Study Shows the Burden of CDI During the COVID-19 Pandemic: A Retrospective Case-Control Study in Italian Hospitals (CloVid)

Clovid

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Article
The Burden of Clostridioides Difficile Infection
during the COVID-19 Pandemic: A Retrospective
Case-Control Study in Italian Hospitals (CloVid)

Guido Granata 1,* , Alessandro Bartoloni 2, , Mauro Codeluppi 3, , Ilaria Contadini 4, Francesco Criistini 4, , Massimo Fantoni 5, , Alice Ferraresi 6, , Chiara Fornabaio 6, , Sara Grasselli 3,
Filippo Lagi 2, , Luca Masucci 5,, Massimo Puoti 7, , Alessandro Raimondi 7, , Eleonora Taddei 8
,Filippo Fabio Trapani 9, , Pierluigi Viale 9, , Stuart Johnson 10, Nicola Petrosillo 1, and on behalf of the CloVid Study Group †

1 Clinical and Research Department for Infectious Diseases, Severe and Immunedepression-Associated
Infections Unit, National Institute for Infectious Diseases L. Spallanzani IRCCS, 00149 Rome, Italy;  nicola.petrosillo@inmi.it
2 Department of Infectious Diseases, Careggi Hospital, University of Florence, 50121 Florence, Italy;alessandro.bartoloni@unifi.it (A.B.); filippo.lagi@unifi.it (F.L.)
3Infectious Diseases Unit, Guglielmo da Saliceto Hospital, 29121 Piacenza, Italy;
m.codeluppi@ausl.pc.it (M.C.); s.grasselli@ausl.pc.it (S.G.)
4Infectious Diseases Unit, Rimini-Forlì-Cesena Hospitals, 48121 Rimini, Italy;
ilaria.contadini@auslromagna.it (I.C.); francesco.cristini@auslromagna.it (F.C.)
5 Dipartimento di Scienze di Laboratorio e Infettivologiche —Fondazione Policlinico A. Gemelli IRCCS,Via della Pineta Sacchetti, 00168 Rome, Italy; massimo.fantoni@policlinicogemelli.it (M.F.);
luca.masucci@policlinicogemelli.it (L.M.)
6Infectious Diseases Unit, ASST Cremona, 26100 Cremona, Italy; alice.ferraresi@asst-cremona.it (A.F.);c.fornabaio@asst-cremona.it (C.F.)
7Infectious Diseases Unit, ASST Grande Ospedale Metropolitano Niguarda, 20162 Milan, Italy;
massimo.puoti@ospedaleniguarda.it (M.P.); alessandro.raimondi@ospedaleniguarda.it (A.R.)
8 Dipartimento di Sicurezza e Bioetica—Sezione di Malattie Infettive—Fondazione Policlinico A.
Gemelli IRCCS, Via della Pineta Sacchetti, 00168 Rome, Italy; eleonora.taddei@policlinicogemelli.it
9 Department of Medical and Surgical Sciences, Infectious Diseases Unit,
Alma Mater Studiorum–University of Bologna, 40126 Bologna, Italy; filippofabio.trapani@aosp.bo.it (F.F.T.);
pierluigi.viale@unibo.it (P.V.)
10 Research Service, Hines VA Hospital and Infectious Disease Section, Loyola University Medical Center,
Maywood, IL 60153, USA; stuart.johnson2@va.gov
* Correspondence: guido.granata@inmi.it; Tel.: +39-065-517-0241
† CloVid (Clostridioides difficile infection during the COVID-19) Study Group.
Received: 28 October 2020; Accepted: 25 November 2020; Published: 27 November 2020

Abstract: Data on the burden of Clostridioides difficile infection (CDI) in Coronavirus Disease
2019 (COVID-19) patients are scant. We conducted an observational, retrospective, multicenter,
1:3 case (COVID-19 patients with CDI)-control (COVID-19 patients without CDI) study in Italy
to assess incidence and outcomes, and to identify risk factors for CDI in COVID-19 patients.
From February through July 2020, 8402 COVID-19 patients were admitted to eight Italian hospitals;

38 CDI cases were identified, including 32 hospital-onset-CDI (HO-CDI) and 6 community-onset,
healthcare-associated-CDI (CO-HCA-CDI). HO-CDI incidence was 4.4 × 10,000 patient-days.
The percentage of cases recovering without complications at discharge (i.e., pressure ulcers, chronic heart decompensation) was lower than among controls (p = 0.01); in-hospital stays were longer among cases, 35.0 versus 19.4 days (p = 0.0007). The presence of a previous hospitalization (p = 0.001), previous
steroid administration (p = 0.008) and the administration of antibiotics during the stay (p = 0.004) were risk factors associated with CDI. In conclusions, CDI complicates COVID-19, mainly in patients with J. Clin. Med. 2020, 9, 3855; doi:10.3390/jcm9123855 http://www.mdpi.com/journal/jcm J. Clin. Med. 2020, 9, 3855 2 of 11 co-morbidities and previous healthcare exposures. Its association with antibiotic usage and hospital-acquired bacterial infections should lead to strengthen antimicrobial stewardship programmes and infection prevention and control activities

1. Introduction
Since 31 December 2019, when the World Health Organization (WHO) was informed of an
outbreak of a respiratory disease affecting the city of Wuhan, the world has been shaken by the
most profound health crisis of the last several decades [1,2]. Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly worldwide with the consequence of causing a serious health threat to humans on every continent.  At present, more than thirty million people are known to have been infected, which has placed a great burden on health care systems and heightened anxiety and psychological stress of medical staff [3].

The lack of high-level evidence, inherent to the novelty and rapid spread of COVID-19, has led to
the adoption of heterogeneous therapeutic management approaches, often without a clear distinction between evidence-based data and expert opinion in informing treatment choices. The high number shortage of beds, especially in critical areas, and the need for healthcare worker protection have challenged compliance with infection control and antibiotic stewardship programs in most health-care facilities facing this emergent threat of COVID-19 [4]. During the pandemic many health-care facilities gave priority to the protection of their healthcare workers from COVID-19, reducing attention to the prevention of other bacterial infections transmitted by interpersonal contact. Moreover, most of the early recommendations for the management of COVID-19 patients considered the use of empirical antibiotic treatment, resulting in large usage of antimicrobials in COVID-19 patients. Up to 94% of COVID-19 patients have been reported to receive empirical antibiotic therapy during their hospital stay [4–9]. Bacterial superinfections have been described in the course of COVID-19 disease
and early reports of Clostridioides difficile infection (CDI) co-infection have been published [10,11]. CDI is commonly associated with the use of broad-spectrum antibiotics, absence of antimicrobial stewardship, inadequate infection control, and hospital overcrowding [12]. Currently, we do not have a clear picture of the burden of CDI in COVID-19 patients and there is a lack of data on the prevalence and clinical manifestations of CDI in COVID-19 patients.
The aim of this study was to assess the incidence of CDI in hospitalized COVID-19 patients,
to describe the clinical characteristics and outcomes of COVID-19 patients with CDI and to identify risk factors for the onset of CDI in COVID-19 patients.

2. Materials and Methods
We conducted an observational, retrospective, national multicenter, case-control study with 1:3
matching to assess the incidence, clinical characteristics, and outcomes of COVID-19 patients with CDI. In addition, we evaluated risk factors associated with the occurrence of CDI in COVID-19 patients. The study was performed in 8 acute-care Italian hospitals admitting COVID-19 patients, between February 2020 and July 2020 (Figure 1 and Table S1). All the hospitals have an Infectious Disease Unit. The study was approved by the Ethics Committees of the participant hospitals.J. Clin. Med. 2020, 9, 3855 3 of 11 J. Clin. Med. 2020, 9, x FOR PEER REVIEW 3 of 11

Figure 1. Geographical distribution of participating centers. The detailed list of the eight participating centers is available as supplementary material (Table S1).
2.1. Study Design Hospitalized adult (>18 years old) patients with COVID-19 and CDI were identified from the databases of the participant centers. Cases were defined as COVID-19 patients with CDI; controls were COVID-19 patients without CDI. Cases were matched 1:3 with controls. Demographic, epidemiological, and clinical data (COVID-19 onset and clinical characteristics, medications given for COVID-19, antimicrobial treatments before and after the diagnosis of COVID-19, laboratory data, CDI onset and characteristic, and patient’s outcome) were collected in clinical record forms (CRF)

(Table S2).
Controls were matched to cases according to the following criteria:
1. Same gender
2. Hospitalization in the same hospital and in the same unit
3. Same date of hospital admission ± 7 days
4. Same age ± 3 years
All cases and controls were followed up to 30 days from their hospital discharge to assess for
new onset of diarrhea, recurrence of CDI, and mortality at 30 days from the hospital discharge.
The definitions of CDI, microbiological evidence of C. difficile, CDI recurrence, mild CDI, severe
CDI and complicated CDI and the definitions of the clinical syndromes associated with COVID-19
adopted in the study are described in Table S3.

2.2. Data Analysis
The incidence of CDI among all COVID-19 patients admitted to the participating hospitals was
calculated using as the numerator the number of CDI cases and as the denominator the number of days of hospitalization of the COVID-19 patients (× 10,000). The characteristics of the study population and Figure 1. Geographical distribution of participating centers. The detailed list of the eight participating centers is available as supplementary material (Table S1).

2.1. Study Design
Hospitalized adult (>18 years old) patients with COVID-19 and CDI were identified from the
databases of the participant centers. Cases were defined as COVID-19 patients with CDI; controls were COVID-19 patients without CDI. Cases were matched 1:3 with controls. Demographic, epidemiological, and clinical data (COVID-19 onset and clinical characteristics, medications given for COVID-19, antimicrobial treatments before and after the diagnosis of COVID-19, laboratory data, CDI onset and characteristic, and patient’s outcome) were collected in clinical record forms (CRF) (Table S2).

Controls were matched to cases according to the following criteria:
1. Same gender
2. Hospitalization in the same hospital and in the same unit
3. Same date of hospital admission ±7 days
4. Same age ±3 years
All cases and controls were followed up to 30 days from their hospital discharge to assess for new onset of diarrhea, recurrence of CDI, and mortality at 30 days from the hospital discharge.
The definitions of CDI, microbiological evidence of C. difficile, CDI recurrence, mild CDI, severe
CDI and complicated CDI and the definitions of the clinical syndromes associated with COVID-19
adopted in the study are described in Table S3.

2.2. Data Analysis
The incidence of CDI among all COVID-19 patients admitted to the participating hospitals was
calculated using as the numerator the number of CDI cases and as the denominator the number of days of hospitalization of the COVID-19 patients (× 10,000). The characteristics of the study population and the patient outcome were evaluated by means of descriptive statistics. The potential correlations J. Clin. Med. 2020, 9, 3855 4 of 11
between CDI and clinical variables of COVID-19 (infection onset, severity) and laboratory findings were analyzed by univariate and multivariate analysis. To identify risk factors for onset of CDI in COVID-19 patients and any determinants of delayed diagnosis of CDI, the characteristics of the CDI group were compared to the control group by means of univariate and multivariate analysis.

2.3. Statistical Analysis
Quantitative variables were tested for normal distribution and compared by means of a paired
t-test. Qualitative differences between groups were assessed by use of Fisher’s exact test. The precision of odd ratio (OR) was determined by calculating a 95% confidence interval (CI). A p value less than 0.05 was considered statistically significant. Variables from the univariate analysis were considered for inclusion in multivariate logistic regression analysis if p-value was less than 0.05. Backward stepwise logistic regression was performed, and the model that was considered biologically plausible and had the lowest −2 log-likelihood ratio was chosen as the final model. Statistical analysis was performed using the software program IBM SPSS version 24.

3. Results
3.1. CDI Incidence among COVID-19 Patients
Overall, during the study period, a total of 40,315 patients were admitted to the eight participant hospitals; of these, 8402 were COVID-19 patients. The mean hospital stay for COVID-19 patients was 13.8 days (range 1–59 days). Thirty-eight CDI cases were identified, including 32 hospital-onset CDI (HO-CDI) and 6 community-onset, healthcare-associated CDI (CO-HCA-CDI) cases. Therefore, during the study period, 32 COVID-19 patients developed HO-CDI, corresponding to an HO-CDI prevalence of 0.38%, and an HO-CDI incidence of 4.4 × 10,000 patient days ranging in the hospitals from 0.7 to 12.3 × 10,000 patient days (Table S4).
3.2. Clinical Features of Clostridioides Difficile Infection in COVID-19 Patients
The demographic and epidemiological data, the comorbidities, the clinical characteristics, and
the outcome of the 38 COVID-19 patients with CDI and of the 114 controls included in the study are described in Table 1. The mean laboratory findings at the admission of the 38 COVID-19 patients with CDI and of the 114 controls are shown in Table 2. The CDI characteristics, severity, management, and follow-up of the 38 COVID-19 patients with CDI included in the study are shown in Table 3.

Table 1. Demographic and epidemiological data, comorbidities, clinical characteristics of the Coronavirus Disease 2019 (COVID-19), and outcome of the 38 COVID-19 patients with CDI and of the 114 COVID-19 controls included in the study. CCI: Charlson Co-morbidity Index. LTHCF: long-term health care facility. ARDS: Acute Respiratory Distress Syndrome. LMWH: Low Molecular Weight

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