Category Archives: C. diff. Research & Development

U.S. Burden of CDI and Outcomes – Trends in the US – Publication

Trends in U.S. Burden of Clostridioides difficile Infection and Outcomes

List of authors.
Alice Y. Guh, M.D., M.P.H., Yi Mu, Ph.D., Lisa G. Winston, M.D., Helen Johnston, M.P.H., Danyel Olson, M.S., M.P.H., Monica M. Farley, M.D., Lucy E. Wilson, M.D., Stacy M. Holzbauer, D.V.M., M.P.H., Erin C. Phipps, D.V.M., M.P.H., Ghinwa K. Dumyati, M.D., Zintars G. Beldavs, M.S., Marion A. Kainer, M.B., B.S., M.P.H., et al., for the Emerging Infections Program Clostridioides difficile Infection Working Group*

 

BACKGROUND

Efforts to prevent Clostridioides difficile infection continue to expand across the health care spectrum in the United States. Whether these efforts are reducing the national burden of C. difficile infection is unclear.

METHODS

The Emerging Infections Program identified cases of C. difficile infection (stool specimens positive for C. difficile in a person ≥1 year of age with no positive test in the previous 8 weeks) in 10 U.S. sites. We used case and census sampling weights to estimate the national burden of C. difficile infection, first recurrences, hospitalizations, and in-hospital deaths from 2011 through 2017. Healthcare-associated infections were defined as those with onset in a health care facility or associated with recent admission to a health care facility; all others were classified as community-associated infections. For trend analyses, we used weighted random-intercept models with a negative binomial distribution and logistic regression models to adjust for the higher sensitivity of nucleic acid amplification tests (NAATs) as compared with other test types.

RESULTS

The number of cases of C. difficile infection in the 10 U.S. sites was 15,461 in 2011 (10,177 healthcare-associated and 5284 community-associated cases) and 15,512 in 2017 (7973 healthcare-associated and 7539 community-associated cases). The estimated national burden of C. difficile infection was 476,400 cases (95% confidence interval [CI], 419,900 to 532,900) in 2011 and 462,100 cases (95% CI, 428,600 to 495,600) in 2017. With accounting for NAAT use, the adjusted estimate of the total burden of C. difficile infection decreased by 24% (95% CI, 6 to 36) from 2011 through 2017; the adjusted estimate of the national burden of healthcare-associated C. difficile infection decreased by 36% (95% CI, 24 to 54), whereas the adjusted estimate of the national burden of community-associated C. difficile infection was unchanged. The adjusted estimate of the burden of hospitalizations for C. difficile infection decreased by 24% (95% CI, 0 to 48), whereas the adjusted estimates of the burden of first recurrences and in-hospital deaths did not change significantly.

CONCLUSIONS

The estimated national burden of C. difficile infection and associated hospitalizations decreased from 2011 through 2017, owing to a decline in healthcare-associated infections. (Funded by the Centers for Disease Control and Prevention.)

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https://www.nejm.org/doi/10.1056/NEJMoa1910215

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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Study Finds the Impact of COVID-19 Prevention Reduce Healthcare-Associated (HA) C. difficile Infections (CDI) Incidence

Impact of COVID-19 prevention measures on risk of health care-associated Clostridium difficile infection

Highlights

  • Many strategies to reduce microorganism spread were adopted during the COVID-19 pandemic.
  • We have retrospectively analyzed the period of the pandemic and previous years.
  • Such strategies reduce healthcare-associated (HA)  C difficile infection (HA-CDI) incidence.
  • Maintaining these measures over time could reduce HA-CDI and related expenses.
  • •This study helps to understand effective hygiene interventions to prevent CDI.

Abstract

Clostridium difficile is the most common pathogen between healthcare-associated infections and its incidence has increased during the last years. lack of enough evidence about effective hygiene interventions to prevent this disease. Due to the coronavirus disease 2019 (COVID‑19) pandemic, several strategies to reduce microorganism spread were adopted in a hospital setting. The objective of this study was to establish whether such strategies can reduce healthcare-associated C difficile infection (HA-CDI) incidence. We found that during the pandemic (2020) HA-CDI incidence was significantly lower with respect to the previous years. This work demonstrates that maintaining this level of attention regarding control activities related to the prevention of microorganism transmission significantly reduces HA-CDI and related expenses in terms of health costs and human lives.
 

Background

Clostridium difficile (CD) is the most common pathogen among healthcare-associated (HA) infections.

,

An important obstacle in the prevention of C difficile infection (CDI) is the lack of enough evidence about effective hygiene interventions to prevent this disease. Although preventive contact precautions are recommended, there is no sufficient data on their effectiveness for its prevention.

,

Due to the coronavirus disease 2019 (COVID-19) pandemic, several strategies to reduce microorganism spread were adopted in a hospital setting.

The objective of this study was to establish whether such strategies can reduce HA-CDI incidence. The primary task was to identify differences in HA-CDI incidence in medical wards before and during the COVID-19 pandemic. The secondary task was to evaluate if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could influence the incidence of CDI.

Methods

We conducted a retrospective analysis on medical wards’ discharges (n. 1617) in S. Andrea Hospital (Rome) from March 1 to June 30, 2020, comparing data before (2017, 2018, and 2019) and during (2020) the COVID-19 pandemic. Intensive care units and paediatric wards were excluded. CDI diagnosis was confirmed by clinical suspicious (presence of diarrhea defined as ≥3 unformed stools in 24 hours) plus stool tests positive for CD. HA-CDI incidence was depicted as CDI diagnosed ≥72 hours after admission per 100 total discharges. Data was collected using Excel Office, and χ² test was performed to detect differences in HA-CDI incidence between different groups. Value of P< .05 was considered significant.

Results

The number of discharges and HA-CDI diagnosis for each medical ward is reported in Table 1. No statistically significant difference of HA-CDI incidence between the years 2017, 2018, and 2019 was observed. Conversely, during the pandemic (2020) HA-CDI incidence was significantly lower with respect to 2017 (odds ratio [OR] = 2.98; P = .002), 2018 (OR = 2.27; P = .023) and 2019 (OR = 2.07; P = .047) (see Table 1 and Fig. 1). Interestingly, during 2020, COVID-19 departments showed higher HA-CDI incidence respect to Covid-19 free wards (not significative). This data suggests SARS-Cov2 infection as a possible risk factor for CDI in agreement with recent evidences that report altered gut microbiota in COVID-19 patients.

Furthers studies are needed to confirm this hypothesis.

 

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resource:  https://www.ajicjournal.org/article/S0196-6553(20)30891-9/fulltext

A Team, Led by Travis J. Carlson, Department of Clinical Sciences, High Point University Fred Wilson School of Pharmacy, Define Kidney Injuries as a CDI Disease Severity Marker

Travis Carlson, PharmD

A recent update (Oct. 2020)  of the guidelines for Clostridioides difficile infections (CDI) might allow clinicians to accurately predict viral severity in kidney disease patients.

In 2017, the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) revised their C. diff infection severity classification criteria to include an absolute serum creatinine (SCr) value above the threshold of at least 1.5 mg/dL as opposed to a relative increase from baseline of at least 1.5 times the premorbid level.

A team, led by Travis J. Carlson, Department of Clinical Sciences, High Point University Fred Wilson School of Pharmacy, sought to best define kidney injuries as a CDI disease severity marker to make it easier to assess severe outcomes linked to CDI.

In the multicenter, cohort study, the investigators assessed adult hospitalized patients with a C. diff infection for the presence of an acute kidney injury (AKI), chronic kidney disease (CKD), and CDI severity using the 2010 and 2017 IDSA/SHEACDI guidelines.

The investigators sought primary outcomes of all-cause inpatient mortality.

In the final analysis, the investigators examined 770 C. diff infection episodes from a total of 705 patients aged 65±17 years (female, 54%; CKD, 36.5%; AKI, 29.6%).

In addition, 82 episodes (10.6%) showed discordant severity classification results because of the inclusion of more patients with preexisting chronic kidney disease in the severe disease category using an absolute SCr threshold criterion.

The absolute SCr criterion better correlated with all-cause mortality (OR, 4.04; 95% CI, 1.76-9.28; P = 0.001) than the relative increase in SCr (OR, 1.34; 95% CI, 0.62-2.89; = 0.46).

The investigators found this corresponded with an increased likelihood of the 2017 CDI severity classification criteria to predict mortality (OR, 5.33; 95% CI, 1.81-15.72; = 0.002) compared to the 2010 criteria ( OR, 2.71; 95% CI, 1.16-6.32; = 0.02).

“Our findings support the 2017 IDSA/SHEA CDI severity classification criteria of a single pre-treatment SCr in future CDI guideline updates,” the authors wrote.

New data shows positive trends regarding C. diff infections and hospitalization within the last 10 years.

A team, led by Alice Y. Guh, MPH, identified cases of C. diff infections in stool specimens positive for C. diff in an individual at least 1-year-old with no positive test in the previous 8 weeks in 10 US sites.

Overall, they identified 15,461 cases in 2011—10,177 healthcare-associated cases and 5284 community-associated cases. In 2017, they identified 15,512 cases—7973 healthcare-associated cases and 7539 community-associated cases.

The estimated national burden of infections was 476,400 (95% CI, 419,900-532,900) in 2011 and 462,100 cases (95% CI, 428,600-495,600) in 2017.

After accounting for NAAT use, the adjusted estimate of the total burden of C. diff infection decreased by 24% from 2011 through 2017 (95% CI, 6-36).

The study, “Assessment of Kidney Injury as a Severity Criteria for Clostridioides difficile Infection,” was published online in Open Forum Infectious Diseases

Study Finds C. difficile (CDI) Has the Potential Role of Transmission In Home Environment

 

 

 

 

Findings from a study by researchers from the University of Iowa highlights the potential role of the home environment in Clostridioides difficile transmission.

Using data from a commercial insurance claims database, the researchers found that the incidence of C difficile infection (CDI) among individuals living with a family member who had CDI was more than 12 times greater than the incidence in those without prior family exposure. The incidence rate was even higher in certain groups less likely to have other risk-increasing exposures.

The results of the study appeared Jun 26 in JAMA Open Network.

While the level of absolute CDI risk attributable to the household transmission was extremely low, the authors of the study say the findings may have practical implications for preventing the spread of CDI in households.

CDI can be spread in the community

C. difficile infection (CDI)  is a common, typically hospital-acquired infection that is mainly associated with antibiotic use and healthcare settings. While antibiotics create the conditions that allow for C difficile to flourish in the gut and cause infection, spores shed by infected patients (through fecal matter) and can be spread by healthcare workers and are frequently found on *bed rails, in the patient bathrooms, and other parts of the hospital environment.

(*High touch areas can be easily contaminated with Clostridioides difficile (C. difficile, C. diff.) spores) cdf note.

Those spores are often difficult to eliminate because they are resistant to many cleaning agents.

In 2017, according to the most recent data from the Centers for Disease Control and Prevention, there were an estimated 223,900 CDI cases in hospitalized patients.

But not all CDI cases start in hospitals. Some studies have found that CDI can be transmitted outside of healthcare settings, with persistent contamination of the household environment occurring in patients with documented infection. Others have found household pets colonized with the bacterium.

To better understand the potential role of household C difficile transmission, the University of Iowa researchers used a large population-based, commercial insurance claims data set to examine whether family members of CDI patients had a greater risk of acquiring the infection. Limiting the analysis to households with two or more family member enrolled in the same insurance plan for an entire month, they grouped individuals into four categories based on CDI status and family exposure to CDI: (1) CDI and prior family exposure, (2) no CDI and prior family exposure, (3) CDI and no family exposure, and (4) no CDI and no family exposure.

The primary outcome of the case-control study was the incidence of CDI in a given monthly enrollment stratum. Aside from exposure to CDI diagnosed in a family member, other CDI exposure risks were considered, including prior hospitalization, age, and antibiotic use. The researchers also conducted a separate analysis for CDI diagnosed in hospital or outpatient settings.

Higher risk from family exposure

Analysis of data covering 2001 through 2017 found that 224,818 CDI cases, representing 194,424 enrollees, occurred in families with at least two enrollees. Of these, 1,074 CDI cases (0.48%) occurred following a diagnosis in a separate family member, representing possible transmission. In general, the index cases of CDI tended to occur in older enrollees (ages 45 to 64 years), while the CDI cases that represented potential transmission events occurred in children.

A comparison of the incidence rate ratio (IRR) between individuals with and without family exposure showed that prior family exposure was significantly associated with an increased incidence of CDI (IRR, 12.47; 95% confidence interval [CI], 8.86 to 16.97) even after controlling for other risk factors. This was the second-highest IRR behind hospital exposure (IRR, 16.18; 95% CI, 15.31 to 17.10).

Increased CDI incidence was also associated with age (IRR, 9.90; 95% CI, 8.93 to 10.98 for people over age 65 compared with those aged 0 to 17) and antibiotic use (IRR, 7.78; 95% CI, 7.33 to 8.25 for people on high-CDI-risk antibiotics compared with no antibiotics).

When the researchers looked at subgroups of CDI cases less likely to be attributed to hospital exposure, they found that the IRR associated with family exposure was even higher—16.00 (95% CI, 11.72 to 21.22) for community-onset CDI and 21.74 (95% CI, 15.12 to 30.01) for community-onset CDI without prior hospitalization.

“For individuals with family exposure, the risk for being diagnosed with CDI remained consistent after controlling for CDI risk factors and different model specifications,” the authors wrote. “Together, these results suggest that individuals with family exposure may be at greater risk for acquiring CDI than those without exposure and highlight the importance of the shared environment in the transmission and acquisition of C difficile.”

The authors note that because they were not able to conduct whole-genome sequencing, they cannot confirm whether CDI cases within families represent identical strains. They also said the study is limited by the reliance on insurance claims data, which do not provide all the details necessary to determine attributable risk.

Despite the low absolute risk of acquiring CDI from a family member, the authors suggested that cleaning shared bathrooms with effective cleaning agents could be a practical way to minimize transmission risk.

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https://www.cidrap.umn.edu/news-perspective/2020/06/study-suggests-household-exposure-may-increase-c-difficile-risk