https://ojs.wpro.who.int/ 1WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999 Original Research C oronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2), was first documented in Wuhan, Hubei Province, China in December 2019.1 According to the World Health Organization (WHO), as of April 2023, there have been 762 million COVID-19 cases with over 6.8 million deaths worldwide. In the Philippines, there have been over 4 million confirmed cases with over 66 000 deaths.2 The global incidence has steadily declined in 2023 after a peak in December 2022.2 However, severe and critical disease remains a concern; in one study from the United States of America, 5.3% of cases infected with the Omicron variant were hospitalized, with 3% requiring oxygen.3 Internationally4 and in the Philippines,5 severe and critical infections usually affect older patients and those with multiple comorbidities. Respiratory viral infections are a risk factor for bacterial coinfections, which may increase disease sever- ity and mortality.6 Bacterial coinfections are defined as suspected bacterial pneumonia in addition to COVID-19 within 48–72 hours of hospital admission for COVID-19,7 and are relatively common in patients with severe and critical disease.8 Secondary bacterial infections are de- fined as suspected bacterial pneumonia after 72 hours of hospitalization for COVID-19,7 and are diagnosed when patients present with the symptoms and signs of pneumonia and a pathogen is isolated from sputum, blood, endotracheal aspirate or bronchoalveolar lavage cultures following admission.1 There are limited cues for differentiating bacterial and viral respiratory infections. Despite the viral origin of COVID-19, physicians tended to start treatment with antibiotics since cough, a Saint Louis University Hospital of the Sacred Heart, Baguio City, Philippines. Published: 24 June 2023 doi: 10.5365/wpsar.2023.14.2.999 Objective: The ongoing coronavirus disease (COVID-19) pandemic is exacerbating optimal antibiotic stewardship and the promotion of bacterial resistance due to the over-prescribing of antibiotics for patients with COVID-19. This study aimed to determine the prevalence of antibiotic therapy in patients with COVID-19 infection and explore the association of antibiotic prescribing with patients’ demographics and clinical characteristics. Methods: A retrospective analytical cross-sectional study was conducted at a tertiary hospital and training institution in Baguio City, the Philippines from March 2020 to March 2021. Univariate and multivariable logistic regression was used to compare COVID-19 patients who were prescribed antibiotics with those who were not. Results: Of the 157 patients hospitalized with COVID-19 infection, 90 (57.3%) received antibiotics, with only three (1.9%) having confirmed bacterial coinfection. Among those prescribed antibiotics, azithromycin was the most frequently prescribed antibiotic (43.3%), followed by ceftriaxone (33.1%), piperacillin-tazobactam (15.3%), ceftazidime (5.1%), moxifloxacin (1.3%), amikacin (0.6%), ampicillin and sulbactam (0.6%), cefuroxime (0.6%), metronidazole (0.6%) and penicillin (0.6%). Antibiotic use was associated with factors such as having bilateral infiltrates on chest X-ray, the severity of COVID-19 infection and high white blood cell counts. Discussion: Antibiotic use was high among patients with confirmed COVID-19 despite a low prevalence of confirmed bacterial coinfection. This may be due to the similarities in the clinical manifestations of both viral and bacterial infections. Judicious use of antibiotics in the treatment of COVID-19, as well as other viral infections (for example, influenza), is required to prevent antibiotic resistance in accordance with the principles of antimicrobial stewardship. Antimicrobial use in patients with confirmed COVID-19 infection in the Philippines: a cross-sectional study Roanne J Dominguez,a Nicole A Domingo-Cerenoa and Rosemarie T Josue-Domingueza Correspondence to Roanne J Dominguez (email: roannedominguezmd@gmail.com) WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999 https://ojs.wpro.who.int/2 Dominguez et alAntimicrobial use in patients with confirmed COVID-19 infection Data collection Charts of confirmed COVID-19 patients who met the inclusion criteria were reviewed. Data collected were: antibiotic usage (use or non-use, type of antibiotic); age (19–59 years old or ≥60 years old); presence or absence of comorbidities; disease severity (mild, moderate, severe or critical); results of chest X-ray (normal, unilateral infiltrates or bilateral infiltrates); white blood cell count (<5000, 5000–10 000 or >10 000); differential count (neutrophilia or lymphocytosis); procalcitonin (≤2 ng/mL or >2 ng/mL); and blood, sputum and/or endotracheal aspirate cultures (with or without growth) (Table 1). The severity classification of patients with COVID-19 was based on the Unified COVID-19 Algorithms (Table 2).13 The comorbidities included were diabetes, hyperten- sion, coronary artery disease, rheumatic heart disease, asthma, chronic obstructive pulmonary disease, chronic kidney disease, cancer, arrhythmia and stroke. Patients were diagnosed with a bacterial coinfection if there was growth in culture samples conducted within the first 48 hours of admission to hospital. Data analysis Data were encoded and analysed using SPSS v24 (IBM Corp., Armonk, NY, United States of America). Frequencies and percentages were used to describe the prevalence of antibiotic use in patients with COVID-19. To determine the association between antibiotic use and the variables of interest (age, sex, comorbidities, severity of COVID-19 infection, chest X-ray findings, white blood cell count, differential count, procalcitonin, blood culture, and sputum and endotracheal aspirate culture), univariate and multivariable logistic regression was used. Imputation of missing variables for some patients at hospital admis- sion was considered if <20% of values were missing, and imputation based on the expectation−maximization algorithm method was used to replace missing values. A P value of <0.05 was considered statistically significant. RESULTS The charts were reviewed of all 157 hospitalized COVID-19 patients, of whom 90 (57.3%) received fever and infiltrates on chest imaging are markers of bacterial community-acquired pneumonia requiring antibiotics.9 The uncertainty of the COVID-19 pandemic and the absence of antiviral treatments with proven efficacy probably also contributed to the widespread and excessive use of antibiotics,10 especially in the first year of the pandemic. This prescriber behaviour threat- ens antimicrobial stewardship, which is defined as “an organizational or healthcare-system-wide approach to promoting and monitoring judicious use of antimicrobials to preserve their future effectiveness.”11 WHO recom- mends that antimicrobials be used for severe COVID-19 cases at increased risk for secondary bacterial infection and death.12 The main objective of this study is to describe antibiotic use in patients with confirmed COVID-19 in- fection at a tertiary hospital in Baguio City, Philippines. More specifically, the study aims to: (1) determine the prevalence of antibiotic use in patients with confirmed COVID-19 infection; (2) verify the prevalence of bacterial coinfection; (3) ascertain the most frequently prescribed antibiotics; and (4) explore the associations of variables with antibiotic use, specifically, age, sex, comorbidities, severity of COVID-19 infection, chest X-ray findings, white blood cell count, differential count, procalcitonin, blood culture, and sputum and endotracheal aspirate culture. METHODS Study design A retrospective analytical cross-sectional study was conducted at a tertiary hospital and training institution in Baguio City, Philippines. Study population All adult patients (≥19 years old) with mild, moderate, severe and critical confirmed COVID-19 infection who were seen, diagnosed and eventually hospitalized from March 2020 to March 2021 were included in the study. Patients who were asymptomatic, regardless of the pres- ence or absence of comorbidities, as well as patients who developed hospital-acquired infection during the course of their hospital stay, were excluded. WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999https://ojs.wpro.who.int/ 3 Antimicrobial use in patients with confirmed COVID-19 infectionDominguez et al Table 1. Characteristics of hospitalized COVID-19 cases at a tertiary hospital in Baguio City, the Philippines, March 2020 to March 2021 (N = 157) Table 2. Severity classification of COVID-19 cases, the Philippines, 2020 Characteristic Number % Age (years) 19–59 106 67.5 ≥60 51 32.5 Sex Male 96 61.1 Female 61 38.9 Comorbiditiesa Yes 97 61.8 No 46 29.3 Severity Mild 64 40.8 Moderate 36 22.9 Severe 50 31.8 Critical 7 4.5 Chest X-ray Normal 80 51 Unilateral 20 12.7 Bilateral 57 36.3 White blood cell counta <5000 28 17.8 5000–10 000 99 63.1 >10 000 26 16.6 Differential counta Neutrophilia 149 94.9 Lymphocytosis 4 2.5 Procalcitonin ≤2 ng/mL 77 49 >2 ng/mL 5 3.2 Not requested 75 47.8 Bacterial coinfection Yes 3 1.9 No 77 49 Not requested 77 49 a Values are missing from some patients for comorbidities (n = 14), white blood cell count (n = 4) and differential count (n = 4). antibiotics and three (1.9%) had confirmed bacterial coinfection. Among the 90 patients who were given anti- biotics, azithromycin was the most frequently prescribed antibiotic (43.3%), followed by ceftriaxone (33.1%) and piperacillin-tazobactam (15.3%) (Fig. 1). Classification Signs and symptoms Mild Fever, cough, diarrhoea, change in taste or smell, or fatigue; no signs of hypoxia on pulse oximetry or arterial blood gas, or pneumonia on physical examination and chest X-ray Moderate Symptomatic with clinical or radio- graphic evidence of lower respiratory tract disease (infiltrates on chest X- ray, presence of crackles) and oxygen saturation >94% on room air Severe Symptomatic with oxygen saturation ≤94% on room air and lung infiltrates on chest X-ray Critical Respiratory failure not fully explained by cardiac failure or fluid overload (acute respiratory distress syndrome), septic shock or multiple organ dys- function There were 106 patients (67.5%) aged 19–59 years and 51 (32.5%) aged ≥60 years. There were more males (61.1%) than females (38.9%). Comorbidities were reported for 97 patients (61.8%). They included diabetes mellitus, hypertension, cancer, chronic kidney disease, coronary artery disease, bronchial asthma and chronic obstructive pulmonary disease. With regards to the severity of COVID-19 infection, 64 patients (40.8%) were mild, 36 (22.9%) were moderate, 50 (31.8%) were severe and seven (4.5%) were critical (Table 1). Eighty patients (51.0%) had a normal chest X-ray, 20 (12.7%) had unilateral infiltrates and 57 (36.3%) had the presence of bilateral infiltrates on chest X-ray. Twenty-eight patients (17.8%) had white blood cell counts of <5000, 99 (63.1%) had counts of 5000–10 000 and 26 (16.6%) had counts of >10 000. Regarding dif- ferential counts, neutrophilia was noted in 149 patients (94.9%), while only four patients (2.5%) had lymphocy- tosis. Of the 157 patients, procalcitonin was measured in only 82 patients, of whom 77 (49%) had results of ≤2 ng/mL and five (3.2%) of >2 ng/mL (Table 1). Factors significantly associated with antibiotic use in multivariable analysis were: having bilateral chest X-ray infiltrates (odds ratio [OR] 48.11, 95% con- fidence interval [CI] 11.24–205.88, P < 0.001); severity of COVID-19 infection (moderate: OR 8.98, Source: Unified COVID-19 Algorithms.13 WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999 https://ojs.wpro.who.int/4 Dominguez et alAntimicrobial use in patients with confirmed COVID-19 infection In a 2020 global survey of antibiotic-prescribing prac- tices for patients with COVID-19, respondents reported that their decision to use antibiotics was based more on clinical presentation and less on laboratory or radiologic markers.22 Many of these studies were from 2020, early in the COVID-19 pandemic, when antiviral treatments for COVID-19 were not available. Almost half of the patients included in this study had mild COVID-19 infection and, therefore, as per local practice guidelines, sputum and bacterial cultures were not indicated.23 This could account for the low prevalence of bacterial coinfection in this study. Rates of bacterial coinfection in patients with COVID-19 have been low, as confirmed by several studies.14–17,24 In contrast, a study from Wuhan, China revealed a higher bacterial coinfec- tion rate of 25.5% in patients admitted for COVID-19.25 In a study from a secondary-care setting in the United Kingdom of Great Britain and Northern Ireland, blood cultures were positive in 3.2% of patients during the first 5 days of admission; after 5 days of confinement, the positivity rate increased to 6.1%. The same study revealed that pathogenic bacteria were identified at a higher rate (34.8%) from respiratory samples.26 Azithromycin, ceftriaxone, piperacillin-tazobactam and ceftazidime were the most commonly used antibi- 95% CI 2.833–28.477, P < 0.001; severe: OR 4.81, 95% CI 1.38–16.71, P = 0.014; critical: OR 0.24, 95% CI 0.07–0.81, P = 0.021); and hav- ing elevated white blood cell count (5000–10 000: OR 7.85, 95% CI 1.28–48.29, P = 0.026; >10 000: OR 7.12, 95% CI 1.48–34.36, P = 0.015) (Table 3). DISCUSSION The prevalence of empiric antimicrobial use at this tertiary hospital in Baguio City, the Philippines was 57.3%, which is high considering that the prevalence of bacterial coin- fection was 1.9%. However, similar studies have reported higher antibiotic use in patients with COVID-19 from rates of 70–90%.14–17 In a cohort study from Wuhan, China in 2020,1 all patients with laboratory-confirmed COVID-19 were given empiric antibiotic therapy. Prescribing antibiot- ics for COVID-19 patients was based on the WHO interim guidelines to treat for possible bacterial infection.18,19 In two smaller studies from Jiangsu and Wuhan, antibiotics were prescribed to almost all patients.20,21 In a study conducted by Rawson et al.,14 72% of patients with COVID-19 received antimicrobial therapy, though only 8% of patients were reported to have bacterial coinfec- tion. This may be due to difficulty ruling out bacterial coinfection during patients’ admission since viral and bacterial pneumonia have similar clinical manifestations. Fig. 1. Frequency of antibiotics prescribed to hospitalized COVID-19 patients at a tertiary hospital in Baguio City, the Philippines, March 2020 to March 2021 (N = 90) WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999https://ojs.wpro.who.int/ 5 Antimicrobial use in patients with confirmed COVID-19 infectionDominguez et al Table 3. Factors associated with antibiotic use in hospitalized COVID-19 cases at a tertiary hospital in Baguio City, the Philippines, March 2020 to March 2021a Factors Univariate Multivariable OR (95% CI) P OR (95% CI) P Age (years) 19–59 Ref Ref ≥60 2.0 (1.0–4.0) 0.049 0.3 (0.1–1.2) 0.116 Sex Male Ref Ref Female 0.8 (0.4–1.6) 0.644 1.7 (0.3–8.8) 0.507 Comorbidities No Ref Ref Yes 0.5 (0.2–1.0) 0.069 0.4 (0.7–3.0) 0.438 Severity of COVID-19 infection Mild Ref Ref Moderate 22.5 (9.7–52.0) <0.001 8.9 (2.8–28.4) <0.001 Severe 10.7 (4.4–25.9) <0.001 4.8 (1.3–16.7) 0.014 Critical 0.1 (0.0–0.2) <0.001 0.2 (0.0–0.8) 0.021 Chest X-ray Normal Ref Ref Unilateral 3.1 (0.5–17.2) 0.180 1.9 (0.3–11.8) 0.454 Bilateral 57.7 (16.2–206.0) <0.001 48.1 (11.2–205.8) <0.001 White blood cell count <5000 Ref Ref 5000–10 000 8.8 (2.1–36.3) 0.003 7.8 (1.2–48.2) 0.026 >10 000 6.6 (1.8–23.6) 0.003 7.1 (1.4–34.3) 0.015 Differential count Neutrophilia Ref Ref Lymphocytosis 0.2 (0.0–2.2) 0.209 0.1 (0.0–1.8) 0.149 Procalcitonin ≤2 ng/mL Ref Ref >2 ng/mL 1.5 (0.1–14.2) 0.724 0.6 (0.0–11.9) 0.794 Bacterial coinfection No Ref Ref Yes 3.7 (0.3–45.9) 0.297 4.8 (0.1–127.6) 0.346 a Statistically significant P values (<0.05) are in bold. otics in this study. The distribution of antibiotics used follows the Philippine Clinical Practice Guidelines on the management of community-acquired pneumonia27 and the antibiogram of the hospital. This finding was similar to that of a retrospective cohort study done at a COVID-19 referral hospital in the Philippines by Abad et al.28 In contrast, a study from a German university hospital revealed that the most commonly used antibiotics were fluoroquinolones, carbapenems and third-generation cephalosporins;6 however, this may be due to different antibiotic protocols in Europe. The presence of bilateral pulmonary infiltrates on chest X-ray was the most significant predictor of antibiotic use in this study. Such radiologic findings increase the probability of bacterial infection. Cheng WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999 https://ojs.wpro.who.int/6 Dominguez et alAntimicrobial use in patients with confirmed COVID-19 infection a larger and more diverse sample size that could include other provinces in the country to obtain a better under- standing of trends in antimicrobial use in patients with confirmed COVID-19 infection. Antibiotic use was high among patients with confirmed COVID-19 in the tertiary hospital in the Philippines during the first year of the pandemic despite a low prevalence of confirmed bacterial coinfection. Similarly, the high rates of prescribing antibiotics for COVID-19 patients were observed globally, especially in the first year of the pandemic, for both severe and non-severe cases. Factors associated with antibiotic use were radiologic evidence of bilateral infiltrates, severity of COVID-19 pneumonia and leucocytosis. The similarities in the clinical manifestations of both viral and bacterial infections may have contributed to the increased use of antimicrobials during this period, as well as there being no antiviral treatment for COVID-19 available at that time. Judicious use of antibiotics in the treatment of COVID-19, as well as other viral infections (e.g. influenza), is required to prevent antibiotic resistance in accordance with the principles of antimicrobial stewardship. Acknowledgements The authors express their sincere gratitude to Mr Norbert Angalan, Ms Angela J Dominguez and the authors’ fami- lies for their unending support. Conflicts of interest The authors have no conflicts of interest to declare. Ethics approval Permission to conduct this study at the hospital was obtained from the Medical Director and Vice President for Hospital Affairs. Research ethics approval was obtained from the University Research Ethics Committee. All charts were identified by code number and did not contain the names of the participants. All data were coded and were kept confidential and anonymous. Charts were reviewed within the hospital premises. Funding None. et al.24 reported a similar finding in a hospital in Hong Kong Special Administrative Region (China). This study also showed that the severity of illness was associated with antibiotic use, suggesting that disease severity had a potential role in the decision to prescribe antibiotics to COVID-19 patients. Patients who are severely to criti- cally ill develop a systemic inflammatory response that may lead to lung injury and organ dysfunction, ultimately increasing the risk of bacterial coinfection. A study by Nasir et al.29 showed that patients with severe to critical COVID-19 infection on admission had 4.42 times higher risk of bacterial infection. Langford et al.30 reported that the percentage of antibiotic use was especially high in patients in the intensive care unit and for those requiring mechanical ventilation. However, in a scoping review of the first 6 months of the pandemic, antibiotics were prescribed to COVID-19 patients regardless of severity of illness, with similar proportions prescribed to patients with severe or critical illness (75.4%) and patients with mild or moderate illness (75.1%).31 Chedid et al.32 suggested that although antibiotic treatment was more prevalent in more severe patients, half of the patients who received antibiotics were not severe, suggesting a tendency to extend indications of antibiotic therapy to non-severe patients. Antibiotic use was also influenced by elevated white blood cell counts in the present study. COVID-19 patients usually have normal white blood cell counts. A study by Huang et al.18 reported that white blood cell counts in patients with COVID-19 on admission indicated leuco- penia (25%) with lymphocytic predominance (64%). Leucocytosis with neutrophilic predominance alerts phy- sicians to the presence of bacterial coinfection. A study by He et al.33 showed that antibiotic prescription was significantly more common in patients with leucocytosis. In contrast, the study by Cheng et al.24 demonstrated that antibiotics were commonly ordered even if routine blood tests showed normal white blood cell count. The limited number of patients in this study restricts the generalization of the results to a broader population, as does the lack of a comparison group, such as antibi- otic prescription rates prior to the COVID-19 pandemic, to determine if antibiotic-prescribing habits changed or increased during the COVID-19 pandemic. Therefore, we recommend that a similar study be conducted with WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999https://ojs.wpro.who.int/ 7 Antimicrobial use in patients with confirmed COVID-19 infectionDominguez et al 15. Vaughn VM, Gandhi TN, Petty LA, Patel PK, Prescott HC, Malani AN, et al. Empiric antibacterial therapy and community- onset bacterial coinfection in patients hospitalized with coronavi- rus disease 2019 (COVID-19): a multi-hospital cohort study. Clin Infect Dis. 2021;72(10):e533–41. doi:10.1093/cid/ciaa1239 pmid:32820807 16. Garcia-Vidal C, Sanjuan G, Moreno-Garcia E, Puerta-Alcalde P, Garcia-Pouton N, Chumbita M, et al. Incidence of co-infections and superinfections in hospitalized patients with COVID-19: a ret- rospective cohort study. Clin Microbiol Infect. 2021;27(1):83–8. doi:10.1016/j.cmi.2020.07.041 pmid:32745596 17. Langford BJ, So M, Raybardhan S, Leung V, Soucy J-P, Westwood D, et al. Antibiotic prescribing in patients with COVID-19: rapid re- view and meta-analysis. Clin Microbiol Infect. 2021;27(4):520–31. doi:10.1016/j.cmi.2020.12.018 pmid:33418017 18. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical fea- tures of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. doi:10.1016/s0140- 6736(20)30183-5 pmid:31986264 19. Piva S, Filippini M, Turla F, Cattaneo S, Margola A, De Fulviis S, et al. Clinical presentation and initial management critically ill pa- tients with severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infection in Brescia, Italy. J Crit Care. 2020;58:29–33. doi:10.1016/j.jcrc.2020.04.004 pmid:32330817 20. Wu J, Liu J, Zhao X, Liu C, Wang W, Wang D, et al. Clinical characteristics of imported cases of coronavirus disease 2019 (COVID-19) in Jiangsu Province: a multicenter descriptive study. Clin Infect Dis. 2020;71(15):706–12. doi:10.1093/cid/ciaa199 pmid:32109279 21. Zhou P, Liu Z, Chen Y, Xiao Y, Huang X, Fan X-G. Bacterial and fungal infections in COVID-19 patients: a matter of concern. In- fect Control Hosp Epidemiol. 2020;41(9):1124–5. doi:10.1017/ ice.2020.156 pmid:32317036 22. Beovic B, Dousak M, Ferreira-Coimbra J, Nadrah K, Rubulotta F, Belliato M, et al. Antibiotic use in patients with COVID-19: a ‘snapshot’ infectious diseases international research initiative (ID- IRI) survey. J Antimicrob Chemother. 2020;75(11):3386–90. doi:10.1093/jac/dkaa326 pmid:32766706 23. Philippine COVID-19 living recommendations: 2023 update. Quez- on City: Philippine Society for Microbiology and Infectious Diseases; 2023. Available from: https://www.psmid.org/philippine-covid- 19-living-recommendations-3/, accessed 14 April 2023. 24. Cheng LS, Chau SK, Tso EY, Tsang SW, Li IY, Wong BK, et al. Bacterial co-infections and antibiotic prescribing practice in adults with COV- ID-19: experience from a single hospital cluster. Ther Adv Infect Dis. 2020;7:2049936120978095. doi:10.1177/2049936120978095 pmid:33335724 25. Zhang G, Hu C, Luo L, Fang F, Chen Y, Li J, et al. Clinical fea- tures and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. J Clin Virol. 2020;127:104364. doi:10.1016/j. jcv.2020.104364 pmid:32311650 26. Hughes S, Troise O, Donaldson H, Mughal N, Moore LS. Bacte- rial and fungal coinfection among hospitalized patients with COV- ID-19: a retrospective cohort study in a UK secondary-care set- ting. Clin Microbiol Infect. 2020;26(10):1395–9. doi:10.1016/j. cmi.2020.06.025 pmid:32603803 27. Philippine clinical practice guidelines. Diagnosis, empiric manage- ment and prevention of community-acquired pneumonia in immu- nocompetent adults: 2016 update. Quezon City: Philippine Socie- ty for Microbiology and Infectious Diseases; 2016. Available from: http://thepafp.org/website/wp-content/uploads/2017/05/2016- CAP-by-PSMID.pdf, accessed 26 February 2021. References 1. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, Chi- na: a retrospective cohort study. Lancet. 2020;395(10229):1054– 62. doi:10.1016/S0140-6736(20)30566-3 pmid:32171076 2. WHO coronavirus (COVID-19) dashboard. Geneva: World Health Organization; 2020. Available from: https://covid19.who.int/, ac- cessed 14 April 2023. 3. Wrenn JO, Pakala SB, Vestal G, Shilts MH, Brown HM, Strickland BA, et al. COVID-19 severity from Omicron and Delta SARS-CoV-2 variants. Influenza Other Respir Viruses. 2022;16(5):832–6. doi:10.1111/irv.12982 pmid:35415869 4. Lansbury L, Lim B, Baskaran V, Lim WS. Co-infections in peo- ple with COVID-19: a systematic review and meta-analysis. J Infect. 2020;8(2):266–75. doi:10.1016/j.jinf.2020.05.046 pmid:32473235 5. COVID-19 and the older Filipino population: how many are at risk? Quezon City: University of the Philippines Population Institute and Demographic Research and Development Foundation, Inc.; 2020. Available from: https://www.uppi.upd.edu.ph/research/covid-19/ rb1, accessed 30 December 2020. 6. Rothe K, Feihl S, Schneider J, Wallnöfer F, Wurst M, Lukas M, et al. Rates of bacterial co-infections and antimicrobial use in COV- ID-19 patients: a retrospective cohort study in light of antibiotic stewardship. Eur J Clin Microbiol Infect Dis. 2021;40(4):859–69. doi:10.1007/s10096-020-04063-8 pmid:33140176 7. Sieswerda E, de Boer MG, Bonten MM, Boersma WG, Jonkers RE, Aleva RM, et al. Recommendations for antibacterial therapy in adults with COVID-19 – an evidence based guideline. Clin Micro- biol Infect. 2021;27(1):61–6. doi:10.1016/j.cmi.2020.09.041 pmid:33010444 8. Chen X, Liao B, Cheng L, Peng X, Xu X, Li Y, et al. The mi- crobial coinfection in COVID-19. Appl Microbiol Biotechnol. 2020;104(18):7777–85. doi:10.1007/s00253-020-10814-6 pmid:32780290 9. Chen L, Zhou F, Li H, Xing X, Han X, Wang Y, et al. Disease char- acteristics and management of hospitalised adolescents and adults with community-acquired pneumonia in China: a retrospective mul- ticentre survey. BMJ Open. 2018;8(2):e018709. doi:10.1136/ bm- jopen-2017-018709 pmid:29449294 10. Huttner BD, Catho G, Pano-Pardo JR, Pulcini C, Schouten J. COV- ID-19: don’t neglect antimicrobial stewardship principles. Clin Micro- biol Infect. 2020;26(7):808–10. doi:10.1016/j.cmi.2020.04.024 pmid:32360446 11. Antimicrobial stewardship: systems and processes for effective an- timicrobial medicine use. London: National Institute for Health and Care Excellence; 2015. Available from: https://www.nice.org.uk/ guidance/ng15, accessed 5 January 2021. 12. Hsu J. How COVID-19 is accelerating the threat of antimicrobial resistance. BMJ. 2020;369:m1983. doi:10.1136/bmj.m1983 pmid:32423901 13. Healthcare professionals alliance against COVID-19. Unified COV- ID-19 algorithms. Quezon City: Philippine Society for Microbiology and Infectious Diseases; 2022. Available from: https://www.psmid. org/unified-covid-19-algorithms-5/, accessed 31 May 2023. 14. Rawson TM, Moore LS, Zhu N, Ranganathan N, Skolimowska K, Gilchrist M, et al. Bacterial and fungal coinfection in individuals with coronavirus: a rapid review to support COVID-19 antimicrobial pre- scribing. Clin Infect Dis. 2020;71(9):2459–68. doi:10.1093/cid/ ciaa530 pmid:32358954 https://www.uppi.upd.edu.ph/research/covid-19/rb1 https://www.nice.org.uk/guidance/ng15 https://www.psmid.org/unified-covid-19-algorithms-5/ WPSAR Vol 14, No 2, 2023 | doi: 10.5365/wpsar.2023.14.2.999 https://ojs.wpro.who.int/8 Dominguez et alAntimicrobial use in patients with confirmed COVID-19 infection 31. Cong W, Poudel AN, Alhusein N, Wang H, Yao G, Lambert H. Anti- microbial use in COVID-19 patients in the first phase of the SARS- CoV-2 pandemic: a scoping review. Antibiotics. 2021;10(6):745. doi:10.3390/antibiotics10060745 pmid:34205440 32. Chedid M, Waked R, Haddad E, Chetata N, Saliba G, Choucair J. Antibiotics in treatment of COVID-19 complications: a review of frequency, indications, and efficacy. J Infect Pub- lic Health. 2021;14(5):570–6. doi:10.1016/j.jiph.2021.02.001 pmid:33848886 33. He S, Liu W, Jiang M, Huang P, Xiang Z, Deng D, et al. Clinical charac- teristics of COVID-19 patients with clinically diagnosed bacterial co- infection: a multi-center study. PLoS One. 2021;16(4):e0249668. doi:10.1371/journal.pone.0249668 pmid:33819304 28. Abad CL, Sandejas JC, Poblete JB, Malundo AF, Salamat MS, Alejandria MM. Bacterial coinfection and antimicrobial use among patients with COVID-19 infection in a referral center in the Phil- ippines: a retrospective cohort study. IJID Reg. 2022;4:123–30. doi:10.1016/j.ijregi.2022.07.003 pmid:35822190 29. Nasir N, Rehman F, Omair SF. Risk factors for bacterial infections in patients with moderate to severe COVID-19: a case-control study. J Med Virol. 2021;93(7):4564–9. doi:10.1002/jmv.27000 pmid:33822390 30. Langford BJ, So M, Raybardhan S, Leung V, Soucy J-P, Westwood D, et al. Antibiotic prescribing in patients with COVID-19: rapid re- view and meta-analysis. Clin Microbiol Infect. 2021;27(4):520–31. doi:10.1016/j.cmi.2020.12.018 pmid:33418017