEARCH: Preparing mothers for infant NICU hospitalization and creating a NICU parenting environment, which better supports mothers and their engagement in parenting tasks, may help to reduce differences between parenting expectations and NICU experiences. Further research is needed to elucidate the impacts of parenting EEDs in this population.

Using Causal Inference to Estimate the Effect of Pre-Exposure Prophylaxis (PrEP) for HIV Prevention on COVID-19 Mortality.

Traditional machine learning (ML) approaches learn to recognize patterns in the data but fail to go beyond observing associations. Such data-driven methods can lack generalizability when the data is outside the independent and identically distributed (i.i.d) setting. Using causal inference can aid data-driven techniques to go beyond learning spurious associations and frame the data-generating process in a causal lens. We can combine domain expertise and traditional ML techniques to answer causal questions on the data. In this paper, we estimate the causal effect of Pre-Exposure Prophylaxis (PrEP) on mortality in COVID-19 patients from an observational dataset of over 120,000 patients. With the help of medical experts, we hypothesize a causal graph that identifies the causal and non-causal associations, including the list of potential confounding variables. We use estimation techniques such as linear regression, matching, and machine learning (meta-learners) to estimate the causal effect. On average, our estimates show that taking PrEP can result in a 2.1% decrease in the death rate or a total of around 2,540 patients' lives saved in the studied population.

How do the Social Determinants of Health Impact the Post-Acute Sequelae of COVID-19: A Critical Review.

The review critically analyzes the social determinants of health (SDOH) variables in the current literature of patients with post-acute sequelae (PASC) of COVID-19 in the United States. Race, gender, and age were discussed as well as health outcomes, severity of illness, and phenotypes of long-COVID. Most research was retrospectively with samples that had access to health insurance, which did not capture populations with poor or no access to health care. More research is needed that directly addresses the impact on SDOH on PASC. The current literature is sparse and provides little actionable information.

Application of Trauma-Informed Care Principles to Care Needs Identified by Mothers of NICU-Hospitalized Children.

Systematic uptake of family-centered care (FCC) interventions remains challenging and frequently suboptimal in many neonatal intensive care units (NICUs). Across NICUs in the United States, integrating family members as partners in infant caregiving and decision-making has not been well supported and routine screening and provision of psychological support for parents remains inadequate. Trauma-informed care (TIC) may offer a more comprehensive approach to NICU care which can encompass FCC principles and promote family recovery and resilience by recognizing and responding to the traumas experienced by NICU infants and families. The current paper aimed to understand needs identified by mothers of NICU-hospitalized children and reports a focused analysis of one-on-one interview data (n = 13 mothers) collected during a larger mixed methods study. Reflexive thematic analysis was used to understand needs identified by mothers and to explore how these needs aligned with TIC principles. Six themes were identified and subsequently examined in the context of the principles of TIC: I Just Had No Control, That Really Caught Us Off Guard, So Much Was Already Taken Away, We're People and There Needs To Be More Support and Practices Which Helped. Mothers' care needs were found to align with TIC principles. Findings suggest that implementation of TIC principles in NICU settings can support parental presence, participation in infant care, and mental health and support the potential of TIC as a more comprehensive approach to meeting the needs of NICU parents.

The Effect of COVID-19 Public Health Measures On Mental Health in California.

California was the first state to implement statewide public health measures, including lockdown and curfews, to mitigate transmission of SARS-CoV-2. The implementation of these public health measures may have had unintended consequences related to mental health for persons in California. This study is a retrospective review of electronic health records of patients who sought care in the University of California Health System to examine changes in mental health status during the pandemic. Data were extracted prior to the pandemic (March-October 2019) and during the pandemic (March-October 2020). Weekly values of new mental health disorders were extracted and further classified based on age. Paired t-tests were performed to test for differences in the occurrence of each mental health disorder for each age group. A two-way ANOVA was performed to assess for between group differences. When compared with pre-pandemic diagnoses, persons aged 26-35 had the greatest increase in mental health diagnoses overall during the pandemic, specifically for anxiety, bipolar disorder, depression, mood disturbance, and psychosis. The mental health of persons age 25-35 were more affected than any other age group.

The effect of SARS-CoV-2 variant on respiratory features and mortality.

SARS-CoV-2 (COVID-19) has caused over 80 million infections 973,000 deaths in the United States, and mutations are linked to increased transmissibility. This study aimed to determine the effect of SARS-CoV-2 variants on respiratory features, mortality, and to determine the effect of vaccination status. A retrospective review of medical records (n = 55,406 unique patients) using the University of California Health COvid Research Data Set (UC CORDS) was performed to identify respiratory features, vaccination status, and mortality from 01/01/2020 to 04/26/2022. Variants were identified using the CDC data tracker. Increased odds of death were observed amongst unvaccinated individuals and fully vaccinated, partially vaccinated, or individuals who received any vaccination during multiple waves of the pandemic. Vaccination status was associated with survival and a decreased frequency of many respiratory features. More recent SARS-CoV-2 variants show a reduction in lower respiratory tract features with an increase in upper respiratory tract features. Being fully vaccinated results in fewer respiratory features and higher odds of survival, supporting vaccination in preventing morbidity and mortality from COVID-19.

The other COVID-19 survivors: Timing, duration, and health impact of post-acute sequelae of SARS-CoV-2 infection.

AIMS AND OBJECTIVES: To determine the frequency, timing, and duration of post-acute sequelae of SARS-CoV-2 infection (PASC) and their impact on health and function. BACKGROUND: Post-acute sequelae of SARS-CoV-2 infection is an emerging major public health problem that is poorly understood and has no current treatment or cure. PASC is a new syndrome that has yet to be fully clinically characterised. DESIGN: Descriptive cross-sectional survey (n = 5163) was conducted from online COVID-19 survivor support groups who reported symptoms for more than 21 days following SARS-CoV-2 infection. METHODS: Participants reported background demographics and the date and method of their covid diagnosis, as well as all symptoms experienced since onset of covid in terms of the symptom start date, duration, and Likert scales measuring three symptom-specific health impacts: pain and discomfort, work impairment, and social impairment. Descriptive statistics and measures of central tendencies were computed for participant demographics and symptom data. RESULTS: Participants reported experiencing a mean of 21 symptoms (range 1-93); fatigue (79.0%), headache (55.3%), shortness of breath (55.3%) and difficulty concentrating (53.6%) were the most common. Symptoms often remitted and relapsed for extended periods of time (duration M = 112 days), longest lasting symptoms included the inability to exercise (M = 106.5 days), fatigue (M = 101.7 days) and difficulty concentrating, associated with memory impairment (M = 101.1 days). Participants reported extreme pressure at the base of the head, syncope, sharp or sudden chest pain, and "brain pressure" among the most distressing and impacting daily life. CONCLUSIONS: Post-acute sequelae of SARS-CoV-2 infection can be characterised by a wide range of symptoms, many of which cause moderate-to-severe distress and can hinder survivors' overall well-being. RELEVANCE TO CLINICAL PRACTICE: This study advances our understanding of the symptoms of PASC and their health impacts.

COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler Looking for Clarity in the Haze of the Pandemic.

Post-acute sequelae of SARS-CoV-2 (PASC) is defined as persistent symptoms after apparent recovery from acute COVID-19 infection, also known as COVID-19 long-haul. We performed a retrospective review of electronic health records (EHR) from the University of California COvid Research Data Set (UC CORDS), a de-identified EHR of PCR-confirmed SARS-CoV-2-positive patients in California. The purposes were to (1) describe the prevalence of PASC, (2) describe COVID-19 symptoms and symptom clusters, and (3) identify risk factors for PASC. Data were subjected to non-negative matrix factorization to identify symptom clusters, and a predictive model of PASC was developed. PASC prevalence was 11% (277/2,153), and of these patients, 66% (183/277) were considered asymptomatic at days 0-30. Five PASC symptom clusters emerged and specific symptoms at days 0-30 were associated with PASC. Women were more likely than men to develop PASC, with all age groups and ethnicities represented. PASC is a public health priority.

A distinct symptom pattern emerges for COVID-19 long-haul: a nationwide study.

Long-haul COVID-19, also called post-acute sequelae of SARS-CoV-2 (PASC), is a new illness caused by SARS-CoV-2 infection and characterized by the persistence of symptoms. The purpose of this cross-sectional study was to identify a distinct and significant temporal pattern of PASC symptoms (symptom type and onset) among a nationwide sample of PASC survivors (n = 5652). The sample was randomly sorted into two independent samples for exploratory (EFA) and confirmatory factor analyses (CFA). Five factors emerged from the EFA: (1) cold and flu-like symptoms, (2) change in smell and/or taste, (3) dyspnea and chest pain, (4) cognitive and visual problems, and (5) cardiac symptoms. The CFA had excellent model fit (x2 = 513.721, df = 207, p < 0.01, TLI = 0.952, CFI = 0.964, RMSEA = 0.024). These findings demonstrate a novel symptom pattern for PASC. These findings can enable nurses in the identification of at-risk patients and facilitate early, systematic symptom management strategies for PASC.

A novel conceptual model of trauma-informed care for patients with post-acute sequelae of SARS-CoV-2 illness (PASC).

AIM: This paper proposes a novel, trauma-informed, conceptual model of care for Post-Acute Sequelae of COVID-19 illness (PASC). DESIGN: This paper describes essential elements, linkages and dimensions of the model that affect PASC patient experiences and the potential impact of trauma-informed care on outcomes. DATA SOURCES: PASC is a consequence of the global pandemic, and a new disease of which little is known. Our model was derived from the limited available studies, expert clinical experience specific to PASC survivors and publicly available social media narratives authored by PASC survivors. IMPLICATIONS FOR NURSING: The model provides a critical and novel framework for the understanding and care of persons affected by PASC. This model is aimed at the provision of nursing care, with the intention of reducing the traumatic impacts of the uncertain course of this disease, a lack of defined treatment options and difficulties in seeking care. The use of a trauma-informed care approach to PASC patients can enhance nurses' ability to remediate and ameliorate both the traumatic burden of and the symptoms and experience of the illness. CONCLUSION: Applying a trauma-informed perspective to care of PASC patients can help to reduce the overall burden of this complex condition. Owing to the fundamentally holistic perspective of the nursing profession, nurses are best positioned to implement care that addresses multiple facets of the PASC experience. IMPACT: The proposed model specifically addresses the myriad ways in which PASC may affect physical as well as mental and psychosocial dimensions of health. The model particularly seeks to suggest means of supporting patients who have already experienced a life-threatening illness and are now coping with its long-term impact. Since the scope of this impact is not yet defined, trauma-informed care for PASC patients is likely to reduce the overall health and systems burdens of this complex condition.

Antihistamines for Postacute Sequelae of SARS-CoV-2 Infection.

Postacute sequelae of SARS-CoV2 (PASC) infection is an emerging global health crisis, variably affecting millions worldwide. PASC has no established treatment. We describe 2 cases of PASC in response to opportune administration of over-the-counter antihistamines, with significant improvement in symptoms and ability to perform activities of daily living. Future studies are warranted to understand the potential role of histamine in the pathogenesis of PASC and explore the clinical benefits of antihistamines in the treatment of PASC.

Mechanisms and Methods to Understand Depressive Symptoms.

Depressive symptoms, feelings of sadness, anger, and loss that interfere with a person's daily life, are prevalent health concerns across populations that significantly result in adverse health outcomes with direct and indirect economic burdens at a national and global level. This article aims to synthesize known mechanisms of depressive symptoms and the established and emerging methodologies used to understand depressive symptoms; implications and directions for future nursing research are discussed. A comprehensive search was performed by Cumulative Index to Nursing and Allied Health Literature, MEDLINE, and PUBMED databases between 2000-2021 to examine contributing factors of depressive symptoms. Many environmental, psychological, and physiological factors are associated with the development or increased severity of depressive symptoms (anhedonia, fatigue, sleep and appetite disturbances to depressed mood). This paper discusses biological and psychological theories that guide our understanding of depressive symptoms, as well as known biomarkers (gut microbiome, specific genes, multi-cytokine, and hormones) and established and emerging methods. Disruptions within the nervous system, hormonal and neurotransmitters levels, brain structure, gut-brain axis, leaky-gut syndrome, immune and inflammatory process, and genetic variations are significant mediating mechanisms in depressive symptomology. Nursing research and practice are at the forefront of furthering depressive symptoms' mechanisms and methods. Utilizing advanced technology and measurement tools (big data, machine learning/artificial intelligence, and multi-omic approaches) can provide insight into the psychological and biological mechanisms leading to effective intervention development. Thus, understanding depressive symptomology provides a pathway to improve patients' health outcomes, leading to reduced morbidity and mortality and the overall nation-wide economic burden.Supplemental data for this article is available online at https://doi.org/10.1080/01612840.2021.1998261 .