Co-Occurring Catatonia and COVID-19 Diagnoses Among Hospitalized Individuals in 2020: A National Inpatient Sample Analysis.

BACKGROUND: COVID-19 is associated with a range of neuropsychiatric manifestations. While case reports and case series have reported catatonia in the setting of COVID-19 infection, its rate has been poorly characterized. OBJECTIVE: This study reports the co-occurrence of catatonia and COVID-19 diagnoses among acute care hospital discharges in the United States in 2020. METHODS: The National Inpatient Sample, an all-payors database of acute care hospital discharges, was queried for patients of any age discharged with a diagnosis of catatonia and COVID-19 in 2020. RESULTS: Among 32,355,827 hospitalizations in the 2020 National Inpatient Sample, an estimated 15,965 (95% confidence interval: 14,992-16,938) involved a diagnosis of catatonia without COVID-19 infection, 1,678,385 (95% confidence interval: 1,644,738-1,712,022) involved a diagnosis of COVID-19 without a co-occurring catatonia diagnosis, and 610 (95% confidence interval: 578-642) involved both catatonia and COVID-19 infection. In an adjusted model, a diagnosis of COVID-19, but not a diagnosis of catatonia or the combination of catatonia and COVID-19, was associated with increased mortality. Patients with catatonia and COVID-19 were frequently diagnosed with encephalopathy and delirium codes. CONCLUSIONS: Catatonia and COVID-19 were rarely co-diagnosed in 2020, and catatonia diagnosis was not associated with increased mortality in patients with COVID-19. Further research is needed to better characterize the phenomenology of catatonia in the setting of COVID-19 infection and its optimal treatment.

The occurrence of catatonia diagnosis in acute care hospitals in the United States: A national inpatient sample analysis.

OBJECTIVE: Catatonia is a neuropsychiatric disorder that can occur in the setting of many illnesses, but the frequency of catatonia diagnosis among hospitalized patients is poorly characterized. This study reports the occurrence of catatonia diagnosis among acute care hospital discharges in the United States and the cooccurring diagnoses of these patients. METHOD: The National Inpatient Sample, an all-payors database of acute care hospital discharges, was queried for patients older than 18 discharged with a diagnosis of catatonia in 2019. RESULTS: 13,630 encounters among the 30,080,038 adult hospitalizations in the NIS during the study year included a diagnosis of catatonia. Total hospital charges for these admissions were $1.15 billion, with 215,165 cumulative hospital days. In this sample, approximately 60% of admissions had a primary psychiatric discharge diagnosis, while 40% had a primary neurologic or medical discharge diagnosis. Procedures were performed in 36.7% of hospitalizations involving catatonia, of which electroconvulsive therapy was most common. CONCLUSIONS: Catatonia is a rare but costly discharge diagnosis among patients in acute care hospitals. It occurs across the age spectrum and is associated with a range of medical and psychiatric comorbidities. Further research is needed to better characterize the occurrence of catatonia and its optimal treatment.

The Incidence of Catatonia Diagnosis Among Pediatric Patients Discharged From General Hospitals in the United States: A Kids' Inpatient Database Study.

Objective: Catatonia is a neuropsychiatric condition occurring across the age spectrum and associated with great morbidity and mortality. While prospective cohorts have investigated catatonia incidence among psychiatric patients, no studies have comprehensively explored the incidence of catatonia in general hospitals. We examine the incidence of catatonia diagnosis, demographics of catatonia patients, comorbidities, and inpatient procedures utilized among pediatric patients hospitalized with catatonia in the United States. Methods: The Kids' Inpatient Database, a national all-payors sample of pediatric hospitalizations in general hospitals, was examined for the year 2019. Hospitalizations with a discharge diagnosis of catatonia were included in the analysis. Hospitalizations with catatonia as the primary discharge diagnosis were compared to hospitalizations with catatonia as a secondary discharge diagnosis. Results: A total of 900 (95% CI: 850-949) pediatric discharges (291 with catatonia as a primary diagnosis, 609 with catatonia as a secondary diagnosis) occurred during the study year. Mean age was 15.6 ± 2.6 years, and 9.9% were under age 13. Comorbidities were common among patients with catatonia, with psychotic disorders (165; 18.3%), major depressive disorder (69; 7.7%), bipolar disorder (39; 4.3%) and substance-related disorders (20; 2.2%) as the most common primary diagnoses. There was significant comorbidity with neurologic illness, developmental disorders, autism spectrum disorder, and inflammatory conditions. In total 390 catatonia discharges (43.3%) included at least one procedure during admission. Conclusions: catatonia is rarely diagnosed in pediatric patients in general hospitals but is associated with significant and severe psychiatric and medical comorbidities. Further research is needed into the optimal diagnosis, workup, and treatment of catatonia in pediatric patients.

Epidemiology and risk factors for the development of cutaneous toxicities in patients treated with immune-checkpoint inhibitors: A United States population-level analysis.

BACKGROUND: A variety of dermatoses have been reported in the growing number of patients treated with immune-checkpoint inhibitors (ICIs), but the current understanding of cutaneous immune-related adverse events (irAEs) is limited. OBJECTIVE: To determine the cumulative incidence, distribution, and risk factors of cutaneous irAEs after ICI initiation. METHODS: This was a retrospective cohort study of patients in a national insurance claims database including cancer patients treated with ICIs and matched controls. RESULTS: The study included 8637 ICI patients and 8637 matched controls. The overall incidence of cutaneous irAEs was 25.1%, with a median onset time of 113 days. The ICI group had a significantly higher incidence of pruritus, mucositis, erythroderma, maculopapular eruption, vitiligo, lichen planus, bullous pemphigoid, Grover disease, rash, other nonspecific eruptions, and drug eruption or other nonspecific drug reaction. Patients with melanoma and renal cell carcinoma and those receiving combination therapy were at a higher risk of cutaneous irAEs. LIMITATIONS: Retrospective design without access to patient chart data. CONCLUSIONS: This study identifies cutaneous irAEs in a real-world clinical setting and highlights patient groups that are particularly at risk. The results can aid dermatologists at the bedside in the diagnosis of cutaneous irAEs and in formulating management recommendations to referring oncologists regarding the continuation of ICI therapy.

Applying machine learning to smartphone based cognitive and sleep assessments in schizophrenia.

BACKGROUND: Cognitive impairment in schizophrenia remains a chief source of functional disability and impairment, despite the potential for effective interventions. This is in part related to a lack of practical and easy to administer screening strategies that can identify and help triage cognitive impairment. This study explores how smartphone-based assessments may help address this need. METHODS: In this study, data was analyzed from 25 subjects with schizophrenia and 30 controls who engaged with a gamified mobile phone version of the Trails-B cognitive assessment in their everyday life over 90 days and complete a clinical neurocognitive testing battery at the beginning and end of the study. Machine learning was applied to the resulting dataset to predict disease status and neurocognitive function and understand which features were most important for accurate prediction. RESULTS: The generated models predicted disease status with high accuracy using static features alone (AUC = 0.94), with the total number of items collected and the total duration of interaction with the application most predictive. The addition of temporal data statistically significantly improved performance (AUC = 0.95), with the amount of idle time a significant new predictor. Correlates of sleep dysfunction were also predicted (AUC = 0.80), with similar feature importance. DISCUSSION: Machine learning enabled the highly accurate identification of subjects with schizophrenia versus healthy controls, and the accurate prediction of neurocognitive function. The addition of temporal data significantly improved the performance of these models, underscoring the value of smartphone-based assessments of cognition as a practical tool for assessing cognition.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in the staff of a public school system in the midwestern United States.

Since March 2020, the United States has lost over 580,000 lives to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. A growing body of literature describes population-level SARS-CoV-2 exposure, but studies of antibody seroprevalence within school systems are critically lacking, hampering evidence-based discussions on school reopenings. The Lake Central School Corporation (LCSC), a public school system in suburban Indiana, USA, assessed SARS-CoV-2 seroprevalence in its staff and identified correlations between seropositivity and subjective histories and demographics. This study is a cross-sectional, population-based analysis of the seroprevalence of SARS-CoV-2 in LCSC staff measured in July 2020. We tested for seroprevalence with the Abbott Alinity™ SARS-CoV-2 IgG antibody test. The primary outcome was the total seroprevalence of SARS-CoV-2, and secondary outcomes included trends of antibody presence in relation to baseline attributes. 753 participants representative of the staff at large were enrolled. 22 participants (2.9%, 95% CI: 1.8% - 4.4%) tested positive for SARS-CoV-2 antibodies. Correcting for test performance parameters, the seroprevalence is estimated at 1.7% (90% Credible Interval: 0.27% - 3.3%). Multivariable logistic regression including mask wearing, travel history, symptom history, and contact history revealed a 48-fold increase in the odds of seropositivity if an individual previously tested positive for COVID-19 (OR: 48, 95% CI: 4-600). Amongst individuals with no previous positive test, exposure to a person diagnosed with COVID-19 increased the odds of seropositivity by 7-fold (OR: 7.2, 95% CI: 2.6-19). Assuming the presence of antibodies is associated with immunity against SARS-CoV-2 infection, these results demonstrate a broad lack of herd immunity amongst the school corporation's staff irrespective of employment role or location. Protective measures like contact tracing, face coverings, and social distancing are therefore vital to maintaining the safety of both students and staff as the school year progresses.

Prediction of severe immune-related adverse events requiring hospital admission in patients on immune checkpoint inhibitors: study of a population level insurance claims database from the USA.

BACKGROUND: Immune-related adverse events (irAEs) are a serious side effect of immune checkpoint inhibitor (ICI) therapy for patients with advanced cancer. Currently, predisposing risk factors are undefined but understanding which patients are at increased risk for irAEs severe enough to require hospitalization would be beneficial to tailor treatment selection and monitoring. METHODS: We performed a retrospective review of patients with cancer treated with ICIs using unidentifiable claims data from an Aetna nationwide US health insurance database from January 3, 2011 to December 31, 2019, including patients with an identified primary cancer and at least one administration of an ICI. Regression analyses were performed. Main outcomes were incidence of and factors associated with irAE requiring hospitalization in ICI therapy. RESULTS: There were 68.8 million patients identified in the national database, and 14 378 patients with cancer identified with at least 1 administration of ICI in the study period. Patients were followed over 19 117 patient years and 504 (3.5%) developed an irAE requiring hospitalization. The incidence of irAEs requiring hospitalization per patient ICI treatment year was 2.6%, rising from 0% (0/71) in 2011 to 3.7% (93/2486) in 2016. Combination immunotherapy (OR: 2.44, p<0.001) was associated with increased odds of developing irAEs requiring hospitalization, whereas older patients (OR 0.98 per additional year, p<0.001) and those with non-lung cancer were associated with decreased odds of irAEs requiring hospitalization (melanoma OR: 0.70, p=0.01, renal cell carcinoma OR: 0.71, p=0.03, other cancers OR: 0.50, p<0.001). Sex, region, zip-code-imputed income, and zip-code unemployment were not associated with incidence of irAE requiring hospitalization. Prednisone (72%) and methylprednisolone (25%) were the most common immunosuppressive treatments identified in irAE hospitalizations. CONCLUSIONS: We found that 3.5% of patients initiating ICI therapy experienced irAEs requiring hospitalization and immunosuppression. The odds of irAEs requiring hospitalization were higher with younger age, treatment with combination ICI therapy (cytotoxic T lymphocyte-associated 4 and programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1)), and lower for other cancers compared with patients on PD-1 or PD-L1 inhibitors with lung cancer. This evidence from the first nationwide study of irAEs requiring hospitalization in the USA identified the real-world epidemiology, risk factors, and treatment patterns of these irAEs which may guide treatment and management decisions.

Seroprevalence of anti-SARS-CoV-2 IgG Antibodies in the Staff of a Public School System in the Midwestern United States.

BACKGROUND: Since March 2020, the United States has lost over 200,000 lives to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. A growing body of literature describes population-level SARS-CoV-2 exposure, but studies of antibody seroprevalence within school systems are critically lacking, hampering evidence-based discussions on school reopenings. The Lake Central School Corporation (LCSC), a public school system in suburban Indiana, USA, assessed SARS-CoV-2 seroprevalence in its staff and identified correlations between seropositivity and subjective histories and demographics. METHODS: This study is a cross-sectional, population-based analysis of the seroprevalence of SARS-CoV-2 in LCSC staff measured in July 2020. We tested for seroprevalence with the Abbott Alinity™ SARS-CoV-2 IgG antibody test. The primary outcome was the total seroprevalence of SARS-CoV-2, and secondary outcomes included trends of antibody presence in relation to baseline attributes. FINDINGS: 753 participants representative of the staff at large were enrolled. 22 participants (2·9%, 95% CI: 1·8% - 4·4%) tested positive for SARS-CoV-2 antibodies. Correcting for test performance parameters, the seroprevalence is estimated at 1·7% (90% Credible Interval: 0·27% - 3·3%). Multivariable logistic regression including mask wearing, travel history, symptom history, and contact history revealed a 48-fold increase in the odds of seropositivity if an individual previously tested positive for COVID-19 (OR: 48.2, 95% CI: 4 - 600). Amongst individuals with no previous positive test, exposure to a person diagnosed with COVID-19 increased the odds of seropositivity by 7-fold (OR: 6.5, 95% CI: 2.06 - 18.9). INTERPRETATION: Assuming the presence of antibodies is associated with immunity against SARS-CoV-2 infection, these results demonstrate a broad lack of herd immunity amongst the school corporation's staff irrespective of employment role or location. Protective measures like contact tracing face coverings, and social distancing are therefore vital to maintaining the safety of both students and staff as the school year progresses. FUNDING: Lake Central School Corporation. RESEARCH IN CONTEXT: Evidence before this study: We searched PubMed, SSRN, Research Square, and Gale Power Search for peer-reviewed articles, preprints, and research reports on the seroprevalence of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG antibodies, published in English, using the search terms "COVID-19 in schools," "COVID-19 seroprevalence," "COVID antibodies," and similar terms up to August 30, 2020. We identified several articles pertaining to the spread of COVID-19 within schools and among children. Current evidence on the pediatric transmission of COVID-19 is mixed, but early data on secondary school transmission are sobering. Shared among this literature was an acknowledgement of the paucity of data regarding how the pandemic may progress in the students and staff of primary and secondary education systems. To our knowledge, there is no study that specifically interrogates the seroprevalence of COVID-19 among US public school staff.Added value of this study: As of September 2020, the United States has had more COVID-19 cases than any other country. With many US schools opening for in-person classes for the 2020-2021 school year, a granular understanding of the transmission dynamics within public school systems is vital to effectively and appropriately defending against COVID-19. Most seroprevalence studies have been based on city or hospital-level populations; this study establishes a baseline seroprevalence of SARS-CoV-2 antibodies in a Midwest public school district prior to the initiation of the school year.Implications of all available evidence: The results of this study reveal that the majority (98·3%) of LCSC staff have not been exposed to COVID-19 prior to the start of the school year. Staff are therefore vulnerable to a large outbreak after the school opens, underscoring the importance of maintaining rigorous sanitary practices within the schools. It is vital that all members of LCSC and similar school districts across the country continue social distancing and mask wearing throughout the school day to limit exposure to COVID-19. Contact tracing in combination with rapid testing for individuals exposed to an individual with COVID-19 should also be employed.

Deregulation of ribosomal protein expression and translation promotes breast cancer metastasis.

Circulating tumor cells (CTCs) are shed into the bloodstream from primary tumors, but only a small subset of these cells generates metastases. We conducted an in vivo genome-wide CRISPR activation screen in CTCs from breast cancer patients to identify genes that promote distant metastasis in mice. Genes coding for ribosomal proteins and regulators of translation were enriched in this screen. Overexpression of RPL15, which encodes a component of the large ribosomal subunit, increased metastatic growth in multiple organs and selectively enhanced translation of other ribosomal proteins and cell cycle regulators. RNA sequencing of freshly isolated CTCs from breast cancer patients revealed a subset with strong ribosome and protein synthesis signatures; these CTCs expressed proliferation and epithelial markers and correlated with poor clinical outcome. Therapies targeting this aggressive subset of CTCs may merit exploration as potential suppressors of metastatic progression.

Quantitative Analysis of Circulating Tumor Cells Using RNA-Based Digital Scoring.

Circulating tumor cells (CTCs) provide valuable information about the molecular evolution of cancers, as they may initially respond and ultimately progress on therapy. As intact tumor cells isolated from the bloodstream, CTCs also enable assessment of heterogeneous subpopulations, and their analysis may include DNA, RNA, and protein biomarkers. New microfluidic cell isolation strategies greatly facilitate the challenge of enriching viable tumor cells from the billions of hematopoietic cells within a standard blood specimen. While counting and characterization of enriched CTCs have primarily relied on immunostaining for tumor cell-specific antigens, new RNA-based analytic platforms are providing new insight into the identity of CTCs and providing new tools for clinical applications. Single-cell RNA sequencing of CTCs reveals a high degree of heterogeneity among cancer cells from a single individual, while new digital RNA-based amplification platforms may now allow high-sensitivity and high-throughput quantitative scoring of CTCs for clinical applications. Here, we focus on transcriptomic analysis of CTCs and its relevance in understanding metastatic cancer progression and in developing diagnostic assays to monitor cancer.

A Digital RNA Signature of Circulating Tumor Cells Predicting Early Therapeutic Response in Localized and Metastatic Breast Cancer.

The multiplicity of new therapies for breast cancer presents a challenge for treatment selection. We describe a 17-gene digital signature of breast circulating tumor cell (CTC)-derived transcripts enriched from blood, enabling high-sensitivity early monitoring of response. In a prospective cohort of localized breast cancer, an elevated CTC score after three cycles of neoadjuvant therapy is associated with residual disease at surgery (P = 0.047). In a second prospective cohort with metastatic breast cancer, baseline CTC score correlates with overall survival (P = 0.02), as does persistent CTC signal after 4 weeks of treatment (P = 0.01). In the subset with estrogen receptor (ER)-positive disease, failure to suppress ER signaling within CTCs after 3 weeks of endocrine therapy predicts early progression (P = 0.008). Drug-refractory ER signaling within CTCs overlaps partially with presence of ESR1 mutations, pointing to diverse mechanisms of acquired endocrine drug resistance. Thus, CTC-derived digital RNA signatures enable noninvasive pharmacodynamic measurements to inform therapy in breast cancer.Significance: Digital analysis of RNA from CTCs interrogates treatment responses of both localized and metastatic breast cancer. Quantifying CTC-derived ER signaling during treatment identifies patients failing to respond to ER suppression despite having functional ESR1. Thus, noninvasive scoring of CTC-RNA signatures may help guide therapeutic choices in localized and advanced breast cancer. Cancer Discov; 8(10); 1286-99. ©2018 AACR. This article is highlighted in the In This Issue feature, p. 1195.

Molecular signatures of circulating melanoma cells for monitoring early response to immune checkpoint therapy.

A subset of patients with metastatic melanoma have sustained remissions following treatment with immune checkpoint inhibitors. However, analyses of pretreatment tumor biopsies for markers predictive of response, including PD-1 ligand (PD-L1) expression and mutational burden, are insufficiently precise to guide treatment selection, and clinical radiographic evidence of response on therapy may be delayed, leading to some patients receiving potentially ineffective but toxic therapy. Here, we developed a molecular signature of melanoma circulating tumor cells (CTCs) to quantify early tumor response using blood-based monitoring. A quantitative 19-gene digital RNA signature (CTC score) applied to microfluidically enriched CTCs robustly distinguishes melanoma cells, within a background of blood cells in reconstituted and in patient-derived (n = 42) blood specimens. In a prospective cohort of 49 patients treated with immune checkpoint inhibitors, a decrease in CTC score within 7 weeks of therapy correlates with marked improvement in progression-free survival [hazard ratio (HR), 0.17; P = 0.008] and overall survival (HR, 0.12; P = 0.04). Thus, digital quantitation of melanoma CTC-derived transcripts enables serial noninvasive monitoring of tumor burden, supporting the rational application of immune checkpoint inhibition therapies.

An RNA-Based Digital Circulating Tumor Cell Signature Is Predictive of Drug Response and Early Dissemination in Prostate Cancer.

Blood-based biomarkers are critical in metastatic prostate cancer, where characteristic bone metastases are not readily sampled, and they may enable risk stratification in localized disease. We established a sensitive and high-throughput strategy for analyzing prostate circulating tumor cells (CTC) using microfluidic cell enrichment followed by digital quantitation of prostate-derived transcripts. In a prospective study of 27 patients with metastatic castration-resistant prostate cancer treated with first-line abiraterone, pretreatment elevation of the digital CTCM score identifies a high-risk population with poor overall survival (HR = 6.0; P = 0.01) and short radiographic progression-free survival (HR = 3.2; P = 0.046). Expression of HOXB13 in CTCs identifies 6 of 6 patients with ≤12-month survival, with a subset also expressing the ARV7 splice variant. In a second cohort of 34 men with localized prostate cancer, an elevated preoperative CTCL score predicts microscopic dissemination to seminal vesicles and/or lymph nodes (P < 0.001). Thus, digital quantitation of CTC-specific transcripts enables noninvasive monitoring that may guide treatment selection in both metastatic and localized prostate cancer.Significance: There is an unmet need for biomarkers to guide prostate cancer therapies, for curative treatment of localized cancer and for application of molecularly targeted agents in metastatic disease. Digital quantitation of prostate CTC-derived transcripts in blood specimens is predictive of abiraterone response in metastatic cancer and of early dissemination in localized cancer. Cancer Discov; 8(3); 288-303. ©2018 AACR.See related commentary by Heitzer and Speicher, p. 269This article is highlighted in the In This Issue feature, p. 253.

An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma.

Circulating tumor cells (CTCs) are shed into the bloodstream by invasive cancers, but the difficulty inherent in identifying these rare cells by microscopy has precluded their routine use in monitoring or screening for cancer. We recently described a high-throughput microfluidic CTC-iChip, which efficiently depletes hematopoietic cells from blood specimens and enriches for CTCs with well-preserved RNA. Application of RNA-based digital PCR to detect CTC-derived signatures may thus enable highly accurate tissue lineage-based cancer detection in blood specimens. As proof of principle, we examined hepatocellular carcinoma (HCC), a cancer that is derived from liver cells bearing a unique gene expression profile. After identifying a digital signature of 10 liver-specific transcripts, we used a cross-validated logistic regression model to identify the presence of HCC-derived CTCs in nine of 16 (56%) untreated patients with HCC versus one of 31 (3%) patients with nonmalignant liver disease at risk for developing HCC (P < 0.0001). Positive CTC scores declined in treated patients: Nine of 32 (28%) patients receiving therapy and only one of 15 (7%) patients who had undergone curative-intent ablation, surgery, or liver transplantation were positive. RNA-based digital CTC scoring was not correlated with the standard HCC serum protein marker alpha fetoprotein (P = 0.57). Modeling the sequential use of these two orthogonal markers for liver cancer screening in patients with high-risk cirrhosis generates positive and negative predictive values of 80% and 86%, respectively. Thus, digital RNA quantitation constitutes a sensitive and specific CTC readout, enabling high-throughput clinical applications, such as noninvasive screening for HCC in populations where viral hepatitis and cirrhosis are prevalent.