As known, COVID-19 is caused by rapidly spreading virus SARS-CoV-2 and frequently had been referred to novel coronavirus (nCov). It is a novel single-stranded RNA virus sub-family that belongs to the Coronaviridae family [1-5]. The prevalence of SARS-CoV-2 co-bacterial infection is ranging from 5 to 11% [6]. Despite a relatively low bacterial co-infection rate, the prevalence of antibiotic usage in patients with COVID-19 infection was nevertheless considerably high. The clinical manifestations of SARS-CoV-2 infected patients vary from asymptomatic or mild-moderate respiratory symptoms to severe-critical systemic symptoms [7-10]. SARS-COV-2 virus has a distinctive pathogenesis and a novel wide-range propensity in affecting many known and unknown systems in the body [11-12]. Several pathogenesis related theories are submitted for explaining the wide-variability manifestations and mortalities involvement in SARS-CoV-2 infected patients. The first being "Cytokine Storm" and the others being "Radical and Thrombo-embolic Storms" [13-14].

A rapidly review studies on antibiotic usage in the early phase of pandemic revealed that 82.3% received antibiotics therapy without regard to the severity of COVID-19 infection [15]. Several independent factors may affect the clinical decision for prescribing an antibiotic in COVID-19 co-bacterial infection, including but not excluded to, aging, co-morbidities, admission severity grade, actual COVID-19 prognosticators statuses and trending, oxygen statuses and the necessity for mechanical ventilation [16-17]. Also, given variations in the management of COVID-19 in different countries, where some countries admit all COVID-19 severity grades, like our country, others countries admit only patients with severe symptoms. So, the factors affecting the use of antibiotic agents could be also varied and influenced by the health policy that is unique to each country [18]. The distribution of antibiotic usage according to different region in the world, despite varying, it is considerably substantial. East and Southeast Asia (excluding China) reporting the highest (87.5%) and Europe the lowest (63.1%) [19-20]. A meta-analysis shows that approximately 75% of patients with COVID-19 admitted to hospitals were given an antibiotic; yet, only 8% of the patients were confirmed with bacterial co-infection [21].

β-Lactam/β-Lactamase Inhibitors (BL/BLIs) and carbapenems are often considered for the treatment of sepsis when the main suspected pathogens are Gram-negative bacteria, because of their broad spectrum of coverage. These infections include most healthcare-associated infections, intra-abdominal infections, urinary tract infections and febrile neutropenia. A special consideration within this comparison is that of ESBL-producing bacteria, which are found increasingly more frequently among such infections. Our objective was to compare the clinical outcomes of the two most widely used empirical broad-spectrum antibiotics in our institution.

A single-center, retrospectively study was conducted in a specialized COVID-19 isolation center at Queen Alia Military Hospital of the Royal Medical Services (RMS) in Jordan. Over 19 months. All Jordanian mild/moderate-severe/critical SARS-CoV-2 infected patients aged 18 years and above, whose hospital admission days exceeded at least 3 days and whose COVID-19 diagnosis were suspected or confirmed were included in our study.

Tested patients whose retrievable studied variables’ data were totally or partially missed and who’s administered β-lactam antibiotics (β-ABs) weren’t belonged to carbapenems (Imipenem/Cilastatin and Meropenem) or Piperacillin/Tazobactam (PIP/TAZ), were excluded from our study. Owing to our study’s retrospective design, a signed consent form was waived. This study was ethically approved by our Jordanian Royal Medical Services-Ethical Review Board (JRMS-IRB) [Ref# 02/2021_22]. Approval was granted for us to only access data that were relevant to our study. 

We retrospectively retrieved our tested admitted SARS-CoV-2 infected patients’ data from the institutional Electronic Medical Record system (EMR, Hakeem) between Mar 2020 and Sep 2021 and the administrator of the database helped us to extract those patients’ details which primarily including social demography (age and gender), COVID-19 infection severity (according to World Health Organization for COVID-19 severity), Complete Blood Counts (CBCs), full chemistries, hospital Length of Stay (LOS), antibiotic regimes, oxygen therapies, kidney functions, acute phase reactants of C-Reactive Protein (CRP) and Ferritin (FER) levels, anthropometrics (body weight and body mass index), nutritional indices (estimated total calorie and protein density inputs), hemodynamics, antibiogram data and mortality statuses. Affected COVID-19 patients’ survival considered points in our study were pre-defined as point in which admitted SARS-CoV-2 infected patients were either survived 28-day or discharged before, whichone comes first.

Admitted COVID-19 patients were initially categorized, based on the RT-PCR positivity and COVID-19 infection clinical signs and symptoms, to suspected COVID-19 infection (who had negative PCR test but clinically, biochemically and radiologically go with COVID-19 infection) and confirmed COVID-19 infected patients (who had positive PCR test in addition to positive clinically, radiologically and biochemically evidence of COVID-19 infection). COVID-19 patient’s severity, based on World Health Organization [22], were stratified upon admission into mild/moderate grade (non-severe) when there were an absence of sign of severe or critical COVID-9 infections, severe grade when the SpO2 <90% on room air, respiratory rate >30 breath per minute, or critical grade when the severe COVID-19 infection were associated with ARDS, sepsis, or septic shock. 

Culture results were recorded for COVID-19 patients co-infected with Gram-Negative Bacteria (GNB). GNB that were tracked in our study including Enterobacteriaceae.spp (E. coli, Klebsiella. spp, Enterobacter. spp, Proteus. spp, Serratia. Spp, Morganella. spp and Providencia. spp) and non-Enterobacteriaceae. spp of Pseudomonas. spp and Acinentobacter. spp. β-ABs were allocated to Non-PIP/TAZ group (Group I) and PIP/TAZ group (Group II). The prescribing doses of the 3 used broad-spectrum β-ABs, Piperacillin/Tazobactam (Tazocin®), Imipenem/Cilastatin (Tienam®) and Meropenem (Meronem®), were recorded. Based on the studied patients’ creatinine clearance (CrCl_{Jelliffe eq}), we assessed the optimal dosing of each prescribed antibiotic. Deficits in antibiotics dosing were assessed by subtracting the recorded prescribed dosing from the calculated optimal dosing.

Hemodynamics variables of Shock Index (SI) and modified Shock Index (mSI) were mathematically assessed (dividing heart rate to systolic blood pressure and mean arterial pressure, retrospectively). Infectious diseases prognosticator's ratios, including C-Reactive Protein (CRP) to albumin ratio (CRP: ALB), Ferritin to Albumin Ratio (FER: ALB), Neutrophils to Lymphocytes Ratio (NLR) and monocytes to Lymphocytes Ratio (MLR) were also assessed. Sodium and potassium levels were corrected according to blood glucose and pH values, respectively. All retrievable biochemical data were averaged using at least 2 measurements.

All retrievable and calculated variables were thereafter divided into non-categorical data and categorical data for which the comparative data were analyzed across the two studied groups by Independent and One-Sample T-Tests or by Chi-Square Test to express the analysis results as either Mean±SD and Mean difference±SEM or as Number (Percentage) and the relative risk estimates, respectively, as fully described in Table 1-6. IBM SPSS® Statistics Version 26.0 was used to perform descriptive analysis on the data.

Table 1: Comparatively studied variables between Non-PIP/TAZ SARS-CoV-2 infected patients Cohort (Cohort I) and PIP/TAZ SARS-CoV-2 infected patients (Cohort II) among admitted affected COVID-19 patients at Queen Alia Military Hospital, Jordan between Mar 2020 and Sep 2021

Data results of the comparative variables between the Group I and Group II were statistically analyzed by independent T and One-Sample T-Test (at p-value<0.05) and expressed as Mean ± SD and Mean difference ± SEM, Cohort I: Affected COVID-19 patients who weren’t on Piperacillin/Tazobactam,Cohort II:  Affected COVID-19 patients who were on Piperacillin/Tazobactam, 1: Baseline, BW: Body Weight, BMI: Body Mass Index, ALB: Albumin Level, HALB: Human Albumin, SCr: Serum Creatinine, BUN: Blood Urea Nitrogen, CrCl: Creatinine Clearance, Temp: Temperature, PARA: Paracetamol, BG: Blood Glucose Level, cNa: Corrected Sodium Level, HLOS: Hospital Length of Stay

Table 2: Comparatively Studied Variables between Non-PIP/TAZ SARS-CoV-2 Infected Patients Cohort (Cohort I) and PIP/TAZ SARS-CoV-2 Infected Patients (Cohort II) Among Admitted Affected COVID-19 patients at Queen Alia Military Hospital, Jordan between Mar 2020 and Sep 2021

Data results of the comparative variables between the Group I and Group II were statistically analyzed by independent T and One-Sample T-Test (at p-value<0.05) and expressed as Mean ± SD and Mean difference ± SEM, Cohort I: Affected COVID-19 patients who weren’t on Piperacillin/Tazobactam, Cohort II: Affected COVID-19 patients who were on Piperacillin/Tazobactam, DBP: Diastolic blood pressure, SI: Shock Index, mSI: Modified Shock Index, INR: International Normalized Ratio, BIL: Bilirubin level, FLUD: Total fluid (PO/IV) inputs, ENF: Enteral Nutritional Feeding, TCI: Total Calories Inputs, PD: Protein Densities in g per 100 Cal, CarbD: Carb Density in g/100 Cal, cK: Corrected potassium levels

Table 3: Comparatively Studied Variables between Non-PIP/TAZ SARS-CoV-2 Infected Patients Cohort (Cohort I) and PIP/TAZ SARS-CoV-2 Infected Patients (Cohort II) among Admitted Affected COVID-19 Patients at Queen Alia Military Hospital, Jordan between Mar 2020 and Sep 2021

Data results of the comparative variables between the Group I and Group II were statistically analyzed by independent T and One-Sample T-Test (at p-value<0.05) and expressed as Mean ± SD and Mean difference ± SEM, Cohort I: Affected COVID-19 patients who weren’t on Piperacillin/Tazobactam, Cohort II: Affected COVID-19 patients who were on Piperacillin/Tazobactam, WBCs: White blood cells, TLC: Total Lymphocytes Counts, ANC: Absolute Neutrophils Count, MC: Monocytes Coun, NLR: Neutrophils to Lymphocytes Ratio, MLR: Monocytes to Lymphocytes Ratio

Table 4: Comparatively Studied Variables between Non-PIP/TAZ SARS-CoV-2 Infected Patients Cohort (Cohort I) and PIP/TAZ SARS-CoV-2 Infected patients (Cohort II) among Admitted Affected COVID-19 patients at Queen Alia Military Hospital, Jordan between Mar 2020 and Sep 2021

Data results of the comparative variables between the Group I and Group II were statistically analyzed by independent T and One-Sample T-Test (at p-value<0.05) and expressed as Mean ± SD and Mean difference ± SEM, Cohort I: Affected COVID-19 patients who weren’t on Piperacillin/Tazobactam, Cohort II:  Affected COVID-19 patients who were on Piperacillin/Tazobactam, Optimal**: Optimal dosing of the selected antibiotics based on the calculated CrCl, Deficit***: Deficit dosing of the corresponding antibiotics was calculated by subtracting the prescribed dose from the optimal dose and consequently the %Deficit was obtained by dividing the deficit dosing over the prescribed dose,  NA: Not-Applicable and statistically can’t be computed, WBCs: White Blood Cells, TLC: Total Lymphocytes Counts, ANC: Absolute Neutrophils Count, MC: Monocytes Count, NLR: Neutrophils to Lymphocytes Ratio, MLR: Monocytes to Lymphocytes Ratio, PIP/TAZ: Piperacillin/Tazobactam (Tazocin®), MER: Meropenem (Meronem®), IMI/CIL: Imipenem/Cilastatin (Tienam®)

Table 5: Comparatively Studied Variables between Non-PIP/TAZ SARS-CoV-2 Infected Patients Cohort (Cohort I) and PIP/TAZ SARS-CoV-2 Infected Patients (Cohort II) among Admitted Affected COVID-19 patients at Queen Alia Military Hospital, Jordan between Mar 2020 and Sep 2021

Table 5: Continue

Data results of the comparative variables between the Group I and Group II were statistically analyzed by independent T and One-Sample T-Test (at p-value<0.05) and expressed as Mean ± SD and Mean difference ± SEM, Cohort I: Affected COVID-19 patients who weren’t on Piperacillin/Tazobactam, Cohort II: Affected COVID-19 patients who were on Piperacillin/Tazobactam, (FER: ALB) or (CRP: ALB) to inverse ratio of NLR or MLR (LNR or LMR, respectively) are a new proposed indicators by us that integrate two valid prognosticator ratios in one ratio in hopeful to improve the diagnostic and prognostic performance utility in COVID-19 infected patients, FER: Ferritin level, ALB: Albumin level, CRP: C-Reactive protein level, CRP: ALB:  C-Reactive Protein to Albumin levels Ratio, FER: ALB: Ferritin to Albumin levels Ratio, LNR: Lymphocytes to Neutrophils Ratio, LMR: Lymphocytes to Monocytes Ratio

Table 6: Comparatively Studied Variables between Non-PIP/TAZ SARS-CoV-2 Infected Patients Cohort (Cohort I) and PIP/TAZ SARS-CoV-2 Infected Patients (Cohort II) among Admitted Affected COVID-19 Patients at Queen Alia Military Hospital, Jordan between Mar 2020 and Sep 2021

Data results of the comparative variables between the 2 tested cohorts were statistically analyzed by Chi Square Test (at p-value< 0.05) and expressed as Number (Percentage), Cohort I: Affected COVID-19 patients who weren’t on Piperacillin/Tazobactam, Cohort II:  Affected COVID-19 patients who were on Piperacillin/Tazobactam, *: Significant (p-Value <0.05), N: Number of tested COVID-19 infected patients, F: Female, M: Male, M: F: Male to Female ratio, 0₂: Oxygen, NC: Nasal Canula on Oxygen flow rate of 3-6 L/min, NIMV: Non-Invasive Mechanical Ventilation, IMV: Invasive Mechanical Ventilation, PARA: Paracetamol, ALB RSI: Relative Strength Index of Albumin, cNa: Sodium level after correction with BG, PIP/TAZ: Piperacillin/Tazobactam (Tazocin®), MER: Meropenem (Meronem®), IMI/CIL: Imipenem/Cilastatin (Tienam®), MORT: Mortality rate, NA: Can’t be computed

From total admitted COVID-19 infected patients in our isolation departments at Queen Alia Military Hospital, Royal Medical Services, Amman, Jordan between Mar 2020 and Sep 2021, 718 eligible studied patients were finally included in this study (718/4183, 18.67%) in which 247 COVID-19 infected patients (31.6%) had suspected COVID-19 infection [117 (31.0%) belonged to Cohort I and 130 (32.3%) belonged to Cohort II] and 534 COVID-19 infected patients (68.4%) had confirmed COVID-19 infection [261 (69.0%) belonged to Cohort I and 273 (67.7%) belonged to Cohort II]. 378 (48.39%) COVID-19 patients were group to Cohort I compared to 403 (51.61%) COVID-19 patients grouped to Cohort II.

Figure 1: Stacked 3-D bar counts of Non-Tazocin Cohort (Cohort I) versusTazocin Cohort (Cohort II) Satartified Based on Overall-Mortality Rate and Gender,

(Filtered by Suspected Versus Confirmed cases of COVID-19 infection status)

The mean age of the whole study cohort was 59.40±10.60 years and the Non-PIP/TAZ Cohort (Cohort I) was insignificantly older than the PIP/TAZ Cohort (Cohort II) (59.61±10.76 years versus 59.21±10.46 years, respectively, 0.40±0.76 years, p-value = 0.599). Insignificantly, males were distributed in the study in approximately 2.309:1 ratio compared to females [545 (69.8%) versus 236 (30.2%), respectively, p-vale = 0.556] in which 68.8% (260 COVID-19 infected men) and 31.2% (118 COVID-19 infected women) belonged to the Cohort I compared to 70.7% (285 COVID-19 infected men) and 29.3% (118 COVID-19 infected women) were belonged to the Cohort II (Figure 1). 

Oxygen supply strategies for the whole studied cohort were distributed between Cohort I and Cohort II, in which 76 (9.7%), 332 (42.5%), 357 (45.7%) and 16 (2.0%) versus 76 (20.2%), 205 (54.5%), 95 (25.3%) and 0 (0.0%) were on non-O₂ supply, nasal cannula at a flow rate of 3-6 L/min, non-invasive mechanical ventilation and invasive mechanical ventilation, retrospectively. Average Paracetamol dose was insignificantly lower in Cohort I compared to Cohort II [1.89±0.93 g/day vs 1.92±0.95 g/day, -0.03±0.07 g/day, p-value = 0.615] in which the percentages distribution of Paracetamol IV compared to Paracetamol P.O in Cohort I [135 (35.7%) vs 243 (64.3%)] was insignificantly lower than in Cohort II [148 (36.7%) vs 255 (63.3%)]. In our study, we also investigated that the relative risk estimate for consumption Paracetamol IV compared to Paracetamol PO in PIP/TAZ Cohort compared to Non-PIP/TAZ Cohort [1.045 (95% CI; 0.780-1.399)].

There were insignificantly proportional distributions regarding COVID-19 patients on Dexamethasone 6 mg/day across the two tested cohorts [197 (52.1%) vs 208 (51.6%)]. Carbapenem proportional distribution in Non-PIP/TAZ Cohort (Cohort I) were 177 (46.8%) for Imipenem/Cilastatin and 201 (53.2%) for Meropenem. Cohort I had insignificantly lower average blood glucose level (BG₂) and lower total insulin requirement than in Cohort II [151.2±36.9 mg/dL and 32.08±2.05 IU/day vs 152.7±35.8 mg/dL and 32.12±1.88 IU/day, retrospectively, p-value=0,576 and 0.785]. Hemodynamically, Cohort I had insignificantly lower changing in average diastolic blood pressure (%∆ DBP₁₂) and higher increasing in average mSI (%∆mSI₁₂) than Cohort II from admission baseline hemodynamics [48.6%±14.2% vs 48.9%±14.9%, -0.3%±1% and, -20.4%±14.5% vs -26.6%±14.2%, +0.2%±1%, p-value = 0.775 and 0.860, respectively]. COVID-19 patients in Cohort I had insignificantly lower average bilirubin and INR values (BIL₂ and INR₂, respectively) than in Cohort II [2.56±0.18 mg/dL and 2.59±0.11 vs 2.57±0.20 mg/dL and 2.60±0.12, p-value = 0.392 and 0.423, respectively]. 

Haematologically, the percentages reduction in neutrophils and monocytes to lymphocytes ratios (%∆NLR₁₂ and %∆MLR₁₂) were all insignificantly higher in Cohort I compared to Cohort II [-30.3%±98.9% and -45.9%±70.4% vs -37.0%±30.4% and -50.2%±22.3%, +6.7%±5.2% and +4.3%±3.7%, p-values = 0.194 and 0.242]. Regarding acute phase prognosticators and theirs’s albumin ratios, the reduction percentages in FER: ALB and CRP: ALB (%∆FER: ALB₁₂ and %∆CRP: ALB₁₂) were insignificantly lower in Cohort I compared to Cohort II [-58.4%±15.5% and -59.6%±14.8% vs -58.0%±15.5% and 59.1%±14.8%, -0.4%±1.1% and -0.5%±1.1%, p-values = 0.697 and 0.669, respectively].

The present study assessed the clinical impacts variability of using β-ABs among admitted SARS-CoV-2 infected patients with mild/moderate-severe/critical COVID-19 infection statuses on specialized isolation center at Queen Alia Military Hospital of the Royal Medical Services (RMS) in Jordan, between Mar 2020 and Sep 2021. Two β-ABs based categorized cohorts were investigated in this study, Non-PIP/TAZ Cohort (Cohort I) and PIP/TAZ Cohort (Cohort II). The uniqueness of our study is primarily involved in its multi-faceted comparative variables assessment among admitted Jordanian COVID-19 patients with suspected bacterial co-infection.

The main finding of our study was that an investigated overall 28-day SARS-CoV-2 infected patients’ mortality were insignificantly recorded between the two ABs based categorized cohorts [75 (19.8%) vs 80 (19.9%), p-Value = 0.997] over also insignificantly overall hospital Length of Stay (LOS) [11.17±2.79 days vs 11.28±2.91 days, -0.11±0.20 days, p-Value = 0.595] for Cohort I and Cohort II, respectively. When the two aforementioned two phase reactants ratios combined with the two inverse haematological ratios of Lymphocytes to Neutrophils (LNR) and Lymphocytes to Monocytes Ratios (LMR), the reduction percentages in the four yielded combined phase reactants: Inverse haematological ratios (%∆ (FER: ALB): LNR_12, %∆ (FER: ALB): LMR_12, %∆ (CRP: ALB): LNR₁₂ and %∆ (CRP: ALB): LMR₁₂, respectively) were also insignificantly higher in Cohort I compared to Cohort II [-66.4%±62.7%, -74.0%±45.1%, -67.6%±58.6% and -74.9%±42.1% vs -70.2%±24.5%, -76.4%±18.7%, -71.2%±23.5% and -77.1%±18.0%, p-Values = 0.257, 0.324, 0.262 and 0.335, respectively].

The only statistically significant finding across the two studied cohorts was regarding average corrected sodium level (cNa₂) which was significantly lower in Cohort I compared to Cohort II [134.85±4.59 mEq/l vs 137.19±4.93 mEq/l, -2.34±0.34 mEq/l, p-value = 0.00] and the incidence of hyponatremia, cNa₂ be below 140 mEq/l, was significantly higher in Cohort I compared to Cohort II [378 (100.0%) vs 248 (61.5%), respectively, p-value = 0.00]. additionally, when we assessed the percentage changes in cNa from admission baseline levels (%∆ cNa₁₂), they were also significantly lower in Cohort I to Cohort II [6.49%±5.18% vs 8.29%±5.51%, -1.80%±0.38%, p-Value = 0.00]. The significant changes in Na⁺ during antibiotics administration were likely from β-lactam ABs. Meropenem has the highest Na⁺ load per gram of the three tested β-lactam ABs (3.92 mEq Na⁺ /g AB) followed by Imipenem/Cilastatin (3.2 mEq Na⁺/g AB) and Piperacillin/Tazobactam (2.51 mEq Na⁺/g AB). To calculate AB Na⁺ input (mEq Na⁺/day), we multiplied AB Na⁺ load (mEq Na⁺ /g AB) by AB dose input (g AB/day).

In summary, our results demonstrate that there were insignificant differences between Piperacillin/Tazobactam and Carbapenems regarding overall clinical impacts, when they were empirically administered in SARS-CoV-2 infected patients. Also, we explored that significant higher %cNa₁₂ in PIP/TAZ Cohort (Cohort II) may have positive clinical advantages over Carbapenems in Non-PIP/TAZ (Cohort I). This study is limited by its retrospective design, using single-center data. So, our data may be useful in other centers and a larger, multisite and prospective study is needed to control for multiple confounders.

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