Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 20
Filter
1.
Gen Hosp Psychiatry ; 74: 9-17, 2021 Nov 02.
Article in English | MEDLINE | ID: covidwho-1568701

ABSTRACT

OBJECTIVE: To validate a previously published machine learning model of delirium risk in hospitalized patients with coronavirus disease 2019 (COVID-19). METHOD: Using data from six hospitals across two academic medical networks covering care occurring after initial model development, we calculated the predicted risk of delirium using a previously developed risk model applied to diagnostic, medication, laboratory, and other clinical features available in the electronic health record (EHR) at time of hospital admission. We evaluated the accuracy of these predictions against subsequent delirium diagnoses during that admission. RESULTS: Of the 5102 patients in this cohort, 716 (14%) developed delirium. The model's risk predictions produced a c-index of 0.75 (95% CI, 0.73-0.77) with 27.7% of cases occurring in the top decile of predicted risk scores. Model calibration was diminished compared to the initial COVID-19 wave. CONCLUSION: This EHR delirium risk prediction model, developed during the initial surge of COVID-19 patients, produced consistent discrimination over subsequent larger waves; however, with changing cohort composition and delirium occurrence rates, model calibration decreased. These results underscore the importance of calibration, and the challenge of developing risk models for clinical contexts where standard of care and clinical populations may shift.

2.
JAMA Netw Open ; 4(11): e2136113, 2021 Nov 01.
Article in English | MEDLINE | ID: covidwho-1540038

ABSTRACT

Importance: Some studies suggest that social media use is associated with risk for depression, particularly among children and young adults. Objective: To characterize the association between self-reported use of individual social media platforms and worsening of depressive symptoms among adults. Design, Setting, and Participants: This survey study included data from 13 waves of a nonprobability internet survey conducted approximately monthly between May 2020 and May 2021 among individuals aged 18 years and older in the US. Data were analyzed in July and August 2021. Main Outcomes and Measures: Logistic regression was applied without reweighting, with a 5 point or greater increase in 9-item Patient Health Questionnaire (PHQ-9) score as outcome and participant sociodemographic features, baseline PHQ-9, and use of each social media platform as independent variables. Results: In total, 5395 of 8045 individuals (67.1%) with a PHQ-9 score below 5 on initial survey completed a second PHQ-9. These respondents had a mean (SD) age of 55.8 (15.2) years; 3546 respondents (65.7%) identified as female; 329 respondents (6.1%) were Asian, 570 (10.6%) Black, 256 (4.7%) Hispanic, 4118 (76.3%) White, and 122 (2.3%) American Indian or Alaska Native, Pacific Islander or Native Hawaiian, or other. Among eligible respondents, 482 (8.9%) reported 5 points or greater worsening of PHQ-9 score at second survey. In fully adjusted models for increase in symptoms, the largest adjusted odds ratio (aOR) associated with social media use was observed for Snapchat (aOR, 1.53; 95% CI, 1.19-1.96), Facebook (aOR, 1.42; 95% CI, 1.10-1.81), and TikTok (aOR, 1.39; 95% CI, 1.03-1.87). Conclusions and Relevance: Among survey respondents who did not report depressive symptoms initially, social media use was associated with greater likelihood of subsequent increase in depressive symptoms after adjustment for sociodemographic features and news sources. These data cannot elucidate the nature of this association, but suggest the need for further study to understand how social media use may factor into depression among adults.

4.
Depress Anxiety ; 38(10): 1026-1033, 2021 10.
Article in English | MEDLINE | ID: covidwho-1347400

ABSTRACT

INTRODUCTION: The major stressors associated with the COVID-19 pandemic provide an opportunity to understand the extent to which protective factors against depression may exhibit gender-specificity. METHOD: This study examined responses from multiple waves of a 50 states non-probability internet survey conducted between May 2020 and January 2021. Participants completed the PHQ-9 as a measure of depression, as well as items characterizing social supports. We used logistic regression models with population reweighting to examine association between absence of even mild depressive symptoms and sociodemographic features and social supports, with interaction terms and stratification used to investigate sex-specificity. RESULTS: Among 73,917 survey respondents, 31,199 (42.2%) reported absence of mild or greater depression-11,011/23,682 males (46.5%) and 20,188/50,235 (40.2%) females. In a regression model, features associated with greater likelihood of depression-resistance included at least weekly attendance of religious services (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04-1.16) and greater trust in others (OR: 1.04 for a 2-unit increase, 95% CI: 1.02-1.06), along with level of social support measured as number of social ties available who could provide care (OR: 1.05, 95% CI: 1.02-1.07), talk to them (OR: 1.10, 95% CI: 1.07-1.12), and help with employment (OR: 1.06, 95% CI: 1.04-1.08). The first two features showed significant interaction with gender (p < .0001), with markedly greater protective effects among women. CONCLUSION: Aspects of social support are associated with diminished risk of major depressive symptoms, with greater effects of religious service attendance and trust in others observed among women than men.


Subject(s)
COVID-19 , Depressive Disorder, Major , Cross-Sectional Studies , Depression , Depressive Disorder, Major/epidemiology , Female , Humans , Male , Pandemics , SARS-CoV-2
7.
Group Processes & Intergroup Relations ; 24(4):638-657, 2021.
Article in English | Academic Search Complete | ID: covidwho-1255823

ABSTRACT

Concerns about misperceptions among the public are rampant. Yet, little work explores the correlates of misperceptions in varying contexts – that is, how do factors such as group affiliations, media exposure, and lived experiences correlate with the number of misperceptions people hold? We address these questions by investigating misperceptions about COVID-19, focusing on the role of racial/ethnic, religious, and partisan groups. Using a large survey, we find the number of correct beliefs held by individuals far dwarfs the number of misperceptions. When it comes to misperceptions, we find that minorities, those with high levels of religiosity, and those with strong partisan identities – across parties – hold a substantially greater number of misperceptions than those with contrasting group affiliations. Moreover, we show other variables (e.g., social media usage, number of COVID-19 cases in one's county) do not have such strong relationships with misperceptions, and the group-level results do not reflect acquiescence to believing any information regardless of its truth value. Our results accentuate the importance of studying group-level misperceptions on other scientific and political issues and developing targeted interventions for these groups. [ABSTRACT FROM AUTHOR] Copyright of Group Processes & Intergroup Relations is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

8.
Group Processes & Intergroup Relations ; 24(4):638-657, 2021.
Article in English | ProQuest Central | ID: covidwho-1249524

ABSTRACT

Concerns about misperceptions among the public are rampant. Yet, little work explores the correlates of misperceptions in varying contexts – that is, how do factors such as group affiliations, media exposure, and lived experiences correlate with the number of misperceptions people hold? We address these questions by investigating misperceptions about COVID-19, focusing on the role of racial/ethnic, religious, and partisan groups. Using a large survey, we find the number of correct beliefs held by individuals far dwarfs the number of misperceptions. When it comes to misperceptions, we find that minorities, those with high levels of religiosity, and those with strong partisan identities – across parties – hold a substantially greater number of misperceptions than those with contrasting group affiliations. Moreover, we show other variables (e.g., social media usage, number of COVID-19 cases in one’s county) do not have such strong relationships with misperceptions, and the group-level results do not reflect acquiescence to believing any information regardless of its truth value. Our results accentuate the importance of studying group-level misperceptions on other scientific and political issues and developing targeted interventions for these groups.

9.
Am J Psychiatry ; 178(6): 541-547, 2021 06.
Article in English | MEDLINE | ID: covidwho-1169925

ABSTRACT

OBJECTIVE: The authors sought to characterize the association between prior mood disorder diagnosis and hospital outcomes among individuals admitted with COVID-19 to six Eastern Massachusetts hospitals. METHODS: A retrospective cohort was drawn from the electronic health records of two academic medical centers and four community hospitals between February 15 and May 24, 2020. Associations between history of mood disorder and in-hospital mortality and hospital discharge home were examined using regression models among any hospitalized patients with positive tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). RESULTS: Among 2,988 admitted individuals, 717 (24.0%) had a prior mood disorder diagnosis. In Cox regression models adjusted for age, sex, and hospital site, presence of a mood disorder prior to admission was associated with greater in-hospital mortality risk beyond hospital day 12 (crude hazard ratio=2.156, 95% CI=1.540, 3.020; fully adjusted hazard ratio=1.540, 95% CI=1.054, 2.250). A mood disorder diagnosis was also associated with greater likelihood of discharge to a skilled nursing facility or other rehabilitation facility rather than home (crude odds ratio=2.035, 95% CI=1.661, 2.493; fully adjusted odds ratio=1.504, 95% CI=1.132, 1.999). CONCLUSIONS: Hospitalized individuals with a history of mood disorder may be at risk for greater COVID-19 morbidity and mortality and are at increased risk of need for postacute care. Further studies should investigate the mechanism by which these disorders may confer elevated risk.


Subject(s)
COVID-19/psychology , Mood Disorders/complications , Aged , COVID-19/mortality , Cohort Studies , Female , Hospitalization , Humans , Male , Retrospective Studies , Risk Assessment , Treatment Outcome
10.
Transl Psychiatry ; 11(1): 179, 2021 03 19.
Article in English | MEDLINE | ID: covidwho-1142427

ABSTRACT

Microglia, the resident brain immune cells, play a critical role in normal brain development, and are impacted by the intrauterine environment, including maternal immune activation and inflammatory exposures. The COVID-19 pandemic presents a potential developmental immune challenge to the fetal brain, in the setting of maternal SARS-CoV-2 infection with its attendant potential for cytokine production and, in severe cases, cytokine storming. There is currently no biomarker or model for in utero microglial priming and function that might aid in identifying the neonates and children most vulnerable to neurodevelopmental morbidity, as microglia remain inaccessible in fetal life and after birth. This study aimed to generate patient-derived microglial-like cell models unique to each neonate from reprogrammed umbilical cord blood mononuclear cells, adapting and extending a novel methodology previously validated for adult peripheral blood mononuclear cells. We demonstrate that umbilical cord blood mononuclear cells can be used to create microglial-like cell models morphologically and functionally similar to microglia observed in vivo. We illustrate the application of this approach by generating microglia from cells exposed and unexposed to maternal SARS-CoV-2 infection. Our ability to create personalized neonatal models of fetal brain immune programming enables non-invasive insights into fetal brain development and potential childhood neurodevelopmental vulnerabilities for a range of maternal exposures, including COVID-19.


Subject(s)
Brain/growth & development , Brain/immunology , COVID-19/immunology , Cellular Reprogramming , Fetal Blood/immunology , Induced Pluripotent Stem Cells , Leukocytes, Mononuclear/immunology , Microglia/immunology , Pregnancy Complications, Infectious/immunology , Adult , Female , Humans , Infant, Newborn , Pregnancy
12.
J Acad Consult Liaison Psychiatry ; 62(3): 298-308, 2021.
Article in English | MEDLINE | ID: covidwho-1117177

ABSTRACT

Background: The coronavirus disease 2019 pandemic has placed unprecedented stress on health systems and has been associated with elevated risk for delirium. The convergence of pandemic resource limitation and clinical demand associated with delirium requires careful risk stratification for targeted prevention efforts. Objectives: To develop an incident delirium predictive model among coronavirus disease 2019 patients. Methods: We applied supervised machine learning to electronic health record data for inpatients with coronavirus disease 2019 at three hospitals to build an incident delirium diagnosis prediction model. We validated this model in three different hospitals. Both hospital cohorts included academic and community settings. Results: Among 2907 patients across 6 hospitals, 488 (16.8%) developed delirium. Applying the predictive model in the external validation cohort of 755 patients, the c-index was 0.75 (0.71-0.79) and the lift in the top quintile was 2.1. At a sensitivity of 80%, the specificity was 56%, negative predictive value 92%, and positive predictive value 30%. Equivalent model performance was observed in subsamples stratified by age, sex, race, need for critical care and care at community vs. academic hospitals. Conclusion: Machine learning applied to electronic health records available at the time of inpatient admission can be used to risk-stratify patients with coronavirus disease 2019 for incident delirium. Delirium is common among patients with coronavirus disease 2019, and resource constraints during a pandemic demand careful attention to the optimal application of predictive models.


Subject(s)
COVID-19/complications , Delirium/diagnosis , Delirium/etiology , Adult , Aged , Aged, 80 and over , Area Under Curve , Cohort Studies , Delirium/prevention & control , Electronic Health Records , Female , Humans , Machine Learning , Male , Middle Aged , Models, Statistical , Patient Admission , Risk Assessment/methods , SARS-CoV-2 , Sensitivity and Specificity
13.
Neuropsychopharmacology ; 46(13): 2235-2240, 2021 12.
Article in English | MEDLINE | ID: covidwho-1085430

ABSTRACT

Early reports and case series suggest cognitive deficits occurs in some patients with COVID-19. We evaluated the frequency, severity, and profile of cognitive dysfunction in patients recovering from prolonged COVID-19 hospitalization who required acute inpatient rehabilitation prior to discharge. We analyzed cross-sectional scores from the Brief Memory and Executive Test (BMET) in a cohort of N = 57 COVID-19 patients undergoing inpatient rehabilitation, calculating the frequency of impairment based on neuropsychologist diagnosis and by age-normed BMET subtests. In total, 43 patients (75%) were male, 35 (61%) were non-white, and mean age was 64.5 (SD = 13.9) years. In total, 48 (84%) were previously living at home independently. Two patients had documented preexisting cognitive dysfunction; none had known dementia. Patients were evaluated at a mean of 43.2 (SD = 19.2) days after initial admission. In total, 50 patients (88%) had documented hypoxemic respiratory failure and 44 (77%) required intubation.  Forty-six patients (81%) had cognitive impairment, ranging from mild to severe. Deficits were common in working memory (26/47 [55%] of patients), set-shifting (21/44 [47%]), divided attention (18/39 [46%]), and processing speed (14/35 [40%]). Executive dysfunction was not significantly associated with intubation length or the time from extubation to assessment, psychiatric diagnosis, or preexisting cardiovascular/metabolic disease. Attention and executive functions are frequently impaired in COVID-19 patients who require acute rehabilitation prior to discharge. Though interpretation is limited by lack of a comparator group, these results provide an early benchmark for identifying and characterizing cognitive difficulties after COVID-19. Given the frequency and pattern of impairment, easy-to-disseminate interventions that target attention and executive dysfunctions may be beneficial to this population.


Subject(s)
COVID-19 , Cognitive Dysfunction , Cognition , Cognitive Dysfunction/epidemiology , Cross-Sectional Studies , Humans , Male , Middle Aged , Neuropsychological Tests , SARS-CoV-2
15.
Non-conventional | Homeland Security Digital Library, Grey literature | ID: grc-740601

ABSTRACT

From the Document: "We surveyed 19,058 individuals across all 50 states plus the District of Columbia. The survey was conducted on 10-26 July 2020 by PureSpectrum via an online, nonprobability sample, with state-level representative quotas for race/ethnicity, age, and gender (for methodological details on the other waves, see covidstates.org). In addition to balancing on these dimensions, we reweighted our data using demographic characteristics to match the U.S. population with respect to race/ethnicity, age, gender, education, and living in urban, suburban, or rural areas. This was the seventh in a series of surveys we have been conducting since April 2020, examining attitudes and behaviors regarding COVID-19 [coronavirus disease 2019] in the United States."

16.
Non-conventional | Homeland Security Digital Library, Grey literature | ID: grc-740424

ABSTRACT

From the Document: "Rapid turnaround of testing for COVID-19 [coronavirus disease 2019] infection is essential to containing the pandemic. Ideally, test results would be available the same day. Our findings indicate that the United States is not currently performing testing with nearly enough speed. In our large (19,058 respondents) national survey, conducted between July 10 and 26, we asked whether respondents had been tested for COVID-19 and how long they had waited to get results. Our finding: 37% of those who had been tested by nasal swab received results within 2 days, and the average wait time was 4.1 days;with 31% of tests taking more than 4 days, and 10% 10 days or more. Further, there are few signs that turnaround times are diminishing. For individuals who responded that their last test had been in April, they had waited on average 4.2 days to get results;and for individuals tested in July, 4.1 days."

17.
JAMA Netw Open ; 3(10): e2023934, 2020 10 01.
Article in English | MEDLINE | ID: covidwho-893183

ABSTRACT

Importance: The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented stress on health systems across the world, and reliable estimates of risk for adverse hospital outcomes are needed. Objective: To quantify admission laboratory and comorbidity features associated with critical illness and mortality risk across 6 Eastern Massachusetts hospitals. Design, Setting, and Participants: Retrospective cohort study of all individuals admitted to the hospital who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by polymerase chain reaction across these 6 hospitals through June 5, 2020, using hospital course, prior diagnoses, and laboratory values in emergency department and inpatient settings from 2 academic medical centers and 4 community hospitals. The data were extracted on June 11, 2020, and the analysis was conducted from June to July 2020. Exposures: SARS-CoV-2. Main Outcomes and Measures: Severe illness defined by admission to intensive care unit, mechanical ventilation, or death. Results: Of 2511 hospitalized individuals who tested positive for SARS-CoV-2 (of whom 50.9% were male, 53.9% White, and 27.0% Hispanic, with a mean [SD ]age of 62.6 [19.0] years), 215 (8.6%) were admitted to the intensive care unit, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. L1-regression models developed in 3 of these hospitals yielded an area under the receiver operating characteristic curve of 0.807 for severe illness and 0.847 for mortality in the 3 held-out hospitals. In total, 212 of 292 deaths (72.6%) occurred in the highest-risk mortality quintile. Conclusions and Relevance: In this cohort, specific admission laboratory studies in concert with sociodemographic features and prior diagnosis facilitated risk stratification among individuals hospitalized for COVID-19.


Subject(s)
Coronavirus Infections/complications , Critical Illness , Hospital Mortality/trends , Pneumonia, Viral/complications , Adult , Aged , Aged, 80 and over , Area Under Curve , Betacoronavirus/pathogenicity , Blood Urea Nitrogen , C-Reactive Protein/analysis , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Cohort Studies , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/urine , Creatinine/analysis , Creatinine/blood , Critical Illness/epidemiology , Eosinophils , Erythrocyte Count/methods , Female , Glucose/analysis , Hospitalization/statistics & numerical data , Humans , Hydro-Lyases/analysis , Hydro-Lyases/blood , Lymphocyte Count/methods , Male , Massachusetts/epidemiology , Middle Aged , Monocytes , Neutrophils , Pandemics , Platelet Count/methods , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Polymerase Chain Reaction/methods , ROC Curve , Retrospective Studies , SARS-CoV-2 , Troponin T/analysis , Troponin T/blood
18.
Transl Psychiatry ; 10(1):224-224, 2020.
Article in English | MEDLINE | ID: covidwho-662361

ABSTRACT

The etiology of bipolar disorder (BD) is unknown and the neurobiological underpinnings are not fully understood. Both genetic and environmental factors contribute to the risk of BD, which may be linked through epigenetic mechanisms, including those regulated by histone deacetylase (HDAC) enzymes. This study measures in vivo HDAC expression in individuals with BD for the first time using the HDAC-specific radiotracer [11C]Martinostat. Eleven participants with BD and 11 age- and sex-matched control participants (CON) completed a simultaneous magnetic resonance - positron emission tomography (MR-PET) scan with [11C]Martinostat. Lower [11C]Martinostat uptake was found in the right amygdala of BD compared to CON. We assessed uptake in the dorsolateral prefrontal cortex (DLPFC) to compare previous findings of lower uptake in the DLPFC in schizophrenia and found no group differences in BD. Exploratory whole-brain voxelwise analysis showed lower [11C]Martinostat uptake in the bilateral thalamus, orbitofrontal cortex, right hippocampus, and right amygdala in BD compared to CON. Furthermore, regional [11C]Martinostat uptake was associated with emotion regulation in BD in fronto-limbic areas, which aligns with findings from previous structural, functional, and molecular neuroimaging studies in BD. Regional [11C]Martinostat uptake was associated with attention in BD in fronto-parietal and temporal regions. These findings indicate a potential role of HDACs in BD pathophysiology. In particular, HDAC expression levels may modulate attention and emotion regulation, which represent two core clinical features of BD.

SELECTION OF CITATIONS
SEARCH DETAIL
...