Trends in COVID-19 cases and clinical management in Veterans Health Administration medical facilities: A national cohort study

Development and Validation of a Clinical Risk Score to Predict Hospitalization Within 30 Days of Coronavirus Disease 2019 Diagnosis

INTRODUCTION

Early identification of patients with coronavirus disease 2019 (COVID-19) who are at risk for hospitalization may help to mitigate disease burden by allowing healthcare systems to conduct sufficient resource and logistical planning in the event of case surges. We sought to develop and validate a clinical risk score that uses readily accessible information at testing to predict individualized 30-day hospitalization risk following COVID-19 diagnosis.

METHODS

We assembled a retrospective cohort of U.S. Veterans Health Administration patients (age ≥ 18 years) diagnosed with COVID-19 between March 1, 2020, and December 31, 2020. We screened patient characteristics using Least Absolute Shrinkage and Selection Operator logistic regression and constructed the risk score using characteristics identified as most predictive for hospitalization. Patients diagnosed before November 1, 2020, comprised the development cohort, while those diagnosed on or after November 1, 2020, comprised the validation cohort. We assessed risk score discrimination by calculating the area under the receiver operating characteristic (AUROC) curve and calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test. This study was approved by the Veteran's Institutional Review Board of Northern New England at the White River Junction Veterans Affairs Medical Center (Reference no.:1473972-1).

RESULTS

The development and validation cohorts comprised 11,473 and 12,970 patients, of whom 4,465 (38.9%) and 3,669 (28.3%) were hospitalized, respectively. The independent predictors for hospitalization included in the risk score were increasing age, male sex, non-white race, Hispanic ethnicity, homelessness, nursing home/long-term care residence, unemployed or retired status, fever, fatigue, diarrhea, nausea, cough, diabetes, chronic kidney disease, hypertension, and chronic obstructive pulmonary disease. Model discrimination and calibration was good for the development (AUROC = 0.80; HL P-value = .05) and validation (AUROC = 0.80; HL P-value = .31) cohorts.

CONCLUSIONS

The prediction tool developed in this study demonstrated that it could identify patients with COVID-19 who are at risk for hospitalization. This could potentially inform clinicians and policymakers of patients who may benefit most from early treatment interventions and help healthcare systems anticipate capacity surges.

Trends in Outpatient Visits and Hospital and Intensive Care Unit Admissions of Adults With COVID-19 in an Integrated US Health Care System, March 2020 to January 2022

This cohort study of patients at a single integrated health system examines trends in COVID-19–related treatment location and mortality.

Predictors of Death, Survival, Need for Intubation, and Need for Oxygen Support Among Admitted COVID-19 Patients of the Veterans Affairs Greater Los Angeles Healthcare System

Introduction

While risk factors for severe COVID-19 infections have been well explored among the public, population-specific studies for the U.S. Veteran community are limited in the literature. By performing a comprehensive analysis of the demographics, comorbidities, and symptomatology of a population of COVID-19 positive Veterans Affairs (VA) patients, we aim to uncover predictors of death, survival, need for intubation, and need for nasal cannula oxygen support among this understudied community.

Materials and Methods

A retrospective review was conducted of 124 COVID-19 Veteran patients who were admitted from March to October 2020 to the VA Greater Los Angeles Healthcare System (IRB#2020-000272). Chi-square and Fisher’s exact tests were employed to assess differences in baseline demographic and clinical variables between Veterans who survived COVID-19 versus those who succumbed to COVID-19 illness. Multivariate logistic regression and Cox regression analyses were employed to assess predictors of outcome variables, including death, survival, need for intubation, and need for oxygen support (via nasal cannula). Covariates included a wide range of demographic, comorbidity-related, symptom-related, and summary index variables.

Results

Our study population consisted of primarily senior (average age was 73) Caucasian and African American (52.5% and 40.7%, respectively) Veterans. Bivariate analyses indicated that need for intubation was significantly associated with mortality (P = 0.002). Multivariate analyses revealed that age (P < 0.001, adjusted odds ratio (OR) = 1.16), dyspnea (P = 0.015, OR = 7.73), anorexia (P = 0.022, OR = 16.55), initial disease severity as classified by WHO (P = 0.031, OR = 4.55), and having more than one of the three most common comorbidities (hypertension, diabetes, and cardiac disease) and symptoms (cough, fever, and dyspnea) among our sample (P = 0.009; OR = 19.07) were independent predictors of death. Furthermore, age (P < 0.001, hazard ratio (HR) = 1.14), cerebrovascular disease (P = 0.022, HR = 3.76), dyspnea (P < 0.001, HR = 7.71), anorexia (P < 0.001, HR = 16.75), and initial disease severity as classified by WHO (P = 0.025, HR = 3.30) were independent predictors of poor survival. Finally, dyspnea reliably predicted need for intubation (P = 0.019; OR = 29.65).

Conclusions

Several independent predictors of death, survival, and need for intubation were identified. These risk factors may provide guidelines for risk-stratifying Veterans upon admission to VA hospitals. Additional investigations of COVID-19 prognosis should be conducted on the larger U.S. Veteran population to confirm our findings and add to the current body of literature.

The Interaction of Vitamin D and Corticosteroids: A Mortality Analysis of 26,508 Veterans Who Tested Positive for SARS-CoV-2

This data-based cohort consisted of 26,508 (7%) United States veterans out of the 399,290 who tested positive for SARS-CoV-2 from 1 March to 10 September 2020. We aimed to assess the interaction of post-index vitamin D (Vit D) and corticosteroid (CRT) use on 30-day mortality among hospitalized and non-hospitalized patients with coronavirus disease 2019 (COVID-19). Combination Vit D and CRT drug use was assessed according to four multinomial pairs (-|+, -|-, +|+, +|-). Respective categorical effects were computed on a log-binomial scale as adjusted relative risk (aRR). Approximately 6% of veterans who tested positive for SARS-CoV-2 died within 30 days of their index date. Among hospitalized patients, a significantly decreased aRR was observed for the use of Vit D in the absence of CRTs relative to patients who received CRTs but not Vit D (aRR = 0.30; multiplicity corrected, p = 0.0004). Among patients receiving systemically administered CRTs (e.g., dexamethasone), the use of Vit D was associated with fewer deaths in hospitalized patients (aRR = 0.51) compared with non-hospitalized patients (aRR = 2.5) (P-for-Interaction = 0.0071). Evaluating the effect of modification of these compounds in the context of hospitalization may aid in the management of COVID-19 and provide a better understanding of the pathophysiological mechanisms underlying this and future infectious disease outbreaks.