Nursing Variables Predicting Readmissions in Patients With a High Risk: A Scoping Review.

Unplanned readmission endangers patient safety and increases unnecessary healthcare expenditure. Identifying nursing variables that predict patient readmissions can aid nurses in providing timely nursing interventions that help patients avoid readmission after discharge. We aimed to provide an overview of the nursing variables predicting readmission of patients with a high risk. The authors searched five databases-PubMed, CINAHL, EMBASE, Cochrane Library, and Scopus-for publications from inception to April 2023. Search terms included "readmission" and "nursing records." Eight studies were included for review. Nursing variables were classified into three categories-specifically, nursing assessment, nursing diagnosis, and nursing intervention. The nursing assessment category comprised 75% of the nursing variables; the proportions of the nursing diagnosis (25%) and nursing intervention categories (12.5%) were relatively low. Although most variables of the nursing assessment category focused on the patients' physical aspect, emotional and social aspects were also considered. This study demonstrated how nursing care contributes to patients' adverse outcomes. The findings can assist nurses in identifying the essential nursing assessment, diagnosis, and interventions, which should be provided from the time of patients' admission. This can mitigate preventable readmissions of patients with a high risk and facilitate their safe transition from an acute care setting to the community.

Active sensing with predictive coding and uncertainty minimization.

We present an end-to-end architecture for embodied exploration inspired by two biological computations: predictive coding and uncertainty minimization. The architecture can be applied to any exploration setting in a task-independent and intrinsically driven manner. We first demonstrate our approach in a maze navigation task and show that it can discover the underlying transition distributions and spatial features of the environment. Second, we apply our model to a more complex active vision task, whereby an agent actively samples its visual environment to gather information. We show that our model builds unsupervised representations through exploration that allow it to efficiently categorize visual scenes. We further show that using these representations for downstream classification leads to superior data efficiency and learning speed compared to other baselines while maintaining lower parameter complexity. Finally, the modular structure of our model facilitates interpretability, allowing us to probe its internal mechanisms and representations during exploration.

Stimulus type shapes the topology of cellular functional networks in mouse visual cortex.

On the timescale of sensory processing, neuronal networks have relatively fixed anatomical connectivity, while functional interactions between neurons can vary depending on the ongoing activity of the neurons within the network. We thus hypothesized that different types of stimuli could lead those networks to display stimulus-dependent functional connectivity patterns. To test this hypothesis, we analyzed single-cell resolution electrophysiological data from the Allen Institute, with simultaneous recordings of stimulus-evoked activity from neurons across 6 different regions of mouse visual cortex. Comparing the functional connectivity patterns during different stimulus types, we made several nontrivial observations: (1) while the frequencies of different functional motifs were preserved across stimuli, the identities of the neurons within those motifs changed; (2) the degree to which functional modules are contained within a single brain region increases with stimulus complexity. Altogether, our work reveals unexpected stimulus-dependence to the way groups of neurons interact to process incoming sensory information.

Temporal resolution of spike coding in feedforward networks with signal convergence and divergence.

Convergent and divergent structures in the networks that make up biological brains are found universally across many species and brain regions at various scales. Neurons in these networks fire action potentials, or "spikes", whose precise timing is becoming increasingly appreciated as large sources of information about both sensory input and motor output. While previous theories on coding in convergent and divergent networks have largely neglected the role of precise spike timing, our model and analyses place this aspect at the forefront. For a suite of stimuli with different timescales, we demonstrate that structural bottlenecks (small groups of neurons) post-synaptic to network convergence have a stronger preference for spike timing codes than expansion layers created by structural divergence. Additionally, we found that a simple network model with similar convergence and divergence ratios to those found experimentally can reproduce the relative contribution of spike timing information about motor output in the hawkmoth Manduca sexta. Our simulations and analyses suggest a relationship between the level of convergent/divergent structure present in a feedforward network and the loss of stimulus information encoded by its population spike trains as their temporal resolution decreases, which could be confirmed experimentally across diverse neural systems in future studies. We further show that this relationship can be generalized across different models and measures, implying a potentially fundamental link between network structure and coding strategy using spikes.

Exploring the Architectural Biases of the Canonical Cortical Microcircuit.

The cortex plays a crucial role in various perceptual and cognitive functions, driven by its basic unit, the canonical cortical microcircuit. Yet, we remain short of a framework that definitively explains the structure-function relationships of this fundamental neuroanatomical motif. To better understand how physical substrates of cortical circuitry facilitate their neuronal dynamics, we employ a computational approach using recurrent neural networks and representational analyses. We examine the differences manifested by the inclusion and exclusion of biologically-motivated inter-areal laminar connections on the computational roles of different neuronal populations in the microcircuit of two hierarchically-related areas, throughout learning. Our findings show that the presence of feedback connections correlates with the functional modularization of cortical populations in different layers, and provides the microcircuit with a natural inductive bias to differentiate expected and unexpected inputs at initialization. Furthermore, when testing the effects of training the microcircuit and its variants with a predictive-coding inspired strategy, we find that doing so helps better encode noisy stimuli in areas of the cortex that receive feedback, all of which combine to suggest evidence for a predictive-coding mechanism serving as an intrinsic operative logic in the cortex.

Limited Sustained Remission After Nucleos(t)ide Analog Withdrawal: Results From a Large, Global, Multiethnic Cohort of Patients With Chronic Hepatitis B (RETRACT-B Study).

INTRODUCTION: Complete viral suppression with nucleos(t)ide analogs (NAs) has led to a profound reduction in hepatocellular carcinoma and mortality among patients with chronic hepatitis B. Finite therapy yields higher rates of functional cure; however, initial hepatitis B virus (HBV) DNA and alanine aminotransferase (ALT) elevations are almost certain after treatment interruption. We aimed to analyze off-treatment outcomes beyond 12 months after NA cessation. METHODS: Patients with well-suppressed chronic hepatitis B who were hepatitis B e antigen-negative at NA cessation and remained off treatment without hepatitis B surface antigen (HBsAg) loss at 12 months were included (n = 945). HBV DNA and ALT fluctuations were allowed within the first 12 months. We used Kaplan-Meier methods to analyze outcomes beyond 12 months. Sustained remission was defined as HBV DNA <2,000 IU/mL and ALT <2× upper limit of normal (ULN) and an ALT flare as ALT ≥5× ULN. RESULTS: Cumulative probability of sustained remission was 29.7%, virological relapse was 65.2% with a mean peak HBV DNA of 5.0 ± 1.5 log 10 IU/mL, an ALT flare was 15.6% with a median peak ALT × ULN of 8.3 (5.7-11.3), HBsAg loss was 9.9% and retreatment was 34.9% at 48 months after NA cessation. A single occurrence of virological relapse or an ALT flare within the first 12 months off-treatment were associated with significantly lower rates of sustained remission beyond 12 months. DISCUSSION: Despite allowing for HBV DNA and ALT fluctuations within the first 12 months off-treatment, most patients without HBsAg loss did not maintain a sustained response thereafter. The best candidates for NA withdrawal are patients with low HBsAg levels at NA cessation, and those without profound or recurrent virological and biochemical relapses in the first off-treatment year.

White matter microstructure of children with sensory over-responsivity is associated with affective behavior.

BACKGROUND: Sensory processing dysfunction (SPD) is linked to altered white matter (WM) microstructure in school-age children. Sensory over-responsivity (SOR), a form of SPD, affects at least 2.5% of all children and has substantial deleterious impact on learning and mental health. However, SOR has not been well studied using microstructural imaging such as diffusion MRI (dMRI). Since SOR involves hypersensitivity to external stimuli, we test the hypothesis that children with SOR require compensatory neuroplasticity in the form of superior WM microstructural integrity to protect against internalizing behavior, leaving those with impaired WM microstructure vulnerable to somatization and depression. METHODS: Children ages 8-12 years old with neurodevelopmental concerns were assessed for SOR using a comprehensive structured clinical evaluation, the Sensory Processing 3 Dimensions Assessment, and underwent 3 Tesla MRI with multishell multiband dMRI. Tract-based spatial statistics was used to measure diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics from global WM and nineteen selected WM tracts. Correlations of DTI and NODDI measures with measures of somatization and emotional disturbance from the Behavioral Assessment System for Children, 3rd edition (BASC-3), were computed in the SOR group and in matched children with neurodevelopmental concerns but not SOR. RESULTS: Global WM fractional anisotropy (FA) is negatively correlated with somatization and with emotional disturbance in the SOR group but not the non-SOR group. Also observed in children with SOR are positive correlations of radial diffusivity (RD) and free water fraction (FISO) with somatization and, in most cases, emotional disturbance. These effects are significant in boys with SOR, whereas the study is underpowered for girls. The most affected white matter are medial lemniscus and internal capsule sensory tracts, although effects of SOR are observed in many cerebral, cerebellar, and brainstem tracts. CONCLUSION: White matter microstructure is related to affective behavior in children with SOR.

On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks.

Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network's baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory. Our study based on extensive bifurcation analyses thus reveal the functional optimality and criticality of structural and physiological parameters in establishing the baseline operating state of local cortical networks.

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity.

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

Giant primary intracranial multi-fossa leiomyosarcoma involving the frontal sinus, ethmoid air cells, anterior fossa, middle fossa, and intraventricular space: A case report and literature review.

Background: Leiomyosarcomas (LMSs) is a type of sarcoma that arises from smooth muscle and generally presents in the abdomen. Although intracranial LMS has been identified before, most reported presentations have been in immunocompromised patients. Here, we present an intracranial LMS in an immunocompetent patient. Case Description: A 22-year-old male with a history of an atypical pineal parenchymal tumor of intermediate differentiation resected by suboccipital craniotomy at the age of 12 followed by adjuvant radiation therapy, presented with 3 weeks of decreased appetite, weight loss, and lethargy. He subsequently underwent transbasal approach skull base tumor resection. Histologic examination of the mass along with the patient's history of radiation was supportive of a low-grade, radiation-induced LMS arising from the anterior fossa of the skull or meninges and extends to the frontal sinus and ethmoid air cells. Conclusion: Primary intracranial LMS is an extremely rare diagnosis and presenting symptoms vary with the location and size of the tumor. Due to the poor specificity of clinical symptoms, diagnosis is often based on histology. The most common treatment is surgical resection. Adjuvant chemotherapy with various agents has been found to be somewhat effective outside the central nervous system. When LMS does occur, a history of immunocompromised state or previous radiation exposure is often present. Pathological confirmation is required for an appropriate diagnosis.

Stimulus-dependent functional network topology in mouse visual cortex.

Information is processed by networks of neurons in the brain. On the timescale of sensory processing, those neuronal networks have relatively fixed anatomical connectivity, while functional connectivity, which defines the interactions between neurons, can vary depending on the ongoing activity of the neurons within the network. We thus hypothesized that different types of stimuli, which drive different neuronal activities in the network, could lead those networks to display stimulus-dependent functional connectivity patterns. To test this hypothesis, we analyzed electrophysiological data from the Allen Brain Observatory, which utilized Neuropixels probes to simultaneously record stimulus-evoked activity from hundreds of neurons across 6 different regions of mouse visual cortex. The recordings had single-cell resolution and high temporal fidelity, enabling us to determine fine-scale functional connectivity. Comparing the functional connectivity patterns observed when different stimuli were presented to the mice, we made several nontrivial observations. First, while the frequencies of different connectivity motifs (i.e., the patterns of connectivity between triplets of neurons) were preserved across stimuli, the identities of the neurons within those motifs changed. This means that functional connectivity dynamically changes along with the input stimulus, but does so in a way that preserves the motif frequencies. Secondly, we found that the degree to which functional modules are contained within a single brain region (as opposed to being distributed between regions) increases with increasing stimulus complexity. This suggests a mechanism for how the brain could dynamically alter its computations based on its inputs. Altogether, our work reveals unexpected stimulus-dependence to the way groups of neurons interact to process incoming sensory information.

Differential encoding of temporal context and expectation under representational drift across hierarchically connected areas.

The classic view that neural populations in sensory cortices preferentially encode responses to incoming stimuli has been strongly challenged by recent experimental studies. Despite the fact that a large fraction of variance of visual responses in rodents can be attributed to behavioral state and movements, trial-history, and salience, the effects of contextual modulations and expectations on sensory-evoked responses in visual and association areas remain elusive. Here, we present a comprehensive experimental and theoretical study showing that hierarchically connected visual and association areas differentially encode the temporal context and expectation of naturalistic visual stimuli, consistent with the theory of hierarchical predictive coding. We measured neural responses to expected and unexpected sequences of natural scenes in the primary visual cortex (V1), the posterior medial higher order visual area (PM), and retrosplenial cortex (RSP) using 2-photon imaging in behaving mice collected through the Allen Institute Mindscope's OpenScope program. We found that information about image identity in neural population activity depended on the temporal context of transitions preceding each scene, and decreased along the hierarchy. Furthermore, our analyses revealed that the conjunctive encoding of temporal context and image identity was modulated by expectations of sequential events. In V1 and PM, we found enhanced and specific responses to unexpected oddball images, signaling stimulus-specific expectation violation. In contrast, in RSP the population response to oddball presentation recapitulated the missing expected image rather than the oddball image. These differential responses along the hierarchy are consistent with classic theories of hierarchical predictive coding whereby higher areas encode predictions and lower areas encode deviations from expectation. We further found evidence for drift in visual responses on the timescale of minutes. Although activity drift was present in all areas, population responses in V1 and PM, but not in RSP, maintained stable encoding of visual information and representational geometry. Instead we found that RSP drift was independent of stimulus information, suggesting a role in generating an internal model of the environment in the temporal domain. Overall, our results establish temporal context and expectation as substantial encoding dimensions in the visual cortex subject to fast representational drift and suggest that hierarchically connected areas instantiate a predictive coding mechanism.

Association Between the Presence of Metabolic Comorbidities and Liver-Related Events in Patients With Chronic Hepatitis B.

BACKGROUND & AIMS: Patients with chronic hepatitis B (CHB) are at increased risk of hepatocellular carcinoma and (liver-related) mortality. In addition to hepatitis B-related factors, metabolic comorbidities may contribute to the progression of fibrosis. Therefore, we studied the association between metabolic comorbidities and adverse clinical outcomes in patients with CHB. METHODS: We conducted a retrospective cohort study of CHB patients attending the Erasmus MC University Medical Center (Rotterdam, The Netherlands) and CHB patients who underwent liver biopsy at the Toronto General Hospital (Toronto, Canada). The presence of metabolic comorbidities (ie, overweight, diabetes mellitus, hypertension, and dyslipidemia) was assessed based on chart review. The primary end point was liver-related events, defined as the first composite of hepatocellular carcinoma, liver transplantation, or liver-related mortality. RESULTS: We analyzed 1850 patients, of whom 926 (50.1%) were overweight, 161 (8.7%) had hypertension, 116 (6.3%) had dyslipidemia, and 82 (4.4%) had diabetes. During a median follow-up period of 7.3 years (interquartile range, 2.9-11.5 y), a total of 111 first events were recorded. Hypertension (hazard ratio [HR], 8.3; 95% CI, 5.5-12.7), diabetes (HR, 5.4; 95% CI, 3.2-9.1), dyslipidemia (HR, 2.8; 95% CI, 1.6-4.8), and overweight (HR, 1.7; 95% CI, 1.1-2.5) were associated with an increased risk for liver-related events. The presence of multiple comorbidities further increased the risk. Findings were consistent for patients with and without cirrhosis, among noncirrhotic hepatitis B e antigen-negative patients with hepatitis B virus DNA less than 2000 IU/mL and in multivariable analysis adjusting for age, sex, ethnicity, hepatitis B e antigen status, hepatitis B virus DNA, use of antiviral therapy, and the presence of cirrhosis. CONCLUSIONS: Metabolic comorbidities in CHB patients are associated with an increased risk for liver-related events, with the highest risk observed in patients with multiple comorbidities. Findings were consistent in various clinically relevant subgroups, underscoring the need for thorough metabolic assessment in patients with CHB.

Representational integration and differentiation in the human hippocampus following goal-directed navigation.

As we learn, dynamic memory processes build structured knowledge across our experiences. Such knowledge enables the formation of internal models of the world that we use to plan, make decisions, and act. Recent theorizing posits that mnemonic mechanisms of differentiation and integration - which at one level may seem to be at odds - both contribute to the emergence of structured knowledge. We tested this possibility using fMRI as human participants learned to navigate within local and global virtual environments over the course of 3 days. Pattern similarity analyses on entorhinal cortical and hippocampal patterns revealed evidence that differentiation and integration work concurrently to build local and global environmental representations, and that variability in integration relates to differences in navigation efficiency. These results offer new insights into the neural machinery and the underlying mechanisms that translate experiences into structured knowledge that allows us to navigate to achieve goals.

Incidence of Hepatic Decompensation After Nucleos(t)ide Analog Withdrawal: Results From a Large, International, Multiethnic Cohort of Patients With Chronic Hepatitis B (RETRACT-B Study).

INTRODUCTION: Despite improvements in the management of chronic hepatitis B (CHB), risk of cirrhosis and hepatocellular carcinoma remains. While hepatitis B surface antigen loss is the optimal end point, safe discontinuation of nucleos(t)ide analog (NA) therapy is controversial because of the possibility of severe or fatal reactivation flares. METHODS: This is a multicenter cohort study of virally suppressed, end-of-therapy (EOT) hepatitis B e antigen (HBeAg)-negative CHB patients who stopped NA therapy (n = 1,557). Survival analysis techniques were used to analyze off-therapy rates of hepatic decompensation and differences by patient characteristics. We also examined a subgroup of noncirrhotic patients with consolidation therapy of ≥12 months before cessation (n = 1,289). Hepatic decompensation was considered related to therapy cessation if diagnosed off therapy or within 6 months of starting retreatment. RESULTS: Among the total cohort (11.8% diagnosed with cirrhosis, 84.2% start-of-therapy HBeAg-negative), 20 developed hepatic decompensation after NA cessation; 10 events were among the subgroup. The cumulative incidence of hepatic decompensation at 60 months off therapy among the total cohort and subgroup was 1.8% and 1.1%, respectively. The hepatic decompensation rate was higher among patients with cirrhosis (hazard ratio [HR] 5.08, P < 0.001) and start-of-therapy HBeAg-positive patients (HR 5.23, P < 0.001). This association between start-of-therapy HBeAg status and hepatic decompensation remained significant even among the subgroup (HR 10.5, P < 0.001). DISCUSSION: Patients with cirrhosis and start-of-therapy HBeAg-positive patients should be carefully assessed before stopping NAs to prevent hepatic decompensation. Frequent monitoring of viral and host kinetics after cessation is crucial to determine patient outcome.

On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks.

Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network's baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory.

Effectiveness of discharge education using teach-back method on readmission among heart failure patients: A systematic review and meta-analysis.

OBJECTIVE: This study aims to review and evaluate the effectiveness of discharge education using the teach-back method (TBM) on readmission rates among patients with heart failure (HF). METHODS: Searches were conducted in five electronic databases (PubMed, CINAHL, Embase, Cochrane Library, and Web of Science) published until May 2022, followed by a manual search of reference lists. The risk of bias in the studies was assessed using the Cochrane Risk of Bias and Joanna Briggs Institute quasi-experimental critical appraisal tool, and meta-analysis was conducted using Cochrane Review Manager 5. RESULTS: Seven studies were included in the review, and the quality of the studies varied, with two studies scoring low on the overall risk of bias. Meta-analysis was conducted using six studies, demonstrating that discharge education using TBM significantly reduced the overall readmission rates (odds ratio = 0.40, 95% confidence interval 0.17-0.94). CONCLUSIONS: TBM is an effective educational strategy for reducing the readmission rate in discharged patients with HF. More rigorously designed studies evaluating the effectiveness of education using TBM in patients with HF are needed. PRACTICE IMPLICATIONS: Nurses in clinical settings can use TBM in their discharge education to improve HF patients' understanding of the illness and impact long-term outcomes, such as readmission rates.

Exploring the experiences of frontline nurses caring for COVID-19 patients.

AIM: This study seeks to gain a comprehensive understanding of the experiences of frontline nurses who provided direct care for COVID-19 patients. BACKGROUND: Due to the COVID-19 pandemic, the demands on healthcare systems have been higher than before. Although previous studies have explored the experiences of frontline nurses, these experiences could vary depending on each country's social, cultural, and historical contexts. INTRODUCTION: In the midst of the global pandemic, sharing the experiences of COVID-19 frontline nurses could have implications for both nursing and nursing policies that could be applied to future pandemics. METHODS: This descriptive qualitative study comprised 14 South Korean nurses with a minimum of one month of experience working within a COVID-19 department. Individual interviews were conducted on a virtual platform, and a thematic analysis was employed. The consolidated criteria for reporting qualitative studies were used to ensure a detailed reporting of the study. RESULTS: Four themes and 12 subthemes were developed. The themes included: (1) feeling forced into a world of uncertainty; (2) providing unique care for COVID-19 patients; (3) perceiving barriers to providing quality care; and (4) seeking meaning in caring for COVID-19 patients. DISCUSSION: Nurses recognized their unique roles in caring for COVID-19 patients and sought new meanings within their profession. However, the poor work environment exacerbated the physical and emotional burden among the nurses and compromised the provision of quality care. CONCLUSION: This study highlighted the nursing policy issues that need to be improved to ensure better quality care and a stronger healthcare system. IMPLICATIONS FOR NURSING POLICY: Governmental action is essential to ensure that nurses can maintain the quality of care they have provided during COVID-19 and any future pandemics.

Differential Relapse Patterns After Discontinuation of Entecavir vs Tenofovir Disoproxil Fumarate in Chronic Hepatitis B.

BACKGROUND AND AIMS: Whether entecavir (ETV) and tenofovir disoproxil fumarate (TDF) differentially affect relapse and outcomes following treatment discontinuation across different patient subpopulations remains unclear. We aimed to compare rates of off-therapy hepatitis B surface antigen (HBsAg) loss, virological and clinical relapse, and retreatment between chronic hepatitis B (CHB) patients who discontinued TDF or ETV therapy. METHODS: This study included 1402 virally suppressed CHB patients who stopped either ETV (n = 981) or TDF (n = 421) therapy between 2001 and 2020 from 13 participating centers across North America, Europe, and Asia. All patients were hepatitis B e antigen-negative at treatment discontinuation. Inverse probability of treatment weighting was used to balance the treatment groups. Outcomes were analyzed using survival methods. RESULTS: During a median off-treatment follow-up of 18 months, HBsAg loss occurred in 96 (6.8%) patients overall. Compared with ETV, TDF was associated with a higher rate of HBsAg loss (P = .03); however, the association was no longer significant after statistical adjustment (P = .61). Virological relapse occurred earlier among TDF-treated patients (P < .01); nonetheless, rates became comparable after the first year off therapy (P = .49). TDF was significantly associated with a higher clinical relapse rate than ETV throughout follow-up (P < .01). The development of a virological or clinical relapse did not affect the rate of HBsAg loss. Retreatment rates were not significantly different between the treatment groups. CONCLUSIONS: TDF and ETV have differential relapse patterns but are associated with similar rates of HBsAg loss and retreatment following discontinuation. Finite therapy can be considered for CHB patients on either TDF or ETV therapy.