Prognosis of critically ill immunocompromised patients with COVID-19 admitted for acute respiratory failure: a retrospective propensity score analysis

Introduction

A cornerstone of pandemic control is the widespread administration of vaccines. Starting in early 2021, extensive vaccination campaigns have significantly reduced both morbidity and mortality related to Coronavirus Disease 2019 (COVID-19) (1-3). However, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can still lead to acute respiratory failure (ARF), which requires admission to the intensive care unit (ICU), and is associated with high morbidity, mortality, a long duration of mechanical ventilation (MV), and a high incidence of acquired infections (2,4,5).

Since the introduction of vaccination, there appears to be a shift in the population of patients admitted to the ICU with COVID-19 infection, with an increasing proportion of immunocompromised patients (6,7). Unsurprisingly, the vaccine response to SARS-CoV-2 in immunocompromised individuals has been lower than that in the general population, with a lower seroconversion rate (1,8). Although the seroconversion rate in people with solid tumors is only slightly lower than that in people without cancer (8), people with hematological malignancies are less responsive, with early studies reporting seroconversion rates ranging from only 18% to 25% after the first dose of the mRNA vaccine (9,10). Therefore, although fully vaccinated, immunocompromised patients are still at risk for severe COVID-19 and ICU admission (6). These patients have higher rates of ICU admission and mortality compared to non-immunocompromised individuals, and may therefore represent a significant proportion of those hospitalized in the ICU for severe COVID-19 (11). However, due to the heterogeneity of disease pathogenesis or treatments leading to immunosuppression, there is a lack of data regarding the outcomes of patients admitted to the ICU for severe SARS-CoV-2 infection (12). In addition, there are very few data on ICU acquired infections in immunocompromised patients admitted to the ICU for severe SARS-CoV-2 infection. This is surprising because nosocomial infections during ICU stay are frequent in immunocompromised patients, and the incidence of hospital- and ICU-acquired infections in critically ill Covid-19 patients is high, supporting the hypothesis that that COVID-19 suppresses host functional adaptive and innate immunity (13-18).

In our study, we explored the impact of immunocompromised status on ICU outcomes in COVID-19 patients admitted for ARF. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2060/rc).

Methods

In this single-center retrospective observational study conducted in the medical ICU of the CHU Rennes, we collected data on adult patients admitted to the ICU for ARF in the setting of severe SARS-CoV-2 pneumonia. The study was conducted from March 1, 2021 (the arrival of the first vaccinated patient) to December 31, 2022.

The inclusion criteria were age greater than or equal to 18 years, SARS-CoV-2 infection confirmed by reverse transcriptase polymerase-chain reaction (RT-PCR) testing of a respiratory specimen collected by nasopharyngeal swab, tracheal aspiration or bronchoalveolar lavage (BAL), and the presence of ARF. ARF was defined as a respiratory rate of at least 25 breaths per minute and a partial pressure of arterial oxygen relative to the inspired fraction of oxygen of less than 300 mmHg while the patient was breathing oxygen at a flow rate of 10 liters per minute or more for at least 15 minutes (19).

The criteria for non-inclusion initial management in an ICU other than the CHU Rennes, patients with unknown vaccination history or incomplete data that prevented retrospective analysis were excluded from the study.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by The Ethics Committee of the CHU Rennes (No. 22.181) and individual consent for this retrospective analysis was waived.

Patients admitted to the ICU were treated according to COVID-19 recommendations in force at the time of admission (20). The entire population received corticosteroid therapy with dexamethasone 6 mg/d for 10 days. Furthermore, since all patients meet at the time of ICU admission the criteria for severer community acquired pneumonia, they received an empirical combination therapy with a β-lactam plus a macrolide at admission as recommended (21). Macrolide was discontinued when the Legionella pneumoniae urinary antigen test was confirmed to be negative and antibiotics were discontinued if there were no signs of pulmonary co-infection on chest computed tomography (CT) and/or if microbiological samples were negative. Patients mechanically ventilated for more than 48 hours received multisite nasal and digestive decontamination (22). Acute respiratory distress syndrome (ARDS) was defined in accordance with the Berlin definition (23). Management of ARDS followed the recommendations of the French Society of Intensive Care (24).

Data collection

The following data were obtained: age, sex, and the presence and type of immunosuppression at the time of COVID-19 diagnosis. We also collected data on vaccination status (fully or partially vaccinated), vaccine type, and anti-spike serological titer. Patients were considered fully vaccinated if they were admitted ≥2 weeks following receipt of the second dose in a 2-dose series (mRNA vaccines).

Immunosuppression was defined by one of the following criteria: hematologic malignancy (active or in remission for less than 5 years), hematopoietic stem cell transplantation (HSCT), active solid cancer, solid organ transplantation, HIV (human immunodeficiency virus), splenectomy, primary immune deficiency, use of systemic steroids ≥0.5 mg/kg per day prednisone equivalent for at least 3 weeks, or use of immunosuppressive or immunomodulatory drugs (25).

If a hematologic malignancy was present, we collected data on its management, the number and strategy of treatments, and its status at the time of infection. The status of the hematological malignancy at the beginning of COVID-19 was defined as active (early and refractory/resistant), stable disease or controlled (complete and partial response) based on reports from the treating hematology department.

During the ICU stay, the following data were collected: initial severity assessed by Sequential Organ Failure Assessment (SOFA) (26) and Simplified Acute Physiology Score (SAPS) II (27) scores at ICU admission, duration of symptoms before hospitalization, length of stay during infection, treatments received for infection, presence of an initial coinfection, overall mortality at 28 days, ICU and hospital mortality, use and duration of MV.

Respiratory coinfections were defined according to clinical practice guidelines on the management of adult patients with community-acquired pneumonia (28), and classified as bacterial, fungal and viral infections. Bacterial infections were diagnosed by culture- or PCR-positive endotracheal aspirates or culture- or PCR-positive BAL fluid. Viral infections were diagnosed by positive viral PCR on endotracheal aspiration or BAL. Fungal infections were diagnosed by a positive culture on endotracheal aspiration or BAL or a positive galactomannan on endotracheal aspiration, confirmed on BAL, and associated with compatible CT signs (29).

The occurrence of ICU acquired infection was also recorded during the hospital stay. Acquired infections were defined following Centers for Disease Control and Prevention (CDC) criteria as previously described and according to criteria proposed in the recommendations (30). Noteworthy, systematic screening of blood and endotracheal aspirates was performed weekly by Herpes simplex virus (HSV) and cytomegalovirus (CMV) viral PCR. HSV and CMV replication were measured by quantitative real-time PCR on tracheal aspirates twice a week for each patient. Herpesviridae reactivation was defined as two consecutive positive HSV or CMV PCRs on tracheal aspirates. Endotracheal aspirates were sent for mycology and bacteriology. Galactomannan antigen was tested in blood and endotracheal aspiration and confirmed in BAL if positive. Acquired infections were diagnosed by a positive blood culture, or in the case of acquired respiratory infections, they were diagnosed according to the same microbiological criteria as respiratory coinfections associated with clinical and radiological arguments (31).

Statistical analysis

Normally distributed continuous variables are presented as the means ± standard deviations (SDs), whereas nonnormally distributed data are presented as medians and interquartile ranges (IQRs). Categorical variables are presented as numbers (percentages). Continuous variables were compared by using the Mann-Whitney U test. Proportions for categorical variables were compared using the χ² test or Fisher’s exact test when more appropriate.

Because immunocompromised and non-immunocompromised patients are inherently different, we performed, as previously described, a propensity score analysis to better balance baseline characteristics and isolate the effect of immunosuppression (32). The propensity score was calculated by a multivariable logistic regression model near neighbor with 0.25 caliper matching. The following variables were used for the calculation: age, BMI, MV, SOFA score at admission, renal chronic failure, use of vasopressors. These variables were chosen based on the results of the univariable analysis with P<0.1 for enter. The immunocompromised and non-immunocompromised patients were then matched 1:1 on these propensity scores.

Second, we used a Cox proportional hazard model to determine whether an immunocompromised status during the ICU stay was independently associated with mortality on day 90. For this analysis, variables achieving a P value of 0.1 in the univariable regression analysis were used for adjustments. Among related factors (SAPS II at admission and SOFA at intubation) only the most clinically relevant (SAPS II for severity) were included in the multivariable analysis model to minimize the effect of collinearity. Notably, the proportional hazard assumption of the Cox model was assessed graphically using a log-log plot, confirming the validity of the assumption. The results are expressed as hazard ratios (HRs) with 95% confidence intervals (CIs).

Survival curves with 95% CIs were computed until day 90 using the Kaplan-Meier method for unmatched and matched populations and compared with the log-rank test. Patients who were alive on day 90 were censored. We defined ventilator-free days as the number of days in the first 28 days after admission during which the patient was alive without ventilation for any reason. Patients who died within the first 28-day period were recorded as having zero days free of ventilation. Statistical analyses were performed using R 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria), and P values less than 0.05 were considered significant.

To ensure that the number of included patients was sufficient to address our question effectively, we calculated the post hoc sample size based on the observed mortality of immunocompromised patients.

Results

During the study period, we identified 294 patients with a diagnosis of COVID-19 admitted to the ICU for ARF with complete data available for analysis.

Comparison between non-immunocompromised and immunocompromised patients

Unmatched population

Of the 294 patients, 220 were non-immunocompromised, and 74 were immunocompromised. The characteristics of the population are described in Table 1. A detailed list of immunosuppression causes is provided in Table S1. The proportion of fully vaccinated patients was greater in the immunocompromised group (67.6% vs. 19.5%, P<0.001). The median time between the first symptoms and hospital admission was 5 days and was similar for immunocompromised and non-immunocompromised patients (P=0.2). However, the median time between hospital admission and ICU admission was longer in immunocompromised patients than in non-immunocompromised patients [3 (IQR, 1–7) vs. 1 (IQR, 0–3) days, P<0.001]. Noteworthy, the proportion of vaccinated patients over the months increased significantly over the study period as the number of immunocompromised patients increased (Figure S1).

Table 2 reports the characteristics of the ICU stay and the differences between the non-immunocompromised and immunocompromised groups. ARFs more frequently fulfilled the criteria for ARDS in immunocompromised patients than in non-immunocompromised patients (64.9% vs. 48.2%, P=0.02). Notably, the mortality rate for immunocompromised patients was 37.5% for patients with hematological cancer, 66.7% for patients treated by autologous HSCT, 30.8% for patients treated with solid organ transplantation, 11.1% for patients with solid organ malignancies, and 28.6% for patients with autoimmune diseases.

Immunocompromised patients had a longer duration of MV, longer durations of ICU and hospital stays, and greater mortality (Table 2).

Matched population

After matching, despite no differences in mortality rate [13 (17.6%) vs. 23 (31.1%), P=0.09) and a similar MV length [13 (IQR, 6–27) vs. 16 (IQR, 10–28) days, P=0.39], the number of acquired infections remained significantly greater in the immunocompromised group [39 (52.7%) vs. 22 (29.7%), P=0.008], as did the ICU length of stay [13 (IQR, 7–28.8) vs. 8 (IQR, 3–23) days, P=0.046] (Table 3).

Impact of immunocompromised status on mortality

Immunocompromised status did not remain associated with mortality after adjustment for other factors [HR =1.39 (95% CI: 0.64–2.99), P=0.4], while the use of vasopressor [HR =9.40 (95% CI: 2.11–41.8), P=0.003], renal replacement therapy [HR =5.76 (95% CI: 2.28–14.6), P<0.001], and ICU acquired infection [HR =2.27 (95% CI: 1.02–5.06), P=0.044] remained independently associated with increased mortality. Results of the univariable and multivariable Cox regression proportional hazard analysis are reported in Table 4. Notably, among the factors associated with mortality, we found that vaccination was linked to mortality in the univariable analysis, although this association was not significant in the multivariable analysis.

Moreover, the survival probability on day 90 of the full population was significantly lower in immunocompromised patients (P<0.001 by log-rank test, Figure 1A) but did not remain significant after propensity score matching (Figure 1B).

Figure 1 Survival probability on day 90. (A) Day-90 probability of survival according to the immunocompromised status in the full population. (B) Day-90 probability of survival according to the immunocompromised status after propensity score matching. ICU, intensive care unit.

A posteriori sample size

We evaluated whether 74 immunocompromised patients were sufficient to identify significant differences in mortality. Based on the observed mortality rates in the two groups (8.6% vs. 31.1%, P<0.001), with 80% power (β=0.10) and a 5% type I error rate (two-sided tests), the required sample size was calculated to be 92 patients, with 46 patients per group. Therefore, we conclude that 74 immunocompromised patients were sufficient to address our research question.

Discussion

Our retrospective study revealed that after adjustment for prognostic variables in critically ill patients, mortality was not higher in immunocompromised patients than in non-immunocompromised patients despite a significantly longer duration of ICU stay and a greater rate of ICU acquired infections.

We found that an immunocompromised status was linked to an increased risk of ICU acquiring secondary infections. Patients with severe COVID-19 have emerged as a population at a greater risk of acquiring bacterial and fungal infections, along with increased viral replication, than other critically ill patients (31,33). Although it has been shown that immunocompromised patients have a particularly poor outcome in the ICU, due to a higher risk of infection (especially to opportunistic pathogens) (34), there were only limited data on the incidence of acquired infection in the ICU for immunocompromised patients with COVID-19 (7).

Noteworthy, we found a relatively low incidence of acquired bacterial infections (9.1% and 25.7% for non-immunocompromised and immunocompromised, respectively), compared with the incidence of fungal infections and viral reactivations. These results may be explained by the systematic use of multisite nasal and digestive decontamination in patients with a planned duration of MV of more than 48 hours (22). Furthermore, since the usual criteria, based on chest X-ray along with clinical and biological markers, have not been validated for the immunocompromised population, the diagnosis of acquired infections in critically ill patients in the ICU remains challenging. Therefore, in our ICU, a systematic screening for acquired infection was performed weekly, and acquired infections were defined following CDC criteria (4). It has been shown that severe forms of SARS-CoV-2 infection induce profound and lasting immunosuppression. In this context, the administration of corticosteroids further predisposes patients to frequent reactivation of HSV and CMV. Consequently, we implemented a weekly screening of HSV and CMV using viral PCR. However, the necessity of this screening remains uncertain, as we have not evaluated its effectiveness. In our study, all patients received empirical antibiotic therapy (a combination of a β-lactam and a macrolide), despite the World Health Organization (WHO) and The Infectious Diseases Society of America (IDSA) guidelines not recommending empirical antibiotics for COVID-19 patients and their potential negative impact on outcomes. However, as the ICU-admitted patients met the criteria for severe community-acquired pneumonia, empirical anti-biotherapy was initiated and discontinued once the absence of bacterial co-infections was confirmed (21).

Along these lines, we found that immunocompromised patients had a longer duration of MV and a longer duration of ICU stay. The extended duration of MV may be linked to persistent replication of the virus in immunocompromised individuals responsible for immunological autoinflammatory phenomenon (35,36).

Importantly, despite increased severity at admission and higher ICU acquired infections, we did not find that immunocompromised status was significantly associated with increased mortality in covid-19 patients admitted to the ICU for ARF in the matched population. In previous studies, the mortality rate was threefold greater in the immunocompromised group (11,37). Additionally, other findings indicated that COVID-19 patients with active cancer had a significantly greater mortality rate in the ICU than patients without cancer. However, in our study, we used a Cox proportional hazard model to determine whether immunocompromised status during the ICU stay was independently associated with mortality and did not find an association. Furthermore, the outcome may differ according to the type of immunosuppression. Although this was not the aim of our study, we observed that the mortality rate seemed to be greater in patients with hematological diseases than in those with solid tumors. (37.5% vs. 11%, P<0.01). In a study of 3,801 patients, the authors found a mortality of 66% in a subgroup of hematologic malignancies, mostly for non-Hodgkin lymphoma and chronic lymphocytic leukemia (37). Furthermore, other studies found that hospital mortality for covid-19 patients who underwent solid organ transplantation ranged between 6% and 17% (38,39). While we acknowledge that further studies are needed to explore the impact of the cause of immunosuppression, we found that immunocompromised status was not associated with worst outcome in patients admitted in the ICU.

In our study, the proportion of immunocompromised patients increased significantly over the study period. The immune response in immunocompromised patients has been extensively studied, and several studies have shown that the seroconversion rate is significantly lower in immunocompromised patients than in a non-immunocompromised population (8,10). Notably, among immunocompromised patients, hematologic patients who received B-cell-depleting agents in the last 12 months were the most at risk of poor seroconversion (40). Along these lines, we found that vaccination was associated with mortality in the univariable analysis, whereas positive serology tended to be associated with survival. These apparently contradictory results may be interpreted as indicating immune unresponsiveness in immunocompromised patients, rather than as a side effect of vaccination. In addition, because of their altered immune systems and depending on the type of immunosuppression, these patients face a greater risk of developing serious respiratory infections, especially viral infections (41).

Our study has several limitations. First, despite the use of propensity score analysis, this study is observational and residual confounding factors and bias may exist. Second, this study was monocentric, resulting in a limited number of immunocompromised patients. The small number of immunocompromised patients did not allow us to perform analysis by type of immunosuppression. Because anti-spike serology was not performed exhaustively, we do not know whether a positive serology could influence outcomes. Furthermore, the retrospective nature of our study should be considered a limitation, as it may have resulted in an inadequate sample size for evaluating mortality.

However, despite these important limitations, mortality after matching did not differ between non-immunocompromised and immunocompromised patients admitted to the ICU for SARS-CoV-2 associated ARF. Therefore, immunocompromised status should not be the main factor limiting access to the ICU in patients with SARS-CoV-2-associated ARF.

Conclusions

In our study, the immunocompromised status of patients admitted to the ICU for SARS-CoV-2-related ARF was not associated with increased mortality, despite a significantly longer ICU stay and a greater rate of ICU acquired infections.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2060/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2060/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2060/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2060/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by The Ethics Committee of the CHU Rennes (No. 22.181) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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