Incidence of Bloodstream Infections in Patients with COVID-19: A Retrospective Cohort Study of Risk Factors and Outcomes

Abstract

Introduction: Prior evidence found that bloodstream infections (BSIs) are common in viral respiratory infections and can lead to heightened morbidity and mortality. We described the incidence, risk factors, and outcomes of BSIs in patients with COVID-19. Methods: This was a single-center retrospective cohort study of adults consecutively admitted from March to June 2020 for COVID-19 with BSIs. Data were collected by electronic medical record review. BSIs were defined as positive blood cultures (BCs) with a known pathogen in one or more BCs or the same commensal organism in two or more BCs. Results: We evaluated 290 patients with BCs done; 39 (13.4%) had a positive result. In univariable analysis, male sex, black/African American race, admission from a facility, hemiplegia, altered mental status, and a higher Charlson Comorbidity Index were positively associated with positive BCs, whereas obesity and systolic blood pressure (SBP) were negatively associated. Patients with positive BCs were more likely to have severe COVID-19, be admitted to the intensive care unit (ICU), require mechanical ventilation, have septic shock, and higher mortality. In multivariable logistic regression, factors that were independent predictors of positive BCs were male sex (OR = 2.8, p = 0.030), hypoalbuminemia (OR = 3.3, p = 0.013), ICU admission (OR = 5.3, p < 0.001), SBP < 100 mmHg (OR = 3.7, p = 0.021) and having a procedure (OR = 10.5, p = 0.019). Patients with an abnormal chest X-ray on admission were less likely to have positive BCs (OR = 0.3, p = 0.007). Conclusions: We found that male sex, abnormal chest X-ray, low SBP, and hypoalbuminemia upon hospital admission, admission to ICU, and having a procedure during hospitalization were independent predictors of BSIs in patients with COVID-19.

Introduction

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) is responsible for the current coronavirus disease-19 (COVID-19) pandemic. By May 13, 2022, it had affected 1more than 500 million people worldwide and is responsible for more than 6 million deaths. [1] The disease can have a wide range of clinical presentations, potentially affecting the lungs, heart, kidneys, neurological, and gastrointestinal systems. [2] Severe presentations occur in up to 40% of hospitalized cases, commonly due to ventilatory-dependent respiratory failure and requiring intensive care unit (ICU) admission [3].

Bacterial coinfections are common in respiratory viral infections. A previous study in Spanish adults admitted to the ICU during the 2009 H1N1 influenza pandemic found that bacterial coinfection led to increased length of stay and resource utilization. [4] Similarly, bloodstream infections (BSIs) can increase morbidity and mortality when concomitant with viral infections. In hospitalized adults with COVID-19 from the US, [5,6] UK, [7] Italy, [8] and Sweden, [9] the frequency of BSIs ranged from 2.5% to 7.9%. In subjects with severe and critical illness, estimates of BSIs from the US, [10] China, and Italy [11] ranged from 0.9% to 49%. Moreover, BSIs are considered a significant disease burden in the US and Europe. [12] The current evidence highlights a wide range of frequencies of BSIs and the importance of identifying risk factors that can be targeted to decreased morbidity and mortality. Furthermore, minority patients such as black/African Americans are disproportionally affected by a higher incidence and greater disease severity of COVID-19 [2,13].

We evaluated the incidence of BSIs in patients with COVID-19 and described the possible risk factors associated with these infections in predominantly black/African American patients. We sought to identify risk factors that can help predict which patients will develop BSIs, to decrease morbidity and mortality.

Methods Study subjects

We conducted a retrospective, single-center historical cohort study of adults admitted for COVID-19 from March 8 to June 14 of 2020 who had BSIs. BSIs were defined as a positive blood culture (BC) with a known pathogen in one or more BCs or the same commensal organism in two or more BCs. Inclusion criteria were patients (adults 18 years and older) consecutively admitted for COVID-19 diagnosed with a positive reverse-transcriptase-polymerase- chain-reaction (RT-PCR) assay of a nasopharyngeal swab and had at least one BC during hospitalization. Exclusion criteria were adults who did not have BCs drawn during hospitalization or if the positive BC was due to an organism considered a skin contaminant (e.g., diphtheroids, Bacillus species, or coagulase- negative staphylococci) in only 1 of 2 BCs without clinical evidence of bacteremia. Clinical significance and source of BSIs were collected from infectious diseases (ID) consultation or progress notes. The study protocol was approved, and individual patient’s informed consent was waived by the Institutional Review Board (IRB) of Ascension St. John Hospital, IRB number 1582919-17.

Data collection

Data was collected from the electronic medical record (EMR) via retrospective chart review. Demographic data collected comprised age, sex, race, nine-digit zip code, type of insurance, and admission source. Anthropometric data collected was weight, height, and body mass index (BMI). Obesity and morbid obesity were defined using the Centers for Disease Control and Prevention (CDC) guidelines. [14] We included relevant medical comorbidities and calculated the Charlson Comorbidity Index, a weighted score, previously validated and established as a predictor of mortality. [15] We used the World Health Organization (WHO) classification to classify COVID-19 severity. [16] We collected data on vital signs and pulse oximetry on admission along with findings of chest X-ray and chest computed tomography (CT) based on the official radiology report. Laboratory data at the time of hospital admission included total white blood cell, lymphocyte, and platelet counts, C-reactive protein (CRP), procalcitonin (PCT) serum creatinine, alanine aminotransferase (ALT), and aspartate aminotransferase (AST). We classified elevated or low laboratory values based on the hospital’s cut-off points and categorized them as presented in

Table 1. Baseline attributes of the study population by blood culture results.

ALT—alanine aminotransferase; AST—aspartate aminotransferase; BMI—body mass index; df—degrees of freedom; IQR—interquartile range; qSOFA—quick Sequential Organ Failure Assessment. ^a P values were obtained from Student’s t test for continuous variables assuming equal variances, except for respiratory rate, where we could not assume equal variances. For the Charlson comorbidity index, Mann Whitney U test was used. For categorical variables, p vales were obtained from Chi-square tests. We used Fisher’s exact test for the following variables: previous myocardial infarction, cerebrovascular disease, liver disease, malignancy, fatigue, nausea, vomiting, elevated D-dimer, and procedures. ^bChronic pulmonary disease includes asthma, chronic obstructive pulmonary disease, or both.

. Elevated creatinine on admission was defined as a serum creatinine increase ≥1.5 times from baseline within seven days prior or an increase ≥0.3mg/dL within 48 hours of admission. [17] We computed the quick Sequential Organ Failure Assessment (qSOFA) on admission to predict in-hospital sepsis-related mortality. [18] Septic shock was defined as hypotension requiring vasopressors. We defined central line as placement of any catheter (tunneled or non-tunneled) in any central vein during hospitalization. For procedures, we included any major emergent surgeries and any emergent endoscopic or percutaneous procedures done during the hospital stay (Supplemental Table 1).

Data analysis

Descriptive statistics were computed to depict the study groups. We reported continuous variables as means and standard deviations or medians with interquartile range, and categorical variables as frequency distributions. Univariable analysis was conducted using Student’s t-test for continuous normal and Mann-Whitney U tests for variables non-normally distributed. We used Chi-squared tests for categorical variables. For multivariable analysis, we used logistic regression to distinguish independent predictors of BSIs during the hospital stay, and we used stepwise forward regression to build the final model. Data were analyzed using SPSS v. 27.0 (IMB Corp, USA), and a p value less than 0.05 indicated statistical significance.

Results

We had 565 patients admitted with a COVID-19 positive RT-PCR test between March 8 to June 14. Of those, 290 (51.3%) patients had BCs drawn during their hospital stay after exclusion of BCs determined to be a contaminant, which served as the study population. Thirty-nine (13.4%) had a positive BC (Figure 1).

The mean age (SD) of the analyzed population was 64.416.3 years, with 56.2% males and 77.2% black/African American. The prevalence of obesity and morbid obesity were 52.3% and 18.6%, respectively, and hypertension was the most common comorbidity (73.8%). Compared to those with negative BCs, those with positive BCs were more likely to be male, black/African American, be admitted from a facility, have hemiplegia, have a higher Charlson Comorbidity Index, and less likely to be obese (Table 1). Most of the patients (78%) had public insurance (Medicare or Medicaid), with no significant difference between groups.

The most frequent symptoms were shortness of breath, fever, cough. Those with positive BCs were significantly more likely to present with altered mental status and lower systolic blood pressure (SBP) but less likely to present with fatigue, shortness of breath, and cough, compared to those with negative BCs (Table 1). Notably, 94.0% and 80.7% of the patient population had elevated CRP and PCT levels, respectively, without significant difference between BC groups. Compared to those with negative BCs, those with positive BCs were more likely to present with leucopenia and hypoalbuminemia (Table 1).

In the positive BC group, patients had a lower incidence of abnormal chest X-ray on admission compared to those with negative results (66.7% vs. 81.3%, p=0.036). Contrastingly, chest CT on admission was more likely to be abnormal in the positive BC group compared to the negative group (16.2 vs. 6.6%, p=0.043).

Twenty percent (n=58) and 3.1% (n=9) of the analyzed population had at least one central line placed and one procedure done during hospitalization, respectively. Both were significantly higher in the positive BC group (Table 1). Additionally, more than half of the population was treated with steroids during hospitalization (55.5%), and those with positive

BCs were more likely to receive steroids compared to those with negative BCs, approaching significance (69.2%. vs. 53.4%, p=0.064) (Table 1).

The prevalence of severe disease was 21.7%, and around a third of patients (30%) were admitted to ICU at any time during their hospital stay (

Table 2. Treatment and clinical outcomes by blood culture status.

Characteristic	Total (N= 290)	Negative (N=251)	Positive (N=39)	P valuea	Test statistic/df
ICU admission, no. (%)	87 (30.0)	64 (25.5)	23 (59.0)	<0.001	18.013/1
Mechanical ventilation, no. (%)	86 (29.7)	63 (25.1)	23 (59.0)	<0.001	18.568/1
Septic shock, no. (%)	48 (16.6)	35 (13.9)	13 (33.3)	0.002	9.187/1
ARDS, no. (%)	32 (11.0)	25 (10.0)	7 (17.9)	0.139	2.194/1
AKI, no. (%)	125 (43.1)	104 (41.4)	21 (53.8)	0.145	2.120/1
Death	107 (36.9)	82 (32.7)	25 (64.1)	<0.001	15.181/1

AKI—acute kidney injury; ARDS—acute respiratory distress syndrome; df—degrees of freedom; ICU—intensive care unit. ^aP values were obtained from Chi-square tests.

). Compared to those with negative BCs, those with positive BCs were more likely to have severe COVID-19, be admitted to ICU, require mechanical ventilation, have septic shock, and die (64.1% vs. 32.7%, p<0.001).

In multivariable analysis, the variables initially introduced in the stepwise forward logistic regression included sex, Charlson Comorbidity Index, obesity, altered mental status, abnormal chest X-ray on admission, leucopenia, thrombocytopenia, hypoalbuminemia, CRP level, steroid treatment, admission from a facility, central line placement, procedures, severity of disease, admission to ICU, and SBP100 mmHg. The final model included sex, abnormal chest X-ray on admission, hypoalbuminemia, admission to ICU, SBP100 mmHg, and procedures. Notably, compared to those with negative BC, those with positive BCs during hospital stay were ten times more likely to have undergone a procedure, five times more likely to be admitted to ICU, twice as likely to be male, and three times more likely to have hypoalbuminemia and low SBP, and three times less likely to have an abnormal chest X-ray on admission (

Table 3. Multivariable analysis of independent predictors for positive blood cultures.

Characteristic	OR (95% CI)	P valuea	Test statistic/df
Male sex	2.75 (1.10, 6.87)	0.030	4.687/1
Hypoalbuminemia	3.25 (1.28, 8.25)	0.013	6.149/1
ICU admission	5.30 (2.24, 12.51)	<0.001	14.443/1
SBP≤100 mmHg	3.73 (1.22, 11.43)	0.021	5.299/1
Procedures	10.48 (1.47, 74.59)	0.019	5.502/1

df—degrees of freedom; ICU—intensive care unit; SBP—systolic blood pressure. ^aP values from Wald test.

).

Discussion

This study found a 13.4% incidence of BSIs in an urban population from Southeast Michigan, which is slightly higher than previously reported rates in patients from New York, [5,6] Sweden, [9] London, [7] and Italy, [8] but lower than those from New Jersey. [10] The difference in estimates is likely related to variations in case definition, severity of disease, and inclusion of patients admitted to the ICU, as a higher incidence of BSIs has been previously described in patients admitted to the ICU with COVID-19.19 About a third of our population was admitted to the ICU, and patients with positive BCs were more likely to be admitted to the ICU, have more severe disease, and require vasopressor support. Notably, admission to ICU and systolic hypotension were independent predictors of BSIs. Our findings are comparable with a study conducted in adults with severe COVID-19 from several centers from New Jersey [10] that found that patients with positive BCs were more likely to be admitted to ICU, have septic shock, and present with altered mental status than those with negative BCs. Notably, in univariable analysis, patients with positive BCs were more likely to present with altered mental status when compared to those with negative BCs.

Male sex and an increased number of comorbidities were associated with increased BSIs, but only male sex remained an independent predictor. A previous meta-analysis by Wu et al. [20] described an almost two-fold increased odds of severe COVID-19 in males compared to females. One of the proposed mechanisms for males having increased disease severity comes from the hypothesis that androgens facilitate SARS-CoV-2 entry via the transmembrane protease serine 2 (TMPRSS2)-pathway. SARS-CoV-2 spike proteins need trimming by TMPSS2 to bind to angiotensin-converting enzyme 2 (ACE2) receptors for entry to host cells. Androgens activate its receptor (AR), and the AR acts as a promoter of TMPRSS2 transcription resulting in facilitated host cell entry of SARS-CoV-2. [21] We believe males have increased BSIs related to the increased severity of COVID-19.

Several laboratory abnormalities have been described in patients with COVID-19. [2] In our study, patients with positive BCs were more likely to present with leucopenia and hypoalbuminemia when compared to those with negative BCs. On multivariable analysis, only hypoalbuminemia was an independent predictor of BSIs. This is similar to a previous metanalysis by Aziz et al. [22] who found that hypoalbuminemia was associated with increased odds of severe COVID-19 vs. non- severe disease. Additionally, hypoalbuminemia has been associated with increased severity of illness in the context of viral, fungal, and bacterial infections, including COVID-19. [23] This evidence supports the role of hypoalbuminemia as a marker of more severe disease and can be considered a valuable predictor of BSIs in patients with COVID-19. Notably, PCT was not an independent predictor of BSIs in our population. We hypothesized this was related to the widespread elevation of PCT in our population, and therefore our data was not powered enough to discriminate an association between PCT and BSIs in COVID-19. Furthermore, a metanalysis by Lippi et. al. [24] described that PCT could be a better discriminatory marker of superimposed bacterial infection and disease progression in COVID-19 when PCT levels are followed over time.

We also described that abnormal chest X-ray on admission was less likely in the positive BC group when compared to the negative BC group, and this association remained significant in multivariable analysis. Contrastingly, chest CT on admission was more likely to be abnormal in the positive BC group compared to the negative group, but it was not a significant predictor in multivariable analysis. Similar to our results, a previous retrospective study of Chinese adults with COVID-19 reported abnormal findings in 59% of patients with a chest X-ray. [25] We hypothesize that the abnormal chest CT did not remain a significant predictor in the multivariable analysis due to the low number of patients who had a CT chest done on admission compared to those who had a chest X-ray done (6 vs. 29). Additionally, an observational study conducted among adults from the UK described a lower sensitivity of the chest X-ray when compared to CT chest for COVID-19 diagnosis using RT-PCR as gold standard, [26] and we hypothesize that changes in chest CT occur earlier compared to X-ray, which could explain the discrepancy in our results.

Finally, we found that having at least one central line placement or a surgical procedure done during admission was associated with a positive BC, but in multivariable analysis, only having a procedure was associated with higher odds of positive BCs, despite the small number of patients (n=9). Surgical procedures are associated with a higher risk of BSIs but, to the best of our knowledge, no other studies have described an increased risk of BSIs associated with procedures in patients with COVID-19.

Our study faced various limitations. First, because of the small sample size, we were not able to stratify our results based on BC collection timing, and therefore our results also reflect the occurrence of hospital-related BSIs. Thus, we cannot know if BSIs resulted from greater disease severity or if having a BSI led to a more severe presentation. Moreover, due to the observational nature of our data, causal inference cannot be made. Because our study population is predominantly black/African American, and race can influence the association between COVID-19 and its severity, our results may not be generalizable to a broader patient group. We did not find any association of steroid therapy with bloodstream infections, likely because of the low sample size. Finally, we did not have information on immunomodulatory therapies such as tocilizumab, which has been associated with higher risk of BSIs in critically ill patients with COVID-19, [27] nor detailed information on antibiotics usage. Per institution guidelines, antibiotic usage is empirically started exclusively after BCs are drawn, so we do not expect interference of antibiotic usage with BC results.

Our study has several strengths. We were able to identify predictors of bloodstream infections in patients hospitalized for COVID-19. Our results are consistent with previous studies, as stated above. We described potential predictors that can be used for early detection and to identify patients at risk, specifically, patients with COVID-19 admitted to ICU. Our population was predominantly black/African American, previously reported as disproportionally affected by a higher number of COVID-19 cases, and presenting with more severe disease. [13] We were also able to adjust for important risk factors such as placement of central lines and emergent procedures and described the role of procedures as a risk factor, despite the small sample size.

Conclusions

This historical cohort study found that independent predictors of bloodstream infections included male sex, hypoalbuminemia, admission to ICU, SBP100 mmHg, abnormal chest X-ray, and procedures. We recommend further investigations to confirm these potential predictors that can lead to early identification and treatment of BSIs and reduce morbidity and mortality in adults with COVID-19, specifically identifying patients requiring emergency procedures as a high-risk group.