Risk Factors of Fall-Related Emergency Department Visits by Fall Location of Older Adults in the US

Introduction: Prior evidence indicates that predictors of older adult falls vary by indoor-outdoor location of the falls. While a subset of United States’ studies reports this finding using primary data from a single geographic area, other secondary analyses of falls across the country do not distinguish between the two fall locations. Consequently, evidence at the national level on risk factors specific to indoor vs outdoor falls is lacking. Methods: Using the 2017 Nationwide Emergency Department Sample (NEDS) data, we conducted a multivariable analysis of fall-related emergency department (ED) visits disaggregated by indoor vs outdoor fall locations of adults 65 years and older (N = 6,720,937) in the US. Results: Results are compatible with findings from previous primary studies. While women (relative risk [RR] = 1.43, 95% confidence interval [CI], 1.42-1.44) were more likely to report indoor falls, men were more likely to present with an outdoor fall. Visits for indoor falls were highest among those 85 years and older (RR = 2.35, 95% CI, 2.33-2.37) with outdoor fall visits highest among those 84 years and younger. Additionally, the probabilities associated with an indoor fall in the presence of chronic conditions were consistently much higher when compared to an outdoor fall. We also found that residence in metropolitan areas increased the likelihood of an indoor elderly fall compared to higher outdoor fall visits from seniors in non-core rural areas, but both indoor and outdoor fall visits were higher among older adults in higher income ZIP codes. Conclusion: Our findings highlight the contrasting risk profile for elderly ED patients who report indoor vs outdoor falls when compared to the elderly reporting no falls. In conjunction, we highlight implications from three perspectives: a population health standpoint for EDs working with their primary care and community care colleagues; an ED administrative vantage point; and from an individual emergency clinician’s point of view

Interpreting COVID-19 Deaths among Nursing Home Residents in the US: The Changing Role of Facility Quality over Time

A report published last year by the Centers for Medicare & Medicaid Services (CMS) highlighted that COVID-19 case counts are more likely to be high in lower quality nursing homes than in higher quality ones. Since then, multiple studies have examined this association with a handful also exploring the role of facility quality in explaining resident deaths from the virus. Despite this wide interest, no previous study has investigated how the relation between quality and COVID-19 mortality among nursing home residents may have changed, if at all, over the progression of the pandemic. This understanding is indeed lacking given that prior studies are either cross-sectional or are analyses limited to one specific state or region of the country. To address this gap, we analyzed changes in nursing home resident deaths across the US between June 1, 2020 and January 31, 2021 (n = 12,415 nursing homes X 8 months) using both descriptive and multivariable statistics. We merged publicly available data from multiple federal agencies with mortality rate (per 100,000 residents) as the outcome and CMS 5-star quality rating as the primary explanatory variable of interest. Covariates, based on the prior literature, consisted of both facility- and community-level characteristics. Findings from our secondary analysis provide robust evidence of the association between nursing home quality and resident deaths due to the virus diminishing over time. In connection, we discuss plausible reasons, especially duration of staff shortages, that over time might have played a critical role in driving the quality-mortality convergence across nursing homes in the US

SARS-COV-ATE risk assessment model for arterial thromboembolism in COVID-19

Patients with SARS-CoV-2 infection are at an increased risk of cardiovascular and thrombotic complications conferring an extremely poor prognosis. COVID-19 infection is known to be an independent risk factor for acute ischemic stroke and myocardial infarction (MI). We developed a risk assessment model (RAM) to stratify hospitalized COVID-19 patients for arterial thromboembolism (ATE). This multicenter, retrospective study included adult COVID-19 patients admitted between 3/1/2020 and 9/5/2021. Among 3531 patients from the training cohort, 15.5% developed acute in-hospital ATE, including stroke, MI, and other ATE, compared to 13.4% in the validation cohort. The 16-item final score was named SARS-COV-ATE (Sex: male = 1, Age [40-59 = 2, \u3e 60 = 4], Race: non-African American = 1, Smoking = 1 and Systolic blood pressure elevation = 1, Creatinine elevation = 1; Over the range: leukocytes/lactate dehydrogenase/interleukin-6, B-type natriuretic peptide = 1, Vascular disease (cardiovascular/cerebrovascular = 1), Aspartate aminotransferase = 1, Troponin-I [\u3e 0.04 ng/mL = 1, troponin-I \u3e 0.09 ng/mL = 3], Electrolytes derangement [magnesium/potassium = 1]). RAM had a good discrimination (training AUC 0.777, 0.756-0.797; validation AUC 0.766, 0.741-0.790). The validation cohort was stratified as low-risk (score 0-8), intermediate-risk (score 9-13), and high-risk groups (score ≥ 14), with the incidence of ATE 2.4%, 12.8%, and 33.8%, respectively. Our novel prediction model based on 16 standardized, commonly available parameters showed good performance in identifying COVID-19 patients at risk for ATE on admission

Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients

Atrial arrhythmias (AA) are common in hospitalized COVID-19 patients with limited data on their association with COVID-19 infection, clinical and imaging outcomes. In the related research article using retrospective research data from one quaternary care and five community hospitals, patients aged 18 years and above with positive SARS-CoV-2 polymerase chain reaction test were included. 6927 patients met the inclusion criteria. The data in this article provides demographics, home medications, in-hospital events and COVID-19 treatments, multivariable generalized linear regression regression models using a log link with a Poisson distribution (multi-parameter regression [MPR]) to determine predictors of new-onset AA and mortality in COVID-19 patients, computerized tomography chest scan findings, echocardiographic findings, and International Classification of Diseases-Tenth Revision codes. The clinical outcomes were compared to a propensity-matched cohort of influenza patients. For influenza, data is reported on baseline demographics, comorbid conditions, and in-hospital events. Generalized linear regression models were built for COVID-19 patients using demographic characteristics, comorbid conditions, and presenting labs which were significantly different between the groups, and hypoxia in the emergency room. Statistical analysis was performed using R programming language (version 4, ggplot2 package). Multivariable generalized linear regression model showed that, relative to normal sinus rhythm, history of AA (adjusted relative risk [RR]: 1.38; 95% CI: 1.11-1.71; p = 0.003) and newly-detected AA (adjusted RR: 2.02 95% CI: 1.68-2.43; p \u3c 0.001) were independently associated with higher in-hospital mortality. Age in increments of 10 years, male sex, White race, prior history of coronary artery disease, congestive heart failure, end-stage renal disease, presenting leukocytosis, hypermagnesemia, and hypomagnesemia were found to be independent predictors of new-onset AA in the MPR model. The dataset reported is related to the research article entitled Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19 [Jehangir et al. Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19, American Journal of Cardiology] [1]

RISK FACTORS OF ARTERIAL THROMBOEMBOLISM IN HOSPITALIZED COVID-19 PATIENTS: A MULTICENTER COHORT STUDY

Background: Endothelial cell dysfunction from infection by SARS-CoV-2 and inflammatory cytokines leading to hyperinflammatory and hypercoagulable state is thought to be the mechanism of arterial thromboembolism (ATE) in COVID-19 patients. COVID-19 infection is known to be an independent risk factor for acute stroke and myocardial infarction (MI). However, data on the risk factors of ATE in hospitalized COVID-19 patients is limited. Methods: This retrospective, multicenter cohort study included adult patients admitted to one quaternary care and three community hospitals with PCR-proven SARS-CoV-2 infection between 3/1/2020 and 12/31/2020. The composite outcome was in-hospital ATE events, including acute ischemic stroke, MI, and other ATE identified by ICD-10 codes. Student t-test was conducted for continuous variables and the Chi-square test for categorical variables. Multivariate logistic regression using forward selection was conducted. All statistical tests were 2-sided with an α level of 0.05. All data was analyzed using R version 4.0.4. Results: The cohort included 3531 patients with 371 (10.5%) patients who developed acute ATE. There were 398 ATE events: 270 patients had MI, 43 had stroke, 85 had other ATE, 12 had MI + stroke, 13 had MI + other ATE, and 2 had stroke + other ATE. The model suggested that initial systolic blood pressure (BP) \u3c90 mmHg and \u3e160 mmHg; elevated initial biomarkers including B-type natriuretic peptide (\u3e100 pg/mL), troponin-I (\u3e0.03 ng/mL), lactate dehydrogenase (\u3e192 U/L), creatine phosphokinase (male \u3e280 U/L and female \u3e155 U/L), C-reactive protein (\u3e0.5 mg/dL), leukocytes (\u3e11 K/uL), lactate (\u3e2.2 mmol/L), and aspartate aminotransferase (\u3e41 U/L); presenting hypoalbuminemia (\u3c3.5 g/dL) and hypomagnesemia (\u3c1.8 mg/dL); age \u3e60; male sex; and history of cerebrovascular accident (CVA), coronary artery disease (CAD), hyperthyroidism, and cigarette smoking were associated with an increased risk of ATE (all p\u3c0.05). Conclusion: Hypo or hypertension on admission, elevated inflammatory and cardiac markers, hypoalbuminemia, hypomagnesemia, smoking, and comorbidities including CAD and CVA are associated with ATE in hospitalized COVID-19 patients

Venous thromboembolism in COVID-19 patients and prediction model: a multicenter cohort study

BACKGROUND: Patients with COVID-19 infection are commonly reported to have an increased risk of venous thrombosis. The choice of anti-thrombotic agents and doses are currently being studied in randomized controlled trials and retrospective studies. There exists a need for individualized risk stratification of venous thromboembolism (VTE) to assist clinicians in decision-making on anticoagulation. We sought to identify the risk factors of VTE in COVID-19 patients, which could help physicians in the prevention, early identification, and management of VTE in hospitalized COVID-19 patients and improve clinical outcomes in these patients. METHOD: This is a multicenter, retrospective database of four main health systems in Southeast Michigan, United States. We compiled comprehensive data for adult COVID-19 patients who were admitted between 1st March 2020 and 31st December 2020. Four models, including the random forest, multiple logistic regression, multilinear regression, and decision trees, were built on the primary outcome of in-hospital acute deep vein thrombosis (DVT) and pulmonary embolism (PE) and tested for performance. The study also reported hospital length of stay (LOS) and intensive care unit (ICU) LOS in the VTE and the non-VTE patients. Four models were assessed using the area under the receiver operating characteristic curve and confusion matrix. RESULTS: The cohort included 3531 admissions, 3526 had discharge diagnoses, and 6.68% of patients developed acute VTE (N = 236). VTE group had a longer hospital and ICU LOS than the non-VTE group (hospital LOS 12.2 days vs. 8.8 days, p \u3c 0.001; ICU LOS 3.8 days vs. 1.9 days, p \u3c 0.001). 9.8% of patients in the VTE group required more advanced oxygen support, compared to 2.7% of patients in the non-VTE group (p \u3c 0.001). Among all four models, the random forest model had the best performance. The model suggested that blood pressure, electrolytes, renal function, hepatic enzymes, and inflammatory markers were predictors for in-hospital VTE in COVID-19 patients. CONCLUSIONS: Patients with COVID-19 have a high risk for VTE, and patients who developed VTE had a prolonged hospital and ICU stay. This random forest prediction model for VTE in COVID-19 patients identifies predictors which could aid physicians in making a clinical judgment on empirical dosages of anticoagulation

Characterizing Long COVID: Deep Phenotype of a Complex Condition.

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

New insights on patient-related risk factors for venous thromboembolism in patients with solid organ cancers

Patient-related risk factors for venous thromboembolism (VTE) are infrequently studied. We compared the role of patient-related risk factors for VTE in patients with solid organ cancers to their role in patients without cancer using National Inpatient Sample (NIS) data. Patients with cancer: risk of VTE hospitalization; Increased: chronic pulmonary disease (OR 1.172, 95% CI 1.102-1.247), obesity (OR 1.369, 95% CI 1.244-1.506). Decreased: liver disease (OR 0.654, 95% CI 0.562-0.762), chronic kidney disease (CKD) (OR 0.539, 95% CI 0.491-0.593), end-stage renal disease (ESRD) (OR 0.247, 95% CI 0.187-0.326). Patients without cancer: Risk of VTE hospitalization; Increased: age (OR 1.024, 95% CI 1.022-1.025), congestive heart failure (OR 1.221, 95% CI: 1.107-1.346), chronic pulmonary disease (OR 1.372, 95% CI 1.279-1.473), obesity (OR 2.627, 95% CI 2.431-2.838). Decreased: female gender (OR 0.772, 95% CI 0.730-0.816), diabetes (OR 0.756, 95% CI 0.701-0.815), ESRD (OR 0.315, 95% CI 0.252-0.395). In conclusion, chronic pulmonary disease and obesity increase VTE hospitalization risk in patients with and without cancer and the risk decreases in cancer patients with liver disease, CKD or ESRD