Abstract
Objectives:
To determine whether factors associated with COVID-19 hospitalization among people with HIV (PWH) differ by age stratum.
Design:
Retrospective cohort study.
Methods:
All adult PWH with a positive SARS-CoV-2 PCR in a public safety-net health system between March 1, 2020 and February 28, 2021 and a Veterans Affairs Medical Center between March 1, 2020 and November 15, 2020 in Atlanta, GA were included. We performed multivariable logistic regression to determine demographic and clinical factors associated with COVID-19 hospitalization overall and stratified by age <50 and ≥50 years.
Results:
365 PWH (mean age 49 years, 74% cisgender male, 82% Black) were included. 96% were on antiretroviral therapy (ART), 87% had CD4+ T-cell count ≥200 cells/mm3, and 89% had HIV-1 RNA <200 copies/ml. Overall, age [aOR(95% CI) 1.07(1.04-1.10)], later date of SARS-CoV-2 infection [aOR 0.997(0.995-1.00)], heart disease [aOR 2.27(1.06-4.85)], and history of hepatitis C virus (HCV) [aOR 2.59(1.13-5.89)] were associated with COVID-19 hospitalization. Age-adjusted comorbidity burden was associated with 30% increased risk of hospitalization [aOR 1.30(1.11-1.54)]. Among 168 PWH <50 years old, older age [aOR 1.09(1.01-1.18)] and no ART use [aOR 40.26(4.12-393.62)] were associated with hospitalization; age-adjusted comorbidity burden was not (p=0.25). Among 197 PWH ≥50, older age [aOR 1.10(1.04-1.16)], heart disease [aOR 2.45(1.04-5.77)], history of HCV [aOR 3.52(1.29-9.60)], and age-adjusted comorbidity burden [aOR 1.36(1.12-1.66)] were associated with hospitalization.
Conclusions:
Comorbidity burden is more strongly associated with COVID-19 hospitalization among older, rather than younger, PWH. These findings may have important implications for risk stratifying COVID-19 therapies and booster recommendations in PWH.
Keywords: Human immunodeficiency virus, severe acute respiratory syndrome coronavirus 2, coronavirus disease 2019, hospitalization, multimorbidity
Introduction
Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic in late December 2019, it has been well-established that advanced age, comorbidity burden, and immunosuppression are risk factors for severe COVID-19.[1, 2] However, for people with HIV (PWH) risk factors for severe COVID-19 remain unclear. PWH have been shown to be at increased risk of severe COVID-19 including hospitalization[3, 4] and death[5-8] after controlling for age and sex, but reasons for this elevated risk are likely multifactorial. There is mounting evidence, mostly from cohorts of PWH with well-controlled HIV in North America and western Europe, that an increased comorbidity burden plays a large role in severe COVID-19 risk among PWH.[9, 10] Other larger studies from similar settings also implicate HIV-specific parameters including CD4+ T-cell count, CD4/CD8 ratio, HIV-1 RNA viremia, and specific antiretroviral therapy (ART) use.[7, 11-13] These data suggest that, while age and comorbidity burden are important contributors to COVID-19 severity among PWH, HIV-related factors, particularly CD4+ T-cell count, may also play a role.
Most of the available data do not address specific risk factors for COVID-19 hospitalization among PWH by age group. If differences by age group exist, they may have important implications for COVID-19 treatment and prevention guidelines. One cohort study conducted in the United Kingdom through June 2020 found that COVID-19 mortality was greater among PWH age <60 years compared to people without HIV in the same age group.[8] Current COVID-19 treatment guidelines consider age ≥65 years to be a risk factor for severe disease,[14] but this age cutoff may need to be reconsidered in PWH. Stratification at age 50 was chosen a priori based on evidence of increased risk for multimorbidity in PWH at that age.[15] Previous work has shown that PWH experience accelerated aging and age-related comorbidities at earlier ages compared with the general population,[16, 17] and risk of these comorbidities appears to increase after age 50, often sooner than in the general population.[15, 16] Therefore, we sought to determine risk factors for hospitalization for COVID-19 among PWH overall and stratified by age <50 years and ≥50 years.
Methods
Study Population
The Emory Center for AIDS Research (CFAR) supports a well-curated HIV disease Registry that includes all PWH who have received care at the Grady Health System that includes a Ryan White-funded HIV clinic and a public safety-net hospital, or the Atlanta Veterans Affairs Medical Center (AVAMC) in Atlanta, GA, USA. The Registry contains longitudinal demographic, clinical, and laboratory data. Because these sites function as medical homes for their patients where they seek most of their medical care, including for symptomatic COVID-19 and SARS-CoV-2 testing, the Registry provides an ideal opportunity to study COVID-19 hospitalization risk factors in a diverse, urban population of PWH in the first year of the COVID-19 pandemic prior to widespread vaccine uptake. All adult (age ≥18 years) PWH with data in the Emory CFAR HIV Disease Registry with a positive SARS-CoV-2 PCR within the Grady Health System between March 1, 2020 and February 28, 2021, and within the AVAMC between March 1, 2020 and November 15, 2020 were included in this analysis. These dates were chosen to include the first year of the pandemic prior to widespread rollout of COVID-19 vaccinations. This study was approved by the Emory University Institutional Review Board, the Grady Research Oversite Committee, and the AVAMC Research and Development Committee.
Outcome measures
SARS-CoV-2 test results were obtained from the Registry and supplemented by retrospective chart review. A positive SARS-CoV-2 test was defined as a positive PCR within the study period. For patients with multiple positive SARS-CoV-2 tests, the date of the first positive test was considered the index date. Reinfection was rare during this time period, and only the first COVID-19 cases were considered. Hospitalization for COVID-19 was defined as hospital admission within 30 days following a positive SARS-CoV-2 PCR with symptoms related to COVID-19 including fever, chills, cough, dyspnea, vomiting, diarrhea, myalgias, anosmia, dysgeusia, and fatigue/lethargy. Patients incidentally found to have a positive SARS-CoV-2 PCR upon hospitalization for another indication and without symptoms consistent with COVID-19 were not included in the hospitalization group. Patients without symptom data were considered to have at least one COVID-19 symptom. Hospitalization indication was determined by admission and discharge diagnoses and confirmed by chart review. All hospital admissions were reviewed by two infectious diseases physicians (CAM and NTO).
Measurement of covariates
Demographic and clinical characteristics were obtained from the Emory CFAR Disease Registry and supplemented by manual chart abstraction. CD4+ T-cell count, plasma HIV-1 RNA level, and ART use were obtained from the most recent value within 12 months prior to the positive SARS-CoV-2 test. Consistent with other studies,[3, 7, 18-20] HIV-1 viral suppression was defined as HIV-1 RNA <200 copies/ml based on the National Institutes of Health definition for virologic failure.[21] Substance use was obtained by chart abstraction and ICD-10 codes. Illicit drug use was defined as use of crack/cocaine, heroin, methamphetamines, or prescription opioids for non-prescribed purposes. Due to inconsistent documentation, cannabis use was not included in this analysis. Comorbidities of interest for this analysis and included in the calculation for comorbidity burden were based upon prior evidence for severe COVID-19 risk[12, 22] and included hypertension, dyslipidemia, chronic lung disease (asthma or chronic obstructive pulmonary disease (COPD)), heart disease (defined as the presence of either coronary heart disease, chronic arrhythmia, valvular heart disease, or congestive heart failure), diabetes mellitus, obesity, chronic kidney disease (including end-stage renal disease), and active malignancy, and were ascertained by individual ICD-10 codes unless otherwise specified. Diabetes mellitus was further defined as the presence of a glycosylated hemoglobin ≥6.5%, obesity was defined as a body mass index ≥30 kg/m2, chronic kidney disease by two or more consecutive estimated glomerular filtration rate measurements <60 ml/min or requiring chronic renal replacement therapy. History of HBV and HCV infection were determined by ICD-10 code and history of HBV infection by a positive serum Hepatitis B surface antigen or detectable HBV DNA, and history of HCV infection by a positive serum anti-HCV antibody and either detectable HCV RNA or a history of sustained virologic response to anti-HCV treatment.
Missing Data
There were few (<1%) missing data elements in the variables included in our models. Therefore, a complete case analysis was performed.
Statistical Analysis
Baseline characteristics and clinical outcomes of hospitalized and non-hospitalized patients overall and stratified by age (<50 years and ≥50 years) were compared by chi-square or Fisher’s exact test for categorical variables, and Student’s t-tests or Wilcoxon rank-sum tests for continuous variables. Baseline characteristics were also compared for hospitalized PWH by age category. Univariable logistic regression models were used to determine the association between covariates and hospitalization for COVID-19. A multivariable logistic regression model including all covariates except for comorbidity burden that were significantly associated with hospitalization was performed. To determine the association between covariates and COVID-19 hospitalization by age strata, univariable and multivariable logistic regression models were run as above. A separate logistic regression model controlling only for age was run to determine the association between comorbidity burden and COVID-19 hospitalization for the entire cohort and by age strata.
Analyses were conducted using SAS v9.4 (SAS Institute, Cary, NC). Statistical significance was determined using a p-value of <0.05.
Sensitivity Analyses
We conducted sensitivity analyses limiting the cohort to only PWH with a CD4+ T-cell count less than 200 cells/mm3 or who were not virally suppressed and controlling for age. We did not stratify this analysis by age given the small sample size. To assess for misclassification bias, we performed a sensitivity analysis in which all hospitalized patients, regardless of indication, were included in the hospitalization group. In a separate analysis, we excluded all patients with underlying heart disease, chronic lung disease, active malignancy, or organ transplant, as these patients may have been more likely to be admitted for indications other than COVID-19.
Results
Baseline Characteristics
Baseline characteristics for the cohort are presented in Table 1. Of the 365 PWH included in this analysis, 106 (29%) were hospitalized for COVID-19. The mean [standard deviation (SD)] age was 48.6 (13.5) years with a range of 18-80 years. 82% of the cohort was Black and 74% identified as cisgender male. The mean (SD) CD4+ T-cell count was 515 (300) cells/mm3, 96% of patients were on ART, and 89% were virally suppressed. 73% had at least one comorbidity, 50% had two comorbidities, and 31% had three or more comorbidities (16% aged <50 years and 44% aged ≥50 years). Hypertension (45%), obesity (35%) dyslipidemia (30%) and diabetes mellitus (22%) were the most prevalent comorbidities (Table 1). 10 patients incidentally found to have a positive SARS-CoV-2 PCR upon hospitalization for another indication were not included in the hospitalization group in this analysis. Indications for admission included: motor vehicle crash (2), acute osteomyelitis (2), acute appendicitis (1), new diagnosis of pancreatic adenocarcinoma (1), acute renal failure (1), chronic gastritis (1), acute psychosis and decompensated schizophrenia (1), and residence in a nursing home with an inability to house patients with COVID-19 (1).
Table 1.
Baseline characteristics of PWH by COVID-19 hospitalization status for the entire cohort and by age strata
| Entire cohort (n=365) | Age <50 (n=168) | Age ≥50 (n=197) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Variable | Not hospitalized (n=258) |
Hospitalized (n=106) |
P-value | Not hospitalized (n=145) |
Hospitalized (n=23) |
P- value |
Not hospitalized (n=113) |
Hospitalized (n=83) |
P-value |
| Demographic variables | |||||||||
| Age, mean (SD) | 45.1 (12.9) | 57.0 (11.1) | <0.001 | 35.6 (8.3) | 40.4 (7.7) | 0.01 | 57.1 (5.6) | 61.5 (6.6) | <0.001 |
| Gender, n(%) | 0.17 | 0.13 | 0.71 | ||||||
| Cis-male | 195 (76) | 72 (68) | 110 (76) | 14 (61) | 85 (75) | 58 (70) | |||
| Cis-female | 57 (22) | 33 (31) | 30 (21) | 9 (39) | 27 (24) | 24 (29) | |||
| Trans-female | 5 (2) | 1 (1) | 4 (3) | 0 (0) | 1 (1) | 1 (1) | |||
| Race/ethnicity, n(%) | 0.84 | 0.66 | 0.82 | ||||||
| Black | 209 (81) | 88 (83) | 120 (83) | 21 (91) | 89 (79) | 67 (81) | |||
| Hispanic/Latinx | 27 (10) | 11 (10) | 17 (12) | 2 (9) | 10 (9) | 9 (11) | |||
| White | 16 (6) | 6 (6) | 4 (3) | 0 (0) | 12 (11) | 6 (7) | |||
| Other | 6 (2) | 1 (1) | 4 (3) | 0 (0) | 2 (2) | 1 (1) | |||
| Site, n(%) | 0.003 | 0.02 | 0.13 | ||||||
| Grady | 234 (91) | 84 (79) | 135 (93) | 18 (78) | 99 (88) | 66 (80) | |||
| AVAMC | 24 (9) | 22 (21) | 10 (7) | 5 (22) | 14 (12) | 17 (20) | |||
| Current smoker, n(%) | 71 (28) | 19 (18) | 0.054 | 39 (27) | 5 (22) | 0.60 | 32 (28) | 14 (17) | 0.06 |
| Alcohol abuse, n(%) | 22 (9) | 7 (7) | 0.54 | 10 (7) | 2 (9) | 0.67 | 12 (11) | 5 (6) | 0.26 |
| Illicit drug use, n(%) | 21 (8) | 10 (9) | 0.69 | 10 (7) | 5 (22) | 0.04 | 11 (10) | 5 (6) | 0.35 |
| HIV-related clinical variables | |||||||||
| CD4 cells/mm3, mean (SD) | 519 (298) | 507 (307) | 0.73 | 550.3 (336.3) | 500.8 (410.3) | 0.53 | 478.7 (234.5) | 508.7 (275.1) | 0.41 |
| CD4 ≥200 cells/mm3, n(%) | 223 (87) | 92 (87) | 0.86 | 122 (85) | 17 (74) | 0.22 | 101 (90) | 75 (90) | 0.97 |
| HIV-1 RNA <200 copies/ml, n(%) | 227 (89) | 95 (90) | 0.94 | 124 (87) | 18 (78) | 0.34 | 103 (93) | 77 (93) | 0.99 |
| ART, n(%) | 250 (97) | 99 (93) | 0.08 | 142 (99) | 20 (87) | 0.02 | 108 (96) | 79 (95) | 1.00 |
| TDF, n(%) | 14 (6) | 6 (6) | 0.94 | 9 (6) | 1 (4) | 1.00 | 5 (4) | 5 (6) | 0.75 |
| PI, n(%) | 32 (13) | 18 (17) | 0.26 | 18 (13) | 6 (26) | 0.11 | 14 (13) | 12 (15) | 0.67 |
| INSTI, n(%) | 222 (87) | 85 (81) | 0.11 | 125 (88) | 17 (74) | 0.10 | 97 (87) | 68 (83) | 0.48 |
| Comorbidities | |||||||||
| Hypertension, n(%) | 101 (39) | 63 (59) | 0.0004 | 41 (28) | 7 (30) | 0.83 | 60 (53) | 56 (67) | 0.04 |
| Dyslipidemia, n(%) | 62 (24) | 46 (43) | 0.0002 | 22 (15) | 6 (26) | 0.19 | 40 (35) | 40 (48) | 0.07 |
| Diabetes mellitus, n(%) | 40 (16) | 39 (37) | <0.001 | 13 (9) | 5 (22) | 0.08 | 27 (24) | 34 (41) | 0.01 |
| Heart disease, n(%) | 18 (7) | 25 (24) | <0.001 | 6 (4) | 2 (9) | 0.30 | 12 (11) | 23 (28) | 0.002 |
| Chronic lung disease, n(%) | 22 (9) | 16 (15) | 0.06 | 8 (6) | 2 (9) | 0.63 | 14 (12) | 14 (17) | 0.38 |
| Obesity, n(%) | 82 (33) | 43 (41) | 0.15 | 44 (32) | 9 (39) | 0.48 | 38 (34) | 34 (41) | 0.29 |
| BMI, mean (SD) | 28.5 (6.6) | 28.8 (7.3) | 0.75 | 28.3 (6.8) | 29.2 (10.6) | 0.71 | 28.7 (6.2) | 28.6 (6.1) | 0.92 |
| Chronic kidney disease, n(%) | 30 (12) | 26 (25) | 0.002 | 11 (8) | 2 (9) | 0.69 | 19 (17) | 24 (30) | 0.08 |
| History of HBV, n(%) | 13 (5) | 1 (1) | 0.06 | 5 (3) | 0 (0) | 1.00 | 8 (7) | 1 (1) | 0.052 |
| History of HCV, n(%) | 19 (7) | 18 (17) | 0.006 | 8 (6) | 1 (4) | 1.00 | 11 (10) | 17 (20) | 0.03 |
| HCV viremia, n(%) | 10 (4) | 6 (6) | 0.46 | 4 (3) | 0 (0) | 1.00 | 6 (5) | 6 (7) | 0.58 |
| Malignancy, n(%) | 13 (5) | 12 (11) | 0.03 | 8 (6) | 4 (17) | 0.06 | 5 (4) | 8 (10) | 0.15 |
| Solid organ transplant, n(%) | 1 (<1) | 2 (2) | 0.15 | 0 (0) | 1 (4) | 0.14 | 1 (1) | 1 (1) | 1.00 |
| Comorbidity burden, median, (q1, q3) | 1 (0,2) | 3 (1,4) | <0.001 | 1 (2,6) | 2 (3,5) | 0.054 | 2 (1,3) | 3 (2,4) | <0.001 |
Abbreviations: PWH, persons with HIV; COVID-19, coronavirus disease 2019; SD, standard deviation; AVAMC, Atlanta Veterans Affairs Medical Center; ART, antiretroviral therapy; TDF, tenofovir disoproxil fumarate; PI, protease inhibitor; INSTI, integrase strand transfer inhibitor; BMI, body mass index; HBV, hepatitis B virus; HCV, hepatitis C virus; q1,q3, first quartile, third quartile. ART classes are not mutually exclusive.
In hospitalized PWH aged <50 years (n=23) compared with hospitalized PWH aged ≥50 years (n=83), younger PWH were more likely to use illicit drugs (22% vs. 6%), and older PWH were more likely to have hypertension (67% vs. 30%), heart disease (24% vs. 9%), chronic kidney disease (26% vs. 4%), and a greater median number of comorbidities (3 vs. 2). There was a non-significant trend among PWH aged <50 toward less HIV-1 viral suppression (78% vs. 93%, p=0.06) and lower CD4+ T-cell counts ≥200 cells/mm3 (74% vs. 90%, p=0.07) (Supplementary Table 1).
COVID-19 Disease Outcomes
106 (29%) of all patients were hospitalized, including 14% of the 168 patients aged <50 years and 42% of the 197 patients aged ≥50 years. The overall 30-day mortality rate was 4%, and mortality rate was higher among patients ≥50 (6%) vs <50 (1%) years old (p=0.02). Younger patients were more likely to be treated with hydroxychloroquine (17% vs. 5%, p=0.04) and less likely to be treated with monoclonal antibodies (2% vs. 7%, p=0.04); however, other COVID-19 treatments and oxygen requirement did not differ significantly by age (Table 2).
Table 2.
Outcomes of COVID-19 among hospitalized PWH, overall and by age strata
| Outcome | Overall | Age <50 | Age ≥50 | p-value |
|---|---|---|---|---|
| Overall mortality* (n=365), n(%) | 14 (4) | 2 (1) | 12 (6) | 0.02 |
| In-hospital mortality (n=106), n(%) | 13 (12) | 2 (9) | 11 (13) | 0.56 |
| Maximum O2 requirement, n(%) | 0.54 | |||
| Room air | 47 (44) | 13 (57) | 34 (41) | |
| Nasal cannula | 33 (31) | 5 (22) | 28 (34) | |
| HFNC/NRB | 13 (12) | 2 (9) | 11 (13) | |
| IMV/ECMO | 13 (12) | 3 (13) | 10 (12) | |
| LOS (days), median (q1, q3) | 6 (4, 12) | 6 (4, 8) | 6 (4, 13) | 0.17 |
| Discharge disposition | 0.68 | |||
| Home | 74 (80) | 18 (90) | 56 (77) | |
| SNF/SAR | 13 (14) | 2 (10) | 11 (15) | |
| Other acute facility | 2 (2) | 0 (0) | 2 (3) | |
| Hospice | 2 (2) | 0 (0) | 2 (3) | |
| Other | 2 (2) | 0 (0) | 2 (3) | |
| Treatment | ||||
| Clinical trial,** n(%) | 5 (5) | 0 (0) | 5 (6) | 0.23 |
| ACTT1 | 2 (2) | 0 (0) | 2 (2) | 0.45 |
| ACTT2 | 2 (2) | 0 (0) | 2 (2) | 0.45 |
| ACTT4 | 1 (1) | 0 (0) | 1 (1) | 0.60 |
| Sarilumab vs placebo | 1 (1) | 0 (0) | 1 (1) | 0.60 |
| Remdesivir, n(%) | 42 (40) | 6 (26) | 36 (43) | 0.13 |
| Dexamethasone, n(%) | 45 (42) | 8 (35) | 37 (45) | 0.40 |
| Baricitinib, n(%) | 1 (1) | 0 (0) | 1 (1) | 0.60 |
| Tocilizumab, n(%) | 1 (1) | 0 (0) | 1 (1) | 0.60 |
| Hydroxychloroquine, n(%) | 8 (8) | 4 (17) | 4 (5) | 0.04 |
| Azithromycin, n(%) | 11 (10) | 2 (9) | 9 (11) | 0.77 |
| Monoclonal antibodies**, n(%) | 18 (5) | 4 (2) | 14 (7) | 0.04 |
Includes inpatients and outpatients
ACTT1, remdesivir vs placebo; ACTT2, remdesivir + baricitinib vs remdesivir + placebo; ACTT4, remdesivir + baricitinib vs remdesivir + dexamethasone
Abbreviations: HFNC, high-flow nasal cannula; NRB, non-rebreather; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation; LOS, length of stay; SNF, skilled nursing facility; SAR, subacute rehabilitation; ACTT, adaptive COVID-19 treatment trial.
Risk Factors for COVID-19 Hospitalization in the Entire Cohort
Results of univariable and multivariable analyses for the entire cohort are presented in Table 3. In univariable analysis, age, earlier date of SARS-CoV-2 infection, AVAMC site, hypertension, dyslipidemia, diabetes mellitus, heart disease, chronic kidney disease, history of HCV, malignancy, and comorbidity burden were all associated with a risk of COVID-19-related hospitalization. After controlling for these covariates in the multivariable model, age [adjusted odds ratio (aOR) (95% confidence interval (CI)) 1.07 (1.04-1.10)], later date of SARS-CoV-2 infection [aOR 0.997 (0.995-1.00)], heart disease [aOR 2.27 (1.06-4.85)], and history of HCV [aOR 2.59 (1.13-5.89)] were associated with COVID-19 hospitalization. In unadjusted and age-adjusted models, comorbidity burden was associated with higher odds of hospitalization in a stepwise fashion (figure 1a and 1b). After adjusting for age, each additional comorbidity was associated with a 30% increased risk of hospitalization [aOR 1.31 (1.11-1.54)].
Table 3.
Unadjusted and adjusted odds of COVID-19 hospitalization for PWH in the entire cohort
| Variable | OR (95% CI) | p-value | aOR (95% CI) | p-value |
|---|---|---|---|---|
| Demographic variables | ||||
| Age | 1.09 (1.06-1.11) | <0.001 | 1.07 (1.04-1.10) | <0.001 |
| Gender | 0.18 | |||
| Cisgender male | Referent | |||
| Cisgender female | 1.57 (0.95-2.60) | |||
| Transgender female | 0.54 (0.06-4.72) | |||
| Race/Ethnicity | 0.86 | |||
| White | Referent | |||
| Black | 1.12 (0.43-2.96) | |||
| Hispanic/Latinx | 1.09 (0.34-3.51) | |||
| Other | 0.44 (0.04-4.50) | |||
| Date of SARS-CoV-2 | 0.997 (0.995-0.999) | 0.02 | 0.997 (0.995-1.00) | 0.049 |
| Site at AVAMC | 2.55 (1.36-4.80) | 0.004 | 1.54 (0.71-3.34) | 0.28 |
| Current smoking | 0.58 (0.33-1.01) | 0.056 | ||
| Alcohol abuse | 0.76 (0.31-1.83) | 0.54 | ||
| Illicit drug use | 1.17 (0.53-2.59) | 0.69 | ||
| HIV-related clinical variables | ||||
| CD4 count <200 cells/mm3 | 1.06 (0.54-2.08) | 0.86 | ||
| HIV-1 RNA ≥200 copies/ml | 0.97 (0.46-2.04) | 0.94 | ||
| ART (no vs yes) | 2.53 (0.86-7.38) | 0.09 | ||
| TDF | 1.04 (0.39-2.78) | 0.94 | ||
| Protease inhibitor | 1.44 (0.77-2.69) | 0.26 | ||
| INSTI | 0.61 (0.33-1.13) | 0.12 | ||
| Comorbidities | ||||
| Hypertension | 2.28 (1.44-3.61) | <0.001 | 0.93 (0.51-1.69) | 0.82 |
| Dyslipidemia | 2.42 (1.50-3.91) | <0.001 | 1.00 (0.53-1.89) | >0.99 |
| Diabetes mellitus | 3.17 (1.89-5.33) | <0.001 | 1.90 (0.99-3.64) | 0.052 |
| Heart disease | 4.12 (2.14-7.93) | <0.001 | 2.27 (1.06-4.85) | 0.03 |
| Chronic lung disease | 1.91 (0.96-3.80) | 0.07 | ||
| Obesity | 1.42 (0.89-2.26) | 0.15 | ||
| Body mass index | 1.01 (0.97-1.04) | 0.75 | ||
| Chronic kidney disease | 2.47 (1.38-4.43) | 0.002 | 1.36 (0.68-2.72) | 0.39 |
| History of HBV | 0.18 (0.02-1.39) | 0.10 | ||
| History of HCV | 2.56 (1.29-5.11) | 0.008 | 2.59 (1.13-5.89) | 0.02 |
| HCV viremia | 1.48 (0.53-4.19) | 0.46 | ||
| Malignancy | 2.41 (1.06-5.46) | 0.04 | 2.26 (0.85-5.99) | 0.10 |
| Solid organ transplant | 4.94 (0.44-55.09) | 0.19 | ||
| Comorbidity burden* | 1.58 (1.36-1.83) | <0.001 | 1.31 (1.11-1.54) | 0.001 |
Multivariable model adjusted for age, date of SARS-CoV-2 infection, site, hypertension, dyslipidemia, diabetes mellitus, heart disease, chronic kidney disease, chronic HCV, and malignancy.
Adjusted for age only.
Abbreviations: PWH, persons with HIV; OR, odds ratio; aOR, adjusted odds ratio; CI, confidence interval; AVAMC, Atlanta Veterans Affairs Medical Center; ART, antiretroviral therapy; TDF, tenofovir disoproxil fumarate; INSTI, integrase strand transfer inhibitor; HBV, hepatitis B virus; HCV, hepatitis C virus
Figure 1.
Odds of COVID-19 hospitalization by comorbidity burden among PWH a) the entire cohort, p<0.001; b) the entire cohort adjusted for age, p=0.007; c) PWH <50 years old adjusted for age, p=0.62 and d) PWH ≥50 years old adjusted for age, p=0.007.
Risk Factors for COVID-19 Hospitalization by Age Strata
Age ≥50 years versus age <50 was associated with a more than 4-fold increased odds of hospitalization [OR 4.63 (2.74-7.81)]. Results of univariable and multivariable analyses by age strata are presented in Table 4. On univariable analysis, for patients age <50 years, age, earlier date of SARS-CoV-2 infection, AVAMC site, illicit drug use, and no ART use were associated with greater odds of COVID-19 hospitalization. For patients age ≥50 years, age, earlier date of SARS-CoV-2 infection, hypertension, diabetes, heart disease, chronic kidney disease, and history of HCV were associated with greater odds of COVID-19 hospitalization. After controlling for these covariates, age [aOR 1.09 (1.01-1.18)] and no ART use [aOR 40.26 (4.12-393.62)] remained significantly associated with hospitalization in PWH <50. There was a non-significant trend toward greater odds of hospitalization with illicit drug use [aOR 3.86 (0.87-17.25)]. There was no association with age-adjusted comorbidity burden and COVID-19 hospitalization (figure 1c). For PWH ≥50, age [aOR 1.10 (1.04-1.16)], heart disease [aOR 2.45 (1.04-5.77)] and history of HCV [aOR 3.52 (1.29-9.60)] were associated with COVID-19 hospitalization. Unlike in the younger age stratum, age-adjusted comorbidity burden was associated with COVID-19 hospitalization (figure 1d).
Table 4.
Unadjusted and adjusted odds of COVID-19 hospitalization for PWH stratified by age
| Age <50 (n=168) | Age ≥50 (n=197) | |||||||
|---|---|---|---|---|---|---|---|---|
| Variable | OR (95% CI) | p- value |
aOR (95% CI) | p-value | OR (95% CI) | p- value |
aOR (95% CI) | p-value |
| Demographic variables | ||||||||
| Age | 1.08 (1.02-1.15) | 0.01 | 1.09 (1.01-1.18) | 0.04 | 1.12 (1.07-1.18) | <0.001 | 1.10 (1.04-1.16) | 0.001 |
| Cis/trans-female vs cis-male | 2.08 (0.83-5.237) | 0.12 | 1.31 (0.70-2.47) | 0.41 | ||||
| All other race/ethnicity vs Black | 0.46 (0.10-2.08) | 0.31 | 0.89 (0.44-1.80) | 0.74 | ||||
| Date of SARS-CoV-2 | 0.995 (0.990-1.00) | 0.03 | 0.995 (0.009-1.001) | 0.12 | 0.997 (0.994-1.00) | 0.046 | 0.998 (0.994-1.001) | 0.16 |
| Site at AVAMC vs Grady | 3.75 (1.15-12.22) | 0.03 | 1.50 (0.34-6.67) | 0.59 | 1.82 (0.84-3.95) | 0.13 | 1.40 (0.52-3.73) | 0.51 |
| Current smoking | 0.76 (0.26-2.17) | 0.60 | 0.51 (0.25-1.04) | 0.06 | ||||
| Alcohol abuse | 1.29 (0.26-6.28) | 0.76 | 0.54 (0.18-1.60) | 0.26 | ||||
| Illicit drug use | 3.75 (1.15-12.22) | 0.03 | 3.86 (0.87-17.25) | 0.08 | 0.59 (0.20-1.78) | 0.35 | 0.45 (0.12-1.62) | 0.22 |
| HIV-related clinical variables | ||||||||
| CD4 count <200 cells/mm3 | 2.05 (0.73-5.80) | 0.18 | 0.98 (0.38-2.55) | 0.97 | ||||
| HIV RNA ≥200 copies/ml | 1.81 (0.60-5.46) | 0.29 | 1.00 (0.33-3.01) | 0.99 | ||||
| ART (no vs yes) | 10.65 (1.68-67.69) | 0.01 | 40.26 (4.12-393.62) | 0.002 | 1.09 (0.29-4.21) | 0.90 | 1.25 (0.24-6.58) | 0.80 |
| TDF | 0.67 (0.08-5.57) | 0.71 | 1.39 (0.39-4.97) | 0.61 | ||||
| Protease inhibitor | 2.43 (0.85-6.98) | 0.10 | 1.20 (0.52-2.75) | 0.67 | ||||
| INSTI | 0.39 (0.13-1.11) | 0.08 | 0.75 (0.34-1.66) | 0.48 | ||||
| Comorbidities | ||||||||
| Hypertension | 1.11 (0.43-2.90) | 0.83 | 0.58 (0.15-2.25) | 0.43 | 1.83 (1.02-3.30) | 0.04 | 1.15 (0.58-2.30) | 0.69 |
| Dyslipidemia | 1.97 (0.70-5.58) | 0.20 | 1.70 (0.95-3.03) | 0.07 | ||||
| Diabetes mellitus | 2.82 (0.90-8.85) | 0.08 | 3.30 (0.79-13.88) | 0.10 | 2.21 (1.20-4.09) | 0.01 | 1.68 (0.82-3.44) | 0.16 |
| Heart disease | 2.21 (0.42-11.66) | 0.35 | 2.71 (0.31-23.70) | 0.37 | 3.23 (1.50-6.95) | 0.003 | 2.45 (1.04-5.77) | 0.04 |
| Chronic lung disease | 1.63 (0.32-8.21) | 0.55 | 1.44 (0.64-3.20) | 0.38 | ||||
| Obesity | 1.39 (0.56-3.45) | 0.48 | 1.37 (0.76-2.46) | 0.29 | ||||
| Body mass index | 1.02 (0.96-1.07) | 0.61 | 1.00 (0.95-1.05) | 0.92 | ||||
| Chronic kidney disease | 1.16 (0.24-5.60) | 0.85 | 1.13 (0.14-8.99) | 0.91 | 2.01 (1.02-3.99) | 0.045 | 1.60 (0.71-3.60) | 0.26 |
| History of HBV | --- | --- | 0.16 (0.02-1.31) | 0.09 | ||||
| History of HCV | 0.77 (0.09-6.48) | 0.81 | 2.15 (0.18-26.34) | 0.55 | 2.39 (1.05-5.42) | 0.04 | 3.52 (1.29-9.60) | 0.01 |
| HCV viremia | --- | --- | 1.39 (0.43-4.47) | 0.58 | ||||
| Malignancy | 3.61 (0.99-13.13) | 0.052 | 2.30 (0.73-7.32) | 0.16 | ||||
| Solid organ transplant | --- | --- | 1.37 (0.08-22.16) | 0.83 | ||||
| Comorbidity burden* | 1.38 (1.03-1.85) | 0.03 | 1.21 (0.88-1.67) | 0.25 | 1.44 (1.20-1.73) | <0.001 | 1.36 (1.12-1.66) | 0.002 |
aORs adjusted for age, date of SARS-CoV-2 infection, site, illicit drug use, ART, hypertension, diabetes, chronic kidney disease and history of HCV.
aOR adjusted for age only.
Abbreviations: PWH, persons with HIV; OR, odds ratio; CI, confidence interval; aOR, adjusted odds ratio; AVAMC, Atlanta Veterans Affairs Medical Center; ART, antiretroviral therapy; TDF, tenofovir disoproxil fumarate; INSTI, integrase strand transfer inhibitor; HBV, hepatitis B virus; HCV, hepatitis C virus
Sensitivity Analyses
In age-adjusted analyses restricted to CD4+ T-cell count less than 200 cells/mm3 or HIV-1 RNA greater than 200 copies/ml, HIV-related factors including CD4+ T-cell count, HIV-1 RNA, or ART use were not significantly associated with COVID-19 hospitalization.
After reclassifying patients incidentally found to have a positive SARS-CoV-2 PCR upon hospitalization for another condition in the hospitalization group, the association between age-adjusted comorbidity burden and COVID-19 hospitalization was similar to the primary analysis. (Supplementary Table 2). After eliminating patients with heart disease, chronic lung disease, active malignancy, or organ transplant, the association between age-adjusted comorbidity burden and COVID-19 hospitalization by age group was similar to the primary analysis. (Supplementary Table 3).
Discussion
In this cohort of PWH with well-controlled HIV and a high comorbidity burden, greater odds of COVID-19 hospitalization were associated with age, heart disease, history of HCV, and comorbidity burden. Date of SARS-CoV-2 diagnosis later in the study time period was associated with a lower odds of hospitalization, likely due to the limited testing availability early in the pandemic that resulted in prioritization of sicker patients for testing. Among older (aged ≥50) PWH, odds of COVID-19 hospitalization were associated with overall comorbidity burden, heart disease and history of HCV. Among younger (aged <50) PWH, COVID-19 hospitalization was not associated with comorbidity burden or with individual comorbidities but was associated with no ART use in adjusted analyses.
Our findings that age and comorbidity burden are associated with COVID-19 hospitalization in the overall cohort and among PWH aged ≥50 years is consistent with the existing literature. Comorbidity burden is a well-established risk factor for COVID-19 hospitalization in the general population[23] and among PWH.[10, 24, 25]. Two single-center studies in the United States (U.S.) of PWH with well-controlled HIV conducted over a similar time span as our study also found that age and cumulative comorbidity burden were associated with COVID-19 hospitalization.[9, 19] Larger observational studies of PWH with well-controlled HIV in the U.S. and Europe similarly found that age and comorbidity burden were associated with COVID-19 disease severity, and also found that low CD4+ T-cell count and HIV-1 viremia were associated with poorer COVID-19 outcomes.[7, 11] A non-random sampling of PWH with COVID-19 at several U.S. medical centers also identified age, comorbidities, and low CD4+ T-cell count as risk factors for severe COVID-19 disease and hospitalization.[18]
The role of immune exhaustion and immune suppression in severe COVID-19 outcomes is becoming more firmly established. Lee et al. found that a low CD4/CD8 ratio was highly predictive of poor outcomes in COVID-19 and other infectious diseases in the general population[13]. Data from the Center for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort demonstrate that low CD4/CD8 ratio and low nadir CD4+ T-cell count are associated with COVID-19 incidence,[26] and older age, no ART, and low CD4+ T-cell count are associated with intubation and mortality in PWH.[12] Other studies have shown that low CD4+ T-cell count is associated with higher COVID-19-associated respiratory failure[27] and mortality in PWH,[18, 28] suggesting that immune status is an important predictor of poor COVID-19 outcomes among PWH. We found that no ART use was associated with higher odds of COVID-19 hospitalization among younger, but not older, PWH. ART use was equally high in both age groups (96% vs. 95%); however, HIV-1 viral suppression and CD4+ T-cell counts >200 cells/mm3 were higher in the older group. It is possible that not being on ART in PWH in the younger stratum is a surrogate marker for immune suppression as a risk factor for COVID-19 hospitalization. The lack of association of low CD4+ T-cell count or high HIV-1 viral load with COVID-19 hospitalization in our study is likely due to our cohort’s generally well-controlled HIV and small numbers of those with HIV-1 viremia or low CD4+ T-cell counts. This is further reflected in our sensitivity analysis that showed no association with HIV parameters and COVID-19 hospitalization when restricting to CD4+ <200 cells/mm3 or detectable HIV-1 viral load.
Among PWH aged <50 years, we found that the association between COVID-19 hospitalization and comorbidity burden does not remain significant after adjusting for age. It is possible that since the overall burden of comorbidities was higher in older PWH, we were better able to detect differences. However, comorbidities were still highly prevalent in the younger age group, and even in pediatric cohorts, comorbidity burden is associated with more severe COVID-19 outcomes,[29, 30] so this rationale seems less likely. The observation that comorbidity burden and individual comorbidities were not associated with COVID-19 hospitalization among PWH <50, suggests that younger age is protective despite prevalent risk factors, or conversely, that longer duration of a particular comorbidity may increase its severity. This finding is important particularly given the relatively young age at which PWH develop age-related comorbidities.[15, 16]
We did not find any significant association between tenofovir disoproxil fumarate (TDF) or ART drug class with COVID-19 hospitalization despite reports of lower odds of SARS-CoV-2 seropositivity[31] and less severe COVID-19 outcomes with TDF compared with other ART.[6, 24, 32] This discrepancy may be due to differences in the cohorts studied including stage of the COVID-19 pandemic, comorbidity burden, or ART prescribing patterns. Initial studies included only the first pandemic wave in early 2020,[6, 32] or included participants with fewer comorbidities.[24] A recent randomized clinical trial of patients hospitalized with SARS-CoV-2 found no beneficial effect of TDF/emtricitabine on overall mortality,[33] suggesting the benefit of TDF seen in observational studies may be due to other unmeasured confounders rather than a direct effect of TDF on SARS-Cov-2.
We also found a trend toward greater odds of COVID-19 hospitalization with illicit drug use among younger, but not older, PWH, possibly due to a small sample size in the older group. Prior studies have shown an association between substance use disorders and COVID-19 hospitalization[34, 35] and mortality.[36] However, to our knowledge, this association has not been described in PWH. Neither Nomah et al.[11] nor Tesoriero et al.[3] found any association between COVID-19 disease severity and HIV transmission group, including persons who inject drugs, although it is not clear in either study if these patients were still actively injecting drugs.
Our study has several strengths. The CFAR data registry automatically enrolls anyone with a diagnosis of HIV who enters the health system, so our analysis was not subject to recruitment or selection bias. Our population was diverse and representative of the local HIV epidemic.[37] We were able to perform detailed medical record abstraction and adjudicate COVID-19 diagnosis, outcomes, and comorbidity diagnoses to ensure robust data for each patient and reduce the risk of misclassification bias. Limitations include retrospective study design, which did not allow for control of all possible confounders. Our study was cross-sectional, and included demographic, clinical, and laboratory data at the time of COVID-19 diagnosis, but we were unable to account for longitudinal variables that may be relevant including duration of comorbidities, duration of HIV infection, CD4+ T-cell nadir, or ART history, particularly since CD4+ T-cell nadir and other markers of immune dysfunction have been associated with poor COVID-19 outcomes.[12, 13] Our cohort had an overrepresentation of PWH who were virally suppressed on ART compared with the local HIV epidemic,[37] likely a result of persons already engaged in medical care seeking COVID-19 testing and treatment. Therefore, our findings are not generalizable to PWH with detectable HIV-1 viremia or CD4+ T-cell count <200 cells/mm3, a population likely to be at high risk for severe COVID-19.[12] In addition, we were unable to account for unmeasured confounders or data that were irregularly available in the medical record including date of COVID-19 symptom onset. However, our primary outcome was hospitalization within 30 days of the first positive SARS-CoV-2 PCR, which should not be affected by time from symptom onset. Although we were able to capture robust data on current ART use, we were unable to capture all concomitant medications, including long-term corticosteroids, which may have impacted COVID-19 disease outcomes. Patients who receive primary care in our clinics but who sought SARS-CoV-2 testing outside of our health systems were excluded from our analysis, potentially biasing our sample toward sicker patients. However, most patients in these health systems view these systems as their medical home and seek urgent and emergent care within these facilities. Finally, our data analysis was concluded prior to mass vaccination campaigns, the availability of oral SARS-CoV-2 antivirals, more widespread use of monoclonal antibodies and the circulation of Delta and Omicron SARS-CoV-2 variants in the U.S. that may be associated with different risk factors for breakthrough infection and hospitalization. However, data suggest that risk factors for COVID-19 hospitalization due to the Omicron variant are similar to prior variants,[38] but studies specific to PWH are urgently needed.
Conclusion
Our results demonstrate that age and comorbidity burden remain significant risk factors for COVID-19 hospitalization, particularly among older PWH. However, other lifestyle and HIV-related risk factors should be considered among younger PWH for whom comorbidities are less strongly associated with hospitalization. Additional studies are needed to confirm these findings, which, if confirmed, may have important implications for determining eligibility for COVID-19 therapies or prevention strategies.
Supplementary Material
Acknowledgements
C. A. M. and C. D. L. conceived the study design. C. A. M., N. T. O., B. S., and M. T. N. were involved in data collection. C. A. M. led the data analysis and interpretation with significant contribution from N. T. O., L. F. C., M. T. N., A. N. S., C. F. K., V. C. M, and C. D. L. The manuscript was drafted by C. A. M. and revised for intellectual content by N. T. O., B. S., L. F. C., M. T. N., N. S. S., A. M., J. A. C., V. D. C., W. S. A., A. N. S., I. O., C. F. K., V. C. M., and C. D. L. All authors approve the final version of the work and agree to be accountable for all aspects of the work.
Financial support:
This work was supported by the Emory Center for AIDS Research (award number P30-AI-050409). C.A.M. is also supported by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) (award number K23HL152903), L. F. C. by the National Center for Advancing Translational Sciences (NCATS) of the NIH through the Georgia CTSA (award numbers UL1TR002378 and TL1TR002382) and the Program for Retaining, Supporting, and EleVating Early-career Researchers at Emory (PeRSEVERE) from Emory School of Medicine, a gift from the Doris Duke Charitable Foundation, and C.D.L. by the National Institute of Allergy and Infectious Diseases (NIAID) of the NIH (award number K23AI124913). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Footnotes
Conflicts of Interest: V. C. M. has received investigator-initiated research grants (to the institution) and consultation fees (both unrelated to the current work) from Eli Lilly, Bayer, Gilead Sciences and ViiV. None of the other authors declare any conflicts of interest.
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