Sex-Specific Development of ssRNA Virus Receptor Gene Expression in the Human Brain (preprint)

Viral infection severity often varies with host factors such as age and sex. The pathogenesis of infections caused by a broad range of viruses, from neurotropic viruses like Rabies and Zika to respiratory viruses such as influenza and SARS-CoV-2, differ between the sexes and across the lifespan. Typically, older males are more susceptible to severe acute outcomes, while females are more vulnerable to the post-acute sequelae of infections. All of these complications can include neuroinflammation, stroke, cognitive dysfunction, and delirium. While these symptoms can be secondary to infection, recent studies suggest that even peripheral infections can lead to neuropathological changes in the brain. However, few studies have characterized the expression of viral receptors in the human brain or examined age- or sex-related differences in such expression. In this study, we used a publicly accessible transcriptomic database to assess the impact of age and sex on the expression of 67 viral host factor genes, associated with ten virus families. Analyzing data from 15 brain areas (n=33, F=14, M=19, age:4 mo-80 yrs), we determined the lifespan trajectory for each gene in each area via LOESS regressions. We used unsupervised hierarchical clustering to determine if a brain-wide pattern or virus family pattern can be detected. Using Dense-tSNE, a dimension-reduction and visualization technique, we discovered four distinct developmental trajectories, clustering the areas into two mixed-sex subcortical clusters and one each of male and female cortical clusters. Applying Differential Expression Sliding Window Analysis (DeSWAN), we identified the genes driving these age- and sex-related differences. Many sex differences were noted in childhood, potentially impacting the brain\'s susceptibility to viral infections and underscoring a broader dimorphic organization of male and female brains. These insights contribute to our understanding of sex-specific responses to viral infections, offering the potential for more personalized treatment strategies.

Diagnosis of delirium: a practical approach.

Delirium is an acute disorder of fluctuating attention and awareness with cardinal features that allow it to be positively distinguished from other causes of an acute confusional state. These features include fluctuations, prominent inattentiveness with other cognitive deficits, a change in awareness and visual hallucinations. We describe a framework for diagnosing delirium, noting the need to consider certain caveats and differential diagnoses. Delirium is a clinical diagnosis where a thorough history and clinical examination are much more helpful diagnostically than any single test or combination of tests.

The comparison of the consultation-liaison in the psychiatry department of a general hospital before and after the outbreak of COVID-19 (preprint)

Objective: To compare the status of the consultation-liaison in the psychiatry department of inpatients in a general hospital before and after the outbreak of COVID-19.  Methods: 842 patients in a tertiary hospital during 2019 and 904 patients since the beginning of the epidemic in 2020 were enrolled in this study. Demographic data, departments that requested consultation, mental disorders, and the psychiatric treatments were retrospectively analyzed.  Results: Among the 1746 patients, most patients were 45 to 70 years old. The department of hematology received the most applications for consultation. In 2020, requests from the departments of cardiac and vascular surgeries, contrary to the emergency department, increased significantly. 32.6% patients were diagnosed with organic mental disorder. Delirium was the most common disorder, followed by anxiety and depression. After the COVID-19 outbreak in 2020, the stress-associated and sleep disorders increased.  Conclusions: In general hospitals, clinical departments have great demands forpsychiatric consultation.Since the pandemic, patients requiring consultations for stress-related disorders and sleep disorders increased. Moreover, patients with cardiac and major vascular surgeries suffering from mental and emotional disturbances also increased. The ability of non-psychiatrists in identifying and treating mental disorders and the awareness of biopsychosocial (BPS) models need to be improved.

Delirium after COVID-19 vaccination in older adults.

ABSTRACT: The COVID-19 global pandemic has devastated the older adult population. Like all vaccines, adverse reactions of COVID-19 vaccines are possible. This article discusses the increased incidence of delirium and delirium-associated symptoms in older adults following COVID-19 vaccinations.

Delirium as late manifestation of infective endocarditis after transcatheter aortic valve implantation.

More than one-third of the cases of infective endocarditis (IE) occur in older patients. The disease is often characterized by atypical symptoms. The incidence of neurological complications is high and represents a strong independent predictor of severe outcomes and mortality. IE is a rare but serious complication of transcatheter aortic valve implantation (TAVI). A persistent delirium as a unique manifestation of post-TAVI IE in an older patient is presented in this clinical case.

Characteristics and outcomes of COVID-19 inpatients who underwent psychiatric consultations.

Patients hospitalized with COVID-19 are at risk of developing many neuropsychiatric disorders, due to the effects of the disease on the brain and the psychosocial pressures of having the disease. The aim of the present study was to evaluate the characteristics and outcomes of patients who were hospitalized with a diagnosis of COVID-19, who underwent psychiatric consultations. The medical records of 892 patients hospitalized due to COVID-19 and the 89 among them who requested psychiatric consultations were analyzed retrospectively. After the psychiatric consultations, patients were most frequently diagnosed with delirium (38.2 %), adjustment disorder (27.0 %), depressive disorder (19.1 %) and anxiety disorder (11.2 %). Patients with delirium had longer hospital stays (p < 0.001), were transferred more frequently to intensive care units (p < 0.001), and had higher mortality rates during their hospital stays (p < 0.001), than all other patients. The need for oxygen (p < 0.001) and mechanical ventilation (p < 0.001) was also significantly higher in delirium patients, as well as in patients who received other psychiatric diagnoses. Neuropsychiatric disorders develop in patients receiving inpatient treatments in COVID-19 wards, and these disorders negatively affect the prognosis of COVID-19. Our findings suggest that the presence of neuropsychiatric disorders in in-patients with COVID-19 might be associated with the negative outcomes of the disease.

Outcomes in Patients With COVID-19 With Acute Encephalopathy and Coma: An International Prospective Study.

BACKGROUND AND OBJECTIVES: To report the prevalence of acute encephalopathy and outcomes in patients with severe coronavirus disease 2019 (COVID-19) and to identify determinants of 90-day outcomes. METHODS: Data from adults with severe COVID-19 and acute encephalopathy were prospectively collected for patients requiring intensive care unit management in 31 university or university-affiliated intensive care units in 6 countries (France, United States, Colombia, Spain, Mexico, and Brazil) between March and September of 2020. Acute encephalopathy was defined, as recently recommended, as subsyndromal delirium or delirium or as a comatose state in case of severely decreased level of consciousness. Logistic multivariable regression was performed to identify factors associated with 90-day outcomes. A Glasgow Outcome Scale-Extended (GOS-E) score of 1-4 was considered a poor outcome (indicating death, vegetative state, or severe disability). RESULTS: Of 4,060 patients admitted with COVID-19, 374 (9.2%) experienced acute encephalopathy at or before the intensive care unit (ICU) admission. A total of 199/345 (57.7%) patients had a poor outcome at 90-day follow-up as evaluated by the GOS-E (29 patients were lost to follow-up). On multivariable analysis, age older than 70 years (odds ratio [OR] 4.01, 95% CI 2.25-7.15), presumed fatal comorbidity (OR 3.98, 95% CI 1.68-9.44), Glasgow coma scale score <9 before/at ICU admission (OR 2.20, 95% CI 1.22-3.98), vasopressor/inotrope support during ICU stay (OR 3.91, 95% CI 1.97-7.76), renal replacement therapy during ICU stay (OR 2.31, 95% CI 1.21-4.50), and CNS ischemic or hemorrhagic complications as acute encephalopathy etiology (OR 3.22, 95% CI 1.41-7.82) were independently associated with higher odds of poor 90-day outcome. Status epilepticus, posterior reversible encephalopathy syndrome, and reversible cerebral vasoconstriction syndrome were associated with lower odds of poor 90-day outcome (OR 0.15, 95% CI 0.03-0.83). DISCUSSION: In this observational study, we found a low prevalence of acute encephalopathy at ICU admission in patients with COVID-19. More than half of patients with COVID-19 presenting with acute encephalopathy had poor outcomes as evaluated by GOS-E. Determinants of poor 90-day outcome were dominated by older age, comorbidities, degree of impairment of consciousness before/at ICU admission, association with other organ failures, and acute encephalopathy etiology. TRIAL REGISTRATION INFORMATION: The study is registered with ClinicalTrials.gov, number NCT04320472.

Frequency of delirium and its associated factors among COVID-19 inpatients in Iran.

BACKGROUND AND AIM: Delirium has been presented as the leading cause of sudden change in the mental state of patients with coronavirus disease 2019 (COVID-19). Given that the delayed diagnosis of such a dysfunction is often associated with excess mortality, it seems essential to devote vastly more attention to this significant clinical characteristic. MATERIALS AND METHODS: This cross-sectional study was performed on 309 patients [viz. 259 cases hospitalized in general wards and 50 individuals admitted to the intensive care unit (ICU)]. For this purpose, a Demographic-Clinical Information Questionnaire, the Confusion Assessment Method (CAM), the Confusion Assessment Method for the ICU (CAM-ICU), the Richmond Agitation-Sedation Scale (RASS) and face-to-face interviews were completed by a trained senior psychiatry resident. The data analysis was further done with the SPSS Statistics V22.0 software package. RESULTS: Out of 259 patients admitted to the general wards and 50 cases in the ICU due to COVID-19, 41 (15.8%) and 11 (22%) individuals were diagnosed with delirium, respectively. As well, a significant relationship was observed between the incidence rate of delirium and age (p < 0.001), level of education (p < 0.001), hypertension (HTN) (p = 0.029), a history of stroke (p = 0.025), a history of ischemic heart disease (IHD) (p = 0.007), a history of psychiatric disorders, a history of cognitive impairment (p < 0.001), use of hypnotic and antipsychotic medications (p < 0.001) and a history of substance abuse (p = 0.023). Among 52 patients with delirium, only 20 cases had received psychiatric consultation by consultation-liaison psychiatry service for the possibility of delirium. CONCLUSION: In view of the high frequency of delirium among COVID-19 inpatients, their screening for this important mental state should be a priority in clinical settings.

Adaptation and multicentre validation of a patient-centred outcome scale for people severely ill with COVID (IPOS-COV).

BACKGROUND: Patient-centred measures to capture symptoms and concerns have rarely been reported in severe COVID. We adapted and tested the measurement properties of the proxy version of the Integrated Palliative care Outcome Scale-IPOS-COV for severe COVID using psychometric approach. METHODS: We consulted experts and followed consensus-based standards for the selection of health status measurement instruments and United States Food and Drug Administration guidance for adaptation and analysis. Exploratory Factor Analysis and clinical perspective informed subscales. We tested the internal consistency reliability, calculated item total correlations, examined re-test reliability in stable patients, and also evaluated inter-rater reproducibility. We examined convergent and divergent validity of IPOS-COV with the Australia-modified Karnofsky Performance Scale and evaluated known-groups validity. Ability to detect change was examined. RESULTS: In the adaptation phase, 6 new items were added, 7 items were removed from the original measure. The recall period was revised to be the last 12-24 h to capture fast deterioration in COVID. General format and response options of the original Integrated Palliative care Outcome Scale were preserved. Data from 572 patients with COVID from across England and Wales seen by palliative care services were included. Four subscales were supported by the 4-factor solution explaining 53.5% of total variance. Breathlessness-Agitation and Gastro-intestinal subscales demonstrated good reliability with high to moderate (a = 0.70 and a = 0.67) internal consistency, and item-total correlations (0.62-0.21). All except the Flu subscale discriminated well between patients with differing disease severity. Inter-rater reliability was fair with ICC of 0.40 (0.3-0.5, 95% CI, n = 324). Correlations between the subscales and AKPS as predicted were weak (r = 0.13-0.26) but significant (p < 0.01). Breathlessness-Agitation and Drowsiness-Delirium subscales demonstrated good divergent validity. Patients with low oxygen saturation had higher mean Breathlessness-Agitation scores (M = 5.3) than those with normal levels (M = 3.4), t = 6.4 (186), p < 0.001. Change in Drowsiness-Delirium subscale correctly classified patients who died. CONCLUSIONS: IPOS-COV is the first patient-centred measure adapted for severe COVID to support timely management. Future studies could further evaluate its responsiveness and clinical utility with clinimetric approaches.

Analysis of citation trends to identify articles on delirium worth reading using DDPP model with temporal heatmaps (THM): A bibliometric analysis.

BACKGROUND: Delirium is one of the most common geriatric syndromes in older patients, accounting for 25% of hospitalized older patients, 31 to 35% of patients in the intensive care unit, and 8% to 17% of older patients in the emergency department (ED). A number of articles have been published in the literature regarding delirium. However, it is unclear about article citations evolving in the field. This study proposed a temporal heatmap (THM) that can be applied to all bibliographical studies for a better understanding of cited articles worth reading. METHODS: As of November 25, 2022, 11,668 abstracts published on delirium since 2013 were retrieved from the Web of Science core collection. Research achievements were measured using the CJAL score. Social network analysis was applied to examine clusters of keywords associated with core concepts of research. A THM was proposed to detect articles worth reading based on recent citations that are increasing. The 100 top-cited articles related to delirium were displayed on an impact beam plot (IBP). RESULTS: The results indicate that the US (12474), Vanderbilt University (US) (634), Anesthesiology (2168), and Alessandro Morandi (Italy) (116) had the highest CJAL scores in countries, institutes, departments, and authors, respectively. Articles worthy of reading were highlighted on a THM and an IBP when an increasing trend of citations over the last 4 years was observed. CONCLUSION: The THM and IBP were proposed to highlight articles worth reading, and we recommend that more future bibliographical studies utilize the 2 visualizations and not restrict them solely to delirium-related articles in the future.

Predictors and outcomes of delirium in the emergency department during the first wave of the COVID-19 pandemic in Milan.

BACKGROUND: Respiratory infections can be complicated by acute brain failure. We assessed delirium prevalence, predictors and outcomes in COVID-19 ED patients. METHODS: This was a retrospective observational study conducted at the San Raffaele ED (Italy). Patients age >18 years attending the ED between 26 February 2020 and 30 May 2020 and who had a positive molecular nasopharyngeal swab for SARS-CoV-2 were included. The Chart-Based Delirium Identification Instrument (CHART-DEL) was used to retrospectively assess delirium. Univariable and multivariable logistic regression analyses were used to evaluate delirium predictors. Univariable binary logistic regression analyses, linear regression analyses and Cox regression analyses were used to assess the association between delirium and clinical outcomes. Age-adjusted and sex-adjusted models were then run for the significant predictors of the univariable models. RESULTS: Among the 826 included patients, 123 cases (14.9%) of delirium were retrospectively detected through the CHART-DEL method. Patients with delirium were older (76.9±13.15 vs 61.3±14.27 years, p<0.001) and more frequently living in a long-term health facility (32 (26%) vs 22 (3.1%), p<0.001). Age (OR 1.06, 95% CI 1.04 to 1.09, p<0.001), dementia (OR 17.5, 95% CI 7.27 to 42.16, p<0.001), epilepsy (OR 6.96, 95% CI 2.48 to 19.51, p<0.001) and the number of chronic medications (OR 1.09, 95% CI 1.01 to 1.17, p=0.03) were significant predictors of delirium in multivariable analyses. Delirium was associated with increased in-hospital mortality (adjusted HR 2.16, 95% CI 1.55 to 3.03, p<0.001) and with a reduced probability of being discharged home compared with being institutionalised (adjusted OR 0.39, 95% CI 0.25 to 0.61, p<0.001). CONCLUSIONS: Chart review frequently identified ED delirium in patients with COVID-19. Age, dementia, epilepsy and polypharmacy were significant predictors of ED delirium. Delirium was associated with an increased in-hospital mortality and with a reduced probability of being discharged home after hospitalisation. The findings of this single-centre retrospective study require validation in future studies.

Delirium in Patients with COVID-19 in Japan.

Objective The incidence and clinical importance of delirium in coronavirus disease 2019 (COVID-19) have not yet been fully investigated. The present study reported the prevalence of delirium in patients with COVID-19 and identified the factors associated with delirium and mortality. Methods We performed an observational, retrospective study of patients diagnosed with COVID-19 at the Kinki-Chuo Chest Medical Center. Univariate and multivariate logistic regression analyses were used to explore delirium risk factors. Patients All consecutive patients diagnosed with COVID-19 at the Kinki-Chuo Chest Medical Center. Results We identified 600 patients [median age: 61.0 (interquartile range: 49.0-77.0) years old], of whom 61 (10.2%) developed delirium during their stay. Compared with patients without delirium, these patients were older (median age 84.0 vs. 56.0 years old, p<0.01) and had more comorbidities. Based on a multivariate analysis, age, dementia, severe disease, and lactate dehydrogenase (LDH) levels were independent risk factors for developing delirium. For every 1-year increase in age and 10-IU/L increase in LDH, the delirium risk increased by 10.8-12.0% and 4.6-5.7%, respectively. There were 15 (24.6%) in-hospital deaths in the group with delirium and 8 (1.6%) in the group without delirium (p<0.01). Delirium was associated with an increased mortality. Conclusion Delirium in patients with COVID-19 is prevalent and associated with poor clinical outcomes in Japan. Despite difficulties with COVID-19 patient care during the pandemic, physicians should be aware of the risk of delirium and be trained in its optimal management.

Comorbidity and Management of Concurrent Psychiatric and Medical Disorders.

Aging increases susceptibility to medical and psychiatric comorbidity via interrelated biological, psychological, and social mechanisms. Mental status changes or other psychiatric symptoms occurring in older adults with medical disorders most often result from delirium, depression, or the onset of Alzheimer's disease and related dementias (ADRD). Clinicians can use evidence-based tools to evaluate such symptoms including the 4A's Test for delirium, the Saint Louis University Mental Status Exam, and the Geriatric Depression Scale. Innovative models such as collaborative care can improve the outcome of care of older adults with medical disorders requiring treatment for depression or ADRD..

Clinical features and outcomes of hospitalised patients with COVID-19 and Parkinsonian disorders: a multicentre UK-based study (preprint)

Background: Parkinsons disease has been identified as a risk factor for severe Coronavirus disease 2019 (COVID-19) outcomes. However, whether the significant high risk of death from COVID-19 in people with Parkinsons disease is specific to the disease itself or driven by other concomitant and known risk factors such as comorbidities, age, and frailty remains unclear. Objective: To investigate clinical profiles and outcomes of people with Parkinsons disease and atypical parkinsonian syndromes who tested positive for COVID-19 in the hospital setting in a multicentre UK-based study. Methods: A retrospective cohort study of Parkinsons disease patients with a positive COVID-19 test admitted to hospital between February 2020 and July 2021. An online survey was used to collect data from clinical care records, recording patient, Parkinsons disease and COVID-19 characteristics. Associations with time-to-mortality and severe outcomes were analysed using either the Cox proportional hazards model or logistic regression models, as appropriate. Results: Data from 552 admissions were collected: 365 (66%) male; median (inter-quartile range) age 80 (74-85) years. The 34-day mortality rate was 38.4%; male sex, increased age and frailty, Parkinsons dementia syndrome, requirement for respiratory support and no vaccination were associated with increased mortality risk. Community-acquired COVID-19 and co-morbid chronic neurological disorder were associated with increased odds of requiring respiratory support. Hospital-acquired COVID-19 and delirium were associated with requiring an increase in care level post-discharge. Conclusions: This first, multicentre, UK-based study on people with Parkinsons disease or atypical parkinsonian syndromes, hospitalised with COVID-19, adds and expands previous findings on clinical profiles and outcomes in this population.

Unsupervised Machine Learning Unveil Easily Identifiable Subphenotypes of COVID-19 With Differing Disease Trajectories (preprint)

BackgroundGiven the clinical heterogeneity of COVID-19 infection, we hypothesize the existence of subphenotypes based on early inflammatory responses that are associated with mortality and additional complications. MethodsFor this cross-sectional study, we extracted electronic health data from adults hospitalized patients between March 1, 2020 and May 5, 2021, with confirmed primary diagnosis of COVID-19 across five Johns Hopkins Hospitals. We obtained all electronic health records from the first 24h of the patients hospitalization. Mortality was the primary endpoint explored while myocardial infarction (MI), pulmonary embolism (PE), deep vein thrombosis (DVT), stroke, delirium, length of stay (LOS), ICU admission and intubation status were secondary outcomes of interest. First, we employed clustering analysis to identify COVID-19 subphenotypes on admission with only biomarker data and assigned each patient to a subphenotype. We then performed Chi-Squared and Mann-Whitney-U tests to examine associations between COVID-19 subphenotype assignment and outcomes. In addition, correlations between subphenotype and pre-existing comorbidities were measured using Chi-Squared analysis. ResultsA total of 7076 patients were included. Analysis revealed three distinct subgroups by level of inflammation: hypoinflammatory, intermediate, and hyperinflammatory subphenotypes. More than 25% of patients in the hyperinflammatory subphenotype died compared to less than 3% hypoinflammatory subphenotype (p<0.05). Additional analysis found statistically significant increases in the rate of MI, DVT, PE, stroke, delirium and ICU admission as well as LOS in the hyperinflammatory subphenotype. ConclusionWe identify three distinct inflammatory subphenotypes that predict a range of outcomes, including mortality, MI, DVT, PE, stroke, delirium, ICU admission and LOS. The three subphenotypes are easily identifiable and may aid in clinical decision making.