Tag Archives: C. diff. news

Pharmacy OneSource Discusses Artificial Intelligence With Three Wolters Kluwer Experts Developing AI Tools Managing CDIs

Hospitals around the world continue to struggle with preventing and managing Clostridioides difficile (C. diff) infections. They are seeking better ways to predict which patients are at risk for C. diff infections (CDIs) sooner, and to improve prevention and treatment. 

 We ( Pharmacy One Source) sat down with three Wolters Kluwer experts—who have been working on developing, testing and integrating artificial intelligence (AI) tools into Sentri7—to discuss why AI is such an important advance for managing CDIs.  

  • Matt Weissenbach, DrPH, CPH, CIC, is the Director of Clinical Operations, Clinical Surveillance  
  • Steve Mok, PharmD, BCPS, BCIDP, is the Pharmacy Clinical Program Manager and Fellowship Director, Clinical Surveillance 
  • John Langton, PhD, is the Director of Applied Data Science, Wolters Kluwer, Health 

What’s at risk when hospitals do not give their full attention to reducing C. diff infections? 

Matt: C. diff is an opportunistic infection, often healthcare-associated, that is debilitating for patients because it can cause symptoms that range from diarrhea to life-threatening inflammation of the colon. It’s a very hardy bacterium that is spore-forming and is very difficult to remove from the environment, dramatically increasing the risk of transmission.

C. diff is also somewhat difficult to treat because it tends to recur over time. And as hospitals know all too well, patients that do become infected experience sub-optimal outcomes. In the U.S. alone, there are about a half-million C. diff infections each year, responsible for about 29,000 deaths. To make things worse, C. diff infection increases the length of stay and treatment costs. In fact, the CDC estimates that C. diff is responsible for $4.8 billion in costs each year. Financial penalties are also in play because C. diff is monitored within hospital pay-for-performance programs. Those organizations that are not proactively focusing on preventing C. diff will typically find themselves among the poorest performers, and their bottom lines will suffer due to penalties. That’s why so much work goes into controlling and preventing CDIs.

Steve: From a pharmacy and antimicrobial stewardship perspectiveC. diff is concerning because treatment options are limited to three antibiotics, and here is also the high risk of recurrence that Matt referencedEven if we successfully treat the infection, the C. diff bacteria hangs around in the gut or the patient’s surroundings, waiting for the next flora disturbance, and we have to go back to the same three antibiotics. In the past 6-8 years, some people have gotten so desperate to address recurring infections that they’ve opted for a fecal microbiota transplantationThat has shown some promise, but the treatment is not without risk, especially for acquiring other types of infections.  

Why did Wolters Kluwer choose AI technology to address this challenge?  

Matt: We saw an opportunity to leverage AI, identify at-risk patients sooner, and allow clinicians the opportunity to address modifiable risk factors and proactively prevent C. diff infection using known, evidence-based prevention strategies. We know our hospital and health system clients are incredibly concerned with how C. diff tends to increase mortality risk, length of stay, and introduce potential for financial penalties and pressures. Our customers already rely on Sentri7 as a trusted clinical surveillance platform, and this enabled us to provide extended value across members of the care team while addressing this worrisome infection.

What are some of the identifiers of those highrisk patients? 

Steve: Well, there’s a consensus, for example, that some antibiotics, like fluoroquinolones, predispose patients to C. diff infections. If we identify those patients, the physician and pharmacist can assess whether they need that particular antibiotic and then change it, if possible, to lower-risk antibiotics. Another example is the proton pump inhibitor. It is also highly associated with C. diff infection. Again here, with more information, pharmacists can have a meaningful conversation with prescribers to do a better-informed risk-benefit analysis. We see AI as an opportunity to introduce many other risk factors and dimensions to the risk-benefit analysis so providers can make more informed clinical decisions.

John: I agree that the clinical concerns were the most important drivers behind our effort, and I would add, from that perspective, that early identification also enables you to isolate patients more promptly. We’ve statistically shown that when CDI happens in a hospital, it typically occurs in clusters. That is, as soon as the first patient contracts a C. diff infection, usually a number of other people in the same hospital area contract it as well. So if you can detect C. diff earlier, or even predict, you can not only begin treatment, but you can also isolate patients to try to prevent the spread and implement other necessary protocols. With early action, you can keep the infection to one person rather than five.  

Matt: Clinical policies and protocols for environmental cleaning recognize that routine disinfectants are often not sporicidal. If the bacteria are on a bedrail, glove, telephone, etc., it may be transmitted to other patients or providers and may contribute to the clustering effect. At a high level, I view AI-enabled technologies for C. diff—and, ultimately, for other HAIs—as a way to bridge the prevention aspects of public health with the diagnosis and treatment components of clinical medicine. With CDI, we aim to address things earlier in the care process by looking upstream at hospitalized patients to determine if they’re at risk of developing CDI. Then, clinicians may reassess their choices of antimicrobial therapy or other medications that could increase that risk. That’s what I mean by bringing the prevention aspect to clinical medicine. We can create proactive workflows that target the prevention of adverse events.

How does our AI model help this process of identifying patients and instigating proactive prevention? 

John: The simplest way to put it is that AI deals with more than the binary risk indicators assessment that humans commonly perform in their heads. The reality is that we can only look at a small set of variables and how they might factor with the other. Thus, systems that merely assess binary risk indicators are brittle because they are so limited in terms of the complexity of situations they can address. In contrast, the power of AI is its ability to consider many different interaction effects. Working with our clinicians, we incorporate a tremendous number of inputs: lab results, white blood cell count, bilirubin, neutrophils, vital signs, medicine administration, concentrations and durations of meds, duration in hospital, demographics about the patients and demographics on a hospital—to name a few. The AI model can look at hundreds of these things – and the hundreds of correlations among them. To give just one simple example: We know older people are more at risk, and if they are on a particular broad-spectrum antibiotic, there can be a multiplicative effect – that is, the effect is greater than simply adding each of the factors independently. Now expand that to looking at hundreds of things. We’ve trained all of the statistics and variables and have shown that we can be incredibly precise. When you compare them head-to-head, machine learning and AI crush current risk assessment systems.

But given the complexity you’re describing, how can clinicians feel comfortable that this tool is delivering reliable decision support? 

John: A few different things should ease those concerns. First, working with bedside providers in a clinical setting, we’ve shown we can identify a higher percentage of C. diff cases, predict them significantly sooner, and therefore, empower clinicians to respond both more quickly and more effectively.

In addition, one of the features of this model is that it provides a visual picture of its output that explains why it made the predictions it did: what features it identified as most important and why they put the patient at greater risk. For example, it might note it is predicting a CDI in a hospitalized older adult who has a high white blood cell count and fever lasting two days. This information allows physicians to examine the output and decide if the logic makes sense. If there are other considerations rooted in the provider’s clinical experience, he or she can always disregard the tool’s assessments and recommendations.

Finally, and maybe most importantly, there is the time component—the ability to track when all of these factors occur and understand how they figure into the various interaction effects. Time is complicated. Many algorithms become popular because they are easy to use and deploy, in part because they treat each feature independently and don’t perceive an order between input features. But the order of things matters. Knowing when there was an increase or decrease in the white blood cell count, for example, is critical to making accurate predictions.

Other AI tools are emerging. How is this tool different?  

Steve: Well, the time element is pretty rare, if not unique, and it is essential for accuracy. Then there’s the data. The power and reliability of AI tools depend on having the right data and lots of it. A recent survey commissioned by Wolters Kluwer—Mending Healthcare in America 2020—found that nearly 90 percent of hospital executives feel they need more comprehensive patient data to deliver better care, and attribute incorrect or poor quality data as a cause of increased costs. Clinical data is a strength of Wolters Kluwer, as is our ability to integrate a tool like this into an established clinical surveillance solution like Sentri7—one that has a familiar workflow for users. Sentri7 monitors over 500,000 patients at any given time, as well as processing 4 billion lab orders and 677 million drug orders each year. That amount of information dramatically increases the predictive power of the tool.

John: My team at Wolters Kluwer employs rigorous data science approaches, including cross-validation, in which we hold out some data, so that we can do multiple evaluations of the holdout data versus the AI-trained data. We have also completed extensive analysis to understand how different demographic factors, such as age, contribute to predictions to control for bias.  Last of all, and maybe the most important difference, is the way we have always combined data science expertise and clinical expertise at Wolters Kluwer. While building the model, clinicians strongly influenced the feature engineeringthat is the way we determined how to transpose raw data from the electronic medical record in a way that gives the AI algorithm traction to learn from the data and statistics. Clinical expertise is critical both at that point and, of course, in the validation process.  

Steve: Another difference is that the tool offers evidence-based, customizable recommendations on how to treat these high-risk patients. This customizable risk score threshold enables each facility to decide at which point they want to act. We always give our hospital partners the control to fine-tune the alerts for their specific settings.

Any final thoughts? 

Matt: I would reiterate that having this on a trusted clinical surveillance platform already embraced and used by hundreds of hospitals and health systems extends the value of that solution to clinical teams that are hungry for a more progressive and forward-thinking approach to their problems. C. diff is a prime example of that. What I find especially exciting is that we provide transparency to clinicians and hospitals in terms of their patients’ risk and empower them to consider the next steps that are relevant to their circumstances. For example, hospitals can implement a pre-authorization protocol for a certain class of antimicrobials or protocols that avoid inappropriate CDI testing in combination with laxative use, a combination that can artificially inflate CDI rates. Lastly, it’s not a black-box approach, and that’s very, very important for making sure clinicians feel that they can embrace this, interpret it, and use it to its fullest potential within the confines of their facility.

To read the article in its entirety please click on the following link.  Thank You.




Recent Emergence of C.difficile Infection in Romanian Hospitals – Abstract

Recent Emergence of Clostridium Difficile Infection in Romanian Hospitals is Associated With a High Prevalence of Polymerase Chain Reaction Ribotype 027.



To evaluate the epidemiology of Clostridium difficile infection in several Romanian hospitals.


A survey was conducted from November 2013 to February 2014 in 9 hospitals selected from different Romanian regions.


The survey identified 393 patients with C. difficile infection. The median age was 67 years (range: 2-94 years) with 56% of patients older than 65 years. The mean C. difficile infection prevalence was 5.2 per 10.000 patient-days, with the highest prevalence, 24.9 and 20 per 10.000 patients-days, reported in a gastroenterology and an infectious diseases hospital, respectively. The origin of C. difficile infection was health care-associated for 70.5% of the patients, community-acquired for 10.2% of patients and indeterminate for other 19.3%. Severe C. difficile infection was registred in 12.3% cases and in hospital all-cause mortality was 8.8%. Polymerase chain reaction-ribotype 027 was the most prevalent in all participating hospitals, and represented 82.6% of the total ribotyped isolates. Moxifloxacin minimal inhibitory concentrations were higher than 4 μg/mL for 59 of 80 tested isolates (73.8%). Fifty-four of these 59 isolates were highly resistant to moxifloxacin, (minimal inhibitory concentration ≥32 μg/mL) and belonged more frequently to polymerase chain reaction-ribotype 027 (p<0.0001).


The present study is the first multicentre study performed in Romania and shows that the ribotype 027 is largely predominant in C. difficile infection cases in Romania. The prevalence of C. difficile infection in some specialized hospitals is higher than the European mean prevalence and demonstrates the need of strict adherence to infection control programmes.



Seres Therapeutics Focused On Developing Drugs To Treat Diseases Of The Microbiome With First Clinical Program ECOSPOR Research Study In The Treatment Of C. diff. Infection (CDI) And Now Open For Enrollment

Seres Therapeutics is a clinical-stage therapeutics company focused on discovering and developing drugs to treat diseases of the microbiome. The biology of the microbiome is driven by ecologies—the functional collections of various organisms—which are central to health and disease.

Seres is developing Ecobiotic® therapeutics to treat diseases that have an underlying microbiome biology. Seres Therapeutic’s first clinical program, The ECOSPOR Research study is in the treatment of Clostridium difficile  infection (CDI).
About The ECOSPOR Research Study

Although antibiotics are used to treat recurrent C. difficile infection, most of the time they do not cure C. difficile. In addition, antibiotics continue to wipe out the good bacteria that protect you against C. difficile. Currently, there are no medications available that can prevent this infection from coming back when your gut is defenseless.

SER-109 is an investigational medicine being developed to prevent recurrent C. difficile from coming back again. The idea is to first treat patients with antibiotics that work against C. difficile so that the diarrhea goes away. Then patients may get SER-109 to keep the C. difficile infection from coming back.

In the ECOSPOR study, doctors will compare SER-109 to a placebo pill, which looks like SER-109. However, the placebo pill will have no medication inside it. Patients will be randomly assigned to receive either SER-109 or placebo. The study is designed to provide more information about the potential safety and effectiveness of SER-109, and will last about 7 months. The results will help doctors and researchers learn whether SER-109 could one day be used to prevent recurrent CDI.

The ECOSPOR Study is now open for enrollment. If you would like more information the study is posted on ClinicalTrials.gov.

You can all contact clinicalstudies@sereshealth.com or by calling  1-617-945-9626  (USA) to find a doctor near you who is involved in the study.



*Please note – The C Diff Foundation does not endorse this product or any product and this posting is strictly for informational purposes only.

ROCHE cobas® C. diff. Test approved by US Food and Drug Administration (FDA)

US Food and Drug Administration (FDA) has provided 510(k) clearance for the cobas® Cdiff Test to detect Clostridium difficile (C. difficile) in stool specimens.

The cobas® Cdiff Test targets the toxin B gene found in toxigenic C. difficile strains directly in specimens from symptomatic patients. The test provides accurate information which assists clinicians in making timely treatment decisions and aids in the prevention of further infection in healthcare settings.

“Having the ability to provide a result quickly is important when supporting infection control for Clostridium difficile,” said Dr. Steve Young, Professor of Pathology, Department of Pathology UNMHSC and Tricore Reference Lab. “The cobas® 4800 System has the capability to allow for mixed batch testing of the cobas® Cdiff Test alongside testing for Methicillin-resistant Staphylococcus aureus, Staphylococcus aureus, and herpes simplex virus 1 and 2*, all on one platform. We can run these assays together at least once in each shift rather than once a day, which can greatly improve laboratory efficiency, ultimately leading to better infection control and patient care.”

In a clinical trial program conducted at sites throughout the United States, the cobas® Cdiff Test demonstrated excellent performance compared to direct and enrichment toxigenic culture. The test combines high assay sensitivity with rapid turnaround time and a minimum number of pre-analytic steps, to facilitate earlier intervention of patients suffering from

C. difficile-associated disease. Earlier intervention can also lead to more effective implementation of infection control measures, which can prevent further transmission to additional patients.

About the cobas® 4800 System
The cobas® 4800 System offers true walk-away automation of nucleic acid purification, PCR set-up and real-time PCR amplification and detection to help laboratories achieve maximum efficiency. The expanding system menu in the U.S. currently includes the cobas® MRSA/SA Test, cobas® CT/NG Test (Chlamydia trachomatis/Neisseria gonorrhoeae), cobas® HPV Test, cobas® BRAF V600 Mutation Test, cobas® EGFR Mutation Test and cobas® KRAS Mutation Test.

“With the addition of the cobas® Cdiff Test to the cobas® 4800 System menu, Roche is able to expand the tools available to assist clinicians in the management of healthcare associated infections,” said Paul Brown, head of Roche Molecular Diagnostics. “The cobas® Cdiff Test requires less sample handling and provides laboratories with a simplified workflow, when compared to other molecular methods. It also delivers a lower inhibition rate, which means fewer repeat samples and chances for error, enabling better patient care.”


To access the news article:



C. diff. – New CDC Study – National Burden of Clostridium difficile (C. diff.) Infections

Nearly half a million Americans suffered from Clostridium difficile (C. diff.) infections in a single year according to a study released today, February 25, 2015, by the Centers for Disease Control and Prevention (CDC).

• More than 100,000 of these infections developed among residents of U.S. nursing homes.
Approximately 29,000 patients died within 30 days of the initial diagnosis of a C. diff. infection. Of these 29,000 – 15,000 deaths were estimated to be directly related to a
C. diff. infection. Therefore; C. diff. is an important cause of infectious disease death in the U.S.
Previous studies indicate that C. diff. has become the most common microbial cause of Healthcare-Associated Infections found in U.S. hospitals driving up costs to $4.8 billion each year in excess health care costs in acute care facilities alone. Approximately
two-thirds of C. diff. infections were found to be associated with an inpatient stay in a health care facility, only 24% of the total cases occurred in patients while they were hospitalized. The study also revealed that almost as many cases occurred in nursing homes as in hospitals and the remainder of individuals acquired the
Healthcare-Associated infection, C. diff., recently discharged from a health care facility.


This new study finds that 1 out of every 5 patients with the Healthcare-Associated Infection (HAI), C. diff., experience a recurrence of the infection and 1 out of every 9 patients over the age of 65 diagnosed with a HAI – C. diff. infection died within 30 days of being diagnosed. Older Americans are quite vulnerable to this life-threatening diarrhea infection. The CDC study also found that women and Caucasian individuals are at an increased risk of acquiring a C. diff. infection.


CDC Director, Dr. Tom Frieden, MD, MPH said, “C. difficile infections cause immense suffering and death for thousands of Americans each year.” “These infections can be prevented by improving antibiotic prescribing and by improving infection control in the health care system. CDC hopes to ramp up prevention of this deadly infection by supporting State Antibiotic Resistance Prevention Programs in all 50 states.”

The Agency for Healthcare Research and Quality (AHRQ) has developed a toolkit to help all hospitals begin antibiotic stewardship programs to reduce C. diff. infections.
Based on the National Plan to Prevent Healthcare – Associated Infections: Road Map to Elimination, new 2020 national reduction targets are being established for C. diff. and all hospitals participating in the Centers for Medicare & Medicaid Services (CMS) Hospital Inpatient Quality Reporting Program have been reporting C. diff. infection data to the CDC’s National Healthcare Safety Network since 2013. The baseline data allows for continued surveillance for C. diff. infections to monitor progress in prevention.

Improve the use of antibiotics in preventing C. diff. infections:
150,000 of the half a million C. diff. infections – the new study revealed that they were community-associated and had no documented health care exposure. A separate recent CDC study found that 82% of patients with community-associated C. diff. infections reported exposure to outpatient health care settings (e.g., physicians or dentist office) within twelve weeks before being diagnosed with a C. diff. infection. Through this finding confirms the need for infection control in these settings as well and the need for improved antibiotic use. Another recent CDC study showed a 30% decrease in the use of antibiotics lined to a C. diff. infection in hospitals could reduce newly diagnosed infections by more than 25% in hospitalized and recently discharged patients. A new retrospective study being conducted at a Canadian hospital found that a 10% decrease in overall antibiotic usage through different wards was related to a 34% decrease in newly diagnosed C. diff. infections. A third CDC study among patients without a recent hospitalization or nursing home stay (i.e. community-associated cases) found that a 10% reduction in the use of all antibiotics in outpatient settings could reduce newly diagnosed            C. diff. infections by 16%. In recent years England has seen a reduction of newly diagnosed          C. diff. cases by 60% largely due to improvements in antibiotic prescribing.

C. diff.; Different strains? The North American pulsed-field gel electrophoresis type 1 (NAP1) strain was more prevalent among healthcare-associated than community-associated infections. Changes in the epidemiology of C. difficile infections have occurred since the emergence of this strain in 2000, which has been responsible for widespread dispersed hospital-associated outbreaks. The NAP1 strain was first detected in Pittsburgh, PA and Montreal and is now global. It is causing the majority of infections in communities and healthcare settings. 30% detected in the study and increase seen in healthcare facilities as it is more easily transmitted. “All organisms producing toxins, all infections – must be looked upon with seriousness.”                          Dr. Michael Bell, MD and Dr. Clifford McDonald, MD both concurred.

The diagnosing and detection of a C. difficile infection is at the transition point in how this infection is being diagnosed. There is a need to use better methods of testing and who gets tested and a combination of clinical symptoms and laboratory tests. The Enzyme assay may not be sensitive enough and the PCR is more readily used, is more sensitive, and was used in this study with 50% laboratory producing a C. diff. diagnosis.
The care involved treating a patient with a C. difficile infection begins as a short-term treatment and can develop into a long-term illness with many recurrences.

Dr. Michael Bell, MD shared a brief C. diff. infection possible scenario:
• The patient may have been on an antibiotic within 90 days and develops diarrhea, then the individual should see a medical physician and get tested for a C. diff. infection.
• If the test result is positive for a C. diff. infection then treatment begins with a prescribed oral antibiotic.
• It may take multiple rounds of a oral antibiotic to suppress a C. diff. infection.
• There is a challenge treating a C. diff. infection as the antibiotic continually disturbs the bacteria in the bowel.
• Toxic forming C. diff. can put one’s life at risk as leaks develop in the bowel allowing bacteria to enter the blood stream (bacteremia).
• The infection may progress and the physicians may have to perform a surgical procedure and remove part or the entire colon (colectomy).
• Or the progression of a C. diff. infection leads the patient diagnosed with a C. diff. infection into becoming a surgical patient which will change their life through a diversion of the bowel (colostomy).
Ways to prevent C. diff. infection recurrences:
Do not take antibiotics unless absolutely necessary and diagnosed with a infection that a antibiotic will be effective. The use of an antibiotic treating symptoms caused by a virus is not effective. (Antibiotic stewardship).
Make the clinician aware that a antibiotic has been taken to treat a infection.
Antibiotics are lifesaving medications and need to be prescribed correctly to avoid antibiotic-resistance.
Healthcare facilities must implement and maintain Hand-washing (hand-hygiene) programs – Infection control.
Probiotics – are found in foods (e.g., Kefir, Yogurt) and are sold as a nutritional supplement, (1) “The U.S. Food and Drug Administration (FDA) has no definition of probiotics and regulates them based on whether they fall into one of the existing regulated product categories,” says Hoffmann, who along with faculty members from the University of Maryland School of Medicine’s Institute for Genomics Sciences, the University of Maryland School of Pharmacy and the University of Maryland Carey School of Law, investigated how probiotics are being regulated
(1) See more at: http://www.thedailysheeple.com/fda-to-change-regulations-for-probiotics_102013#sthash.4IGLf8aE.dpuf


C. diff. spores and outpatient settings: There were C. diff. spores found in outpatient settings. A study done at outpatient clinics found that patients who had recently been treated for a C. diff. infection in a hospital, and discharged continued shedding C. diff. spores from weeks to months after recovering from the infection. Clostridium difficile (C. diff.) spores were found on the exam table and in the clinic exam areas. Based on this information it is beneficial to continue disinfecting hard non-porous surfaces utilizing EPA registered disinfecting products, with C. diff. kill claim, in home-care and within healthcare facilities to continue decreasing the spread of        C. diff. spores and maintain infection control. There are Infection programs ongoing with the CDC with continued monitoring/studies.


Preventing C. difficile is a National Priority

Based on the National Action Plan to Prevent Health Care-Associated Infections: Road Map to Elimination, new 2020 national reduction targets are being established for C. difficile, and all hospitals participating in the Centers for Medicare & Medicaid Services’ (CMS) Hospital Inpatient Quality Reporting Program have been reporting C. difficile infection data to CDC’s National Healthcare Safety Network since 2013. Those baseline data will allow continued surveillance for C. difficile infections to monitor progress in prevention.

The State Antibiotic Resistance Prevention Programs that would be supported by the funding proposed for CDC in the President’s FY16 budget would work with health care facilities in all 50 states to detect and prevent both C. difficile infections and antibiotic-resistant organisms. The FY 16 budget would also accelerate efforts to improve antibiotic stewardship in inpatient and outpatient settings. During the next five years, CDC’s efforts to combat C. difficile infections and antibiotic resistance under the National Strategy to Combat Antibiotic Resistant Bacteria will enhance national capabilities for antibiotic stewardship, outbreak surveillance, and antibiotic resistance prevention. These efforts hold the potential to cut the incidence of C. difficile infections in half.

For more information please click on the link provided below: