Multisystem Inflammatory Syndrome in Adults: Case Finding Through Systematic Review of Electronic Medical Records

BACKGROUND

Multisystem inflammatory syndrome in adults (MIS-A) is a severe condition temporally associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

In this retrospective cohort study, we applied the US Centers for Disease Control and Prevention (CDC) case definition to identify diagnosed and undiagnosed MIS-A cases among adults discharged during April 2020-January 2021 from 4 Atlanta, Georgia hospitals affiliated with a single medical center. Non-MIS-A coronavirus disease 2019 (COVID-19) hospitalizations were identified using International Classification of Diseases, Tenth Revision, Clinical Modification encounter code U07.1. We calculated the ratio of MIS-A to COVID-19 hospitalizations, compared demographic characteristics of the 2 cohorts, and described clinical characteristics of MIS-A patients.

RESULTS

We identified 11 MIS-A cases, none of which were diagnosed by the treatment team, and 5755 COVID-19 hospitalizations (ratio 1:523). Compared with patients with COVID-19, patients with MIS-A were more likely to be younger than 50 years (72.7% vs 26.1%, P < .01) and to be non-Hispanic Black (81.8% vs 50.0%, P = .04). Ten patients with MIS-A (90.9%) had at least 1 underlying medical condition. Two MIS-A patients (18.2%) had a previous episode of laboratory-confirmed COVID-19, occurring 37 and 55 days prior to admission. All MIS-A patients developed left ventricular systolic dysfunction. None had documented mucocutaneous involvement. All required intensive care, all received systemic corticosteroids, 8 (72.7%) required mechanical ventilation, 2 (18.2%) required mechanical cardiovascular circulatory support, and none received intravenous immunoglobulin. Two (18.2%) died or were discharged to hospice.

CONCLUSIONS

MIS-A is a severe but likely underrecognized complication of SARS-CoV-2 infection. Improved recognition of MIS-A is needed to quantify its burden and identify populations at highest risk.

Characteristics and Risk Factors of Hospitalized and Nonhospitalized COVID-19 Patients, Atlanta, Georgia, USA, March-April 2020

We compared the characteristics of hospitalized and nonhospitalized patients who had coronavirus disease in Atlanta, Georgia, USA. We found that risk for hospitalization increased with a patient’s age and number of concurrent conditions. We also found a potential association between hospitalization and high hemoglobin A1c levels in persons with diabetes.

COVID-19 Clinical Phenotypes: Presentation and Temporal Progression of Disease in a Cohort of Hospitalized Adults in Georgia, United States

BACKGROUND

The epidemiological features and outcomes of hospitalized adults with coronavirus disease 2019 (COVID-19) have been described; however, the temporal progression and medical complications of disease among hospitalized patients require further study. Detailed descriptions of the natural history of COVID-19 among hospitalized patients are paramount to optimize health care resource utilization, and the detection of different clinical phenotypes may allow tailored clinical management strategies.

METHODS

This was a retrospective cohort study of 305 adult patients hospitalized with COVID-19 in 8 academic and community hospitals. Patient characteristics included demographics, comorbidities, medication use, medical complications, intensive care utilization, and longitudinal vital sign and laboratory test values. We examined laboratory and vital sign trends by mortality status and length of stay. To identify clinical phenotypes, we calculated Gower's dissimilarity matrix between each patient's clinical characteristics and clustered similar patients using the partitioning around medoids algorithm.

RESULTS

One phenotype of 6 identified was characterized by high mortality (49%), older age, male sex, elevated inflammatory markers, high prevalence of cardiovascular disease, and shock. Patients with this severe phenotype had significantly elevated peak C-reactive protein creatinine, D-dimer, and white blood cell count and lower minimum lymphocyte count compared with other phenotypes (P < .01, all comparisons).

CONCLUSIONS

Among a cohort of hospitalized adults, we identified a severe phenotype of COVID-19 based on the characteristics of its clinical course and poor prognosis. These findings need to be validated in other cohorts, as improved understanding of clinical phenotypes and risk factors for their development could help inform prognosis and tailored clinical management for COVID-19.

Predictors at admission of mechanical ventilation and death in an observational cohort of adults hospitalized with COVID-19

Background

Coronavirus disease (COVID-19) can cause severe illness and death. Predictors of poor outcome collected on hospital admission may inform clinical and public health decisions.

Methods

We conducted a retrospective observational cohort investigation of 297 adults admitted to eight academic and community hospitals in Georgia, United States, during March 2020. Using standardized medical record abstraction, we collected data on predictors including admission demographics, underlying medical conditions, outpatient antihypertensive medications, recorded symptoms, vital signs, radiographic findings, and laboratory values. We used random forest models to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CI) for predictors of invasive mechanical ventilation (IMV) and death.

Results

Compared with age <45 years, ages 65–74 years and ≥75 years were predictors of IMV (aOR 3.12, CI 1.47–6.60; aOR 2.79, CI 1.23–6.33) and the strongest predictors for death (aOR 12.92, CI 3.26–51.25; aOR 18.06, CI 4.43–73.63). Comorbidities associated with death (aORs from 2.4 to 3.8, p <0.05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Pre-hospital use vs. non-use of angiotensin receptor blockers (aOR 2.02, CI 1.03–3.96) and dihydropyridine calcium channel blockers (aOR 1.91, CI 1.03–3.55) were associated with death.

Conclusions

After adjustment for patient and clinical characteristics, older age was the strongest predictor of death, exceeding comorbidities, abnormal vital signs, and laboratory test abnormalities. That coronary artery disease, but not chronic lung disease, was associated with death among hospitalized patients warrants further investigation, as do associations between certain antihypertensive medications and death.

Characteristics Associated with Hospitalization Among Patients with COVID-19 - Metropolitan Atlanta, Georgia, March-April 2020

The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age ≥65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.

The need for guidance and consistency in adolescent privacy policies: a survey of CMIOs

Research examining whether and how adolescent patients should gain access to their electronic health records is gaining momentum. We conducted a survey to explore diversity in adolescent privacy policies and identify common approaches in health information technology management for adolescent patients. Through descriptive analyses of survey data, we found a wide range of institutional policies regarding adolescent patient privacy, and large variations in health IT executives' baseline knowledge of access policies. A majority of respondents agreed that formal guidelines pertaining to adolescent health record privacy would be helpful. Respondents suggested that these guidelines can be developed through the synthesis of multiple perspectives, including those of pediatricians, adolescent specialists, privacy experts, parents, patient advocates, and other professional entities.