Initial Empirical Antibiotic Treatment in Patients with COVID-19 is Associated with Excess Adverse Drug Reactions without Clinical Benefit
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Original Article

Initial Empirical Antibiotic Treatment in Patients with COVID-19 is Associated with Excess Adverse Drug Reactions without Clinical Benefit

Turk J Pharm Sci 2024;21(6):489-498 DOI: 10.4274/tjps.galenos.2023.44675
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Abstract

Objectives

Empirical antibiotic use is common among hospitalized patients with coronavirus disease-2019 (COVID-19) pneumonia because it is difficult to differentiate it from concurrent bacterial pneumonia. The aim of this study was to determine risk factors for concurrent bacterial community-acquired pneumonia (b-CAP) and the need for initial empirical antibiotic coverage in patients with pulmonary involvement caused by Severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) infection. 

Materials and Methods

This prospective observational study was conducted at a tertiary university hospital between March 2020 and April 2021. Patients aged over 18 years who were hospitalized due to COVID-19 were included. Risk factors and outcomes were compared between patients who initially received empirical antibiotics and those who did not.

Results

The presence of respiratory viral pathogens other than SARS-CoV-2 was investigated via respiratory panel multiplex polymerase chain reaction in 295 patients and potential bacterial respiratory pathogens in 306 patients admitted to the hospital.  The co-infection rate was low (17.4%) and half of the patients (205/409, 50.1%) were administered initial empirical antibiotics for suspected concurrent b-CAP. Antibiotic use was higher in patients with multiple comorbidities, severe to critical pneumonia, and patients older than 65 years (p < 0.001). The overall 30-day mortality rate was significantly higher (26.3% and 2.0%, p < 0.001), and the duration of hospital stay was longer (median 13.0 and 5.5 days, p < 0.001) in patients who received empirical antibacterial agents compared to those who did not.

Conclusion

Initial empirical antibiotic treatment is common among patients infected with SARS-CoV-2, although the coinfection rate is low. Empirical antibiotic(s) did not improve the clinical course in COVID-19 patients.

Keywords: SARS-CoV-2, COVID-19, antimicrobial, empirical therapy, co-infections, community-acquired pneumonia

INTRODUCTION

Differential diagnosis of bacterial co-infections may be challenging in patients with severe to critical coronavirus disease-2019 (COVID-19) on hospital admission because the clinical presentation of COVID-19 may mimic atypical bacterial pneumonia, and pulmonary consolidation develops later during the disease. In addition, physicians overwhelmed by pandemic conditions might tend to cover all potential causes of community-acquired pneumonia (CAP) and leave no button unturned.,

The World Health Organization guidelines recommend empirical antibiotic therapy based on local epidemiology for bacterial pneumonia in patients with severe COVID-19, older patients, and long-term nursing home residents, but a few studies have shown that the rate of antibiotic usage is high despite low microbiological evidence. In most of these studies, empirical antibacterial treatment of suspected hospital-acquired and ventilator-associated pneumonia was investigated., A meta-analysis emphasized that the incidence of co-infection was low (8%) at hospital admission, yet empirical antibacterial therapy was started in 48.6% to 72% of these patients. During the COVID-19 pandemic in Türkiye, antibacterial drug sales decreased by 24.30% in 2020 compared with 2019, which was probably associated with the quarantine. However, a study conducted on Severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2)-infected patients in Türkiye showed that 71.2% of the patients were prescribed inappropriate antibiotics.

Antibiotic misuse/abuse is well known to have a negative impact, such as increased antimicrobial resistance and adverse events related to the medication. Therefore, the aim of this study was to determine the risk factors for concomitant bacterial CAP (b-CAP) and the need for initial empirical antibiotic coverage in patients with SARS-Cov-2 infection.

MATERIALS AND METHODS

This prospective, observational, and single-center study was conducted at an tertiary university hospital between March 20, 2020, and April 15, 2021. This study was conducted by the Declaration of Helsinki, and the study protocol was reviewed and approved by the Hacettepe University Non-Interventional Clinical Research Ethics Committee and the Ministry of Health (approval number: GO 22/520, date: 31.05.2022). All participants provided informed consent.

In this hospital, authorization to use carbapenems, ceftazidime, cefepime, piperacillin-tazobactam, polymyxins, quinolones (except oral forms), glycopeptide antibiotics (vancomycin and teicoplanin), daptomycin, and linezolid as well as more than three days of treatment with the 3rd generation cephalosporins and intravenous fluoroquinolones requires infectious diseases (ID) approval because of reimbursement rules by the Social Security Institution. There is a close collaboration between the department of ID and other clinical departments in the management of patients with suspicious infections. Routine clinical practice includes daily clinical rounds of patients treated with an antimicrobial agent by an ID specialist, residents, and a clinical pharmacist during antimicrobial treatment.

Study population

Patients aged over 18 years who tested positive by SARS-CoV-2 polymerase chain reaction (PCR) were included. Those with negative PCR test results but diagnosed presumptively based on characteristic findings on chest computed tomography (CT) and/or positive anti-SARS-CoV-2 immunoglobulin M (IgM) antibodies were also included in the analysis., Chest imaging and respiratory panel multiplex PCR test (Seegene, South Korea) were used to diagnose concurrent b-CAP (). Patients younger than 18 years, those with nosocomial pneumonia (pneumonia that developed 72 hours or more after hospital admission), or those without pulmonary involvement were excluded.

Data collection

Data on patient characteristics, diagnostic and clinical parameters, such as changes in oxygen requirement and fever, and antimicrobial therapy were collected. Patients were followed until the discontinuation of antimicrobial agents, discharge from the hospital, or death.

CURB-65 scores and pneumonia severity index (PSI) were used to predict mortality and determine severity of CAP. The CURB-65 and PSI scores at hospital admission were calculated. The severity of COVID-19 was classified according to the World Health Organization-China Joint Mission definitions. Patients with tachypnea, oxygen saturation ≤ 93% or PaO2/FiO2 ratio < 300 mmHg, respiratory failure requiring mechanical ventilation, and septic shock were defined as severe to critical COVID-19 pneumonia. Patients with mild pneumonia were classified as mild to moderate COVID-19 patients.  

Fever was defined as body temperature > 38 °C, whereas oxygen demand was defined as SaO2 < 90% and/or the need for oxygen supplementation. Changes in the fever pattern and oxygen demand were recorded. A leukocyte count of less than 4.1 x 103/µL was defined as leukopenia, whereas a leukocyte count of more than 11.2 x 103/µL was defined as leukocytosis. C-reactive protein (CRP) values greater than 0.8 mg/dL and a procalcitonin (PCT) value greater than 0.1 ng/mL were considered abnormal/high.

The Kidney Disease: Improving Global Outcomes (KDIGO) criteria were used to define drug-related nephrotoxicity. To summarize, nephrotoxicity was defined as an increase in serum creatinine (SCr) by ≥ 0.3 mg/dL within 48 hours or an increase in SCr by ≥ 1.5 times the baseline within seven days after the initiation of the antibacterial agent. According to KDIGO guidelines, an increase in SCr to 1.5-1.9 times the baseline or an increase in SCr of  > 0.3 mg/dL was considered stage 1, and an increase in SCr to 2.0-2.9 times the baseline was considered stage 2, and an increase in SCr to ≥ 3.0 times the baseline or > 4.0 mg/dL or the initiation of renal replacement therapy was considered stage 3. The Cancer Therapy Evaluation Program of the National Cancer Institute of the National Institutes of Health, which has been accepted as the common toxicity criteria for adverse events, was used to determine drug-induced hepatotoxicity. The Sanford Guide to Antimicrobial Therapy recommendations were used to determine the appropriateness of antimicrobial doses. “Drugs.com Drug Interactions Checker” (https://www.drugs.com/drug_interactions.html) database was used to detect potential drug-drug interactions (pDDIs) among antibacterial agents, and pDDIs were classified as “minor”, “moderate” and “major” interactions.

Statistical analysis

Statistical analysis was performed using IBM SPSS Statistics 23.0 for patients who were given empirical antibiotic treatment for b-CAP within 72 hours of admission and those who were not. In addition, SARS-CoV-2 PCR-positive patients were compared with those who tested negative but had highly suggestive CT findings or were SARS-CoV-2 IgM antibody-positive. The Shapiro-Wilk goodness-of-fit test will test whether the distributions related to the numerical variables match the normal distribution. Descriptive statistics, such as mean, standard deviation, median [IQR], minimum, and maximum, were used for numerical variables that conformed to the normal distribution. For categorical variables, percentage values and frequency tables are given. Categorical variables were compared with the χ2 tests. Mann-Whitney U non-parametric test was used to compare two independent groups. Univariate and multivariate logistic regression models were used to identify risk factors associated with antibiotic treatment. The logistic regression models included independent variables found to be significant predictors (p < 0.05).

RESULTS

A total of 262 patients (262/409, 64.1%) with positive PCR for COVID-19 and 147 (147/409, 35.9%) PCR-negative but diagnosed with COVID-19 according to clinical and CT imaging findings were evaluated. The median age of the patients was 62 years [IQR: 48-75 years], and 58.7% were males. The most common comorbidity was hypertension, followed by diabetes mellitus and coronary artery disease ().

Table 1. Demographic and clinical characteristics of patients with COVID-19 pneumonia

Total (n= 409)

Initial antibiotic therapy (n=205)

Not initially receiving antibiotic therapy (n= 204)

p value

Age

Age (years), median (IQR)

62 (48-75)

70 (57.5-80.0)

54 (40.5-67.0)

< 0.001

> 65 years, n (%)

184 (45.0)

126 (61.5)

58 (28.4)

< 0.001

Sex, n (%)

Male

240 (58.7)

134 (65.4)

106 (52.0)

0.006

Vaccination rate, n (%)

Influenza vaccine

17 (4.2)

9 (4.4)

8 (3.9)

0.085

Pneumococcal vaccine

9 (2.2)

7 (3.4)

2 (0.98)

0.692

Comorbidities, n (%)

Hypertension

166 (40.6)

103 (50.2)

63 (30.9)

< 0.001

Diabetes mellitus

111 (27.1)

73 (35.6)

38 (18.6)

< 0.001

Coronary artery disease

106 (25.9)

66 (32.2)

40 (19.6)

0.004

Malignancy

63 (15.4)

48 (23.4)

15 (7.4)

< 0.001

Neurological disease

56 (13.7)

48 (23.4)

8 (3.9)

< 0.001

COPD

44 (10.8)

38 (18.5)

6 (2.9)

< 0.001

Congestive heart failure

37 (9.0)

29 (14.1)

8 (3.9)

< 0.001

Benign prostatic hyperplasia

30 (7.3)

19 (9.3)

11 (5.4)

0.133

Chronic kidney disease

25 (6.1)

19 (9.3)

6 (2.9)

0.008

Asthma

25 (6.1)

8 (3.9)

17 (8.3)

0.061

Atrial fibrillation

23 (5.6)

20 (9.8)

3 (1.5)

< 0.001

Rheumatological diseases

19 (4.6)

8 (3.9)

11 (5.4)

0.474

Liver failure

7 (1.7)

4 (2.0)

3 (1.5)

1.000

Presence of comorbidity

308 (75.3)

189 (92.2)

119 (58.3)

< 0.001

Number of comorbidities, median (IQR)

2 (1-3)

3.0 (1.0-4.0)

1.0 (0.0-2.0)

< 0.001

Severity of COVID-19, n (%)

Severe-to-critical patient

168 (41.1)

129 (62.9)

39 (19.1)

< 0.001

Mild-moderate patient

241 (58.9)

76 (37.1)

165 (80.8)

Corticosteroid therapy, n (%)

Yes

158 (38.6)

125 (61.0)

33 (16.2)

< 0.001

No

251 (61.4)

80 (39.0)

171 (83.8)

Risk factors for CAP, n (%)

Risk factors

239 (58.4)

167 (81.5)

72 (35.3)

< 0.001

Number of patients monitored for biochemical markers, n (%)

PCT

348 (85.1)

191 (93.2)

157 (77.0)

< 0.001

CRP

383 (93.6)

195 (95.1)

188 (92.2)

0.219

Erythrocyte sedimentation rate

302 (73.8)

157 (76.6)

145 (71.1)

0.205

Development of nosocomial infections during hospitalization, n (%)

Presence of nosocomial infections

103 (25.2)

80 (39.0)

23 (11.3)

< 0.001

Hospital stay [median (IQR)]

Duration of hospital stay: day

9.0 (5.0-17.0)

13.0 (8.0-27.5)

5.5 (4.0-10.0)

< 0.001

Criteria for evaluating the severity of the disease, [median (IQR)]

CURB-65 score

2.0 (0.0-2.0)

2.0 (1.0-3.0)

0.0 (0.0-1.0)

< 0.001

PSI

94 (51.0-139.0)

132 (104.5-164.0)

54 (39.25-88.0)

< 0.001

Adverse events

Acute kidney injury

46 (11.2)

37 (18.0)

9 (4.4)

< 0.001

ALT elevation

203 (49.6)

108 (52.7)

95 (46.6)

0.236

AST elevation

214 (52.3)

119 (58.0)

95 (46.6)

0.023

Mortality, n (%)

30-day mortality

58 (14.2)

54 (26.3)

4 (2.0)

< 0.001

Mortality (in hospital)

79 (19.3)

70 (34.1)

9 (4.4)

< 0.001

ALT: Alanine aminotransferase, AST: Aspartate aminotransferase, CAP: Community-acquired pneumonia, PCT: Procalcitonin, CRP: C-reactive protein, IQR: Interquartile range, COPD: Chronic obstructive pulmonary disease, COVID-19: Coronavirus disease-2019, PSI: Pneumonia severity index

Four hundred and five patients received antiviral treatment in accordance with the recommendations of the Turkish Ministry of Health at the time of diagnosis: favipiravir (76.8%, n= 311), redeliver (3.2%, n= 13), and hydroxychloroquine (20%, n= 81). Antiviral therapy was not prescribed to four patients because of severe liver failure. Oseltamivir was added in 14 (6.8%) patients empirically.

Pulmonary co-infection was detected in 71 (17.4%) patients. Among the coinfecting agents, 83.1% (n= 59) were bacteria and 16.9% (n= 12) were respiratory viruses. The most common bacterial pathogen was Haemophilus influenzae (n= 36, 60.0%), followed by Streptococcus pneumoniae (n= 20, 33.3%) (). Urinary Legionella antigen was positive in one patient despite a negative respiratory multiplex PCR.

Table 2. Initial empirical antibiotic treatment for CAP in patients with COVID-19 confirmed via PCR positive for SARS-CoV-2 and those with suggestive clinical and radiological findings

Parameters

Total (n= 409)

COVID-19 patients with positive PCR (n= 262)

COVID-19 patients with suggestive CT imaging & negative PCR (n= 147)

p value

Antibiotic use, n (%)

Rate of antibiotic use

205 (50.1)

131 (50.0)

74 (50.3)

0.947

Coverage of atypical pathogens during treatment

178 (86.8)

112 (85.5)

66 (89.2)

0.453

Antibacterial treatment duration (day), median (IQR)

7 (6-10)

7.5 (6.0-10.0)

7 (6.75-10.0)

0.999

Preference of antibiotics for the treatment of CAP, n (%)

Cefuroxime

5 (2.4)

2 (1.5)

3 (4.1)

0.354

Ceftriaxone

73 (35.6)

48 (36.6)

25 (33.8)

0.682

Amoxicillin-clavulanic acid

10 (4.9)

5 (3.8)

5 (6.8)

0.501

Ampicillin-sulbactam

45 (22.0)

26 (19.8)

19 (25.7)

0.333

Piperacillin-tazobactam

81 (39.5)

50 (38.2)

31 (41.9)

0.600

Meropenem

51 (24.9)

37 (28.2)

14 (18.9)

0.138

Fluoroquinolones

9 (4.4)

5 (3.8)

4 (5.4)

0.725

Macrolides

23 (11.2)

15 (11.5)

8 (10.8)

0.889

Doxycycline

147 (71.7)

92 (70.2)

55 (74.3)

0.532

Respiratory multiplex PCR at admission, n (%)

Bacteria (n= 295)

59 (20.0)

33 (18.0)

26 (23.2)

0.280

Detected pathogens (n= 60)

Haemophilus influenzae

36 (60.0)

18 (52.9)

18 (69.2)

Streptococcus pneumoniae

20 (33.3)

14 (41.2)

6 (23.1)

Dual pathogen†

4 (6.7)

2 (5.9)

2 (7.7)

Virus (n= 306)

12 (3.9)

8 (4.2)

4 (3.5)

1.000

Detected viruses (n= 12)

Human rhinovirus

3 (25.0)

1 (12.5)

2 (50.0)

Influenza A

2 (16.7)

2 (25.0)

0 (0.0)

Influenza B

2 (16.7)

1 (12.5)

1 (25.0)

Bocavirus

2 (16.7)

1 (12.5)

1 (25.0)

Adenovirus

2 (16.7)

2 (25.0)

0 (0.0)

Dual pathogen‡

1 (8.3)

1 (12.5)

0 (0.0)

COVID-19 severity, n (%)

Severe-to-critical

168 (41.1)

112 (42.7)

56 (38.1)

0.359

Mild-moderate

241 (58.9)

150 (57.3)

91 (61.9)

Nosocomial infections during hospitalization, n (%)

Presence of nosocomial infections

103 (25.2)

76 (29.0)

27 (18.4)

0.017

Mortality, n (%)

30-day mortality

58 (14.2)

41 (15.6)

17 (11.6)

0.256

Mortality (in hospital)

79 (19.3)

58 (22.1)

21 (14.3)

0.054

†Dual pathogens in bacterial respiratory, PCR: Haemophilus influenza and Streptococcus pneumoniae, ‡Dual pathogens in viral respiratory PCR: Human rhinovirus and Influenza B, COVID-19: Coronavirus disease 2019, CT: Computed tomography, PCR: Polymerase chain reaction, IQR: Interquartile range, CAP: Community-acquired pneumonia, SARS-CoV-2: Severe acute respiratory syndrome-Coronavirus-2

In total, 205 (50.1%) patients received initial empirical antibiotics for suspected b-CAP (). Antibacterial treatment with atypical coverage was given in 178 patients (86.8%). Chest CT did not suggest concurrent bacterial pneumonia in 66.8% (n= 138) of the patients. Patients with high PCT and CRP levels, leukocytosis, oxygen demand, and fever were more likely to receive initial empirical antibiotic therapy (). Corticosteroid use was also significantly more common in patients who received antibiotic treatment (61%, n= 125) compared to those who did not (16.2%, n= 33, p < 0.001). Anti-inflammatory treatment was given to 3 patients due to cytokine storm (tocilizumab in 2 patients, pulse corticosteroid in one). All three patients also received empirical antibiotics at admission to the hospital. Initial empirical antibiotic coverage was 5.338 (95% Cl: 2.130-13.379) times more frequent in patients with chronic obstructive pulmonary disease (COPD), 4.457 (95% Cl: 1.220-16.276) times with atrial fibrillation (AF), and 1.784 (95% Cl: 1.060-3.004) times with diabetes mellitus. The PSI was higher in patients who received antibiotic treatment than in those who did not [132 (range: 104.5-164.0) versus 54 (range: 39.25-88.0); p < 0.001]. However, discontinuation of oxygen supplementation, clinical improvement, and defervescence were similar between patients who received antibiotics and those who did not (). Thirty-day mortality was significantly higher in patients who received initial antibiotics (26.3%) than in those who did not (2.0%) (p < 0.001) (). The mortality rate increased with older age (1.028-fold), severe to critical patients (3.411-fold), antibiotic therapy (5.726-fold), and nosocomial infection (3.557-fold) ().

Table 3. Antibiotic treatment and clinical, biochemical, and microbiological parameters

Total

Initial antibiotic therapy

Not receiving initial antibiotic therapy

p value

Baseline inflammatory marker levels, n (%)

PCT (n= 397)

≥ 0.1 ng/mL

167 (42.1)

133 (65.5)

34 (17.5)

< 0.001

< 0.1 ng/mL

230 (57.9)

70 (34.5)

160 (82.5)

CRP (n= 405)

≥ 0.8 mg/dL

345 (85.2)

197 (97.0)

148 (73.3)

< 0.001

< 0.8 mg/dL

60 (14.8)

6 (3.0)

54 (26.7)

Leukocyte count (n= 409)

< 4.1 x 103/µL

53 (13.0)

20 (9.8)

33 (16.2)

< 0.001

4.1-11.2 x 103/µL

269 (65.8)

114 (55.6)

155 (76.0)

> 11.2 x 103/µL

87 (21.3)

71 (34.6)

16 (7.8)

Inflammatory markers at antibiotic discontinuation, n (%)

PCT (n= 147)

No change

47 (32.0)

34 (28.3)

13 (48.1)

0.046

Improved

100 (68.0)

86 (71.7)

14 (51.9)

CRP (n= 321)

No change

97 (30.2)

42 (22.8)

55 (40.1)

0.001

Improved

224 (69.8)

142 (77.2)

82 (59.9)

Leukocyte (n= 136)

No change

61 (44.9)

36 (39.6)

25 (55.6)

0.078

Improved

75 (55.1)

55 (60.4)

20 (44.4)

Baseline clinical parameters, n (%)

Oxygen saturation (n= 409)

SaO2 ≥ 90 mmHg

200 (48.9)

35 (17.1)

165 (80.9)

< 0.001

SaO2 < 90 mmHg

209 (51.1)

170 (82.9)

39 (19.1)

Fever (n= 409)

< 38 °C

130 (31.8)

48 (23.4)

82 (40.2)

0.001

≥ 38 °C

279 (68.2)

157 (76.6)

122 (59.8)

Clinical parameters at antibiotic discontinuation, n (%)

Oxygen saturation (n= 209)

No change

96 (45.9)

77 (45.3)

19 (48.7)

0.699

Improved

113 (54.1)

93 (54.7)

20 (51.3)

Fever  (n= 279)

No change

95 (34.1)

48 (30.6)

47 (38.5)

0.164

Improved

184 (65.9)

109 (69.4)

75 (61.5)

Respiratory PCR monitoring, n (%)

Bacterial multiplex PCR (n= 295)

Positive

59 (20.0)

28 (17.9)

31 (22.3)

0.351

Negative

236 (80.0)

128 (82.1)

108 (77.7)

Viral multiplex PCR (n= 306)

Positive

12 (3.9)

8 (5.0)

4 (2.8)

0.320

Negative

294 (96.1)

153 (95.0)

141 (97.2)

Bacterial culture within 72 hours of hospitalization, n (%)

Growth of the sputum culture (n= 52)

Yes

9 (17.3)

8 (17.8)

1 (14.3)

1.000

No

43 (82.7)

37 (82.2)

6 (85.7)

Growth of the blood culture (n= 272)

Yes

11 (4.0)

10 (6.0)

1 (1.0)

0.055

No

261 (96.0)

157 (94.0)

104 (99.0)

PCT: Procalcitonin, CRP: C-reactive protein, PCR: Polymerase chain reaction

Table 4. Factors influencing mortality in logistic regression analysis

Univariable analysis

Multivariable analysis

Odds ratio (95% CI)

p value

Odds ratio (95% CI)

p value

Male

2.485 (1.314-4.701)

0.005

1.997 (0.963-4.142)

0.063

Age

1.057 (1.034-1.079)

< 0.001

1.028 (1.003-1.053)

0.030

Comorbidities

7.101 (2.171-23.231)

0.001

1.366 (0.276-6.768)

0.702

Presence of risk factors for CAP

6.317 (2.789-14.305)

< 0.001

1.653 (0.533-5.126)

0.384

Severe-to-critical patient

10.614 (5.042-22.344)

< 0.001

3.411 (1.506-7.724)

0.003

Initial antibiotic therapy

17.881 (6.337-50.456)

< 0.001

5.726 (1.866-17.569)

0.002

Nosocomial infection

6.936 (3.832-12.556)

< 0.001

3.557 (1.826-6.930)

< 0.001

CAP: Community-acquired pneumonia, CI: Confidence interval

Administration of antibiotics was comparable between SARS-CoV-2 PCR-positive (131/262, 50.0%) and PCR-negative patients (74/147, 50.3%) (p= 0.947). In the severe to critical disease subgroup, empirical antibiotics were administered more frequently in patients with positive PCR than in those with negative PCR (64.9% versus 59.5%, p < 0.001). Corticosteroid use (dexamethasone or methylprednisolone) was more frequent in SARS-CoV-2 PCR-positive patients (43.1% versus 30.6%, p= 0.013). Nosocomial infections were more common in the SARS-CoV-2 PCR-positive group than in the PCR-negative group (29.0% versus 18.4%, respectively, p= 0.017), and in those who received corticosteroids compared with those who did not (59.2% versus 40.8%, respectively, p < 0.001). The median duration of antibiotic treatment did not differ between PCR-positive and PCR-negative patients (p= 0.999) (). Antibiotic treatment did not improve the clinical course of patients with positive SARS-CoV-2 PCR and negative results (data not shown).

Adverse events and pDDIs during follow-up

Acute kidney injury occurred in 11.2% of patients. Thirty-seven patients who received antibiotic treatment experienced nephrotoxicity ( 52.8% for stage 1; 36.1% for stage 2; and 11.1% for stage 3). Nephrotoxicity was significantly higher in patients treated with antibiotics than in patients not treated with antibiotics  (18.0% versus 4.4%; p < 0.001). Patients treated with piperacillin-tazobactam experienced more nephrotoxicity than those treated with other antibiotics (31.3% versus 9.6%, p < 0.001). 

Elevated aminotransferase levels occurred in 60.9% (n= 249) of the patients. Elevated aspartate aminotransferase levels were observed more frequently in patients receiving antibiotic treatment than in those who were not receiving antibiotic treatment [58.0% (n= 119) versus 46.6% (n= 95), p= 0.023]. Alanine aminotransferase elevation was similar between patients who did and did not receive antibiotic(s) [52.7% (n= 108) versus 46.6% (n= 95), p= 0.236].

Antibiotic-related pDDIs were detected in 77.1% of the patients treated with antibiotics (the rate of minor pDDIs was 30.7%, the rate of moderate pDDIs was 68.3%, and the rate of major pDDIs was 15.1%)  (). The median number of pDDIs detected with antibiotics was 2 (1-3). The 30-day mortality was similar between patients with and without antibiotic-related pDDIs (25.3% versus 29.8%, p= 0.541).

DISCUSSION

Our results emphasize that initial empirical antibiotic treatment is mostly unnecessary in patients with COVID-19. We observed that empirical antibiotics did not affect mortality regardless of comorbidities and severity of pneumonia. In contrast, they lead to drug-related problems, such as nephrotoxicity and pDDIs. Although inflammatory markers were improved, clinical parameters remained similar between patients who did and did not receive antibiotics.

Several studies reported an incidence of 2.0-17.2% bacterial co-infection in patients with COVID-19. However, antibiotic therapy was administered to 48.6-100% of patients., - In our study (n= 409) antibiotics were used in 50.1% of the COVID-19 patients for presumptive b-CAP. A cross-sectional study from our center found that respiratory bacterial co-infection was present in 26 (13.1%) of 198 outpatients with COVID-19, with only 10.6% received. This could be explained by the preference of the physician for antibiotic administration to patients who require hospitalization for pulmonary infection.

Whether the patient was positive by PCR for SARS-CoV-2 or diagnosed presumptively based on clinical and imaging findings did not affect the clinical decision-making of the physicians to start antibiotics. Antibiotic treatment rates and antibiotic preferences were similar between patients with and without SARS-CoV-2 PCR (p= 0.947). In a study by Beović et al., clinical presentation was the most common indication for antibiotic therapy in patients with COVID-19. It was also emphasized that laboratory markers and radiological evaluation were effective in the antibiotic therapy decision. Similarly, in our study, antibiotic use was related to supplemental oxygen therapy, fever, and elevated acute-phase reactants.

The role of inflammatory markers in determining the efficacy of antibiotic therapy is limited. In our study, significant improvement was achieved in these parameters but not in the clinical course. The use of anti-inflammatory agents (corticosteroids or tocilizumab) and the rate of concomitant nosocomial infection are confounding factors in determining the impact of antibiotic treatment on serum levels of inflammatory markers. In our study, more patients who received empirical antibiotics were also treated with corticosteroids (61.0% versus 16.2%; p < 0.001). This finding could explain the improvement in inflammatory marker levels observed in the antibiotic-treated group, despite no clinical improvement.

Empirical antibacterial therapy may have undesirable consequences. Contrary to other studies,, , we found that the nosocomial infection rate was significantly higher in patients treated with antibiotics for CAP (39.0% versus 11.3%, respectively, p < 0.001). In addition, hospital stay was longer among patients treated with antibiotics (p < 0.001). This could also be related to a more severe initial clinical presentation, the presence of certain comorbidities, such as COPD and diabetes mellitus, which are known to have a negative effect on the hospital stay of patients with COVID-19, and the more frequent use of corticosteroids in this patient population.

Pettit et al. reported that the mortality rate of patients with COVID-19 receiving empirical antibiotic therapy for CAP was 13.8%. A retrospective study by Ng et al. On patients with COVID-19 showed that mortality was higher in patients receiving antibiotic treatment (13.3% versus 0.5%, p < 0.001). Furthermore, their study did not associate antibiotic therapy with lower mortality [adjusted odds ratio 14,492, (95% CI 0.533-393.875)]. We found that initial empirical antibacterial treatment was an independent risk factor for mortality ().

Study limitations

This was a single-center, observational study; thus, the results may not be applicable to other centers. In some patients with positive CT imaging but negative PCR results, the absence of antibody test results makes the definitive diagnosis of COVID-19 unclear. We did our best to rule out other viral/bacterial infections and non-infectious causes, such as congestive heart failure, leaving us with a COVID-19 diagnosis during the pandemic.

CONCLUSION

Attending physicians tend to prescribe antimicrobials to prevent adverse outcomes in high-risk COVID-19 patients, i.e., patients with older age, severe disease, comorbidities such as COPD, AF, and diabetes mellitus, high inflammatory marker levels, fever, and the necessity for oxygen supplementation even when there is no evidence of co-infection. Irrational use of antibiotics may cause drug-related problems and negative effects by disrupting the gastrointestinal microbiota in patients with COVID-19, including altered metabolic activity and increased antibiotic resistance. This study provides further evidence for antimicrobial stewardship efforts and recommends discontinuing empirical antibiotics, even if they are not started.

Acknowledgment

This study was presented at the 16th World Intensive and Critical Care Congress (WICC), İstanbul, Türkiye, on 26-30 August 2023.

Ethics

Ethics Committee Approval: This study was conducted in accordance with the Declaration of Helsinki, and the study protocol was reviewed and approved by the Hacettepe University Non-Interventional Clinical Research Ethics Committee (approval number: GO 22/520, date: 31.05.2022).

Informed Consent: All participants provided informed consent.

Authorship Contributions

Surgical and Medical Practices: P.B.E., E.K., G.T.D., M.Ç.S., Concept: P.B.E., E.K., A.Ç.İ., K.D., S.Ü., Ö.U., Design: P.B.E., G.T.D., M.Ç.S., A.C.I., K.D., S.Ü., Ö.U., Data Collection or Processing: P.B.E., E.K., G.T.D., M.Ç.S., Analysis or Interpretation: P.B.E.,E.K, A.Ç.İ, Literature Search: P.B.E., A.Ç.İ., K.D., S.Ü., Ö.U., Writing: P.B.E., E.K.

Conflict of Interest: The authors have no conflicts of interest to declare.

Financial Disclosure: The authors declared that this study received no financial support.

Footnotes

Acknowledgment

This study was presented at the 16th World Intensive and Critical Care Congress (WICC), İstanbul, Türkiye, on 26-30 August 2023.

Ethics

Ethics Committee Approval: This study was conducted in accordance with the Declaration of Helsinki, and the study protocol was reviewed and approved by the Hacettepe University Non-Interventional Clinical Research Ethics Committee (approval number: GO 22/520, date: 31.05.2022).

Informed Consent: All participants provided informed consent.

Authorship Contributions

Surgical and Medical Practices: P.B.E., E.K., G.T.D., M.Ç.S., Concept: P.B.E., E.K., A.Ç.İ., K.D., S.Ü., Ö.U., Design: P.B.E., G.T.D., M.Ç.S., A.C.I., K.D., S.Ü., Ö.U., Data Collection or Processing: P.B.E., E.K., G.T.D., M.Ç.S., Analysis or Interpretation: P.B.E.,E.K, A.Ç.İ, Literature Search: P.B.E., A.Ç.İ., K.D., S.Ü., Ö.U., Writing: P.B.E., E.K.

Conflict of Interest: The authors have no conflicts of interest to declare.

Financial Disclosure: The authors declared that this study received no financial support.

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Supplementary Materials

Supplement 2. Classification of antibiotic-drug interactions. Supplement 2. Classification of antibiotic-drug interactions

Major antibiotic-drug interactions (n= 42)*

Moderate antibiotic-drug ınteractions (n= 221)*

Clarithromycin and atorvastatin

Clarithromycin-methylprednisolone

Moxifloxacin-dexamethasone

Clarithromycin, fentanyl

Clarithromycin/haloperidol

Clarithromycin and quetiapine

Clarithromycin and tamsulosin

Clarithromycin and midazolam

Clarithromycin and amiodarone

Clarithromycin and silodosin

Meropenem and tramadol

Clarithromycin and warfarin

Clarithromycin-colchicine

Clarithromycin and escitalopram

Clarithromycin-hydroxychloroquine

Levofloxacin-methylprednisolone

Levofloxacin-dexamethasone

Levofloxacin/haloperidol

Levofloxacin-insulin

Moxifloxacin (granisetron)

Moxifloxacin-insulin

Meropenem-valproic acid

14.3%

9.5%

9.5%

7.1%

4.8%

4.8%

4.8%

4.8%

4.8%

4.8%

4.8%

2.4%

2.4%

2.4%

2.4%

2.4%

2.4%

2.4%

2.4%

2.4%

2.4%

2.4%

Doxycyclin-piperacillin

Doxycycline-calcium carbonate

Doxycycline-insulin

Doxycycline-ampicillin

Clarithromycin and dexamethasone

Ceftriaxone-furosemide

Clarithromycin-lactulose

Doxycycline-digoxin

Clarithromycin-amlodipine

Clarithromycin, lansoprazole

Doxycycline (warfarin)

Doxycycline-rocuronium

Clarithromycin-ınsulin

Clarithromycin and propofol

Levofloxacin, quetiapine

Levofloxacin-lactulose

Ceftriaxone (warfarin)

Cefuroxime-pantoprazole

Piperacillin and warfarin

Moxifloxacin, aspirin (low strength)

Moxifloxacin/famotidine

Moxifloxacin/ibuprofen

Levofloxacin, aspirin (low strength)

Levofloxacin, mirtazapine

Doxycycline-sucralfate

Doxycycline (primidone)

Doxycycline, carbamazepine

Clarithromycin, clopidogrel

Clarithromycin-sertraline

21.7%

20.8%

16.3%

10.4%

6.3%

5.9%

2.3%

1.8%

1.8%

1.4%

0.9%

0.9%

0.9%

0.9%

0.9%

0.9%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

0.5%

*Indicates the total number of interactions

Supplement 1. Respiratory pathogens were tested using respir. Supplement 1. Respiratory pathogens were tested using respiratory panel multiplex PCR (Seegene, South Korea)

Viral pathogens

Bacterial pathogens

Adenovirus

Bocavirus

Enterovirus

Human rhinovirus

Influenza A

Influenza B

Metapneumovirus

Coronavirus OC43

Coronavirus HKU1

Coronavirus 229E

Coronavirus NL63

Parainfluenza 1

Parainfluenza 2

Parainfluenza 3

Parainfluenza 4

RSV A

RSV B

Streptococcus pneumoniae

Haemophilus influenza

Mycoplasma spp.

Legionella spp.

Microbiological culture (deep tracheal aspirate or sputum)

-

Meticillin-sensitive Staphylococcus aureus

Streptococcus parasanguinis

Haemophilus influenzae

Klebsiella pneumoniae

Klebsiella aerogenes

PCR: Polymerase chain reaction, RSV: Respiratory Syncytial Virus