Factors Influencing Central Venous Catheter-Associated Bloodstream Infections in COVID-19 Patients

Abstract

During the pandemic of COVID-19, the rates of bloodstream infection associated with venous catheter in patients infected with the disease admitted to an intensive care unit rose significantly. In this study, we evaluated the occurrence of bloodstream infections in patients with SARS-CoV-2 and the variables that made the patients more susceptible to the catheter-associated bloodstream infection (CABSI). Blood culture results from patients interned between March 2020 and December 2021 (n= 109) were collected electronically from the hospital information system and then analyzed. The following variables presented statistical relevance after an adjusted model as follows: obesity (p = 0.003) and time of use of catheter before infection (p = 0.019). In conclusion, patients with shorter catheter use time and obesity had higher incidence of CABSI.

1. Introduction

The serious global health crisis caused by the coronavirus disease 2019 (COVID-19) pandemic caused the health workforce, and material and financial resources routinely used to prevent healthcare-associated infections (HAIs), to be redirected to manage the pandemic [1]. Added to this, patients who develop the severe form of COVID-19 are more prone to HAI due to the pathogenic mechanism of the virus and the use of immunosuppressive medications, along with other risk factors such as staying in intensive care units (ICU) [2,3]. Studies, including systematic reviews and meta-analyses, indicate an up to 24% higher incidence of secondary infections, whether bacterial or fungal, in patients hospitalized with COVID-19 [4,5,6]. Furthermore, higher rates of catheter-associated bloodstream infection (CABSI) are observed in these patients compared to those not infected with COVID-19 [7].

Bloodstream infections are among the most serious in critically ill COVID-19 patients [8], and the main related risk factors are hypertension, diabetes and obesity [9]. These factors are associated with greater clinical severity and the need for invasive procedures, making patients more susceptible to CABSI [10]. It is reported that up to 50% of patients with COVID-19 who died had secondary infections [11]. Knowing the frequency of CABSI, finding related microorganisms and factors associated with infection contribute to the management and prevention of HAIs. Especially for COVID-19 patients, the need to know this frequency is reinforced given that these infections increase hospital costs, length of stay and patient morbidity and mortality [12], reducing the availability of resources and beds, common problems experienced during the pandemic.

Thus, this study aimed to describe the occurrence of CABSI in patients with COVID-19 admitted to an intensive care unit and its related factors.

2. Materials and Methods

This is a retrospective cohort whose inclusion criteria were patients aged over 18 years and who had used a central venous catheter (CVC) for at least 48 h. This was because the objective of the study was to analyze the population of adults admitted to an ICU due to the worsening of COVID-19, and because CABSI is defined as an infection occurring at least 48 h after central line insertion [13]. The patients selected had been admitted from March 2020 to December 2021. The study was carried out at a Brazilian public university and tertiary hospital. This hospital has approximately 500 beds and offers complex treatments. There were no exclusion criteria. The research was approved by the local Human Research Ethics Committee, CAAE: 51805021.5.0000.5152, under opinion number 5.043.636/2021.

The following characteristics were evaluated: age, sex, comorbidities, clinical data such as symptoms upon admission to the hospital, duration of symptoms and vital signs on the first day of hospitalization, laboratory results upon admission and treatments performed in the ICU. All data, including blood culture results from blood samples obtained by peripheral venipuncture, were collected electronically from the hospital information system and the patients’ electronic medical records. In this case, the identified germs and the resistance profile of the antibiogram were collected, following the institution’s protocol. For classification of resistance, the following definition was considered: resistant (R), microorganisms that present resistance to at least one class of antimicrobial; multidrug-resistant microorganisms (MDR), resistant to three or more classes of antimicrobials after accounting for intrinsic resistance; extensively resistant (XDR), resistant to most standard antimicrobials; pandrug resistant (PDR), resistant to all antimicrobials [14].

2.1. Defining the Outcome of Catheter-Associated Bloodstream Infection

CABSI is defined as an infection occurring at least 48 h after central line insertion, with at least one positive peripheral blood culture sample. In our study, the date of infection was defined as the date of positive blood culture collection. Microorganisms classified by the Centers for Disease Control and Prevention (CDC) as commensal, present on the skin, such as coagulase-negative staphylococci (including S. epidermidis) and viridians group streptococci, which are identified by the culture of two or more blood samples collected on separate occasions, were not considered in this study due to the lack of a second sample that could differentiate from contamination. Infections were defined according to CDC standards [13].

2.2. Statistical Analysis

For quantitative data, the median, first quartile and third quartile were calculated, given the absence of normality assessed by the Kolmogorov–Smirnov Lilliefors test. For qualitative data, the relative frequency in percentage and 95% confidence interval were calculated for each of the variable levels. To compare groups with and without CABSI in association analyses, the likelihood ratio test was used for qualitative variables and the Mann–Whitney test for quantitative variables. To control confounding variations, logistic regression models were used. For the logistic regression models, we chose the variable obesity due to lower sample loss compared to weight. To predict the presence of CABSI, simple and multiple logistic regression analysis was used. The simple (unadjusted) and multiple (adjusted) regression models were only built for variables that had previously shown a significant difference in prior association analyses and without data absence to avoid convergence and parameter estimation problems, since we had a lot of missing data in some variables. These variables with missing data were maintained in text for better patient characterization. The adjusted model included the presence of obesity, COVID-19 vaccination prior to hospital admission, hydrocortisone use prior to CABSI, 3 or more antibiotic use prior to CABSI, use of antifungal prior to CABSI, lactate dehydrogenase in U/L and days of central venous catheter use until diagnosis. Furthermore, the odds ratio and its 95% confidence interval were calculated for all models, unadjusted or adjusted.

All analyses were conducted using SPSS software version 20.0. A significance level of 5% was adopted for all analyses.

3. Results

During the study period, 596 COVID-19 patients were evaluated, of which 413 used CVC for at least 48 h and were included in the study. A total of 62.5% were male and had a median age close to 60 years. Patients with CABSI had shorter catheter use times before infection (median 9 vs. 11 days) compared to those who did not have infection (

Table 1. Qualitative variables related to catheter-associated bloodstream infection (CABSI) in patients with COVID-19 in an adult intensive care unit.

Variables	N of Yes (% of Yes) [95% Confidence Interval]		p-Value
	CABSI Presence (n = 104)	CABSI Absence (n = 309)
Admitted from another service	69 (66.35) [57.26–5.43]	200 (64.72) [59.4–70.5]	0.764
Obesity presence	45 (43.27) [33.75–57.79]	99 (32.04) [26.84–37.24]	0.040
Systemic arterial hypertension presence	60 (57.69) [48.2–67.19]	155 (50.16) [44.59–55.74]	0.183
Diabetes mellitus presence	35 (33.65) [24.57–42.74]	89 (28.8) [23.75–33.85]	0.354
Cardiovascular disease presence	14 (13.46) [6.9–20.02]	34 (11) [7.51–14.49]	0.505
Chronic obstructive pulmonary disease presence	10 (9.62) [3.95–15.28]	32 (10.36) [6.96–13.75]	0.828
Chronic kidney disease presence	11 (10.58) [4.67–16.49]	24 (7.77) [4.78–10.75]	0.384
Etilism habit presence	7 (6.73) [1.92–11.55]	25 (8.09) [5.05–11.13]	0.649
Smoking habit presence	22 (21.15) [13.3–29]	65 (21.04) [16.49–25.58]	0.980
COVID-19 vaccine prior to hospital admission	26 (25) [16.68–33.32]	50 (16.18) [12.07–20.29]	0.050
Renal replacement therapy prior to CABSI	40 (38.46) [29.11–47.81]	142 (45.95) [40.4–51.51]	0.181
Hydrocortisone use prior to CABSI	50 (48.08) [38.47–57.68]	185 (59.87) [54.41–65.34]	0.036
Antibiotic use prior to CABSI	83 (79.81) [72.09–87.52]	253 (81.88) [77.58–86.17]	0.642
3 or more antibiotics use prior to CABSI	26 (25) [16.68–33.32]	122 (39.48) [34.03–44.93]	0.007
Use of cephalosporin prior to CABSI	19 (18.27) [10.84–25.7]	56 (18.12) [13.83–22.42]	0.973
Use of carbapenem prior to CABSI	41 (39.42) [30.03–48.82]	153 (49.51) [43.94–55.09]	0.073
Use of antifungal prior to CABSI	11 (10.58) [4.67–16.49]	65 (21.04) [16.49–25.58]	0.013

and

Table 2. Quantitative variables related to catheter-associated bloodstream infection (CABSI) in patients with COVID-19 in an adult intensive care unit.

Variable	Median (Quartile 1–Quartile 3) [n]		p-Value
	CABSI Presence	CABSI Absence
Age in years	60 (45.75–68) [104]	61 (49–71) [309]	0.396
Weight in Kg	80 (71–95) [94]	75.5 (68–87.2) [248]	0.007
Height in m	1.68 (1.64–1.73) [101]	1.67 (1.6–1.72) [256]	0.782
Body Mass Index in Kg/m2	28.03 (25.01–33.3) [93]	26.99 (24.69–31.24) [235]	0.008
Total number of comorbidities	1 (1–3) [104]	1 (0–2) [309]	0.070
Simplified Acute Physiology Score	57 (44.75–70) [104]	59 (46–69) [309]	0.417
Simplified Acute Physiology Score prognosis in %	32 (11.75–57.25) [104]	34 (13–56.5) [309]	0.362
Days of central venous catheter use until diagnosis	9 (6–14) [99]	11 (6–20) [294]	0.043
Creatine in mg/dL	1.06 (0.76–1.75) [104]	1.1 (0.78–1.9) [308]	0.945
Albumin in mg/dL	3.15 (2.73–3.44) [248]	3.22 (2.63–3.52) [93]	0.362
Glutamic-Oxaloacetic Transaminase in U/L	49.65 (39–71.85) [100]	50.75 (33–86.48) [276]	0.852
Pyruvic Glutamic Transaminase in U/L	38.9 (29.8–53.9) [99]	39 (23–66.4) [277]	0.819
Lactate Dehydrogenase in U/L	636 (519–850) [75]	563 (423–800) [241]	0.042
Polymerase Chain Reaction in mg/dL	13.61 (7.83–20.28) [101]	12.77 (6.92–20.86) [293]	0.654
D-Dimer in mg/dL	2149 (595.5–5845) [87]	1928 (775.14–5897) [257]	0.537
Interleukin-6 in pg/dL	74.55 (23.77–124.38) [72]	86.22 (34.64–186) [217]	0.114
Prothrombin Activity Time in %	100 (83.75–100) [98]	100 (77–100) [295]	0.262
International Standardized Prothrombin Ratio	1 (1–1.08) [98]	1 (1–1.1) [293]	0.334

). Furthermore, they showed higher weight and body mass index values, reflecting the higher prevalence of obesity (43.27 vs. 32.04%) and use of the COVID vaccine (25.0 vs. 16.18%), together with lower prevalence of hydrocortisone use before infection (48.8 vs. 59.87%), use of more than three antibiotics before infection (25.0 vs. 39.48%) and antifungals before infection (10.58 vs. 21.04%) (Table 1 and Table 2). The hematological parameters of patients upon admission to the ICU did not differ between the two groups.

In the simple models, all variables that showed a difference between the two groups were also efficient in predicting CABSI, except for lactic dehydrogenase (OR = 1.00) (

Table 3. Simple (or unadjusted) and multiple (or adjusted) logistic regression models related to presence of catheter-associated bloodstream infection (CABSI) in patients with COVID-19 in an adult intensive care unit.

Significant Variables in the Association Tests	Odds Ratio (95% Confidence Interval)
		Simple Model		Multiple Model
	p-Value	Unadjusted	p-Value	Adjusted
Obesity presence	0.038	1.62 (1.03–2.55)	0.003	2.39 (1.36–4.22)
COVID-19 vaccination prior to hospital admission	0.046	1.73 (1.01–2.96)	0.232	1.50 (0.77–2.91)
Hydrocortisone use prior to CABSI	0.036	0.62 (0.40–0.97)	0.585	0.85 (0.48–1.51)
3 or more antibiotics use prior to CABSI	0.008	0.51 (0.31–0.88)	0.597	1.21 (0.60–2.42)
Use of antifungal prior to CABSI	0.020	0.44 (0.22–0.88)	0.242	0.56 (0.22–1.47)
Lactate Dehydrogenase in U/L	0.940	1.00 (1.00–1.00)	0.647	0.99 (0.9996–1.0003)
Days of central venous catheter use until diagnosis	0.002	0.96 (0.94–0.99)	0.019	0.95 (0.91–0.99)

). Obesity was considered a risk factor, and prior vaccination for COVID-19, the use of hydrocortisone, use of three or more antibiotics and use of antifungals were considered protective factors. When the models were adjusted, we saw that only two variables were able to predict infection, with obesity increasing the chances of CABSI by 1.39 times (OR = 2.39; 95%CI: 1.36–4.22) and the number of days of CVC use prior to infection reducing the chances by 0.05 times per day (OR = 0.91; 95%CI: 0.91–0.99) (Table 3). CABSI increased the patient’s length of stay in the ICU (median of 20.5 vs. 12 days) and the length of hospital stay (median of 26.5 vs. 19 days) when compared to the times of those who did not have the infection. CABSI alone was not able to affect patient mortality, with mortality in the group without CABSI being 72.2% (95% CI:67.85–77.78; n = 225 deaths) and in the group with CABSI being 75.96% (95% CI:67.65–84.17, n = 79 deaths) with an odds ratio of 1.18 (95% CI:0.70–1.97; p-value = 0.597). This result needs to be evaluated with caution, as confounding factors were not considered.

A total of 109 positive blood cultures for bacteria or fungi were found in 104 patients (of which five had simultaneously positive samples for fungus and bacteria). Most microorganisms found were gram negative bacteria (55.05% of germs), with 55.96% of germs resistant to three or more antibiotics. The most prevalent germs were Klebsiella pneumoniae (17.43%), Acinetobacter baumanni (15.6%) and Staphylococcus aureus (13.76%). These germs also showed the highest number of samples with resistance (

Table 4. Microorganisms isolated in 109 blood cultures from patients admitted with COVID-19 to an intensive care unit and evaluated for the presence or absence of catheter-associated bloodstream infection (CABSI).

Variable	Level	% (n) [95% Confidence Interval]
Isolated microorganism	Staphylococcus aureus	13.76 (15) [7.29–20.23]
	Enterococcus faecium	3.67 (4) [0.14–7.2]
	Proteus mirabilis	0.92 (1) [0–2.71]
	Acinetobacter baumanni	15.6 (17) [8.78–22.41]
	Enterecoccus faecalis	12.84 (14) [6.56–19.13]
	Klebisiela pneumoniae	17.43 (19) [10.31–24.55]
	Pseudomonas aeruginosa	5.5 (6) [1.22–9.79]
	Stenotropomonas maltophilia	3.67 (4) [0.14–7.2]
	Burkholderia cepacia	0.92 (1) [0–2.71]
	Serratia mascescens	0.92 (1) [0–2.71]
	Escherichia coli	0.92 (1) [0–2.71]
	Pasteurella sp.	0.92 (1) [0–2.71]
	Klebisiella oxytoca	0.92 (1) [0–2.71]
	Streptococcus viridans	0.92 (1) [0–2.71]
	Candida peliculosa	0.92 (1) [0–2.71]
	Candida tropicalis	0.92 (1) [0–2.71]
	Candida albicans	11.01 (12) [5.13–16.89]
	Candida utilis	0.92 (1) [0–2.71]
	Candida glabrata	0.92 (1) [0–2.71]
	Aspergillu sp.	1.83 (2) [0–4.35]
	Geotrichum candidum	0.92 (1) [0–2.71]
Agent classification	Gram positive bacteria	27.52 (30) [19.14–35.91]
	Gram negative bacteria	55.05 (60) [45.71–64.38]
	Fungi	17.43 (19) [10.31–24.55]
ESBL resistance mechanism	No	96.63 (86) [92.88–100.38]
	Yes	3.37 (3) [0–7.12]
Resistant to 3 or more antibiotics	No	55.96 (61) [46.64–65.28]
	Yes	44.04 (48) [34.72–53.36]

and

Table 5. Frequency of resistance in microorganisms isolated in 109 blood cultures from patients admitted with COVID-19 to an intensive care unit and evaluated for the presence or absence of catheter-associated bloodstream infection (CABSI).

Antibiotics	Microorganisms 1
	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10
Amikacin	2	0	0	0	1	1	0	0	0	0
Ampicillin	0	0	4	1	18	1	1	0	3	0
Ampicilin-Sulbactam	14	0	0	1	16	1	0	0	3	0
Benziylpenicillin	0	0	0	0	0	0	0	0	0	13
Cefepime	14	0	0	1	15	1	0	0	2	0
Ceftriaxone	0	0	0	1	17	1	0	0	2	0
Ciprofloxacin	14	0	0	1	15	1	0	1	1	0
Clindamycin	0	0	0	0	0	0	0	0	0	10
Erythomicin	0	0	0	0	0	0	0	0	0	12
Ertapenem	0	0	0	0	14	1	0	0	1	0
Gentamicin	4	6	0	0	12	1	0	1	0	0
Imipenem	13	0	0	0	14	1	0	1	1	0
Meropenem	13	0	0	0	14	1	0	1	1	0
Oxacilin	0	0	0	0	0	0	0	0	0	7
Piperacilin-Tazobac	0	0	0	0	13	1	0	3	1	0
Rifampicin	0	0	0	0	0	0	0	0	0	1
Sulfazotrim	1	0	0	0	0	0	0	0	0	2
Tigecycline	3	0	0	0	0	0	0	0	0	0
Vancomycin	0	2	0	0	0	0	0	0	0	0

¹ Microorganisms: M1: Acinetobacter baumanni, M2: Enterecoccus faecalis, M3: Enterococcus faecium, M4: Escherichia coli, M5: Klebisiela pneumoniae, M6: Klebisiella oxytoca, M7: Pasteurella sp, M8: Pseudomonas aeruginosa, M9: Serratia mascescens, M10: Staphylococcus aureus.

, Figure 1).

4. Discussion

COVID-19 has negatively affected health services in several ways, including an increase in HAI rates [15]. Patients with CABSI had had a shorter time using a catheter before infection compared to those who did not have infection. This was also observed in another study that compared CABSI in a pre-COVID-19 cohort and a COVID-19 cohort, showing in its results that, in the pre-pandemic period, the length of catheter use was approximately 4 days and after the pandemic the length of use was approximately 3 days [16]. The hypothesis is that with a shorter period of time using a catheter, the patient with COVID-19 in the ICU with a predisposition to CABSI will already need to undergo several invasive procedures, thus becoming susceptible to greater exposure and infection by different microorganisms [17]. As a result, the infection sets in soon after exposure and contamination. A study assessed that the incidence of CABSI before COVID-19 was equal to 1.89 per 1000 patients admitted, and during the pandemic the incidence increased to 5.53 per 1000 patients admitted [18], which may suggest a lower quality of care in maintenance and insertion of the catheter during the pandemic, possibly caused by the stress of healthcare professionals faced with exposure to the new virus and decreased adherence to standard precautions, as shown by some studies [9,15,16]. We saw obesity as a risk factor for CABSI. Obesity contributes to worse prognoses in patients with established COVID-19. Furthermore, metabolic deregulations, which are common in the obese population and closely related to an impaired immune system, together with an altered response to viral infection can lead to a greater predisposition to other infections and greater virulence, duration and severity of the disease [19]. Regarding length of stay, it was found that CABSI was associated with higher values both in the ICU and in the hospital. This result is in line with other studies, wherein prolonged hospitalization was also associated with the presence of CABSI [20,21]. An elevated serum DHL level was seen in patients with infection, as in another study, resulting from the greater release of this enzyme into the bloodstream because of cellular damage caused by the infectious processes to which these patients are subjected [20]. Patients with more severe cases of COVID-19 infection have higher levels of DHL than patients with milder cases, this being a biomarker that can be used to show the severity of patients’ status in relation to COVID-19 [22].

The use of hydrocortisone, three or more antibiotics and antifungals were protective factors for CABSI, which corroborated other studies in which patients with concomitant use of antibiotics showed a lower association with CABSI [23,24]. Although the literature links corticosteroid therapy with increased rates of fungemia [10,25], there are reports of the protective effect of hydrocortisone against candidemia in patients with severe COVID-19 [26]. The Pan American Health Organization points to a reduction in the risk of death for patients with COVID-19 with the use of corticosteroids, such as hydrocortisone, due to the effectiveness of this medication in treating and controlling the inflammatory process caused by COVID-19 [27]. The microorganisms isolated in the observed blood cultures were gram negative, with a predominance of Klebsiella pneumoniae and Acinetobacter baumanni. Gram negative bacilli present greater multidrug resistance, being more resistant after the COVID-19 pandemic [24] and presenting a need for greater control of the use of antimicrobials. A study that compared COVID-19 ICUs with non-COVID-19 ICUs showed that Acinetobacter baumanni had increased resistance to carbapenems. However, during the pandemic there was a significant increase in the consumption of broad-spectrum antimicrobials, disproportionate to the increase in infections with MDR microorganisms. Considering the need to avoid excessive use of antimicrobials but without delaying the start of effective treatment, it is important to create antimicrobial management programs, in addition to spreading greater knowledge of infection rates and the microorganisms involved [16]. This is important to minimize morbidity, mortality, hospitalization time and costs.

Studies show that the more invasive procedures are conducted, the greater the exposure to such microorganisms and, so, to CABSI [28,29,30]. Is important to remember the importance of knowing the risk factors involved in co-infections, which contribute to the development of preventive actions, thus ensuring greater quality in the care provided and reducing morbidity, mortality and patient hospitalization times. The occurrence of HAIs in general has increased patients’ length of stay and hospital costs, thus creating an overload on health systems. Reducing infection rates related to HAIs both reduces hospital costs and increases the availability of ICU beds in the world [31], which are still scarce, and were even more scarce during the COVID-19 pandemic.

There was a higher incidence of CABSI in vaccinated patients compared to those who were not vaccinated, although we were unable to verify how long ago the patient had been vaccinated or whether the vaccination schedule had been completed. A justification for this finding may be related to the vaccination of risk groups, corroborating this hypothesis with the fact that, in the adjusted models, only obesity remained a risk factor. The occurrence of CABSI is associated with greater severity of COVID-19 and risk factors prior to hospitalization in these patients. In a retrospective cohort study conducted in Hungary, no statistical difference was seen relating vaccinated patients to bloodstream infections [32], but that was in a more accelerated vaccination context compared to Brazil.

This study brought interesting information about the association of obesity, time of catheter use, CABSI and COVID-19 infection. Although the pandemic has ended, COVID-19 infections will continue to occur and new previously unknown variants of the virus may appear, which requires the preparation of health services in terms of caring for the population and preventing other complications due to hospitalization. In this way, the results found can collaborate with future studies.

Our findings also contribute to elucidating the risk factors and risk indicators for the development of CABSI in patients seriously ill due to COVID-19, emphasizing the need for greater control and prevention of infections during other pandemic periods, not only COVID-19. Furthermore, other studies in other regions of the world will contribute to better evaluating the robustness of the data found in this study. Future studies, involving large control centers in this country and others, will be able to point out the variables that best relate to the outcome of patients infected with diseases such as COVID-19 and will also be able investigate health care actions that can mitigate the occurrence of catheter-associated bloodstream infections, especially in vulnerable patients such as those requiring intensive care.

The study, however, has some limitations, such as the lack of prospective analysis and a control group without COVID-19, in addition to the fact that data collection was conducted in a single center, and records had a high loss of information in some variables, preventing in-depth analysis, which limits the generalization of results.

5. Conclusions

Patients with a shorter time using a catheter and with obesity had a higher incidence of CABSI compared to patients with a longer period of use and without obesity. The occurrence of CABSI also increased patients’ length of stay in the ICU and in the hospital.