Risk Factors for Intensive Care Unit Admission and In-hospital Mortality among Hospitalized Adults Identified through the U.S. Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET)

Abstract Background Currently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk factors for severe outcomes among adults hospitalized with COVID-19. Methods We analyzed data from 2,491 adults hospitalized with laboratory-confirmed COVID-19 during March 1–May 2, 2020 identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network comprising 154 acute care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality. Results Ninety-two percent of patients had ≥1 underlying condition; 32% required ICU admission; 19% invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84 and ≥85 years versus 18-39 years (adjusted risk ratio (aRR) 1.53, 1.65, 1.84 and 1.43, respectively); male sex (aRR 1.34); obesity (aRR 1.31); immunosuppression (aRR 1.29); and diabetes (aRR 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84 and ≥85 years versus 18-39 years (aRR 3.11, 5.77, 7.67 and 10.98, respectively); male sex (aRR 1.30); immunosuppression (aRR 1.39); renal disease (aRR 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR 1.28); neurologic disorders (aRR 1.25); and diabetes (aRR 1.19). Conclusion In-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.


INTRODUCTION
Since a new coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first identified in China in December 2019, approximately 6 million cases of coronavirus disease-2019 (COVID -19) have been reported globally [1]. As of July 7, approximately 3 million cases, including ~130,000 deaths, have been reported in the United States, and case counts continue to rise [1] with evidence of widespread community transmission [2].
Reports from China, Italy, and New York City have demonstrated that hospitalized patients are generally older and have underlying medical conditions, such as hypertension and diabetes [3][4][5].
These studies have also found that older patients and those with certain underlying medical conditions were at higher risk for severe outcomes [3,6,7]. Among cases reported to the U.S.
Centers for Disease Control and Prevention (CDC) from local and state health departments, the prevalence of underlying medical conditions increased as severity of infections increased [8,9], although findings were limited by incomplete information. Questions remain about the independent association of sex, race and ethnicity, and specific underlying conditions with severe outcomes among persons hospitalized with COVID-19, after adjusting for age and other potential confounders.
Comprehensive data on U.S. patients with severe COVID-19 infections are needed to better inform clinicians' understanding of groups at risk for poor outcomes and to inform prevention efforts and future interventions. We implemented population-based surveillance for laboratoryconfirmed COVID-19-associated hospitalizations, collecting clinical data from hospitalized patients in 154 hospitals in 13 states since March 1, 2020. Using a convenience sample of patients identified though this surveillance system, we describe the characteristics of U.S. adults hospitalized with COVID-19 and assess risk factors for intensive care unit (ICU) admission and in-hospital mortality.
A c c e p t e d M a n u s c r i p t 7

Surveillance Overview
The Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET) has been previously described [10]. Eligible COVID-19-associated hospitalizations occurred among persons who (1) resided in a pre-defined surveillance catchment area; and (2) had a positive SARS-CoV-2 test within 14 days prior to or during hospitalization.
COVID-NET surveillance occurs in acute care hospitals within 99 counties in 14 states (California, Colorado, Connecticut, Georgia, Iowa, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah), covering a catchment population of approximately 32 million persons (~10% of the U.S. population). COVID-NET surveillance was initiated for cases with hospital admission on or after March 1, 2020. Although COVID-NET includes all age groups, for this analysis, we excluded children <18 years of age due to small counts (n=101) and one surveillance site (Iowa) for which medical chart abstractions were not conducted. We also excluded patients who were still hospitalized at the time of this analysis and all patients for whom medical chart abstractions had not yet been completed as of May 2, 2020. Because the COVID-19 pandemic limited the ability of surveillance officers to access medical records at facilities, patients were more likely to be included in this analysis if they were hospitalized at facilities that allowed remote chart access, participated in Health Information Exchanges, or were able to mail or fax records.
Laboratory-confirmed COVID-19-associated hospitalizations were identified using laboratory and reportable condition databases, hospital infection control databases, electronic medical records, and/or review of hospital discharge records. Laboratory tests were ordered at the discretion of the treating healthcare provider.
A c c e p t e d M a n u s c r i p t 8 Medical chart reviews were conducted by trained surveillance officers using a standard case report form. Underlying medical conditions were categorized into major groups (Appendix Table 1).
Obesity and severe obesity were defined as a calculated body mass index (BMI) ≥30 kg/m 2 and BMI ≥40 kg/m 2 , respectively. Chest radiograph results were obtained from the radiology reports and not from review of the original radiograph. We defined severe outcomes as either ICU admission or inhospital mortality.

Statistical Analysis
After the exclusions noted above, we included adults hospitalized within 154 acute care hospitals in 74 counties in 13 states with an admission date during March 1-May 2, 2020 who had either been discharged from the hospital or died during hospitalization and had complete medical chart abstractions. We calculated proportions using the number of patients with data available on each characteristic as the denominator.
We examined the association of demographic factors, underlying medical conditions, and use of angiotensin-converting enzyme (ACE)-inhibitors and angiotensin receptor blockers (ARBs) prior to hospitalization with ICU admission and in-hospital death using chi square tests. Variables considered for inclusion in the final models included current or former smoker, hypertension, obesity, diabetes, chronic lung disease (CLD), cardiovascular disease (CVD) (excluding hypertension), neurologic disorders, renal disease, immunosuppression, gastrointestinal/liver disease, hematologic conditions, rheumatologic/autoimmune conditions, and use of ACE-inhibitors or ARBs prior to hospitalization. All multivariable models included age groups (18-39, 40-49, 50-64, 65-74, 75-84, and ≥85 years), sex, and race and ethnicity; models incorporated clustering by site to account for geographic differences. Other variables with p-values <0.10 in bivariate analyses were included in the multivariable analyses. Log-linked Poisson generalized estimating equations regression with an A c c e p t e d M a n u s c r i p t 9 exchangeable correlation matrix [11,12] was used to generate adjusted risk ratios (aRR) and 95% confidence intervals (CI) for the risk of ICU admission and in-hospital death. Additional multivariable models were used to examine the association between the number of underlying medical conditions and ICU admission or in-hospital death. Two-sided p-values <0.05 were considered statistically significant. All analyses were performed using the SAS 9.4 software (SAS Institute Inc., Cary, NC, USA).
These data were collected as part of routine public health surveillance and determined to be non-research by CDC. Participating sites obtained approval for the COVID-NET surveillance protocol from their respective state and local IRBs, as required.

RESULTS
A total of 2,491 COVID-19-associated hospitalized adults from 13 surveillance sites were included (Appendix Figure 1). Patients came from 43% (154/357) of the acute care hospitals included in COVID-NET surveillance across the 13 sites (Appendix Table 2). The median age and sex distribution of included and excluded patients were similar (Appendix Table 3).
Having ≥3 underlying medical conditions was significantly associated with higher risk of ICU admission and death after adjusting for age, sex, and race and ethnicity (Appendix Tables 9A and   9B).

DISCUSSION
Using a geographically diverse, multi-site, population-based U.S. surveillance system, we found that among a sample of adults hospitalized with laboratory-confirmed COVID-19, almost onethird required ICU admission, 19% received invasive mechanical ventilation, and 17% died during hospitalization. About 75% of patients were ≥50 years, and >90% had underlying medical conditions. Older age, being male, and the presence of certain underlying medical conditions were associated with a higher risk of ICU admission and in-hospital mortality.
In a published COVID-NET analysis, we found that when comparing the racial and ethnic distribution of residents of the surveillance catchment areas to the racial and ethnic distribution of COVID-19-associated hospitalizations, non-Hispanic blacks were disproportionately hospitalized with COVID-19 compared to non-Hispanic whites [10]. In this analysis, however, we found that once hospitalized, non-Hispanic blacks did not have increased risk of poorer outcomes compared to other race and ethnicities after adjusting for age and underlying conditions. Other recent U.S. studies have also found no association between black race and ICU admission or in-hospital mortality [4,13,14].
A c c e p t e d M a n u s c r i p t 13 COVID-19-associated hospitalizations, ICU admissions, and deaths have been shown to occur more frequently with increasing age [6,9,15]. In our study, age ≥65 years was the strongest independent predictor of ICU admission and in-hospital mortality. Persons aged 75-84 years had the highest the risk of ICU admission compared to 18-49 years old, and those ≥85 years experienced 11 times the risk of death. These findings are similar to other studies from China, Europe, and the United States [4,9,[15][16][17][18]. Our data provide support that older persons are particularly vulnerable to severe COVID-19 disease and should be targeted for aggressive preventive measures [8].
Being male was associated with a higher risk of ICU admission and death after adjusting for age, race and ethnicity, and underlying conditions. Other studies have similarly shown male sex to be associated with COVID-19-associated hospitalizations [4,19], ICU admissions [20], and need for mechanical ventilation [21].
Similar to other U.S. studies, we found that nearly all hospitalized patients with COVID-19 had at least one underlying medical condition [4,22]. In contrast, underlying medical conditions were documented in only 25-50% of hospitalized cases from China [3,23]. Our analysis further demonstrated that a higher number of underlying medical conditions increased the risk of ICU admission (1.3 times the risk in persons with ≥3 vs. no underlying condition) and in-hospital mortality (1.8 times the risk in persons with ≥3 vs. no underlying condition).
In a retrospective case study among 1590 laboratory-confirmed hospitalized COVID-19 cases in 575 Chinese hospitals, Guan et al. found that after adjusting for age and smoking status, chronic obstructive pulmonary disease, diabetes, hypertension and malignancy were risk factors for a composite endpoint of ICU admission, invasive mechanical ventilation, and death [3]. Similarly, we found an association between underlying medical conditions and severe outcomes, with diabetes, CLD, CVD, neurologic disease, renal disease and immunosuppression associated with in-hospital death, and diabetes, obesity, and immunosuppression associated with ICU admission. While hypertension was highly prevalent in our patient population, it was not associated with ICU A c c e p t e d M a n u s c r i p t 14 admission or death. This is similar to recently published U.S. studies that did not find an association between hypertension and mortality [24,25]. While several Chinese studies found hypertension to be associated with more severe clinical outcomes, the prevalence of hypertension was much lower than reported in U.S. studies, and management and control of hypertension might vary between China and the U.S [3,18,26]. Additional studies are needed to determine whether hypertension, which is highly prevalent in the U.S. population, increases the risk of COVID-19-associated hospitalizations and whether the duration of hypertension and the degree to which it is controlled impact the risk for severe COVID-19 disease. Similarly, the associations between the duration and degree of glycemic control in diabetes and severity of COVID-19 disease require further investigation. Obesity, which was also highly prevalent in our study, imparted increased risk for ICU admission, but not death. This finding may, in part, be explained by a trend of decreasing obesity prevalence with increasing age, which was a strong risk factor for mortality. Healthcare providers should be aware of these findings to appropriately triage and manage patients with high-risk conditions that may either increase risk for hospitalization or poorer outcomes once hospitalized [27,28].
In our study, which was limited to patients that had either been discharged or died inhospital, 15% of patients received vasopressor support, and 19% received invasive mechanical ventilation. Other U.S. studies have found that up to 32% of hospitalized patients have received vasopressors and 17-33% have received invasive mechanical ventilation [20][21][22]29], though some of these studies included patients who were still hospitalized at the time of analysis. In our study, 53% of patients requiring mechanical ventilation died, which is slightly lower than the 60% published in a recent study from New York City [4], which reported a similar age distribution and prevalence of underlying medical conditions among hospitalized cases as our data. These proportions of severe outcomes among U.S. patients are also generally higher than those found in U.S. adults hospitalized with seasonal influenza [30,31]. Our findings may help to inform resource planning and allocation in healthcare facilities during the COVID-19 pandemic.
A c c e p t e d M a n u s c r i p t 15 There are limitations to our analysis. COVID-NET is an ongoing surveillance system, and a convenience sample of COVID-19 hospitalized patients was included, representing those who were discharged or died in-hospital during March 1-May 2, 2020 and for whom medical records were available and chart abstractions were completed. The hospitals that contributed cases to this analysis represented 43% of all the hospitals under surveillance; therefore, our findings may not be representative of the entire COVID-NET population or all adults hospitalized with COVID-19 in the United States. Nevertheless, COVID-NET encompasses a large geographic area with multiple hospitals and likely offers a more racially and ethnically diverse patient population compared to other single-center or state-based studies. Additionally, it is likely that not all COVID-19-associated hospitalizations were captured because of the lack of widespread testing capability during the study period and because identification of COVID-19 patients was largely reliant on clinician-directed testing.
Based on findings from this multi-site, geographically diverse study, a high proportion of patients hospitalized with COVID-19 received aggressive interventions and had poor outcomes.
Increasing age was the strongest predictor of in-hospital mortality. These findings alert healthcare providers to patient populations at highest risk for severe COVID-19-associated outcomes.
Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.