Invest Clin 64(3): 355 - 367, 2023 https://doi.org/10.54817/IC.v64n3a8

Corresponding author: Jesús Dawaher. Facultad de Medicina, Pontificia Universidad Católica del Ecuador, Quito,

Ecuador. E-mail jedawaher@hotmail.com

COVID-19 and bacterial superinfections:

clinical and microbiological profiles, and

determinants of mortality in a reference

center in Quito, Ecuador.

Jesús Elías Dawaher Dawaher

1,2

, Rafael Salazar Montesdeoca

Santiago Aguayo-Moscoso

, Wendy C Bonilla Poma

and Jorge Luis Vélez-Páez

Hospital General Pablo Arturo Suárez, Quito, Ecuador.

Facultad de Medicina, Pontificia Universidad Católica del Ecuador, Quito, Ecuador.

Keywords: sepsis; COVID-19; mortality; antibacterials.

Abstract. The massive prescription of antimicrobials accelerated the gen-

eration of multi-resistant bacteria during the SARS-CoV-2 pandemic. This work

aims to present the epidemiological, clinical, and microbiological profiles of

a series of patients with bacterial superinfections hospitalized in a COVID-19

reference center. We conducted a retrospective observational study in adult

COVID-19 patients hospitalized between January and December 2021 who pre-

sented with bacterial superinfections. Mortality at discharge was the variable

outcome. The median age of the 240 patients included in the study was 55

years, and the male sex predominated at 68.75%. The median stay of hospi-

talization was 24 days. Superinfections occurred in 55% of patients with me-

chanical ventilation. The most frequent bacteria were KPC-producing Klebsiella

pneumoniae complex (24.17%), ESBL-producing Klebsiella pneumoniae com-

plex (17.92%), and carbapenem-resistant Pseudomonas aeruginosa (13.75%).

The most used empirical and targeted antibiotic schemes consisted of the asso-

ciation of carbapenem, glycopeptides, and aminoglycosides (56.09 and 38.55%,

respectively). In the multivariate analysis, older age (p= 0.006, OR 1.03, 95%

CI: 1.01-1.06), central venous catheter-related bacteremia (CLBSI) (p= 0.028,

OR 1.94, 95%CI: 1.07-3.49), and the use of colistin associated with other anti-

biotics as targeted therapy (p: 0.028, OR 12, 95%CI: 1.30-110.52), were inde-

pendent predictors of mortality. In this series, we found that in patients with

COVID-19 and bacterial superinfection, age, CLBSI, and colistin use were in-

dependent predictors of non-survival. The most frequently isolated microor-

ganisms were ESBL- and KPC-producing enterobacterales and non-fermenting

Gram-negative bacilli resistant to carbapenems.

356 Dawaher et al.

Investigación Clínica 64(3): 2023

COVID-19 y sobreinfección bacteriana: perfil clínico,

microbiológico y determinantes de mortalidad en un centro

de referencia en Quito, Ecuador.

Invest Clin 2023; 64 (3): 355 – 367

Palabras clave: septicemia; COVID-19; mortalidad; antibacterianos.

Resumen.

En la pandemia por SARS-CoV-2, la prescripción masiva de anti-

microbianos aceleró la generación de bacterias multirresistentes. El objetivo de

este trabajo fue presentar el perfil epidemiológico, clínico y microbiológico de

una serie de pacientes con sobreinfección bacteriana, hospitalizados en un cen-

tro de referencia COVID-19. Se realizó un estudio observacional retrospectivo,

en pacientes adultos hospitalizados entre enero y diciembre de 2021 con CO-

VID-19, que presentaron sobreinfecciones bacterianas. La mortalidad al egreso

fue la variable desenlace. En 240 pacientes, la mediana de edad fue 55 años y

predominó el sexo masculino 68,75%. La mediana de hospitalización, fue 24

días. El 55% de las sobreinfecciones se presentó en pacientes con ventilación

mécanica. Las bacterias más frecuentes, fueron Klebsiella pneumoniae complex

productora KPC (24,17%), Klebsiella pneumoniaecomplex productora ESBL

(17,92%) y Pseudomonas aeruginosa resistente a carbapenémicos (13,75%).

Los esquemas antibióticos empíricos y dirigidos más utilizados constaron de la

asociación de carbapenémico, glicopéptido y aminoglucósido (56,09 y 38,55%

respectivamante). En el análisis multivariado la mayor edad (p= 0,006 OR 1,03

IC95%: 1,01-1,06); la bacteriemia relacionada a catéter venoso central (CLBSI)

(p: 0,028 OR 1,94 IC95%: 1,07-3,49) y el uso de colistina asociado a otros an-

tibióticos como terapia dirigida (p= 0,028 OR 12 IC95%: 1,30-110,52), fueron

predictores independientes de mortalidad. En esta serie encontramos que en

pacientes con COVID-19 y sobreinfección bacteriana, la edad, la CLBSI y el

uso de colistina, fueron predictores independientes de no supervivencia. Los

microorganismos más frecuentemente aislados fueron los enterobacterales pro-

ductores de ESBL y KPC y los bacilos Gram negativos no fermentadores resis-

tentes a carbapenémicos.

Received: 28-02-2023 Accepted: 03-06-2023

INTRODUCTION

COVID-19 is an emerging viral disease

initially reported in Wuhan-China at the end

of 2019, rapidly expanding and, in months,

collapsed global health systems

. Regardless

of the speed with which the causative agent,

a beta coronavirus, was identified and se-

quenced and what this meant for developing

the first vaccines, compassionate drug use

and the abuse of antibiotics were common

global scenarios

2,3

The prescription and self-medication of

antimicrobials, many of them for exclusive

and restricted hospital use, seeking to re-

duce the mortality and morbidity associated

with this disease, accelerated the selective

appearance of multi-resistant bacteria

COVID-19 and bacterial superinfections: clinical and microbiological profiles 357

Vol. 64(3): 355 - 367, 2023

These bacteria generated significant

phenotypic and antibiotype changes in glob-

al hospital epidemiology, which propelled a

revolution in the massive use of empirical

and targeted (directed) antibiotic therapy,

using multiple schemes and with unusual

antibiotics such as polymyxins and car-

bapenems on a large scale

. In addition,

given the high rates of multi-resistance, new

broad-spectrum antibiotics were required.

However, they were not available in the lists

of essential drugs in the public system and

were particularly expensive. This kind of an-

tibiotic therapy made the availability of the

drugs the exception and not the rule in low-

income centers.

With the advent and mass use of vac-

cines and the use of drugs such as steroids,

specific antivirals, and monoclonal antibod-

ies that have demonstrated their efficacy in

extensive clinical studies, COVID-19 is on

the brink of becoming endemic, and its mor-

bidity and mortality are minor, despite the

appearance of more effective variants in its

transmission

Falcone et al.

have reported the results

from a nationwide multicenter study in Italy,

performed with 1276 patients with bactere-

mia due to Gram-negative bacilli, in which

they observed a marked expansion of resis-

tance to carbapenems and other molecules,

new resistance mechanisms, and associated

high mortality.

This work aims to present the epidemio-

logical, clinical, and microbiological profiles

of a series of patients with bacterial superin-

fections hospitalized in a center that exclu-

sively treated COVID-19 in Quito, Ecuador.

MATERIALS AND METHODS

Location

The study was performed in a second-

level hospital, a regional reference center

for COVID-19, located in Quito, Ecuador’s

capital (2850 meters above sea level), in the

province of Pichincha (with a total popula-

tion of 3,340,039).

Study design

We conducted an analytical retrospec-

tive observational study. The universe to be

considered consisted of all adult patients

hospitalized from January 1, 2021, to De-

cember 31, 2021, with a diagnosis of COV-

ID-19. Anonymized data were collected from

the consultation database of the Infectolo-

gist in charge of infection control and from

the electronic clinical records of adult pa-

tients admitted to the different areas of the

hospital with a diagnosis of COVID-19.

Population and sample size

The universe to be considered consisted

of all adult patients hospitalized from Janu-

ary 2021 to December 2021 with a diagnosis

of COVID-19. All adult patients diagnosed

with healthcare-associated infections (su-

perinfections) were included in the study. A

total of 240 patients met the inclusion cri-

teria.

Inclusion criteria

Patients admitted to the health cen-

ter with a diagnosis of COVID-19 confirmed

by rt-PCR and who presented during their

hospital stay any healthcare-associated in-

fection (superinfection) determined by the

clinical judgment of the treating physician

and the infectious disease specialist, whose

evaluation was requested. This request was

based on findings from the physical exami-

nation, laboratory tests, and imaging stud-

ies and, with microbiological confirmation,

by isolating pathogenic microorganisms in

samples taken appropriately.

Exclusion criteria

Patients admitted to our hospital with-

out a confirmed diagnosis of COVID-19 were

not included in the study, nor were those

who did not present superadded infections

during their hospital stay, patients with

known coinfections on admission, or trans-

ferred with infections acquired in other hos-

pitals. Neither were included those patients

with negative microbiological results, whose

358 Dawaher et al.

Investigación Clínica 64(3): 2023

cultures were not taken, or whose reports

suggested sample contamination.

Data Collection

The clinical and epidemiological vari-

ables obtained and analyzed from electronic

medical records were age, gender, comorbid-

ity, diagnosis of associated bacterial infec-

tions,

antibiotic treatment schemes received

(empirical and culture-directed), hospital

stay, and outcome. Severity indicator bio-

markers were also collected: complete blood

count and glucose, creatinine, D-dimer, fer-

ritin, lactate dehydrogenase, and C-reactive

protein levels.

The information on the cultures taken,

the microbiological isolation, and suscep-

tibility profiles were obtained directly from

the reports of the Microbiology area of the

Hospital’s Clinical Laboratory.

Statistical analysis

The analyses were performed with the

IBM SPSS version 23 statistical package.

Descriptive statistics was used, employing

tables and graphs, representing the qualita-

tive variables in absolute and relative values,

whereas measures of central tendencies and

variabilities were used for the quantitative

variables.

In inferential statistics, bivariate analy-

ses were performed to determine the vari-

ables to be considered in the multivariate

analysis. With this purpose, the Chi-square

test or Fisher’s exact statistic were applied

for the qualitative variables, while for the

quantitative ones, the Mann-Whitney test

was used when data did not comply with

normality. Multivariate logistic regression

analysis was used to relate the variables with

mortality. Statistical significance was estab-

lished as p<0.05.

RESULTS

Two hundred forty patients with a me-

dian age of 55 and a predominance of men

(68.75%) were analyzed. The median hospi-

tal stay was 24 days. When comparing age

by the discharge condition, significant dif-

ferences were observed with p= 0.002, with

medians of 52.5 years in survivors vs. 58.5

years in non-survivors. The hospital stay pre-

sented significant differences by discharge

condition with p<0.001, with the median

stay being 29 days in survivors vs. 16 days in

non-survivors (Table 1).

Table 2 reports the analytical and cyto-

metric values, which indicate that although

the elevation of biomarkers characteristic of

severe forms of the disease is striking, such

as the white count, C-reactive protein, D-

dimer, and ferritin, there were no significant

differences when compared to the condition

at discharge.

Regarding associated infections, ven-

tilator-associated pneumonia (VAP) was

observed more frequently in 55% of cases,

Table 1

Relationship between clinical characteristics and discharge condition.

Clinical Characteristics Total

Discharge Condition

Survivor Non-survivor

Age (median (IQR))* 55 (45-64) 52.5 (42.75-62) 58.5 (48.75-67.25) 0.002

Sex (n (%))**

Female 75 (31.25) 45 (30.82) 30 (31.91)

0.858

Male 165 (68.75) 101 (69.18) 64 (68.09)

Days of stay (median (IQR))* 24 (16-35) 29 (21-41.5) 16 (12-22.5) <0.001

* Mann-Whitney test, ** Chi-square test.

COVID-19 and bacterial superinfections: clinical and microbiological profiles 359

Vol. 64(3): 355 - 367, 2023

followed by catheter-associated urinary in-

fections (CAUTI) at 43.75%, central line-

associated bloodstream infection (CLBSI)

31. 25%, and colonization at 15.42%, among

others. The CLBSI presented significant di-

fferences by discharge condition with a p of

0.030; the proportions were 26.03% in sur-

vivors vs. 39.36% in non-survivors (Table 3).

Among the most frequent bacteria

causing superadded infections in our stu-

dy, KPC-type carbapenem-producing Kleb-

siella pneumoniae complex was observed in

24.17% of the cases, followed by Klebsiella

pneumoniae producing extended-spectrum

β-lactamase (ESBL) in 17.92%, and carba-

penem-resistant Pseudomonas aeruginosa in

13.75%, among others. Serratia marcescens

presented significant differences by dischar-

ge condition with a p of 0.013, the propor-

tion of this bacterium being 6.16% in survi-

vors vs. 0% in non-survivors (Table 4).

Among the most used antibiotic

schemes, meropenem + vancomycin + ami-

kacin was observed in 56.09% of the empiri-

cal scheme and 38.55% of directed schemes.

In the directed scheme, significant differenc-

es were observed by discharge condition with

a p = 0.036, specifically for colistin + others,

whose proportions were 16.95% in survivors

vs. 41.67% in non-survivors (Table 5).

Multivariate logistic regression analysis

was performed to determine the relationship

between age, CLBSI, and antibiotic scheme

with mortality, observing the following: age

was related to mortality with p = 0.006,

whereas due to the one-year increase in pa-

tients, the risk of mortality of patients was

increased by 3%.

Table 2

Relationship between analytical parameters and cytometry by discharge condition.

Cytometry and

Analytical

Parameters

Total

Discharge Condition

Survivor Non-Survivor

Median (IQR) Median (IQR) Median (IQR)

Leukocytes (cells x mm

) 11510 (8210-14770) 11940 (8120-14910) 10710 (8400-14590) 0.6531

Neutrophils (cells x mm

) 9640 (6840-13320) 9920 (6620-13190) 9100 (7200-13340) 0.8527

Lymphocytes (cells x mm

) 750 (520-1130) 760 (540-1160) 710 (470-1030) 0.2554

NLR (Neutr-Lymph ratio) 12.85 (7.46-21.09) 13.11 (7.13-20.52) 12.36 (7.48-22.4) 0.6191

Neutrophils (%) 88 (82-91) 88 (81-91) 88 (83-92) 0.4382

Lymphocytes (%) 7 (4-11) 7 (4-11) 7 (4-11) 0.6428

Hemoglobin (g/dL) 15.5 (14.2-17) 15.55 (14.1-17) 15.45 (14.3-17.2) 0.8504

Hematocrit (%) 46 (42-50) 47 (42-51) 0.46 (42-50) 0.5625

Platelets (cells x mm

) 253500

(204250-331750)

271000

(206750-342500)

238500

(198500-312750)

0.0732

MPV (fL) 8.8 (8.3-9.6) 8.7 (8.3-9.55) 8.9 (8.3-9.63) 0.4118

Glucose (mg/dL) 134 (107-168) 133 (106-171.2) 137 (109-164.25) 0.6469

Creatinine (mg/dL) 0.87 (0.68-1.09) 0.86 (0.66-1.08) 0.89 (0.75-1.09) 0.3726

D Dímer (ng/mL) 1027.25 (653.28-1741.28) 1100.6 (653.4-1860.1) 972.5 (640.3-1672.1) 0.4093

Ferritin (ng/mL) 1087.2 (604.6-1639.7) 1026.7 (595.98-1649.75) 1111 (649.25-1543.55) 0.6414

LDH (UI/L) 855 (627-1045.75) 838 (627-1078) 864 (629-982) 0.5934

PCR (mg/dL) 15.39 (9.19-23.25) 16.42 (8.3-24.37) 14.67 (10.23-21.22) 0.7600

Mann-Whitney test.

360 Dawaher et al.

Investigación Clínica 64(3): 2023

Table 3

Relationship between associated infections and discharge condition.

Associated

Infections

Total

Discharge Condition

pSurvivor Non-Survivor

n (%) n (%) n (%)

VAP 132 (55) 80 (54,79) 52 (55,32) 0,936

CAUTI 105 (43,75) 68 (46,58) 37 (39,36) 0,272

CLBSI 75 (31,25) 38 (26,03) 37 (39,36) 0,030*

Colonization 37 (15,42) 27 (18,49) 10 (10,64) 0,100

SSTI 5 (2,08) 2 (1,37) 3 (3,19) 0,383

SSI 5 (2,08) 4 (2,74) 1 (1,06) 0,651

ENT 1 (0,42) 1 (0,68) 0 (0) 1,000

Bacteria

Total

Discharge Condition

pSurvivor Non-Survivor

n (%) n (%) n (%)

E. coli 32 (13.33) 21 (14.38) 11 (11.7) 0.698

E. coli ESBLs 24 (10) 17 (11.64) 7 (7.45) 0.290

Enterobacter cloacae complex 5 (2.08) 3 (2.05) 2 (2.13) 1.000

Enterococcus faecalis 9 (3.75) 5 (3.42) 4 (4.26) 0.740

K. oxytoca 5 (2.08) 3 (2.05) 2 (2.13) 1.000

K. oxytoca ESBLs 5 (2.08) 4 (2.74) 1 (1.06) 0.651

K. pneumoniae complex 14 (5.83) 10 (6.85) 4 (4.26) 0.403

K. pneumoniae complex ESBLs 43 (17.92) 22 (15.07) 21 (22.34) 0.152

K. pneumoniae complex KPC 58 (24.17) 40 (27.4) 18 (19.15) 0.145

Morganella morganii 6 (2.5) 3 (2.05) 3 (3.19) 0.681

Proteus mirabilis 5 (2.1) 2 (1.4) 3 (3.2) 0.383

Proteus mirabilis ESBLs 7 (2.92) 3 (2.05) 4 (4.26) 0.437

P. aeruginosa 19 (7.92) 11 (7.53) 8 (8.51) 0.784

P. aeruginosa CR 33 (13.75) 18 (12.33) 15 (15.96) 0.426

Serratia marcescens 9 (3.75) 9 (6.16) 0 (0) 0.013*

S. aureus complex 19 (7.92) 12 (8.22) 7 (7.45) 1.000

S. aureus complex MR 11 (4.58) 5 (3.42) 6 (6.38) 0.348

S. epidermidis 17 (7.08) 8 (5.48) 9 (9.57) 0.303

S. hominis MR 6 (2.5) 4 (2.74) 2 (2.13) 1.000

Streptococcus pneumoniae 5 (2.16) 4 (2.86) 1 (1.1) 0.651

*significant difference, Chi-square test or Fisher’s exact test. ESBLs: extended-spectrum beta-lactamase; KPC:

KPC-type carbapenemase; MR: methicillin-resistant; CR: carbapenemase-resistant.

Table 4

Relationship between the type of bacteria and discharge condition.

* significant difference, Chi-square test or Fisher’s exact test. VAP: ventilator-associated pneumonia; CAUTI: cathe-

ter-associated urinary infections; CLBSI: central line-associated bloodstream infection; SSTI: skin and soft tissue

infections; SSI: surgical site infection; ENT: ear, nose, and throat infections (otitis, retro tonsillar abscesses, etc.).

COVID-19 and bacterial superinfections: clinical and microbiological profiles 361

Vol. 64(3): 355 - 367, 2023

CLBSI infections were related to mor-

tality with a p of 0.028, whereas patients

with CLBSI infections were 1.94 times more

likely not to survive (Table 6).

Among the directed (targeted) antibi-

otic schemes, it was observed that Colistin +

others were related to mortality with a p =

0.028, where patients treated with these anti-

biotics presented a 12 times greater probabil-

ity of not surviving compared to those who

received aminopenicillins + others (Table 7).

The enzymatic resistance of these bac-

teria was studied. 40% of the K. pneumoniae

complex and E. coli isolates were ESBL pro-

ducers. In addition, one out of every five K.

pneumoniae complex isolates was a KPC pro-

ducer. The resistance observed to carbape-

nems by P. aeruginosa is very high: resistan-

ce to carbapenems was found in seven out of

ten isolates. S. aureus complex and S. epi-

dermidis showed 30 and 80% resistance to

methicillin, respectively (Table 8).

DISCUSSION

This study, conducted on 240 hospital-

ized patients with COVID-19 who presented

with bacterial superinfection, has shown

that older male patients with bacteremia

who received treatment with antibiotic regi-

mens containing colistin were associated

with lower survival.

Of these factors, age, bloodstream in-

fection, and colistin use were independent

factors for mortality when adjusted in a mul-

tivariate model. Furthermore, it was also ob-

served that VAP was the most frequent site

of superinfection; and that enzymatic resis-

tance due to ESBL and KPC-type serine beta-

lactamases was frequent in enterobacteria.

The most used empirical scheme was com-

posed of carbapenems, aminoglycosides, and

glycopeptides (meropenem, amikacin, and

vancomycin), and the presence of carbapen-

em-resistant P. aeruginosa was relevant.

Patients with severe COVID-19 admit-

ted to a hospital are at greater risk of de-

veloping infections during their hospital stay

8–11,

and this risk increases as their hospital

stay is prolonged

. This increased risk of

superinfection is due to greater exposure of

patients to immunosuppressive treatments

(especially steroids) and also for reasons

specific to health centers, of a structural

Table 5

Relationship between antibiotic scheme and discharge condition.

Antibiotic Scheme

Total

Discharge Condition

pSurvivor Non-survivor

n (%) n (%) n (%)

Empirical

Aminopenicillin + others 41 (17,83) 29 (20,57) 12 (13,48)

0,151

Colistin + others 28 (12,17) 21 (14,89) 7 (7,87)

Meropenem + vancomycin + Amikacin 129 (56,09) 73 (51,77) 56 (62,92)

Piperacillin/tazobactam + others 32 (13,91) 18 (12,77) 14 (15,73)

Directed

Aminopenicillin + others 13 (15,66) 12 (20,34) 1 (4,17)

0,036*

Colistin + others 20 (24,1) 10 (16,95)a 10 (41,67)b

Meropenem + vancomycin + Amikacin 32 (38,55) 22 (37,29) 10 (41,67)

Piperacillin/tazobactam + others 18 (21,69) 15 (25,42) 3 (12,5)

*significant difference; different superscripts indicate antibiotics that differ by discharge condition, Chi-square test.

362 Dawaher et al.

Investigación Clínica 64(3): 2023

type (opening of new ICU beds in other areas

of the hospital), organizational (hiring or

transferring personnel without prior train-

ing in the management of critical patients)

and functional (changes in patient care stan-

dards, and prolonged use of personal protec-

tive equipment). In addition, these patients

require vascular access, urinary devices, and

invasive mechanical ventilation due to their

condition, increasing the risk of infections.

These hospital infections are more complex

than usual because they are associated with

bacteria with resistance to antibiotics

The documented evidence demon-

strates that male patients with COVID-19

are at greater risk of presenting more severe

forms of COVID-19, with prolonged hospital-

izations and more extended use of invasive

devices, which increases the risk of super-

infection,

according to the findings of our

study. The mean age in the sample was 55

years, with age ranges between 50 and 60

years, similar to the data reported by other

authors

5,10,14

. In addition, this data was as-

sociated with higher mortality: the increase

in one year of age increases mortality risk by

3%, agreeing with what has been reported in

the literature

5,7,10

The average hospital stay was 24 days,

less in the non-survivor group, with a statis-

tically significant difference. As a possible

hypothesis, it is proposed that they were pa-

tients with more severe diseases that coursed

with more torpid and abrupt evolutions, con-

Table 6

Multivariate analysis for mortality based on age, CLBSI, and empirical antibiotic scheme.

Variables B p OR

OR (95% CI)

Lower Upper

AGE 0.03 0.006* 1.03** 1.01 1.06

CLBSI 0.66 0.028* 1.94** 1.07 3.49

Aminopenicillin + others (reference)

Colistin + others -0.15 0.797 0.86 0.28 2.68

Meropenem + Vancomycin + Amikacin 0.59 0.136 1.81 0.83 3.94

Piperacillin/tazobactam + others 0.55 0.278 1.74 0.64 4.71

Note: *significant variables, **factor associated with mortality, based on logistic regression: OR (95% CI): Odds

ratio (95% Confidence interval). CLBSI: central venous catheter-related bacteremia.

Table 7

Multivariate analysis for mortality based on a culture-directed antibiotic regimen.

Directed Scheme B p OR

OR (95% CI)

Li LS

Aminopenicillin + others (reference) 1.3

Colistin + others 2.48 0.028* 12** 0 110.52

Meropenem + Vancomycin + Amikacin 1.70 0.126 5.45 0.62 47.90

Piperacillin/tazobactam + others 0.88 0.472 2.40 0.22 26.12

Note: *significant variable, ** mortality associated factor, based on logistic regression. OR (95% CI): Odds ratio

(95% Confidence interval).

COVID-19 and bacterial superinfections: clinical and microbiological profiles 363

Vol. 64(3): 355 - 367, 2023

sistent with what has been reported by some

authors

10,12,15,16

The laboratory data (Table 2) show that

the two groups (survivors and deceased)

generally presented similar patterns of

acute inflammatory reaction, state of hyper-

inflammation, and hypercoagulability, with

no statistically significant differences. It is

suggested that both groups were patients

admitted with severe disease with systemic

involvement. From the point of view of the

severity of the condition caused by COV-

ID-19, they were similar groups.

VAP was the most common infection

reported in this investigation, representing

55% of infections. In other studies, it has

been reported that VAP represented between

40% and 60% of documented superinfections

in patients with COVID-19. The highest pre-

disposition to these processes has been asso-

ciated with prolonged ventilation, prone po-

sition, use of corticosteroids, lung damage,

and episodes of cross-contamination, most

likely due to the prolonged use of personal

protective equipment. In addition, the same

COVID-19 infection can cause inflammation

of the pulmonary vascular endothelium and

subsequent thrombosis, creating an environ-

ment conducive to bacterial growth

17–19

The incidence of CLBSI tripled during

the pandemic

. In this study, patients with

this type of infection were 1.94 times more

likely not to survive. Other authors have re-

ported higher mortality from CLBSI in pa-

tients with COVID-19 (between 40 and 54%)

than from this type of infection in pre-pan-

demic or non-COVID-19 patients (between

24 and 33%)

20–22

. This higher mortality may

be due to the use of these devices for a lon-

ger time, the prone position that limited the

care of the line, and the breach of asepsis

and antisepsis when manipulating the cath-

eter in the harsh conditions faced during the

health emergency, generating bacteremia

more frequently with a more significant in-

oculum.

K. pneumoniae complex was the most

frequently recovered bacterium in cultures,

followed by P. aeruginosa and E. coli. Gener-

ally, the reports in the literature vary widely

because of local microbiology. However, most

of the studies at a global and regional level,

carried out during the pandemic, agree with

this research, showing that these bacteria

are the most frequent

5,8,15-17,23

In our study series, a high percentage of

Enterobacterales were ESBL producers, and

one in five K. pneumoniae complex isolates

were KPC-type carbapenemase producers,

consistent with other reports in Latin Amer-

ica during the pandemic

. Most recovered

Pseudomonas cultures reported resistance

to carbapenems (70%). These findings are

worrying due to the impact on public health

and the limitation of the therapeutic arsenal

against such microorganisms, especially in

countries such as Ecuador

In non-randomized clinical studies, us-

ing colistin as monotherapy or combination

therapy has mixed results; however, it pres-

ents higher mortality in patients who previ-

Table 8

Isolated bacteria and enzymatic resistance.

Bacterial species Enzyme

production

Klebsiella pneumoniae

complex

ESBL/KPC 39.10%/

20.96%

Pseudomonas

aeruginosa

CR 70.42%

Escherichia coli ESBL 40.57%

Staphylococcus aureus

complex

MRSA 31.11%

Staphylococcus

epidermidis

MR 81.25%

Proteus mirabilis ESBL 68.75%

Enterobacter aerogenes AmpC 10.00%

Klebsiella oxytoca ESBL/ KPC 12.50%/

12.50%

Enterobacter cloacae

complex

ESBL 16.60%

ESBL: extended-spectrum beta-lactamase, KPC: KPC-

type carbapenemase, MR: methicillin-resistant, CR:

carbapenemase-resistant.

364 Dawaher et al.

Investigación Clínica 64(3): 2023

ously received carbapenems

26–28

. In the IDSA

guidelines, the use of colistin as targeted

therapy is discouraged, giving preference

to monotherapy with new antibiotics such

as ceftazidime-avibactam

. Patients who

received colistin (combined with other anti-

biotics) were associated with higher mortal-

ity in our series. We attributed this finding

to prior treatment with carbapenems and

subsequent resistance to them, the side ef-

fects of colistin and associated antibiotics,

and the fact that they presented a more se-

vere disease. Moreover, this higher mortality

could occur because colistin was indicated

as a desperate measure since there were no

better therapeutic options available in the

hospital or because its susceptibility to the

microorganism could not be confirmed since

the sensitivity cut-off points had not been es-

tablished with an antibiogram for the said

antibiotic, against certain bacteria and/or in

some tissues.

On the other hand, it should be consid-

ered that the hospital in this study is locat-

ed almost 3000 meters above sea level. Al-

though the effect of high altitude (≥1500m)

and its potential association with mortality

from COVID-19 is still controversial, there

are studies in this direction

30,31

; therefore,

more research is required in this regard and

its impact on the high mortality of severely

ill patients with bacterial superinfections.

This work has significant limitations. It

is monocentric and retrospective, with the

biases inherent in this design; furthermore,

there was no control group. There could

also be a possible underdiagnosis of fungal

infections, which were not reported in this

series and constitute a clinical challenge,

especially in the context of patients in-

fected with SARS-CoV-2. Finally, the health

center needed molecular biology studies to

determine resistance genes. Nevertheless,

in the case of the K. pneumoniae complex

isolates, in those cases where the automat-

ed system reported strains probably produc-

ing KPC, lateral flow tests were carried out,

and the strains were sent to the national

reference laboratory in Ecuador: Instituto

Nacional de Investigación en Salud Pública

“Dr. Leopoldo Izquieta Pérez” (INSPI). Mo-

lecular biology studies were performed at

the institution for confirmation, and the

hospital was notified.

In the present retrospective study, we

found that in patients with COVID-19 and

bacterial superinfection, age, central ve-

nous catheter-associated bacteremia, and

colistin use were independent predictors

of mortality. The most frequently isolated

microorganisms were ESBL- and KPC-pro-

ducing Enterobacterales and non-ferment-

ing Gram-negative bacilli resistant to car-

bapenems.

These findings are consistent with what

has been reported in world and regional se-

ries and emphasize the urgent need to estab-

lish programs for the rational use of antibi-

otics, especially in countries with a limited

therapeutic arsenal.

Funding

This work received funding from the

Pontificia Universidad Católica del Ecuador

(Dirección de Investigación, budget item

QINV0011-IINV533010100).

Conflict of interest

There is no conflict of interest.

ORCID number authors

• Jesús E. Dawaher Dawaher (JEDD):

0000-0002-2117-1656

• Rafael Salazar Montesdeoca (RSM):

0000-0003-1803-3372

• Santiago Aguayo-Moscoso (SXAM):

0000-0003-4919-5497

• Wendy C Bonilla Poma (WCBP):

0000-0002-8156-2253

• Jorge Luis Vélez-Páez (JLVP):

0000-0002-6956-4475

COVID-19 and bacterial superinfections: clinical and microbiological profiles 365

Vol. 64(3): 355 - 367, 2023

Contribution of the authors

JEDD: lead author, conception/design,

data collection and analysis, manuscript

preparation, and revision. RSM and WCBP:

data collection and analysis, literature re-

view. SAM data collection and analysis, pre-

paration, and manuscript revision. JLVP:

conception/design, statistical analysis, pre-

paration, and manuscript review. All authors

have read and approved submitting the final

manuscript to the journal.

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