Outcomes Among HIV-Positive Patients Hospitalized With COVID-19

Savannah Karmen-Tuohy, BS; Philip M. Carlucci, BS; Fainareti N. Zervou, MD; Ioannis M. Zacharioudakis, MD; Gabriel Rebick, MD; Elizabeth Klein, BS; Jenna Reich, BS; Simon Jones, PhD; Joseph Rahimian, MD


J Acquir Immune Defic Syndr. 2020;85(1):6-10. 

In This Article


Data were collected from electronic medical records (Epic Systems, Verona, WI) for all patients hospitalized with COVID-19 at any of 4 acute care NYU Langone Health hospitals in New York City between March 2, 2020, and April 23, 2020. Patients were included in the study if they had at least 1 positive COVID-19 polymerase chain reaction test, were admitted to the hospital, and had been discharged from the hospital, transitioned to hospice, or died at the time of analysis. Patients who did not test positive for COVID-19, who were never admitted to the hospital, and who had not yet completed their clinical course were excluded from the study. With an automated approach, we collected demographics, medical history, admission vitals and laboratory test results, and hospital outcomes. On generating our matched patients, manual chart review was performed to collect information, such as CD4 counts, HIV medications, peak laboratory test results, culture results, thrombotic events, and imaging results.

Statistical Analysis

We identified 21 HIV-positive patients and 2617 non-HIV patients who met the inclusion criteria. Greedy 1:2 nearest-neighbor matching was employed using the MatchIt package, Version 3.0.2, in RStudio, Version 1.2.5042, to generate 42 matched non-HIV patients for our comparison group.[6] Patients were matched by admission date, age, body mass index, gender, tobacco history, and a history of chronic kidney disease, hypertension, asthma, chronic obstructive pulmonary disease, and heart failure. Descriptive statistics are presented as mean and SD or median and interquartile range for continuous variables and frequencies for categorical variables. Normality of distribution for continuous variables was assessed by measures of skewness and kurtosis. A 2-tailed Student t test was used for parametric analysis, and a Mann-Whitney U test was used for nonparametric data analysis. A Pearson χ 2 test was used to compare categorical characteristics. Logistic regression was used to test associations among variables. All analyses were performed using STATA/SE 16.0 software (STATA Corp.).

Study Approval

The study was approved by the NYU Grossman School of Medicine Institutional Review Board. A waiver of informed consent and a waiver of the Health Information Portability Privacy Act were granted.